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Sample records for resting-state functional mri

  1. Functional connectivity analysis of the brain network using resting-state fMRI

    International Nuclear Information System (INIS)

    Hayashi, Toshihiro

    2011-01-01

    Spatial patterns of spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals reflect the underlying neural architecture. The study of the brain network based on these self-organized patterns is termed resting-state functional MRI (fMRI). This review article aims at briefly reviewing a basic concept of this technology and discussing its implications for neuropsychological studies. First, the technical aspects of resting-state fMRI, including signal sources, physiological artifacts, image acquisition, and analytical methods such as seed-based correlation analysis and independent component analysis, are explained, followed by a discussion on the major resting-state networks, including the default mode network. In addition, the structure-function correlation studied using diffuse tensor imaging and resting-state fMRI is briefly discussed. Second, I have discussed the reservations and potential pitfalls of 2 major imaging methods: voxel-based lesion-symptom mapping and task fMRI. Problems encountered with voxel-based lesion-symptom mapping can be overcome by using resting-state fMRI and evaluating undamaged brain networks in patients. Regarding task fMRI in patients, I have also emphasized the importance of evaluating the baseline brain activity because the amplitude of activation in BOLD fMRI is hard to interpret as the same baseline cannot be assumed for both patient and normal groups. (author)

  2. Increased interhemispheric resting-state functional connectivity after sleep deprivation: a resting-state fMRI study.

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    Zhu, Yuanqiang; Feng, Zhiyan; Xu, Junling; Fu, Chang; Sun, Jinbo; Yang, Xuejuan; Shi, Dapeng; Qin, Wei

    2016-09-01

    Several functional imaging studies have investigated the regional effects of sleep deprivation (SD) on impaired brain function; however, potential changes in the functional interactions between the cerebral hemispheres after SD are not well understood. In this study, we used a recently validated approach, voxel-mirrored homotopic connectivity (VMHC), to directly examine the changes in interhemispheric homotopic resting-state functional connectivity (RSFC) after SD. Resting-state functional MRI (fMRI) was performed in 28 participants both after rest wakefulness (RW) and a total night of SD. An interhemispheric RSFC map was obtained by calculating the Pearson correlation (Fisher Z transformed) between each pair of homotopic voxel time series for each subject in each condition. The between-condition differences in interhemispheric RSFC were then examined at global and voxelwise levels separately. Significantly increased global VMHC was found after sleep deprivation; specifically, a significant increase in VMHC was found in specific brain regions, including the thalamus, paracentral lobule, supplementary motor area, postcentral gyrus and lingual gyrus. No regions showed significantly reduced VMHC after sleep deprivation. Further analysis indicates that these findings did not depend on the various sizes of smoothing kernels that were adopted in the preprocessing steps and that the differences in these regions were still significant with or without global signal regression. Our data suggest that the increased VMHC might reflect the compensatory involvement of bilateral brain areas, especially the bilateral thalamus, to prevent cognitive performance deterioration when sleep pressure is elevated after sleep deprivation. Our findings provide preliminary evidence of interhemispheric correlation changes after SD and contribute to a better understanding of the neural mechanisms of SD.

  3. Infinite Relational Modeling of Functional Connectivity in Resting State fMRI

    DEFF Research Database (Denmark)

    Mørup, Morten; Madsen, Kristoffer H.; Dogonowski, Anne Marie

    2010-01-01

    Functional magnetic resonance imaging (fMRI) can be applied to study the functional connectivity of the neural elements which form complex network at a whole brain level. Most analyses of functional resting state networks (RSN) have been based on the analysis of correlation between the temporal...... dynamics of various regions of the brain. While these models can identify coherently behaving groups in terms of correlation they give little insight into how these groups interact. In this paper we take a different view on the analysis of functional resting state networks. Starting from the definition...... of resting state as functional coherent groups we search for functional units of the brain that communicate with other parts of the brain in a coherent manner as measured by mutual information. We use the infinite relational model (IRM) to quantify functional coherent groups of resting state networks...

  4. A SVM-based quantitative fMRI method for resting-state functional network detection.

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    Song, Xiaomu; Chen, Nan-kuei

    2014-09-01

    Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Exploring connectivity with large-scale Granger causality on resting-state functional MRI.

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    DSouza, Adora M; Abidin, Anas Z; Leistritz, Lutz; Wismüller, Axel

    2017-08-01

    Large-scale Granger causality (lsGC) is a recently developed, resting-state functional MRI (fMRI) connectivity analysis approach that estimates multivariate voxel-resolution connectivity. Unlike most commonly used multivariate approaches, which establish coarse-resolution connectivity by aggregating voxel time-series avoiding an underdetermined problem, lsGC estimates voxel-resolution, fine-grained connectivity by incorporating an embedded dimension reduction. We investigate application of lsGC on realistic fMRI simulations, modeling smoothing of neuronal activity by the hemodynamic response function and repetition time (TR), and empirical resting-state fMRI data. Subsequently, functional subnetworks are extracted from lsGC connectivity measures for both datasets and validated quantitatively. We also provide guidelines to select lsGC free parameters. Results indicate that lsGC reliably recovers underlying network structure with area under receiver operator characteristic curve (AUC) of 0.93 at TR=1.5s for a 10-min session of fMRI simulations. Furthermore, subnetworks of closely interacting modules are recovered from the aforementioned lsGC networks. Results on empirical resting-state fMRI data demonstrate recovery of visual and motor cortex in close agreement with spatial maps obtained from (i) visuo-motor fMRI stimulation task-sequence (Accuracy=0.76) and (ii) independent component analysis (ICA) of resting-state fMRI (Accuracy=0.86). Compared with conventional Granger causality approach (AUC=0.75), lsGC produces better network recovery on fMRI simulations. Furthermore, it cannot recover functional subnetworks from empirical fMRI data, since quantifying voxel-resolution connectivity is not possible as consequence of encountering an underdetermined problem. Functional network recovery from fMRI data suggests that lsGC gives useful insight into connectivity patterns from resting-state fMRI at a multivariate voxel-resolution. Copyright © 2017 Elsevier B.V. All

  6. Large-scale Granger causality analysis on resting-state functional MRI

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    D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

    2016-03-01

    We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

  7. Effects of Field-Map Distortion Correction on Resting State Functional Connectivity MRI

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    Hiroki Togo

    2017-12-01

    Full Text Available Magnetic field inhomogeneities cause geometric distortions of echo planar images used for functional magnetic resonance imaging (fMRI. To reduce this problem, distortion correction (DC with field map is widely used for both task and resting-state fMRI (rs-fMRI. Although DC with field map has been reported to improve the quality of task fMRI, little is known about its effects on rs-fMRI. Here, we tested the influence of field-map DC on rs-fMRI results using two rs-fMRI datasets derived from 40 healthy subjects: one with DC (DC+ and the other without correction (DC−. Independent component analysis followed by the dual regression approach was used for evaluation of resting-state functional connectivity networks (RSN. We also obtained the ratio of low-frequency to high-frequency signal power (0.01–0.1 Hz and above 0.1 Hz, respectively; LFHF ratio to assess the quality of rs-fMRI signals. For comparison of RSN between DC+ and DC− datasets, the default mode network showed more robust functional connectivity in the DC+ dataset than the DC− dataset. Basal ganglia RSN showed some decreases in functional connectivity primarily in white matter, indicating imperfect registration/normalization without DC. Supplementary seed-based and simulation analyses supported the utility of DC. Furthermore, we found a higher LFHF ratio after field map correction in the anterior cingulate cortex, posterior cingulate cortex, ventral striatum, and cerebellum. In conclusion, field map DC improved detection of functional connectivity derived from low-frequency rs-fMRI signals. We encourage researchers to include a DC step in the preprocessing pipeline of rs-fMRI analysis.

  8. Resting-state, functional MRI on regional homogeneity changes of brain in the heavy smokers

    International Nuclear Information System (INIS)

    Yang Shiqi; Wu Guangyao; Lin Fuchun; Kong Xiangquan; Zhou Guofeng; Pang Haopeng; Zhu Ling; Liu Guobing; Lei Hao

    2012-01-01

    Objective: To explore the mechanism of self-awareness in the heavy smokers (HS) by using regional homogeneity (ReHo) combined with resting-state functional MRI (fMRI). Methods: Thirty HS and 31 healthy non-smokers (NS) matched for age and sex underwent a 3.0 T resting-state fMRI. The data were post-processed by SPM 5 and then the ReHo values were calculated by REST software. The ReHo values between the two groups were compared by two-sample t-test. The brain map with significant difference of ReHo value was obtained. Results: Compared with that in NS group, the regions with decreased ReHo value included the bilateral precuneus, superior frontal gyrus,medial prefrontal cortex, right angular gyrus, inferior frontal gyrus, inferior occipital gyrus, cerebellum, and left middle frontal gyrus in HS group. The regions of increased ReHo value included the bilateral insula, parahippocampal gyrus, white matter of parietal lobe, pons, left inferior parietal lobule, lingual gyrus, thalamus, inferior orbital gyrus, white matter of temporal-frontal lobe, and cerebellum. The difference was more obvious in the left hemisphere. Conclusions: In HS, abnormal ReHo on a resting state which reflects network of smoking addiction. This method may be helpful in understanding the mechanism of self-awareness in HS. (authors)

  9. Altered resting-state functional connectivity in post-traumatic stress disorder: a perfusion MRI study

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    Li, Baojuan; Liu, Jian; Liu, Yang; Lu, Hong-Bing; Yin, Hong

    2013-03-01

    The majority of studies on posttraumatic stress disorder (PTSD) so far have focused on delineating patterns of activations during cognitive processes. Recently, more and more researches have started to investigate functional connectivity in PTSD subjects using BOLD-fMRI. Functional connectivity analysis has been demonstrated as a powerful approach to identify biomarkers of different brain diseases. This study aimed to detect resting-state functional connectivity abnormities in patients with PTSD using arterial spin labeling (ASL) fMRI. As a completely non-invasive technique, ASL allows quantitative estimates of cerebral blood flow (CBF). Compared with BOLD-fMRI, ASL fMRI has many advantages, including less low-frequency signal drifts, superior functional localization, etc. In the current study, ASL images were collected from 10 survivors in mining disaster with recent onset PTSD and 10 survivors without PTSD. Decreased regional CBF in the right middle temporal gyrus, lingual gyrus, and postcentral gyrus was detected in the PTSD patients. Seed-based resting-state functional connectivity analysis was performed using an area in the right middle temporal gyrus as region of interest. Compared with the non-PTSD group, the PTSD subjects demonstrated increased functional connectivity between the right middle temporal gyrus and the right superior temporal gyrus, the left middle temporal gyrus. Meanwhile, decreased functional connectivity between the right middle temporal gyrus and the right postcentral gyrus, the right superior parietal lobule was also found in the PTSD patients. This is the first study which investigated resting-state functional connectivity in PTSD using ASL images. The results may provide new insight into the neural substrates of PTSD.

  10. Presbycusis Disrupts Spontaneous Activity Revealed by Resting-State Functional MRI

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    Yu-Chen Chen

    2018-03-01

    Full Text Available Purpose: Presbycusis, age-related hearing loss, is believed to involve neural changes in the central nervous system, which is associated with an increased risk of cognitive impairment. The goal of this study was to determine if presbycusis disrupted spontaneous neural activity in specific brain areas involved in auditory processing, attention and cognitive function using resting-state functional magnetic resonance imaging (fMRI approach.Methods: Hearing and resting-state fMRI measurements were obtained from 22 presbycusis patients and 23 age-, sex- and education-matched healthy controls. To identify changes in spontaneous neural activity associated with age-related hearing loss, we compared the amplitude of low-frequency fluctuations (ALFF and regional homogeneity (ReHo of fMRI signals in presbycusis patients vs. controls and then determined if these changes were linked to clinical measures of presbycusis.Results: Compared with healthy controls, presbycusis patients manifested decreased spontaneous activity mainly in the superior temporal gyrus (STG, parahippocampal gyrus (PHG, precuneus and inferior parietal lobule (IPL as well as increased neural activity in the middle frontal gyrus (MFG, cuneus and postcentral gyrus (PoCG. A significant negative correlation was observed between ALFF/ReHo activity in the STG and average hearing thresholds in presbycusis patients. Increased ALFF/ReHo activity in the MFG was positively correlated with impaired Trail-Making Test B (TMT-B scores, indicative of impaired cognitive function involving the frontal lobe.Conclusions: Presbycusis patients have disrupted spontaneous neural activity reflected by ALFF and ReHo measurements in several brain regions; these changes are associated with specific cognitive performance and speech/language processing. These findings mainly emphasize the crucial role of aberrant resting-state ALFF/ReHo patterns in presbycusis patients and will lead to a better understanding of the

  11. Presbycusis Disrupts Spontaneous Activity Revealed by Resting-State Functional MRI.

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    Chen, Yu-Chen; Chen, Huiyou; Jiang, Liang; Bo, Fan; Xu, Jin-Jing; Mao, Cun-Nan; Salvi, Richard; Yin, Xindao; Lu, Guangming; Gu, Jian-Ping

    2018-01-01

    Purpose : Presbycusis, age-related hearing loss, is believed to involve neural changes in the central nervous system, which is associated with an increased risk of cognitive impairment. The goal of this study was to determine if presbycusis disrupted spontaneous neural activity in specific brain areas involved in auditory processing, attention and cognitive function using resting-state functional magnetic resonance imaging (fMRI) approach. Methods : Hearing and resting-state fMRI measurements were obtained from 22 presbycusis patients and 23 age-, sex- and education-matched healthy controls. To identify changes in spontaneous neural activity associated with age-related hearing loss, we compared the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) of fMRI signals in presbycusis patients vs. controls and then determined if these changes were linked to clinical measures of presbycusis. Results : Compared with healthy controls, presbycusis patients manifested decreased spontaneous activity mainly in the superior temporal gyrus (STG), parahippocampal gyrus (PHG), precuneus and inferior parietal lobule (IPL) as well as increased neural activity in the middle frontal gyrus (MFG), cuneus and postcentral gyrus (PoCG). A significant negative correlation was observed between ALFF/ReHo activity in the STG and average hearing thresholds in presbycusis patients. Increased ALFF/ReHo activity in the MFG was positively correlated with impaired Trail-Making Test B (TMT-B) scores, indicative of impaired cognitive function involving the frontal lobe. Conclusions : Presbycusis patients have disrupted spontaneous neural activity reflected by ALFF and ReHo measurements in several brain regions; these changes are associated with specific cognitive performance and speech/language processing. These findings mainly emphasize the crucial role of aberrant resting-state ALFF/ReHo patterns in presbycusis patients and will lead to a better understanding of the

  12. Functional network centrality in obesity: A resting-state and task fMRI study.

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    García-García, Isabel; Jurado, María Ángeles; Garolera, Maite; Marqués-Iturria, Idoia; Horstmann, Annette; Segura, Bàrbara; Pueyo, Roser; Sender-Palacios, María José; Vernet-Vernet, Maria; Villringer, Arno; Junqué, Carme; Margulies, Daniel S; Neumann, Jane

    2015-09-30

    Obesity is associated with structural and functional alterations in brain areas that are often functionally distinct and anatomically distant. This suggests that obesity is associated with differences in functional connectivity of regions distributed across the brain. However, studies addressing whole brain functional connectivity in obesity remain scarce. Here, we compared voxel-wise degree centrality and eigenvector centrality between participants with obesity (n=20) and normal-weight controls (n=21). We analyzed resting state and task-related fMRI data acquired from the same individuals. Relative to normal-weight controls, participants with obesity exhibited reduced degree centrality in the right middle frontal gyrus in the resting-state condition. During the task fMRI condition, obese participants exhibited less degree centrality in the left middle frontal gyrus and the lateral occipital cortex along with reduced eigenvector centrality in the lateral occipital cortex and occipital pole. Our results highlight the central role of the middle frontal gyrus in the pathophysiology of obesity, a structure involved in several brain circuits signaling attention, executive functions and motor functions. Additionally, our analysis suggests the existence of task-dependent reduced centrality in occipital areas; regions with a role in perceptual processes and that are profoundly modulated by attention. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  13. Graph-based network analysis of resting-state functional MRI

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    Jinhui Wang

    2010-06-01

    Full Text Available In the past decade, resting-state functional MRI (R-fMRI measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain’s spontaneous or intrinsic (i.e., task-free activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain’s intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

  14. Graph-based network analysis of resting-state functional MRI.

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    Wang, Jinhui; Zuo, Xinian; He, Yong

    2010-01-01

    In the past decade, resting-state functional MRI (R-fMRI) measures of brain activity have attracted considerable attention. Based on changes in the blood oxygen level-dependent signal, R-fMRI offers a novel way to assess the brain's spontaneous or intrinsic (i.e., task-free) activity with both high spatial and temporal resolutions. The properties of both the intra- and inter-regional connectivity of resting-state brain activity have been well documented, promoting our understanding of the brain as a complex network. Specifically, the topological organization of brain networks has been recently studied with graph theory. In this review, we will summarize the recent advances in graph-based brain network analyses of R-fMRI signals, both in typical and atypical populations. Application of these approaches to R-fMRI data has demonstrated non-trivial topological properties of functional networks in the human brain. Among these is the knowledge that the brain's intrinsic activity is organized as a small-world, highly efficient network, with significant modularity and highly connected hub regions. These network properties have also been found to change throughout normal development, aging, and in various pathological conditions. The literature reviewed here suggests that graph-based network analyses are capable of uncovering system-level changes associated with different processes in the resting brain, which could provide novel insights into the understanding of the underlying physiological mechanisms of brain function. We also highlight several potential research topics in the future.

  15. Altered spontaneous brain activity in patients with hemifacial spasm: a resting-state functional MRI study.

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    Ye Tu

    Full Text Available Resting-state functional magnetic resonance imaging (fMRI has been used to detect the alterations of spontaneous neuronal activity in various neurological and neuropsychiatric diseases, but rarely in hemifacial spasm (HFS, a nervous system disorder. We used resting-state fMRI with regional homogeneity (ReHo analysis to investigate changes in spontaneous brain activity of patients with HFS and to determine the relationship of these functional changes with clinical features. Thirty patients with HFS and 33 age-, sex-, and education-matched healthy controls were included in this study. Compared with controls, HFS patients had significantly decreased ReHo values in left middle frontal gyrus (MFG, left medial cingulate cortex (MCC, left lingual gyrus, right superior temporal gyrus (STG and right precuneus; and increased ReHo values in left precentral gyrus, anterior cingulate cortex (ACC, right brainstem, and right cerebellum. Furthermore, the mean ReHo value in brainstem showed a positive correlation with the spasm severity (r = 0.404, p = 0.027, and the mean ReHo value in MFG was inversely related with spasm severity in HFS group (r = -0.398, p = 0.028. This study reveals that HFS is associated with abnormal spontaneous brain activity in brain regions most involved in motor control and blinking movement. The disturbances of spontaneous brain activity reflected by ReHo measurements may provide insights into the neurological pathophysiology of HFS.

  16. Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

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    Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

    2017-01-01

    Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

  17. Abnormal regional homogeneity in patients with essential tremor revealed by resting-state functional MRI.

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    Weidong Fang

    Full Text Available Essential tremor (ET is one of the most common movement disorders in human adults. It can be characterized as a progressive neurological disorder of which the most recognizable feature is a tremor of the arms or hands that is apparent during voluntary movements such as eating and writing. The pathology of ET remains unclear. Resting-state fMRI (RS-fMRI, as a non-invasive imaging technique, was employed to investigate abnormalities of functional connectivity in ET in the brain. Regional homogeneity (ReHo was used as a metric of RS-fMRI to assess the local functional connectivity abnormality in ET with 20 ET patients and 20 age- and gender-matched healthy controls (HC. The ET group showed decreased ReHo in the anterior and posterior bilateral cerebellar lobes, the bilateral thalamus and the insular lobe, and increased ReHo in the bilateral prefrontal and parietal cortices, the left primary motor cortex and left supplementary motor area. The abnormal ReHo value of ET patients in the bilateral anterior cerebellar lobes and the right posterior cerebellar lobe were negatively correlated with the tremor severity score, while positively correlated with that in the left primary motor cortex. These findings suggest that the abnormality in cerebello-thalamo-cortical motor pathway is involved in tremor generation and propagation, which may be related to motor-related symptoms in ET patients. Meanwhile, the abnormality in the prefrontal and parietal regions may be associated with non-motor symptoms in ET. These findings suggest that the ReHo could be utilized for investigations of functional-pathological mechanism of ET.

  18. Progesterone mediates brain functional connectivity changes during the menstrual cycle - A pilot resting state MRI study

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    Katrin eArelin

    2015-02-01

    Full Text Available The growing interest in intrinsic brain organization has sparked various innovative approaches to generating comprehensive connectivity-based maps of the human brain. Prior reports point to a sexual dimorphism of the structural and functional human connectome. However, it is uncertain whether subtle changes in sex hormones, as occur during the monthly menstrual cycle, substantially impact the functional architecture of the female brain. Here, we performed eigenvector centrality (EC mapping in 32 longitudinal resting state fMRI scans of a single healthy subject without oral contraceptive use, across four menstrual cycles, and assessed estrogen and progesterone levels. To investigate associations between cycle-dependent hormones and brain connectivity, we performed correlation analyses between the EC maps and the respective hormone levels. On the whole brain level, we found a significant positive correlation between progesterone and EC in the bilateral DLPFC and bilateral sensorimotor cortex. In a secondary region-of-interest analysis, we detected a progesterone-modulated increase in functional connectivity of both bilateral DLPFC and bilateral sensorimotor cortex with the hippocampus. Our results suggest that the menstrual cycle substantially impacts intrinsic functional connectivity, particularly in brain areas associated with contextual memory-regulation, such as the hippocampus. These findings are the first to link the subtle hormonal fluctuations that occur during the menstrual cycle, to significant changes in regional functional connectivity in the hippocampus in a longitudinal design, given the limitation of data acquisition in a single subject. Our study demonstrates the feasibility of such a longitudinal rs-fMRI design and illustrates a means of creating a personalized map of the human brain by integrating potential mediators of brain states, such as menstrual cycle phase.

  19. Clinical applications of resting state functional connectivity

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    Michael D Fox

    2010-06-01

    Full Text Available During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level dependent (BOLD signal of fMRI. The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.

  20. Resting state functional MRI in Parkinson's disease: the impact of deep brain stimulation on 'effective' connectivity.

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    Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl; Foltynie, Tom

    2014-04-01

    Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.

  1. Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

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    Chyzhyk, Darya; Graña, Manuel; Öngür, Döst; Shinn, Ann K

    2015-05-01

    Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mechanisms underlying AH in schizophrenia may offer insight into the pathophysiology associated with AH more broadly across multiple neuropsychiatric disease conditions. In this paper, we address the problem of classifying schizophrenia patients with and without a history of AH, and healthy control (HC) subjects. To this end, we performed feature extraction from resting state functional magnetic resonance imaging (rsfMRI) data and applied machine learning classifiers, testing two kinds of neuroimaging features: (a) functional connectivity (FC) measures computed by lattice auto-associative memories (LAAM), and (b) local activity (LA) measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF). We show that it is possible to perform classification within each pair of subject groups with high accuracy. Discrimination between patients with and without lifetime AH was highest, while discrimination between schizophrenia patients and HC participants was worst, suggesting that classification according to the symptom dimension of AH may be more valid than discrimination on the basis of traditional diagnostic categories. FC measures seeded in right Heschl's gyrus (RHG) consistently showed stronger discriminative power than those seeded in left Heschl's gyrus (LHG), a finding that appears to support AH models focusing on right hemisphere abnormalities. The cortical brain localizations derived from the features with strong classification performance are consistent with proposed AH models, and include left inferior frontal gyrus (IFG), parahippocampal gyri, the cingulate cortex, as well as several temporal and prefrontal cortical brain regions. Overall, the observed findings suggest that

  2. Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: a resting-state functional MRI study

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    Zhang, Ye; Wang, Li; Zhang, Jingna; Sang, Linqiong; Li, Pengyue; Qiu, Mingguo [Third Military Medical University, Department of Medical Imaging, College of Biomedical Engineering, Chongqing (China); Liu, Hongliang; Yan, Rubing [Third Military Medical University, Department of Rehabilitation, Southwest Hospital, Chongqing (China); Yang, Jun; Wang, Jian [Third Military Medical University, Department of Radiology, Southwest Hospital, Chongqing (China)

    2016-05-15

    Resting-state functional magnetic resonance imaging (fMRI) has been used to examine the brain mechanisms of stroke patients with hemiplegia, but the relationship between functional connectivity (FC) and treatment-induced motor function recovery has not yet been fully investigated. This study aimed to identify the brain FC changes in stroke patients and study the relationship between FC and motor function assessment using the resting-state fMRI. Seventeen stroke patients with hemiplegia and fifteen healthy control subjects (HCSs) were recruited in this study. We compared the FC between the ipsilesional primary motor cortex (M1) and the whole brain of the patients with the FC of the HCSs and studied the FC changes in the patients before and after conventional rehabilitation and motor imagery therapy. Additionally, correlations between the FC change and motor function of the patients were studied. Compared to the HCSs, the FC in the patient group was significantly increased between the ipsilesional M1 and the ipsilesional inferior parietal cortex, frontal gyrus, supplementary motor area (SMA), and contralesional angular and decreased between the ipsilesional M1 and bilateral M1. After the treatment, the FC between the ipsilesional M1 and contralesional M1 increased while the FC between the ipsilesional M1 and ipsilesional SMA and paracentral lobule decreased. A statistically significant correlation was found between the FC change in the bilateral M1 and the Fugl-Meyer assessment (FMA) score change. Our results revealed an abnormal motor network after stroke and suggested that the FC could serve as a biomarker of motor function recovery in stroke patients with hemiplegia. (orig.)

  3. Relationship between functional connectivity and motor function assessment in stroke patients with hemiplegia: a resting-state functional MRI study

    International Nuclear Information System (INIS)

    Zhang, Ye; Wang, Li; Zhang, Jingna; Sang, Linqiong; Li, Pengyue; Qiu, Mingguo; Liu, Hongliang; Yan, Rubing; Yang, Jun; Wang, Jian

    2016-01-01

    Resting-state functional magnetic resonance imaging (fMRI) has been used to examine the brain mechanisms of stroke patients with hemiplegia, but the relationship between functional connectivity (FC) and treatment-induced motor function recovery has not yet been fully investigated. This study aimed to identify the brain FC changes in stroke patients and study the relationship between FC and motor function assessment using the resting-state fMRI. Seventeen stroke patients with hemiplegia and fifteen healthy control subjects (HCSs) were recruited in this study. We compared the FC between the ipsilesional primary motor cortex (M1) and the whole brain of the patients with the FC of the HCSs and studied the FC changes in the patients before and after conventional rehabilitation and motor imagery therapy. Additionally, correlations between the FC change and motor function of the patients were studied. Compared to the HCSs, the FC in the patient group was significantly increased between the ipsilesional M1 and the ipsilesional inferior parietal cortex, frontal gyrus, supplementary motor area (SMA), and contralesional angular and decreased between the ipsilesional M1 and bilateral M1. After the treatment, the FC between the ipsilesional M1 and contralesional M1 increased while the FC between the ipsilesional M1 and ipsilesional SMA and paracentral lobule decreased. A statistically significant correlation was found between the FC change in the bilateral M1 and the Fugl-Meyer assessment (FMA) score change. Our results revealed an abnormal motor network after stroke and suggested that the FC could serve as a biomarker of motor function recovery in stroke patients with hemiplegia. (orig.)

  4. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    OpenAIRE

    Tingting Xu; Kathryn R. Cullen; Bryon Mueller; Mindy W. Schreiner; Kelvin O. Lim; S. Charles Schulz; Keshab K. Parhi

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and construc...

  5. Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity.

    Science.gov (United States)

    Chan, Russell W; Leong, Alex T L; Ho, Leon C; Gao, Patrick P; Wong, Eddie C; Dong, Celia M; Wang, Xunda; He, Jufang; Chan, Ying-Shing; Lim, Lee Wei; Wu, Ed X

    2017-08-15

    The hippocampus, including the dorsal dentate gyrus (dDG), and cortex engage in bidirectional communication. We propose that low-frequency activity in hippocampal-cortical pathways contributes to brain-wide resting-state connectivity to integrate sensory information. Using optogenetic stimulation and brain-wide fMRI and resting-state fMRI (rsfMRI), we determined the large-scale effects of spatiotemporal-specific downstream propagation of hippocampal activity. Low-frequency (1 Hz), but not high-frequency (40 Hz), stimulation of dDG excitatory neurons evoked robust cortical and subcortical brain-wide fMRI responses. More importantly, it enhanced interhemispheric rsfMRI connectivity in various cortices and hippocampus. Subsequent local field potential recordings revealed an increase in slow oscillations in dorsal hippocampus and visual cortex, interhemispheric visual cortical connectivity, and hippocampal-cortical connectivity. Meanwhile, pharmacological inactivation of dDG neurons decreased interhemispheric rsfMRI connectivity. Functionally, visually evoked fMRI responses in visual regions also increased during and after low-frequency dDG stimulation. Together, our results indicate that low-frequency activity robustly propagates in the dorsal hippocampal-cortical pathway, drives interhemispheric cortical rsfMRI connectivity, and mediates visual processing.

  6. Associations of resting-state fMRI functional connectivity with flow-BOLD coupling and regional vasculature.

    Science.gov (United States)

    Tak, Sungho; Polimeni, Jonathan R; Wang, Danny J J; Yan, Lirong; Chen, J Jean

    2015-04-01

    There has been tremendous interest in applying functional magnetic resonance imaging-based resting-state functional connectivity (rs-fcMRI) measurements to the study of brain function. However, a lack of understanding of the physiological mechanisms of rs-fcMRI limits their ability to interpret rs-fcMRI findings. In this work, the authors examine the regional associations between rs-fcMRI estimates and dynamic coupling between the blood oxygenation level-dependent (BOLD) and cerebral blood flow (CBF), as well as resting macrovascular volume. Resting-state BOLD and CBF data were simultaneously acquired using a dual-echo pseudocontinuous arterial spin labeling (pCASL) technique, whereas macrovascular volume fraction was estimated using time-of-flight MR angiography. Functional connectivity within well-known functional networks—including the default mode, frontoparietal, and primary sensory-motor networks—was calculated using a conventional seed-based correlation approach. They found the functional connectivity strength to be significantly correlated with the regional increase in CBF-BOLD coupling strength and inversely proportional to macrovascular volume fraction. These relationships were consistently observed within all functional networks considered. Their findings suggest that highly connected networks observed using rs-fcMRI are not likely to be mediated by common vascular drainage linking distal cortical areas. Instead, high BOLD functional connectivity is more likely to reflect tighter neurovascular connections, attributable to neuronal pathways.

  7. Baseline brain activity changes in patients with clinically isolated syndrome revealed by resting-state functional MRI

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Yaou; Duan, Yunyun; Liang, Peipeng; Jia, Xiuqin; Yu, Chunshui [Dept. of Radiology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Ye, Jing [Dept. of Neurology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Butzkueven, Helmut [Dept. of Medicine, Univ. of Melbourne, Melbourne (Australia); Dong, Huiqing [Dept. of Neurology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Li, Kuncheng [Dept. of Radiology, Xuanwu Hospital, Capital Medical Univ., Beijing (China); Beijing Key Laboratory of MRI and Brain Informatics, Beijing (China)], E-mail: likuncheng1955@yahoo.com.cn

    2012-11-15

    Background A clinically isolated syndrome (CIS) is the first manifestation of multiple sclerosis (MS). Previous task-related functional MRI studies demonstrate functional reorganization in patients with CIS. Purpose To assess baseline brain activity changes in patients with CIS by using the technique of regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI. Material and Methods Resting-state fMRIs data acquired from 37 patients with CIS and 37 age- and sex-matched normal controls were compared to investigate ALFF differences. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration, and T2 lesion volume (T2LV) were further explored. Results Patients with CIS had significantly decreased ALFF in the right anterior cingulate cortex, right caudate, right lingual gyrus, and right cuneus (P < 0.05 corrected for multiple comparisons using Monte Carlo simulation) compared to normal controls, while no significantly increased ALFF were observed in CIS. No significant correlation was found between the EDSS, disease duration, T2LV, and ALFF in regions with significant group differences. Conclusion In patients with CIS, resting-state fMRI demonstrates decreased activity in several brain regions. These results are in contrast to patients with established MS, in whom ALFF demonstrates several regions of increased activity. It is possible that this shift from decreased activity in CIS to increased activity in MS could reflect the dynamics of cortical reorganization.

  8. Working memory capacity and the functional connectome - insights from resting-state fMRI and voxelwise centrality mapping.

    Science.gov (United States)

    Markett, Sebastian; Reuter, Martin; Heeren, Behrend; Lachmann, Bernd; Weber, Bernd; Montag, Christian

    2018-02-01

    The functional connectome represents a comprehensive network map of functional connectivity throughout the human brain. To date, the relationship between the organization of functional connectivity and cognitive performance measures is still poorly understood. In the present study we use resting-state functional magnetic resonance imaging (fMRI) data to explore the link between the functional connectome and working memory capacity in an individual differences design. Working memory capacity, which refers to the maximum amount of context information that an individual can retain in the absence of external stimulation, was assessed outside the MRI scanner and estimated based on behavioral data from a change detection task. Resting-state time series were analyzed by means of voxelwise degree and eigenvector centrality mapping, which are data-driven network analytic approaches for the characterization of functional connectivity. We found working memory capacity to be inversely correlated with both centrality in the right intraparietal sulcus. Exploratory analyses revealed that this relationship was putatively driven by an increase in negative connectivity strength of the structure. This resting-state connectivity finding fits previous task based activation studies that have shown that this area responds to manipulations of working memory load.

  9. Functional connectivity associated with social networks in older adults: A resting-state fMRI study.

    Science.gov (United States)

    Pillemer, Sarah; Holtzer, Roee; Blumen, Helena M

    2017-06-01

    Poor social networks and decreased levels of social support are associated with worse mood, health, and cognition in younger and older adults. Yet, we know very little about the brain substrates associated with social networks and social support, particularly in older adults. This study examined functional brain substrates associated with social networks using the Social Network Index (SNI) and resting-state functional magnetic resonance imaging (fMRI). Resting-state fMRI data from 28 non-demented older adults were analyzed with independent components analyses. As expected, four established resting-state networks-previously linked to motor, vision, speech, and other language functions-correlated with the quality (SNI-1: total number of high-contact roles of a respondent) and quantity (SNI-2: total number of individuals in a respondent's social network) of social networks: a sensorimotor, a visual, a vestibular/insular, and a left frontoparietal network. Moreover, SNI-1 was associated with greater functional connectivity in the lateral prefrontal regions of the left frontoparietal network, while SNI-2 was associated with greater functional connectivity in the medial prefrontal regions of this network. Thus, lateral prefrontal regions may be particularly linked to the quality of social networks while medial prefrontal regions may be particularly linked to the quantity of social networks.

  10. Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

    Science.gov (United States)

    Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

    2017-01-01

    Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed. PMID:28009983

  11. Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study.

    Science.gov (United States)

    Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

    2017-01-24

    Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

  12. Resting-State fMRI Functional Connectivity Is Associated with Sleepiness, Imagery, and Discontinuity of Mind

    Science.gov (United States)

    Chen, Gang; den Braber, Anouk; van ‘t Ent, Dennis; Boomsma, Dorret I.; Mansvelder, Huibert D.; de Geus, Eco; Van Someren, Eus J. W.; Linkenkaer-Hansen, Klaus

    2015-01-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to investigate the functional architecture of the healthy human brain and how it is affected by learning, lifelong development, brain disorders or pharmacological intervention. Non-sensory experiences are prevalent during rest and must arise from ongoing brain activity, yet little is known about this relationship. Here, we used two runs of rs-fMRI both immediately followed by the Amsterdam Resting-State Questionnaire (ARSQ) to investigate the relationship between functional connectivity within ten large-scale functional brain networks and ten dimensions of thoughts and feelings experienced during the scan in 106 healthy participants. We identified 11 positive associations between brain-network functional connectivity and ARSQ dimensions. ‘Sleepiness’ exhibited significant associations with functional connectivity within Visual, Sensorimotor and Default Mode networks. Similar associations were observed for ‘Visual Thought’ and ‘Discontinuity of Mind’, which may relate to variation in imagery and thought control mediated by arousal fluctuations. Our findings show that self-reports of thoughts and feelings experienced during a rs-fMRI scan help understand the functional significance of variations in functional connectivity, which should be of special relevance to clinical studies. PMID:26540239

  13. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Bum Seok [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Choi, Jee Wook [Daejeon St. Mary' s Hospital, The Catholic University of Korea College of Medicine, Daejeon (Korea, Republic of); Kim, Ji Woong [College of Medical Science, Konyang University, Daejeon(Korea, Republic of)

    2012-06-15

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  14. MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

    International Nuclear Information System (INIS)

    Jeong, Bum Seok; Choi, Jee Wook; Kim, Ji Woong

    2012-01-01

    Resting-state networks (RSNs), including the default mode network (DMN), have been considered as markers of brain status such as consciousness, developmental change, and treatment effects. The consistency of functional connectivity among RSNs has not been fully explored, especially among resting-state-related independent components (RSICs). This resting-state fMRI study addressed the consistency of functional connectivity among RSICs as well as their spatial consistency between 'at day 1' and 'after 4 weeks' in 13 healthy volunteers. We found that most RSICs, especially the DMN, are reproducible across time, whereas some RSICs were variable in either their spatial characteristics or their functional connectivity. Relatively low spatial consistency was found in the basal ganglia, a parietal region of left frontoparietal network, and the supplementary motor area. The functional connectivity between two independent components, the bilateral angular/supramarginal gyri/intraparietal lobule and bilateral middle temporal/occipital gyri, was decreased across time regardless of the correlation analysis method employed, (Pearson's or partial correlation). RSICs showing variable consistency are different between spatial characteristics and functional connectivity. To understand the brain as a dynamic network, we recommend further investigation of both changes in the activation of specific regions and the modulation of functional connectivity in the brain network.

  15. Functional Connectivity Estimated from Resting-State fMRI Reveals Selective Alterations in Male Adolescents with Pure Conduct Disorder.

    Directory of Open Access Journals (Sweden)

    Feng-Mei Lu

    Full Text Available Conduct disorder (CD is characterized by a persistent pattern of antisocial behavior and aggression in childhood and adolescence. Previous task-based and resting-state functional magnetic resonance imaging (fMRI studies have revealed widespread brain regional abnormalities in adolescents with CD. However, whether the resting-state networks (RSNs are altered in adolescents with CD remains unknown. In this study, resting-state fMRI data were first acquired from eighteen male adolescents with pure CD and eighteen age- and gender-matched typically developing (TD individuals. Independent component analysis (ICA was implemented to extract nine representative RSNs, and the generated RSNs were then compared to show the differences between the CD and TD groups. Interestingly, it was observed from the brain mapping results that compared with the TD group, the CD group manifested decreased functional connectivity in four representative RSNs: the anterior default mode network (left middle frontal gyrus, which is considered to be correlated with impaired social cognition, the somatosensory network (bilateral supplementary motor area and right postcentral gyrus, the lateral visual network (left superior occipital gyrus, and the medial visual network (right fusiform, left lingual gyrus and right calcarine, which are expected to be relevant to the perceptual systems responsible for perceptual dysfunction in male adolescents with CD. Importantly, the novel findings suggested that male adolescents with pure CD were identified to have dysfunctions in both low-level perceptual networks (the somatosensory network and visual network and a high-order cognitive network (the default mode network. Revealing the changes in the functional connectivity of these RSNs enhances our understanding of the neural mechanisms underlying the modulation of emotion and social cognition and the regulation of perception in adolescents with CD.

  16. Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS).

    Science.gov (United States)

    Fox, Michael D; Halko, Mark A; Eldaief, Mark C; Pascual-Leone, Alvaro

    2012-10-01

    Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include using resting state fcMRI to guide target selection for TMS and using TMS to modulate pathological network interactions identified with resting state fcMRI. The combination of TMS and resting state fcMRI has the potential to accelerate the translation of both techniques into the clinical realm and promises a new approach to the diagnosis and treatment of neurological and psychiatric diseases that demonstrate network pathology. Copyright © 2012 Elsevier Inc. All rights reserved.

  17. Modafinil alters intrinsic functional connectivity of the right posterior insula: a pharmacological resting state fMRI study.

    Directory of Open Access Journals (Sweden)

    Nicoletta Cera

    Full Text Available Modafinil is employed for the treatment of narcolepsy and has also been, off-label, used to treat cognitive dysfunction in neuropsychiatric disorders. In a previous study, we have reported that single dose administration of modafinil in healthy young subjects enhances fluid reasoning and affects resting state activity in the Fronto Parietal Control (FPC and Dorsal Attention (DAN networks. No changes were found in the Salience Network (SN, a surprising result as the network is involved in the modulation of emotional and fluid reasoning. The insula is crucial hub of the SN and functionally divided in anterior and posterior subregions.Using a seed-based approach, we have now analyzed effects of modafinil on the functional connectivity (FC of insular subregions.Analysis of FC with resting state fMRI (rs-FMRI revealed increased FC between the right posterior insula and the putamen, the superior frontal gyrus and the anterior cingulate cortex in the modafinil-treated group.Modafinil is considered a putative cognitive enhancer. The rs-fMRI modifications that we have found are consistent with the drug cognitive enhancing properties and indicate subregional targets of action.ClinicalTrials.gov NCT01684306.

  18. Altered interhemispheric functional connectivity in patients with anisometropic and strabismic amblyopia: a resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Minglong; Xie, Bing; Yin, Xuntao; Wang, Jian [Third Military Medical University, Department of Radiology, Southwest Hospital, 30 Gaotanyan Street, Shapingba District, Chongqing (China); Yang, Hong; Wang, Hao [Third Military Medical University, Ophthalmology Research Center, Southwest Eye Hospital/Southwest Hospital, Chongqing (China); Yu, Longhua [Third Military Medical University, Department of Radiology, Southwest Hospital, 30 Gaotanyan Street, Shapingba District, Chongqing (China); 401st Hospital of PLA, Department of Radiology, Qingdao (China); He, Sheng [University of Minnesota Twin Cities, Department of Psychology, Minneapolis, MN (United States)

    2017-05-15

    Altered brain functional connectivity has been reported in patients with amblyopia by recent neuroimaging studies. However, relatively little is known about the alterations in interhemispheric functional connectivity in amblyopia. The present study aimed to investigate the functional connectivity patterns between homotopic regions across hemispheres in patients with anisometropic and strabismic amblyopia under resting state. Nineteen monocular anisometropic amblyopia (AA), 18 strabismic amblyopia (SA), and 20 normal-sight controls (NC) were enrolled in this study. After a comprehensive ophthalmologic examination, resting-state fMRI scanning was performed in all participants. The pattern of the interhemispheric functional connectivity was measured with the voxel-mirrored homotopic connectivity (VMHC) approach. VMHC values differences within and between three groups were compared, and correlations between VMHC values and each the clinical variable were also analyzed. Altered VMHC was observed in AA and SA patients in lingual gyrus and fusiform gyrus compared with NC subjects. The altered VMHC of lingual gyrus showed a pattern of AA > SA > NC, while the altered VMHC of fusiform gyrus showed a pattern of AA > NC > SA. Moreover, the VMHC values of lingual gyrus were positively correlated with the stereoacuity both in AA and SA patients, and the VMHC values of fusiform gyrus were positively correlated with the amount of anisometropia just in AA patients. These findings suggest that interhemispheric functional coordination between several homotopic visual-related brain regions is impaired both in AA and SA patients under resting state and revealed the similarities and differences in interhemispheric functional connectivity between the anisometropic and strabismic amblyopia. (orig.)

  19. Altered interhemispheric functional connectivity in patients with anisometropic and strabismic amblyopia: a resting-state fMRI study

    International Nuclear Information System (INIS)

    Liang, Minglong; Xie, Bing; Yin, Xuntao; Wang, Jian; Yang, Hong; Wang, Hao; Yu, Longhua; He, Sheng

    2017-01-01

    Altered brain functional connectivity has been reported in patients with amblyopia by recent neuroimaging studies. However, relatively little is known about the alterations in interhemispheric functional connectivity in amblyopia. The present study aimed to investigate the functional connectivity patterns between homotopic regions across hemispheres in patients with anisometropic and strabismic amblyopia under resting state. Nineteen monocular anisometropic amblyopia (AA), 18 strabismic amblyopia (SA), and 20 normal-sight controls (NC) were enrolled in this study. After a comprehensive ophthalmologic examination, resting-state fMRI scanning was performed in all participants. The pattern of the interhemispheric functional connectivity was measured with the voxel-mirrored homotopic connectivity (VMHC) approach. VMHC values differences within and between three groups were compared, and correlations between VMHC values and each the clinical variable were also analyzed. Altered VMHC was observed in AA and SA patients in lingual gyrus and fusiform gyrus compared with NC subjects. The altered VMHC of lingual gyrus showed a pattern of AA > SA > NC, while the altered VMHC of fusiform gyrus showed a pattern of AA > NC > SA. Moreover, the VMHC values of lingual gyrus were positively correlated with the stereoacuity both in AA and SA patients, and the VMHC values of fusiform gyrus were positively correlated with the amount of anisometropia just in AA patients. These findings suggest that interhemispheric functional coordination between several homotopic visual-related brain regions is impaired both in AA and SA patients under resting state and revealed the similarities and differences in interhemispheric functional connectivity between the anisometropic and strabismic amblyopia. (orig.)

  20. Functional connectivity in resting-state fMRI: Is linear correlation sufficient?

    Czech Academy of Sciences Publication Activity Database

    Hlinka, Jaroslav; Paluš, Milan; Vejmelka, Martin; Mantini, D.; Corbetta, M.

    2011-01-01

    Roč. 54, č. 3 (2011), s. 2218-2225 ISSN 1053-8119 R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : fMRI * functional connectivity * Gaussianity * nonlinearity * correlation * mutual information Subject RIV: FH - Neurology Impact factor: 5.895, year: 2011

  1. Genetic and Diagnostic Biomarker Development in ASD Toddlers Using Resting State Functional MRI

    Science.gov (United States)

    2016-09-01

    temporal lobe and partial volumes of sulcal CSF at this early stage in brain development when white matter tracts are not yet robust enough to be...ages 3 to 4 years. 2. KEYWORDS Autism spectrum disorder, ASD, early brain development , intrinsic functional brain networks, fMRI, infants, toddlers...TD in bottom left triangle and ASD in top right triangle. Figure 4. Within-network ( left ) and Between-Network (Out-of-Network) ( right ) connectivity

  2. Altered functional connectivity of fusiform gyrus in subjects with amnestic mild cognitive impairment: a resting state fMRI study

    Directory of Open Access Journals (Sweden)

    SuPing eCai

    2015-08-01

    Full Text Available Visual cognition such as face recognition requires a high level of functional interaction between distributed regions of a network. It has been reported that the fusiform gyrus (FG is an important brain area involved in facial cognition; altered connectivity of FG to some other regions may lead to a deficit in visual cognition especially face recognition. However, whether functional connectivity between the FG and other brain regions changes remains unclear during the resting state in amnestic mild cognitive impairment (aMCI subjects. Here, we employed a resting state functional MRI (fMRI to examine changes in functional connectivity of left/right FG comparing aMCI patients with age-matched control subjects. Forty-eight aMCI and thirty-eight control subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI were analyzed. We focused on the correlation between low frequency fMRI signal fluctuations in the FG and those in all other brain regions. Compared to the control group, we found some discrepant regions in the aMCI group which presented increased or decreased connectivity with the left/right FG including the left precuneus, left lingual gyrus, right thalamus, supramarginal gyrus, left supplementary motor area, left inferior temporal gyrus, and left parahippocampus. More importantly, we also obtained that both left and right FG have increased functional connections with the left middle occipital gyrus (MOG and right anterior cingulate gyrus (ACC in aMCI patients. That was not a coincidence and might imply that the MOG and ACC also play a critical role in visual cognition, especially face recognition. These findings in a large part supported our hypothesis and provided a new insight in understanding the important subtype of MCI.

  3. Frequency-dependent changes in the regional amplitude and synchronization of resting-state functional MRI in stroke.

    Directory of Open Access Journals (Sweden)

    Jianfang Zhu

    Full Text Available Resting-state functional magnetic resonance imaging (R-fMRI has been intensively used to assess alterations of inter-regional functional connectivity in patients with stroke, but the regional properties of brain activity in stroke have not yet been fully investigated. Additionally, no study has examined a frequency effect on such regional properties in stroke patients, although this effect has been shown to play important roles in both normal brain functioning and functional abnormalities. Here we utilized R-fMRI to measure the amplitude of low-frequency fluctuations (ALFF and regional homogeneity (ReHo, two major methods for characterizing the regional properties of R-fMRI, in three different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.73 Hz; and typical band: 0.01-0.1 Hz in 19 stroke patients and 15 healthy controls. Both the ALFF and ReHo analyses revealed changes in brain activity in a number of brain regions, particularly the parietal cortex, in stroke patients compared with healthy controls. Remarkably, the regions with changed activity as detected by the slow-5 band data were more extensive, and this finding was true for both the ALFF and ReHo analyses. These results not only confirm previous studies showing abnormality in the parietal cortex in patients with stroke, but also suggest that R-fMRI studies of stroke should take frequency effects into account when measuring intrinsic brain activity.

  4. State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

    Science.gov (United States)

    Suk, Heung-Il; Wee, Chong-Yaw; Lee, Seong-Whan; Shen, Dinggang

    2016-04-01

    Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over time. In terms of a large-scale brain network, in this paper, we focus on time-varying patterns of functional networks, i.e., functional dynamics, inherent in rs-fMRI, which is one of the emerging issues along with the network modelling. Specifically, we propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. We first devise a Deep Auto-Encoder (DAE) to discover hierarchical non-linear functional relations among regions, by which we transform the regional features into an embedding space, whose bases are complex functional networks. Given the embedded functional features, we then use a Hidden Markov Model (HMM) to estimate dynamic characteristics of functional networks inherent in rs-fMRI via internal states, which are unobservable but can be inferred from observations statistically. By building a generative model with an HMM, we estimate the likelihood of the input features of rs-fMRI as belonging to the corresponding status, i.e., MCI or normal healthy control, based on which we identify the clinical label of a testing subject. In order to validate the effectiveness of the proposed method, we performed experiments on two different datasets and compared with state-of-the-art methods in the literature. We also analyzed the functional networks learned by DAE, estimated the functional connectivities by decoding hidden states in HMM, and investigated the estimated functional connectivities by means of a graph-theoretic approach. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study.

    Science.gov (United States)

    Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong

    2011-01-01

    We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.

  6. Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

    Science.gov (United States)

    Li, Zhengjun; Vidorreta, Marta; Katchmar, Natalie; Alsop, David C; Wolf, Daniel H; Detre, John A

    2018-06-01

    Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Fractional amplitude analysis of low frequency fluctuation in alcohol dependent individuals: a resting state functional MRI study

    International Nuclear Information System (INIS)

    Yan Dingfang; Cheng Jun; Wu Hanbin; Xu Liangzhou; Liu Jinhuan; Zhao Yilin; Lin Xue; Liu Changsheng; Qiu Li

    2012-01-01

    Objective: To explore brain activity features during the resting state in alcohol dependent individuals, and study the relationship between the brain activity features and alcohol dependent individuals' clinical symptoms. Methods: Twenty-four alcohol dependent individuals and 22 healthy control subjects, well matched in gender, age, education and handedness, were enrolled as the alcohol dependent group and control group respectively. A GE 3.0 T MR scanner was used to acquire all the subjects' resting state data. DPARSF software was used to process resting functional MRI data, and then the whole brain fractional amplitudes of low frequency fluctuation (fALFF) data were acquired. Two-sample t test statistical analysis was made to access fALFF difference between the two groups. Results: In comparison with the control group, the alcohol dependent group showed reduced fALFF in bilateral medial prefrontal gyrus, right inferior occipital gyrus, left precuneus,left inferior temporal gyrus, and left posterior lobe of cerebellum (0.64-1.69 vs. 0.87-1.78, t=-4.23- -2.79, P<0.05). fALFF was increased in the alcohol dependent group at the anterior cingulate,bilateral inferior frontal gyrus,right middle frontal gyrus,bilateral insular lobe,bilateral dorsal thalamus (0.86-1.82 vs. 0.76-1.58, t=3.56-3.96, P<0.05). Conclusion: Alcohol dependent individuals had abnormal activity at the bilateral prefrontal lobe,anterior cingulate, bilateral dorsal thalamus, bilateral insular lobe, left posterior lobe of cerebellum et al, during the resting state, and these abnormal activities might be related with clinical manifestation and pathophysiology. (authors)

  8. Amplitude of low-frequency fluctuation (ALFF) and fractional ALFF in migraine patients: a resting-state functional MRI study

    International Nuclear Information System (INIS)

    Wang, J.-J.; Chen, X.; Sah, S.K.; Zeng, C.; Li, Y.-M.; Li, N.; Liu, M.-Q.; Du, S.-I.

    2016-01-01

    Aim: To evaluate the amplitude of low-frequency oscillations (LFOs) of the brain in migraine patients using amplitude of low-frequency fluctuation (ALFF) and fractional ALFF in the interictal period, in comparison to healthy controls (HCs). Materials and methods: A total of 54 subjects, including 30 migraineurs and 24 gender- and age-matched HCs completed the fMRI. All the data and ALFF, fALFF analyses were preprocessed with the Data Processing Assistant for Resting-State fMRI (DPARSF). All of the statistical analyses were performed using the REST software to explore the differences in ALFF and fALFF between migraine patients and HCs. Results: In contrast to HCs, migraine patients showed significant ALFF increase in the left medulla and pons, the bilateral cerebellum posterior lobe and right insula. The regions showing decreased ALFF in migraine patients included the bilateral cerebellum posterior lobe, left cerebellum anterior lobe, bilateral orbital cortex, right middle frontal gyrus, bilateral occipital lobe, right fusiform gyrus, and bilateral postcentral gyrus. The fALFFs in migraine patients were significantly increased in the bilateral insular and left orbital cortex, but were decreased in the left occipital lobe and bilateral cerebellum posterior lobe. Conclusion: These ALFF and fALFF alterations in the brain regions of migraineurs are in keeping with the domains associated with pain and cognition. Such brain functional alteration may contribute to further understanding of migraine-related network imbalances demonstrated in previous studies. - Highlights: • Migraine is a common, paroxysmal, highly disabling primary headache disorder. • Resting-state fMRI offers a novel approach to measure spontaneous brain activity in migraine patients • The ALFF and fALFF alterations in migraineurs' brain regions are in keeping with the domains associated with pain and cognition.

  9. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: Evidence from resting-state fMRI

    International Nuclear Information System (INIS)

    Zhang, Wei; Liu, Xianjun; Zhang, Yi; Song, Lingheng; Hou, Jingming; Chen, Bing; He, Mei; Cai, Ping; Lii, Haitao

    2014-01-01

    Objective: The hippocampus expresses high levels of thyroid hormone receptors, suggesting that hippocampal functions, including cognition and regulation of mood, can be disrupted by thyroid pathology. Indeed, structural and functional alterations within the hippocampus have been observed in hyperthyroid patients. In addition to internal circuitry, hippocampal processing is dependent on extensive connections with other limbic and neocortical structures, but the effects of hyperthyroidism on functional connectivity (FC) with these areas have not been studied. The purpose of this study was to investigate possible abnormalities in the FC between the hippocampus and other neural structures in hyperthyroid patients using resting-state fMRI. Methods: Seed-based correlation analysis was performed on resting-state fMRI data to reveal possible differences in hippocampal FC between hyperthyroid patients and healthy controls. Correlation analysis was used to investigate the relationships between the strength of FC in regions showing significant group differences and clinical variables. Results: Compared to controls, hyperthyroid patients showed weaker FC between the bilateral hippocampus and both the bilateral anterior cingulate cortex (ACC) and bilateral posterior cingulate cortex (PCC), as well as between the right hippocampus and right medial orbitofrontal cortex (mOFC). Disease duration was negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC and PCC. Levels of depression and anxiety were negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC. Conclusion: Decreased functional connectivity between the hippocampus and bilateral ACC, PCC, and right mOFC may contribute to the emotional and cognitive dysfunction associated with hyperthyroidism

  10. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: Evidence from resting-state fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Wei, E-mail: will.zhang.1111@gmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People' s Armed Police Forces, Leshan 614000 (China); Liu, Xianjun, E-mail: xianjun6.liu@gmail.com [Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People' s Armed Police Forces, Leshan 614000 (China); Zhang, Yi, E-mail: yi.zhang.0833@gmail.com [Department of Radiology, Sichuan Provincial Corps Hospital, Chinese People' s Armed Police Forces, Leshan 614000 (China); Song, Lingheng, E-mail: songlh1023@hotmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Hou, Jingming, E-mail: jingminghou@hotmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Chen, Bing, E-mail: chenbing3@medmail.com.cn [Department of Endocrinology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); He, Mei, E-mail: sunnusunny0105@gmail.com [Department of Clinical Psychology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Cai, Ping, E-mail: pingc_ddd@sina.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China); Lii, Haitao, E-mail: haitaolii023@gmail.com [Department of Radiology, Southwest Hospital, Third Military Medical University, Chongqing 400038 (China)

    2014-10-15

    Objective: The hippocampus expresses high levels of thyroid hormone receptors, suggesting that hippocampal functions, including cognition and regulation of mood, can be disrupted by thyroid pathology. Indeed, structural and functional alterations within the hippocampus have been observed in hyperthyroid patients. In addition to internal circuitry, hippocampal processing is dependent on extensive connections with other limbic and neocortical structures, but the effects of hyperthyroidism on functional connectivity (FC) with these areas have not been studied. The purpose of this study was to investigate possible abnormalities in the FC between the hippocampus and other neural structures in hyperthyroid patients using resting-state fMRI. Methods: Seed-based correlation analysis was performed on resting-state fMRI data to reveal possible differences in hippocampal FC between hyperthyroid patients and healthy controls. Correlation analysis was used to investigate the relationships between the strength of FC in regions showing significant group differences and clinical variables. Results: Compared to controls, hyperthyroid patients showed weaker FC between the bilateral hippocampus and both the bilateral anterior cingulate cortex (ACC) and bilateral posterior cingulate cortex (PCC), as well as between the right hippocampus and right medial orbitofrontal cortex (mOFC). Disease duration was negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC and PCC. Levels of depression and anxiety were negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC. Conclusion: Decreased functional connectivity between the hippocampus and bilateral ACC, PCC, and right mOFC may contribute to the emotional and cognitive dysfunction associated with hyperthyroidism.

  11. Disrupted functional connectivity of the hippocampus in patients with hyperthyroidism: evidence from resting-state fMRI.

    Science.gov (United States)

    Zhang, Wei; Liu, Xianjun; Zhang, Yi; Song, Lingheng; Hou, Jingming; Chen, Bing; He, Mei; Cai, Ping; Lii, Haitao

    2014-10-01

    The hippocampus expresses high levels of thyroid hormone receptors, suggesting that hippocampal functions, including cognition and regulation of mood, can be disrupted by thyroid pathology. Indeed, structural and functional alterations within the hippocampus have been observed in hyperthyroid patients. In addition to internal circuitry, hippocampal processing is dependent on extensive connections with other limbic and neocortical structures, but the effects of hyperthyroidism on functional connectivity (FC) with these areas have not been studied. The purpose of this study was to investigate possible abnormalities in the FC between the hippocampus and other neural structures in hyperthyroid patients using resting-state fMRI. Seed-based correlation analysis was performed on resting-state fMRI data to reveal possible differences in hippocampal FC between hyperthyroid patients and healthy controls. Correlation analysis was used to investigate the relationships between the strength of FC in regions showing significant group differences and clinical variables. Compared to controls, hyperthyroid patients showed weaker FC between the bilateral hippocampus and both the bilateral anterior cingulate cortex (ACC) and bilateral posterior cingulate cortex (PCC), as well as between the right hippocampus and right medial orbitofrontal cortex (mOFC). Disease duration was negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC and PCC. Levels of depression and anxiety were negatively correlated with FC strength between the bilateral hippocampus and bilateral ACC. Decreased functional connectivity between the hippocampus and bilateral ACC, PCC, and right mOFC may contribute to the emotional and cognitive dysfunction associated with hyperthyroidism. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Altered functional connectivity architecture of the brain in medication overuse headache using resting state fMRI.

    Science.gov (United States)

    Chen, Zhiye; Chen, Xiaoyan; Liu, Mengqi; Dong, Zhao; Ma, Lin; Yu, Shengyuan

    2017-12-01

    Functional connectivity density (FCD) could identify the abnormal intrinsic and spontaneous activity over the whole brain, and a seed-based resting-state functional connectivity (RSFC) could further reveal the altered functional network with the identified brain regions. This may be an effective assessment strategy for headache research. This study is to investigate the RSFC architecture changes of the brain in the patients with medication overuse headache (MOH) using FCD and RSFC methods. 3D structure images and resting-state functional MRI data were obtained from 37 MOH patients, 18 episodic migraine (EM) patients and 32 normal controls (NCs). FCD was calculated to detect the brain regions with abnormal functional activity over the whole brain, and the seed-based RSFC was performed to explore the functional network changes in MOH and EM. The decreased FCD located in right parahippocampal gyrus, and the increased FCD located in left inferior parietal gyrus and right supramarginal gyrus in MOH compared with NC, and in right caudate and left insula in MOH compared with EM. RSFC revealed that decreased functional connectivity of the brain regions with decreased FCD anchored in the right dorsal-lateral prefrontal cortex, right frontopolar cortex in MOH, and in left temporopolar cortex and bilateral visual cortices in EM compared with NC, and in frontal-temporal-parietal pattern in MOH compared with EM. These results provided evidence that MOH and EM suffered from altered intrinsic functional connectivity architecture, and the current study presented a new perspective for understanding the neuromechanism of MOH and EM pathogenesis.

  13. The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity

    OpenAIRE

    Hallquist, Michael N.; Hwang, Kai; Luna, Beatriz

    2013-01-01

    Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent...

  14. Interhemispheric Functional and Structural Disconnection in Alzheimer's Disease: A Combined Resting-State fMRI and DTI Study.

    Directory of Open Access Journals (Sweden)

    Zhiqun Wang

    Full Text Available Neuroimaging studies have demonstrated that patients with Alzheimer's disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI, as well as 16 cognitive normal healthy subjects (CN. The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of ADfunctional connectivity changes in the AD and MCI, which can be significantly correlated with the integrity changes in the midline white matter structures. These results suggest that VMHC can be used as a biomarker for the degeneration of the interhemispheric connectivity in AD.

  15. Interhemispheric functional connectivity and its relationships with clinical characteristics in major depressive disorder: a resting state fMRI study.

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    Li Wang

    Full Text Available BACKGROUND: Abnormalities in large-scale, structural and functional brain connectivity have been increasingly reported in patients with major depressive disorder (MDD. However, MDD-related alterations in functional interaction between the cerebral hemispheres are still not well understood. Resting state fMRI, which reveals spontaneous neural fluctuations in blood oxygen level dependent signals, provides a means to detect interhemispheric functional coherence. We examined the resting state functional connectivity (RSFC between the two hemispheres and its relationships with clinical characteristics in MDD patients using a recently proposed measurement named "voxel-mirrored homotopic connectivity (VMHC". METHODOLOGY/PRINCIPAL FINDINGS: We compared the interhemispheric RSFC, computed using the VMHC approach, of seventeen first-episode drug-naive patients with MDD and seventeen healthy controls. Compared to the controls, MDD patients showed significant VMHC decreases in the medial orbitofrontal gyrus, parahippocampal gyrus, fusiform gyrus, and occipital regions including the middle occipital gyrus and cuneus. In MDD patients, a negative correlation was found between VMHC of the fusiform gyrus and illness duration. Moreover, there were several regions whose VMHC showed significant negative correlations with the severity of cognitive disturbance, including the prefrontal regions, such as middle and inferior frontal gyri, and two regions in the cereballar crus. CONCLUSIONS/SIGNIFICANCE: These findings suggest that the functional coordination between homotopic brain regions is impaired in MDD patients, thereby providing new evidence supporting the interhemispheric connectivity deficits of MDD. The significant correlations between the VMHC and clinical characteristics in MDD patients suggest potential clinical implication of VMHC measures for MDD. Interhemispheric RSFC may serve as a useful screening method for evaluating MDD where neural connectivity is

  16. Identification of Voxels Confounded by Venous Signals Using Resting-State fMRI Functional Connectivity Graph Clustering

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    Klaudius eKalcher

    2015-12-01

    Full Text Available Identifying venous voxels in fMRI datasets is important to increase the specificity of fMRI analyses to microvasculature in the vicinity of the neural processes triggering the BOLD response. This is, however, difficult to achieve in particular in typical studies where magnitude images of BOLD EPI are the only data available. In this study, voxelwise functional connectivity graphs were computed on minimally preprocessed low TR (333 ms multiband resting-state fMRI data, using both high positive and negative correlations to define edges between nodes (voxels. A high correlation threshold for binarization ensures that most edges in the resulting sparse graph reflect the high coherence of signals in medium to large veins. Graph clustering based on the optimization of modularity was then employed to identify clusters of coherent voxels in this graph, and all clusters of 50 or more voxels were then interpreted as corresponding to medium to large veins. Indeed, a comparison with SWI reveals that 75.6 ± 5.9% of voxels within these large clusters overlap with veins visible in the SWI image or lie outside the brain parenchyma. Some of the remainingdifferences between the two modalities can be explained by imperfect alignment or geometric distortions between the two images. Overall, the graph clustering based method for identifying venous voxels has a high specificity as well as the additional advantages of being computed in the same voxel grid as the fMRI dataset itself and not needingany additional data beyond what is usually acquired (and exported in standard fMRI experiments.

  17. Mapping brain functional alterations in betel-quid chewers using resting-state fMRI and network analysis.

    Science.gov (United States)

    Weng, Jun-Cheng; Chou, Yu-Syuan; Huang, Guo-Joe; Tyan, Yeu-Sheng; Ho, Ming-Chou

    2018-04-01

    The World Health Organization regards betel quid (BQ) as a human carcinogen, and DSM-IV and ICD-10 dependence symptoms may develop with its heavy use. BQ's possible effects of an enhanced reward system and disrupted inhibitory control may increase the likelihood of habitual substance use. The current study aimed to employ resting-state fMRI to examine the hypothesized enhanced reward system (e.g., the basal forebrain system) and disrupted inhibitory control (e.g., the prefrontal system) in BQ chewers. The current study recruited three groups of 48 male participants: 16 BQ chewers, 15 tobacco- and alcohol-user controls, and 17 healthy controls. We used functional connectivity (FC), mean fractional amplitude of low-frequency fluctuations (mfALFF), and mean regional homogeneity (mReHo) to evaluate functional alternations in BQ chewers. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the functional network differences among the three groups. Our hypothesis was partially supported: the enhanced reward system for the BQ chewers (e.g., habitual drug-seeking behavior) was supported; however, their inhibitory control was relatively preserved. In addition, we reported that the BQ chewers may have enhanced visuospatial processing and decreased local segregation. The current results (showing an enhanced reward system in the chewers) provided the clinicians with important insight for the future development of an effective abstinence treatment.

  18. Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

    Science.gov (United States)

    DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

    2017-02-01

    We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

  19. Alternations of functional connectivity in amblyopia patients: a resting-state fMRI study

    Science.gov (United States)

    Wang, Jieqiong; Hu, Ling; Li, Wenjing; Xian, Junfang; Ai, Likun; He, Huiguang

    2014-03-01

    Amblyopia is a common yet hard-to-cure disease in children and results in poor or blurred vision. Some efforts such as voxel-based analysis, cortical thickness analysis have been tried to reveal the pathogenesis of amblyopia. However, few studies focused on alterations of the functional connectivity (FC) in amblyopia. In this study, we analyzed the abnormalities of amblyopia patients by both the seed-based FC with the left/right primary visual cortex and the network constructed throughout the whole brain. Experiments showed the following results: (1)As for the seed-based FC analysis, FC between superior occipital gyrus and the primary visual cortex was found to significantly decrease in both sides. The abnormalities were also found in lingual gyrus. The results may reflect functional deficits both in dorsal stream and ventral stream. (2)Two increased functional connectivities and 64 decreased functional connectivities were found in the whole brain network analysis. The decreased functional connectivities most concentrate in the temporal cortex. The results suggest that amblyopia may be caused by the deficits in the visual information transmission.

  20. Changes in low-frequency fluctuations in patients with antisocial personality disorder revealed by resting-state functional MRI.

    Directory of Open Access Journals (Sweden)

    Huasheng Liu

    Full Text Available Antisocial Personality Disorder (APD is a personality disorder that is most commonly associated with the legal and criminal justice systems. The study of the brain in APD has important implications in legal contexts and in helping ensure social stability. However, the neural contribution to the high prevalence of APD is still unclear. In this study, we used resting-state functional magnetic resonance imaging (fMRI to investigate the underlying neural mechanisms of APD. Thirty-two healthy individuals and thirty-five patients with APD were recruited. The amplitude of low-frequency fluctuations (ALFF was analyzed for the whole brain of all subjects. Our results showed that APD patients had a significant reduction in the ALFF in the right orbitofrontal cortex, the left temporal pole, the right inferior temporal gyrus, and the left cerebellum posterior lobe compared to normal controls. We observed that the right orbitofrontal cortex had a negative correlation between ALFF values and MMPI psychopathic deviate scores. Alterations in ALFF in these specific brain regions suggest that APD patients may be associated with abnormal activities in the fronto-temporal network. We propose that our results may contribute in a clinical and forensic context to a better understanding of APD.

  1. Parameterized hemodynamic response function data of healthy individuals obtained from resting-state functional MRI in a 7T MRI scanner

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    D. Rangaprakash

    2018-04-01

    Full Text Available Functional magnetic resonance imaging (fMRI, being an indirect measure of brain activity, is mathematically defined as a convolution of the unmeasured latent neural signal and the hemodynamic response function (HRF. The HRF is known to vary across the brain and across individuals, and it is modulated by neural as well as non-neural factors. Three parameters characterize the shape of the HRF, which is obtained by performing deconvolution on resting-state fMRI data: response height, time-to-peak and full-width at half-max. The data provided here, obtained from 47 healthy adults, contains these three HRF parameters at every voxel in the brain, as well as HRF parameters from the default-mode network (DMN. In addition, we have provided functional connectivity (FC data from the same DMN regions, obtained for two cases: data with deconvolution (HRF variability minimized and data with no deconvolution (HRF variability corrupted. This would enable researchers to compare regional changes in HRF with corresponding FC differences, to assess the impact of HRF variability on FC. Importantly, the data was obtained in a 7T MRI scanner. While most fMRI studies are conducted at lower field strengths, like 3T, ours is the first study to report HRF data obtained at 7T. FMRI data at ultra-high fields contains larger contributions from small vessels, consequently HRF variability is lower for small vessels at higher field strengths. This implies that findings made from this data would be more conservative than from data acquired at lower fields, such as 3T. Results obtained with this data and further interpretations are available in our recent research study (Rangaprakash et al., in press [1]. This is a valuable dataset for studying HRF variability in conjunction with FC, and for developing the HRF profile in healthy individuals, which would have direct implications for fMRI data analysis, especially resting-state connectivity modeling. This is the first public HRF

  2. Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

    Science.gov (United States)

    Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

    2012-10-15

    Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

    Science.gov (United States)

    DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

    2016-03-29

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  4. PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

    Science.gov (United States)

    Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

    2016-10-01

    The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

  5. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

    Science.gov (United States)

    Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

    2017-08-01

    The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

  6. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI.

    Science.gov (United States)

    Xu, Tingting; Cullen, Kathryn R; Mueller, Bryon; Schreiner, Mindy W; Lim, Kelvin O; Schulz, S Charles; Parhi, Keshab K

    2016-01-01

    Borderline personality disorder (BPD) is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI) data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03-0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03-0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study may add new knowledge

  7. Network analysis of functional brain connectivity in borderline personality disorder using resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Tingting Xu

    2016-01-01

    Full Text Available Borderline personality disorder (BPD is associated with symptoms such as affect dysregulation, impaired sense of self, and self-harm behaviors. Neuroimaging research on BPD has revealed structural and functional abnormalities in specific brain regions and connections. However, little is known about the topological organizations of brain networks in BPD. We collected resting-state functional magnetic resonance imaging (fMRI data from 20 patients with BPD and 10 healthy controls, and constructed frequency-specific functional brain networks by correlating wavelet-filtered fMRI signals from 82 cortical and subcortical regions. We employed graph-theory based complex network analysis to investigate the topological properties of the brain networks, and employed network-based statistic to identify functional dysconnections in patients. In the 0.03–0.06 Hz frequency band, compared to controls, patients with BPD showed significantly larger measures of global network topology, including the size of largest connected graph component, clustering coefficient, small-worldness, and local efficiency, indicating increased local cliquishness of the functional brain network. Compared to controls, patients showed lower nodal centrality at several hub nodes but greater centrality at several non-hub nodes in the network. Furthermore, an interconnected subnetwork in 0.03–0.06 Hz frequency band was identified that showed significantly lower connectivity in patients. The links in the subnetwork were mainly long-distance connections between regions located at different lobes; and the mean connectivity of this subnetwork was negatively correlated with the increased global topology measures. Lastly, the key network measures showed high correlations with several clinical symptom scores, and classified BPD patients against healthy controls with high accuracy based on linear discriminant analysis. The abnormal topological properties and connectivity found in this study

  8. Regional homogeneity changes in hemodialysis patients with end stage renal disease: in vivo resting-state functional MRI study.

    Directory of Open Access Journals (Sweden)

    Cheng Li

    Full Text Available OBJECTIVE: To prospectively investigate and detect early cerebral regional homogeneity (ReHo changes in neurologically asymptomatic patients with end stage renal disease (ESRD using in vivo resting-state functional MR imaging (Rs-fMRI. METHODS: We enrolled 20 patients (15 men, 5 women; meanage, 37.1 years; range, 19-49 years with ESRD and 20 healthy controls (15 men, 5 women; mean age, 38.3 years; range, 28-49 years. The mean duration of hemodialysis for the patient group was 10.7±6.4 monthes. There was no significant sex or age difference between the ESRD and control groups. Rs-fMRI was performed using a gradient-echo echo-planar imaging sequence. ReHo was calculated using software (DPARSF. Voxel-based analysis of the ReHo maps between ESRD and control groups was performed with a two-samples t test. Statistical maps were set at P value less than 0.05 and were corrected for multiple comparisons. The Mini-Mental State Examination (MMSE was administered to all participants at imaging. RESULTS: ReHo values were increased in the bilateral superior temporal gyrus and left medial frontal gyrus in the ERSD group compared with controls, but a significantly decreased ReHo value was found in the right middle temporal gyrus. There was no significant correlation between ReHo values and the duration of hemodialysis in the ESRD group. Both the patients and control subjects had normal MMSE scores (≥28. CONCLUSIONS: Our finding revealed that abnormal brain activity was distributed mainly in the memory and cognition related cotices in patients with ESRD. The abnormal spontaneous neuronal activity in those areas provide information on the neural mechanisms underlying cognitive impairment in patients with ESRD, and demonstrate that Rs-fMRI with ReHo analysis is a useful non-invasive imaging tool for the detection of early cerebral ReHo changes in hemodialysis patients with ESRD.

  9. Sparse dictionary learning of resting state fMRI networks.

    Science.gov (United States)

    Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

    2012-07-02

    Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

  10. Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

    Science.gov (United States)

    Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

    2016-01-01

    Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

  11. Disrupted Topological Organization in Whole-Brain Functional Networks of Heroin-Dependent Individuals: A Resting-State fMRI Study

    OpenAIRE

    Jiang, Guihua; Wen, Xue; Qiu, Yingwei; Zhang, Ruibin; Wang, Junjing; Li, Meng; Ma, Xiaofen; Tian, Junzhang; Huang, Ruiwang

    2013-01-01

    Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subj...

  12. Altered Brain Functional Connectome in Migraine with and without Restless Legs Syndrome: A Resting-State Functional MRI Study

    Directory of Open Access Journals (Sweden)

    Fu-Chi Yang

    2018-01-01

    Full Text Available BackgroundMigraine is frequently comorbid with restless legs syndrome (RLS, both displaying functional connectivity (FC alterations in multiple brain networks, although the neurological basis of this association is unknown.MethodsWe performed resting-state functional magnetic resonance imaging and network-wise analysis of FC in migraine patients with and without RLS and healthy controls (CRL. Network-based statistics (NBS and composite FC matrix analyses were performed to identify the patterns of FC changes. Correlation analyses were performed to identify associations between alterations in FC and clinical profiles.ResultsNBS results revealed that both migraine patients with and without RLS exhibited lower FC than CRL in the dorsal attention, salience, default mode, cingulo-opercular, visual, frontoparietal, auditory, and sensory/somatomotor networks. Further composite FC matrix analyses revealed differences in FC of the salience, default mode to subcortical and frontoparietal, auditory to salience, and memory retrieval networks between migraine patients with and without RLS. There was a trend toward a negative association between RLS severity and cross-network abnormalities in the default mode to subcortical network.DiscussionMigraine patients with and without RLS exhibit disruptions of brain FC. Such findings suggest that these disorders are associated with differential neuropathological mechanisms and may aid in the future development of neuroimaging-driven biomarkers for these conditions.

  13. Functional connectivity of the ventral tegmental area and avolition in subjects with schizophrenia: a resting state functional MRI study.

    Science.gov (United States)

    Giordano, Giulia Maria; Stanziano, Mario; Papa, Michele; Mucci, Armida; Prinster, Anna; Soricelli, Andrea; Galderisi, Silvana

    2018-04-10

    Avolition, a deficit in goal-directed behavior, is a key aspect of negative symptoms. It is highly prevalent in schizophrenia and is associated to poor functional outcome and to measures of real life motivation, indicating that central to the concept is the lack of interest and motivation. In this study we tested the hypothesis that avolition is related to altered connectivity within dopaminergic cortico-striatal circuits involved in motivation processes. Since dopamine input to these circuits derives mostly from the ventro-tegmental area (VTA), we investigated the relationships between the resting-state functional connectivity (RS-FC) of the VTA and avolition in twenty-six subjects with schizophrenia (SCZ), treated with second-generation antipsychotics only, compared to twenty-two healthy controls (HC). SCZ, in comparison to HC, showed significantly reduced RS-FC of the VTA with bilateral ventro-lateral prefrontal cortex (VLPFC), bilateral insular cortex (IC) and right (R) lateral occipital complex (LOC) and increased RS-FC of the VTA with bilateral dorso-lateral prefrontal cortex (DLPFC). Significant negative correlations were found between avolition and RS-FC of the VTA with the bilateral IC, R VLPFC and R LOC. According to our findings, avolition is linked to a disconnectivity of the VTA from several key cortical regions involved in the integration of value information with action selection. These findings are in line with translational animal models of "auto-activation apathy". Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.

  14. Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS)

    OpenAIRE

    Fox, Michael D.; Halko, Mark A.; Eldaief, Mark C.; Pascual-Leone, Alvaro

    2012-01-01

    Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include...

  15. Resting state functional connectivity predicts neurofeedback response

    Directory of Open Access Journals (Sweden)

    Dustin eScheinost

    2014-09-01

    Full Text Available Tailoring treatments to the specific needs and biology of individual patients – personalized medicine – requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD. Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI, to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC and anterior prefrontal cortex, Brodmann area (BA 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety.

  16. How motor, cognitive and musical expertise shapes the brain: Focus on fMRI and EEG resting-state functional connectivity

    DEFF Research Database (Denmark)

    Cantou, Pauline; Platel, Hervé; Desgranges, Béatrice

    2017-01-01

    about functional cerebral reorganization due to expertise at the whole-brain level and might facilitate comparison across studies. Resting-state functional MRI and EEG makes it possible to explore the functional traces of expertise in the brain by measuring temporal correlations of blood oxygen level......, to determine whether there is a domain-specific neural signature of expertise. After highlighting expertise-related changes within resting-state networks for each domain, we discuss their specificity to the trained activity and the methodological considerations concerning different conditions and analyses used......-dependent (BOLD) and spontaneous neural activity fluctuations at rest. Since these correlations are thought to reflect a prior history co-activation of brain regions, we propose reviewing studies that focused on the effects of expertise in the motor, cognitive and musical domains on brain plasticity at rest...

  17. Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

    Science.gov (United States)

    Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

    2017-10-01

    Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.

  18. Altered regional homogeneity in the development of minimal hepatic encephalopathy: a resting-state functional MRI study.

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    Ling Ni

    Full Text Available BACKGROUND: Little is known about how spontaneous brain activity progresses from non-hepatic encephalopathy (non-HE to minimal HE (MHE. The purpose of this study was to evaluate the evolution pattern of spontaneous brain activities in cirrhotic patients using resting-state fMRI with a regional homogeneity (ReHo method. METHODOLOGY/PRINCIPAL FINDINGS: Resting-state fMRI data were acquired in 47 cirrhotic patients (minimal HE [MHE], n = 20, and non-HE, n = 27 and 25 age-and sex-matched healthy controls. The Kendall's coefficient of concordance (KCC was used to measure the regional homogeneity. The regional homogeneity maps were compared with ANOVA tests among MHE, non-HE, and healthy control groups and t-tests between each pair in a voxel-wise way. Correlation analyses were performed to explore the relationships between regional ReHo values and Child-Pugh scores, number connection test type A (NCT-A, digit symbol test (DST scores, venous blood ammonia levels. Compared with healthy controls, both MHE and non-HE patients showed decreased ReHo in the bilateral frontal, parietal and temporal lobes and increased ReHo in the bilateral caudate. Compared with the non-HE, MHE patients showed decreased ReHo in the bilateral precuneus, cuneus and supplementary motor area (SMA. The NCT-A of cirrhotic patients negatively correlated with ReHo values in the precuneus, cuneus and lingual gyrus. DST scores positively correlated with ReHo values in the cuneus, precuneus and lingual gyrus, and negatively correlated with ReHo values in the bilateral caudate (P<0.05, AlphaSim corrected. CONCLUSIONS/SIGNIFICANCE: Diffused abnormal homogeneity of baseline brain activity was nonspecific for MHE, and only the progressively decreased ReHo in the SMA and the cuneus, especially for the latter, might be associated with the development of MHE. The ReHo analysis may be potentially valuable for detecting the development from non-HE to MHE.

  19. Effect of Integrated Cognitive Therapy on Hippocampal Functional Connectivity Patterns in Stroke Patients with Cognitive Dysfunction: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Shanli Yang

    2014-01-01

    Full Text Available Objective. This study aimed to identify abnormal hippocampal functional connectivity (FC following ischemic stroke using resting-state fMRI. We also explored whether abnormal hippocampal FC could be modulated by integrated cognitive therapy and tested whether these alterations were associated with cognitive performance. Methods. 18 right-handed cognitively impaired ischemic stroke patients and 18 healty control (HC subjects were included in this study. Stroke subjects were scanned at baseline and after integrated cognitive therapy, while HCs were only scanned at baseline, to identify regions that show significant correlations with the seed region. Behavioral and cognitive assessments were obtained before each scan. Results. During the resting state, we found abnormal hippocampal FC associated with temporal regions, insular cortex, cerebellum, and prefrontal cortex in stroke patients compared to HCs. After integrated cognitive therapy, however, the stroke group showed increased hippocampal FC mainly located in the prefrontal gyrus and the default mode network (DMN. Altered hippocampal FC was associated with cognitive improvement. Conclusion. Resting-state fMRI may provide novel insight into the study of functional networks in the brain after stroke. Furthermore, altered hippocampal FC may be a compensatory mechanism for cognitive recovery after ischemic stroke.

  20. Altered brain function in new onset childhood acute lymphoblastic leukemia before chemotherapy: A resting-state fMRI study.

    Science.gov (United States)

    Hu, Zhanqi; Zou, Dongfang; Mai, Huirong; Yuan, Xiuli; Wang, Lihong; Li, Yue; Liao, Jianxiang; Liu, Liwei; Liu, Guosheng; Zeng, Hongwu; Wen, Feiqiu

    2017-10-01

    Cognitive impairments had been reported in childhood acute lymphoblastic leukemia, what caused the impairments needed to be demonstrated, chemotherapy-related or the disease itself. The primary aim of this exploratory investigation was to determine if there were changes in brain function of children with acute lymphoblastic leukemia before chemotherapy. In this study, we advanced a measure named regional homogeneity to evaluate the resting-state brain activities, intelligence quotient test was performed at same time. Using regional homogeneity, we first investigated the resting state brain function in patients with new onset childhood acute lymphoblastic leukemia before chemotherapy, healthy children as control. The decreased ReHo values were mainly founded in the default mode network and left frontal lobe, bilateral inferior parietal lobule, bilateral temporal lobe, bilateral occipital lobe, precentral gyrus, bilateral cerebellum in the newly diagnosed acute lymphoblastic leukemia patients compared with the healthy control. While in contrast, increased ReHo values were mainly shown in the right frontal lobe (language area), superior frontal gyrus-R, middle frontal gyrus-R and inferior parietal lobule-R for acute lymphoblastic leukemia patients group. There were no significant differences for intelligence quotient measurements between the acute lymphoblastic leukemia patient group and the healthy control in performance intelligence quotient, verbal intelligence quotient, total intelligence quotient. The altered brain functions are associated with cognitive change and language, it is suggested that there may be cognition impairment before the chemotherapy. Regional homogeneity by functional magnetic resonance image is a sensitive way for early detection on brain damage in childhood acute lymphoblastic leukemia. Copyright © 2017 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

  1. Functional connectivity of motor cortical network in patients with brachial plexus avulsion injury after contralateral cervical nerve transfer: a resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Aihong; Cheng, Xiaoguang; Liang, Wei; Bai, Rongjie [The 4th Medical College of Peking University, Department of Radiology, Beijing Jishuitan Hospital, Xicheng Qu, Beijing (China); Wang, Shufeng; Xue, Yunhao; Li, Wenjun [The 4th Medical College of Peking University, Department of Hand Surgery, Beijing Jishuitan Hospital, Beijing (China)

    2017-03-15

    The purpose of this study is to assess the functional connectivity of the motor cortical network in patients with brachial plexus avulsion injury (BPAI) after contralateral C7 nerve transfer, using resting-state functional magnetic resonance imaging (RS-fMRI). Twelve patients with total brachial plexus root avulsion underwent RS-fMRI after contralateral C7 nerve transfer. Seventeen healthy volunteers were also included in this fMRI study as controls. The hand motor seed regions were defined as region of interests in the bilateral hemispheres. The seed-based functional connectivity was calculated in all the subjects. Differences in functional connectivity of the motor cortical network between patients and healthy controls were compared. The inter-hemispheric functional connectivity of the M1 areas was increased in patients with BPAI compared with the controls. The inter-hemispheric functional connectivity between the supplementary motor areas was reduced bilaterally. The resting-state inter-hemispheric functional connectivity of the bilateral M1 areas is altered in patients after contralateral C7 nerve transfer, suggesting a functional reorganization of cerebral cortex. (orig.)

  2. Functional connectivity of motor cortical network in patients with brachial plexus avulsion injury after contralateral cervical nerve transfer: a resting-state fMRI study

    International Nuclear Information System (INIS)

    Yu, Aihong; Cheng, Xiaoguang; Liang, Wei; Bai, Rongjie; Wang, Shufeng; Xue, Yunhao; Li, Wenjun

    2017-01-01

    The purpose of this study is to assess the functional connectivity of the motor cortical network in patients with brachial plexus avulsion injury (BPAI) after contralateral C7 nerve transfer, using resting-state functional magnetic resonance imaging (RS-fMRI). Twelve patients with total brachial plexus root avulsion underwent RS-fMRI after contralateral C7 nerve transfer. Seventeen healthy volunteers were also included in this fMRI study as controls. The hand motor seed regions were defined as region of interests in the bilateral hemispheres. The seed-based functional connectivity was calculated in all the subjects. Differences in functional connectivity of the motor cortical network between patients and healthy controls were compared. The inter-hemispheric functional connectivity of the M1 areas was increased in patients with BPAI compared with the controls. The inter-hemispheric functional connectivity between the supplementary motor areas was reduced bilaterally. The resting-state inter-hemispheric functional connectivity of the bilateral M1 areas is altered in patients after contralateral C7 nerve transfer, suggesting a functional reorganization of cerebral cortex. (orig.)

  3. The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity.

    Science.gov (United States)

    Hallquist, Michael N; Hwang, Kai; Luna, Beatriz

    2013-11-15

    Recent resting-state functional connectivity fMRI (RS-fcMRI) research has demonstrated that head motion during fMRI acquisition systematically influences connectivity estimates despite bandpass filtering and nuisance regression, which are intended to reduce such nuisance variability. We provide evidence that the effects of head motion and other nuisance signals are poorly controlled when the fMRI time series are bandpass-filtered but the regressors are unfiltered, resulting in the inadvertent reintroduction of nuisance-related variation into frequencies previously suppressed by the bandpass filter, as well as suboptimal correction for noise signals in the frequencies of interest. This is important because many RS-fcMRI studies, including some focusing on motion-related artifacts, have applied this approach. In two cohorts of individuals (n=117 and 22) who completed resting-state fMRI scans, we found that the bandpass-regress approach consistently overestimated functional connectivity across the brain, typically on the order of r=.10-.35, relative to a simultaneous bandpass filtering and nuisance regression approach. Inflated correlations under the bandpass-regress approach were associated with head motion and cardiac artifacts. Furthermore, distance-related differences in the association of head motion and connectivity estimates were much weaker for the simultaneous filtering approach. We recommend that future RS-fcMRI studies ensure that the frequencies of nuisance regressors and fMRI data match prior to nuisance regression, and we advocate a simultaneous bandpass filtering and nuisance regression strategy that better controls nuisance-related variability. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. Decreased functional connectivity of the amygdala in Alzheimer's disease revealed by resting-state fMRI

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Hongxiang [Department of Radiology, Chinese PLA General Hospital, Beijing, 100853 (China); Liu, Yong, E-mail: yliu@nlpr.ia.ac.cn [Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); Zhou, Bo; Zhang, Zengqiang [Department of Neurology, Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing, 100853 (China); An, Ningyu [Department of Radiology, Chinese PLA General Hospital, Beijing, 100853 (China); Wang, Pan; Wang, Luning [Department of Neurology, Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing, 100853 (China); Zhang, Xi, E-mail: zhangxi@301hospital.com.cn [Department of Neurology, Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing, 100853 (China); Jiang, Tianzi [Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 (China); Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054 (China); The Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072 (Australia)

    2013-09-15

    Alzheimer's disease (AD), the most common cause of dementia, is thought to be a progressive neurodegenerative disease that is clinically characterised by a decline of memory and other cognitive functions. Mild cognitive impairment (MCI) is considered to be the prodromal stage of AD. However, the relationship between AD and MCI and the development process remains unclear. The amygdala is one of the most vulnerable structures in the early stages of AD. To our knowledge, this is the first report on the alteration of the functional connectivity of the amygdala in AD and MCI subjects. We hypothesised that the amygdala-cortical loop is impaired in AD and that these alterations relate to the disease severity. In our study, we used resting-state functional MRIs to investigate the altered amygdala connectivity patterns in 35 AD patients, 27 MCI patients and 27 age- and gender-matched normal controls (NC). Compared with the NC, the decreased functional connectivity found in the AD patients was mainly located between the amygdala and the regions that are included in the default mode, context conditioning and extinction networks. Importantly, the decreased functional connectivity between the amygdala and some of the identified regions was positively correlated with MMSE, which indicated that the cognitive function impairment is related to an altered functional connectivity pattern.

  5. Decreased functional connectivity of the amygdala in Alzheimer's disease revealed by resting-state fMRI

    International Nuclear Information System (INIS)

    Yao, Hongxiang; Liu, Yong; Zhou, Bo; Zhang, Zengqiang; An, Ningyu; Wang, Pan; Wang, Luning; Zhang, Xi; Jiang, Tianzi

    2013-01-01

    Alzheimer's disease (AD), the most common cause of dementia, is thought to be a progressive neurodegenerative disease that is clinically characterised by a decline of memory and other cognitive functions. Mild cognitive impairment (MCI) is considered to be the prodromal stage of AD. However, the relationship between AD and MCI and the development process remains unclear. The amygdala is one of the most vulnerable structures in the early stages of AD. To our knowledge, this is the first report on the alteration of the functional connectivity of the amygdala in AD and MCI subjects. We hypothesised that the amygdala-cortical loop is impaired in AD and that these alterations relate to the disease severity. In our study, we used resting-state functional MRIs to investigate the altered amygdala connectivity patterns in 35 AD patients, 27 MCI patients and 27 age- and gender-matched normal controls (NC). Compared with the NC, the decreased functional connectivity found in the AD patients was mainly located between the amygdala and the regions that are included in the default mode, context conditioning and extinction networks. Importantly, the decreased functional connectivity between the amygdala and some of the identified regions was positively correlated with MMSE, which indicated that the cognitive function impairment is related to an altered functional connectivity pattern

  6. Alteration of functional connectivity within visuospatial working memory-related brain network in patients with right temporal lobe epilepsy: a resting-state fMRI study.

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    Lv, Zong-xia; Huang, Dong-Hong; Ye, Wei; Chen, Zi-rong; Huang, Wen-li; Zheng, Jin-ou

    2014-06-01

    This study aimed to investigate the resting-state brain network related to visuospatial working memory (VSWM) in patients with right temporal lobe epilepsy (rTLE). The functional mechanism underlying the cognitive impairment in VSWM was also determined. Fifteen patients with rTLE and 16 healthy controls matched for age, gender, and handedness underwent a 6-min resting-state functional MRI session and a neuropsychological test using VSWM_Nback. The VSWM-related brain network at rest was extracted using multiple independent component analysis; the spatial distribution and the functional connectivity (FC) parameters of the cerebral network were compared between groups. Behavioral data were subsequently correlated with the mean Z-value in voxels showing significant FC difference during intergroup comparison. The distribution of the VSWM-related resting-state network (RSN) in the group with rTLE was virtually consistent with that in the healthy controls. The distribution involved the dorsolateral prefrontal lobe and parietal lobe in the right hemisphere and the partial inferior parietal lobe and posterior lobe of the cerebellum in the left hemisphere (pright superior frontal lobe (BA8), right middle frontal lobe, and right ventromedial prefrontal lobe compared with the controls (pright superior frontal lobe (BA11), right superior parietal lobe, and left posterior lobe of the cerebellum (prights reserved.

  7. Hierarchical Functional Modularity in the Resting-State Human Brain

    NARCIS (Netherlands)

    Ferrarini, Luca; Veer, Ilya M.; Baerends, Evelinda; van Tol, Marie-Jose; Renken, Remco J.; van der Wee, Nic J. A.; Veltman, Dirk. J.; Aleman, Andre; Zitman, Frans G.; Penninx, Brenda W. J. H.; van Buchem, Mark A.; Reiber, Johan H. C.; Rombouts, Serge A. R. B.; Milles, Julien

    Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a

  8. Hierarchical Functional Modularity in the Resting-State Human Brain

    NARCIS (Netherlands)

    Ferrarini, L.; Veer, I.M.; Baerends, E.; van Tol, M.J.; Renken, R.J.; van der Wee, N.J.A.; Veltman, D.J.; Aleman, A.; Zitman, F.G.; Penninx, B.W.J.H.; van Buchem, M.A.; Reiber, J.H.C.; Rombouts, S.A.R.B.; Milles, J.

    2009-01-01

    Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a

  9. Characterizing Resting-State Brain Function Using Arterial Spin Labeling

    Science.gov (United States)

    Jann, Kay; Wang, Danny J.J.

    2015-01-01

    Abstract Arterial spin labeling (ASL) is an increasingly established magnetic resonance imaging (MRI) technique that is finding broader applications in studying the healthy and diseased brain. This review addresses the use of ASL to assess brain function in the resting state. Following a brief technical description, we discuss the use of ASL in the following main categories: (1) resting-state functional connectivity (FC) measurement: the use of ASL-based cerebral blood flow (CBF) measurements as an alternative to the blood oxygen level-dependent (BOLD) technique to assess resting-state FC; (2) the link between network CBF and FC measurements: the use of network CBF as a surrogate of the metabolic activity within corresponding networks; and (3) the study of resting-state dynamic CBF-BOLD coupling and cerebral metabolism: the use of dynamic CBF information obtained using ASL to assess dynamic CBF-BOLD coupling and oxidative metabolism in the resting state. In addition, we summarize some future challenges and interesting research directions for ASL, including slice-accelerated (multiband) imaging as well as the effects of motion and other physiological confounds on perfusion-based FC measurement. In summary, this work reviews the state-of-the-art of ASL and establishes it as an increasingly viable MRI technique with high translational value in studying resting-state brain function. PMID:26106930

  10. Abnormal regional spontaneous neural activity in visual pathway in retinal detachment patients: a resting-state functional MRI study

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    Huang X

    2017-11-01

    Full Text Available Xin Huang,1,2,* Dan Li,3,* Hai-Jun Li,3 Yu-Lin Zhong,1 Shelby Freeberg,4 Jing Bao,1 Xian-Jun Zeng,3 Yi Shao1 1Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Clinical Ophthalmology Institute, Nanchang, Jiangxi, People’s Republic of China; 2Department of Ophthalmology, Eye Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, People’s Republic of China; 3Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 4Department of Ophthalmology, University of Florida, Gainesville, FL, USA *These authors contributed equally to this work Objective: The aim of the study was to investigate changes of brain neural homogeneity in retinal detachment (RD patients using the regional homogeneity (ReHo method to understand their relationships with clinical features. Materials and methods: A total of 30 patients with RD (16 men and 14 women, and 30 healthy controls (HCs (16 men and 14 women closely matched in age and sex were recruited. Resting-state functional magnetic resonance imaging scans were performed for all subjects. The ReHo method was used to investigate the brain regional neural homogeneity. Patients with RD were distinguished from HCs by receiver operating characteristic curve. The relationships between the mean ReHo signal values in many brain regions and clinical features in RD patients were calculated by Pearson correlation analysis. Results: Compared with HCs, RD patients had significantly decreased ReHo values in the right occipital lobe, right superior temporal gyrus, bilateral cuneus and left middle frontal gyrus. Moreover, we found that the mean ReHo signal of the bilateral cuneus showed positive relationships with the duration of the RD (r=0.392, P=0.032. Conclusion: The RD patients showed brain neural homogeneity dysfunction in the visual pathway, which may underline the pathological mechanism

  11. Large scale fusion of gray matter and resting-state functional MRI reveals common and shared biological markers across the psychosis spectrum in the B-SNIP cohort

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    Zheng eWang

    2015-12-01

    Full Text Available To investigate whether aberrant interactions between brain structure and function present similarly or differently across probands with psychotic illnesses (schizophrenia (SZ, schizoaffective disorder (SAD, and bipolar I disorder with psychosis (BP and whether these deficits are shared with their first-degree non-psychotic relatives. A total of 1199 subjects were assessed, including 220 SZ, 147 SAD, 180 psychotic BP, 150 first-degree relatives of SZ, 126 SAD relatives, 134 BP relatives and 242 healthy controls. All subjects underwent structural MRI (sMRI and resting-state functional MRI (rs-fMRI scanning. Joint independent analysis (jICA was used to fuse sMRI gray matter (GM and rs-fMRI amplitude of low frequency fluctuations (ALFF data to identify the relationship between the two modalities. Joint ICA revealed two significantly fused components. The association between functional brain alteration in a prefrontal-striatal-thalamic-cerebellar network and structural abnormalities in the default mode network (DMN was found to be common across psychotic diagnoses and correlated with cognitive function, social function and Schizo-Bipolar Scale (SBS scores. The fused alteration in the temporal lobe was unique to SZ and SAD. The above effects were not seen in any relative group (including those with cluster-A personality. Using a multivariate fused approach involving two widely used imaging markers we demonstrate both shared and distinct biological traits across the psychosis spectrum. Further, our results suggest that the above traits are psychosis biomarkers rather than endophenotypes.

  12. Connectivity differences between adult male and female patients with attention deficit hyperactivity disorder according to resting-state functional MRI

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    Bo-yong Park

    2016-01-01

    Full Text Available Attention deficit hyperactivity disorder (ADHD is a pervasive psychiatric disorder that affects both children and adults. Adult male and female patients with ADHD are differentially affected, but few studies have explored the differences. The purpose of this study was to quantify differences between adult male and female patients with ADHD based on neuroimaging and connectivity analysis. Resting-state functional magnetic resonance imaging scans were obtained and preprocessed in 82 patients. Group-wise differences between male and female patients were quantified using degree centrality for different brain regions. The medial-, middle-, and inferior-frontal gyrus, superior parietal lobule, precuneus, supramarginal gyrus, superior- and middle-temporal gyrus, middle occipital gyrus, and cuneus were identified as regions with significant group-wise differences. The identified regions were correlated with clinical scores reflecting depression and anxiety and significant correlations were found. Adult ADHD patients exhibit different levels of depression and anxiety depending on sex, and our study provides insight into how changes in brain circuitry might differentially impact male and female ADHD patients.

  13. Hyperactive external awareness against hypoactive internal awareness in disorders of consciousness using resting-state functional MRI: highlighting the involvement of visuo-motor modulation.

    Science.gov (United States)

    He, Jiang-Hong; Yang, Yi; Zhang, Yi; Qiu, Si-You; Zhou, Zhen-Yu; Dang, Yuan-Yuan; Dai, Yi-Wu; Liu, Yi-Jun; Xu, Ru-Xiang

    2014-08-01

    Resting-state functional MRI (fMRI) has emerged as a valuable tool to characterize the complex states encompassing disorders of consciousness (DOC). Awareness appears to comprise two coexistent, anticorrelated components named the external and internal awareness networks. The present study hypothesizes that DOC interrupts the balance between the internal and external awareness networks. To gain more understanding of this phenomenon, the present study analyzed resting-state fMRI data from 12 patients with DOC versus 12 healthy age-matched controls. The data were explored using independent component analysis and amplitude of low-frequency fluctuation (ALFF) analysis. The results indicated that DOC deactivated midline areas associated with internal awareness. In addition, external awareness was strengthened in DOC because of increased activation in the insula, lingual gyrus, paracentral and supplementary motor area. The activity patterns suggested strengthened external awareness against weakened internal awareness in DOC. In particular, increased activity found in the insula, lingual gyrus, paracentral and supplementary motor area of patients with DOC implied possible involvement of augmented visuo-motor modulation in these patients. DOC is probably related to hyperactive external awareness opposing hypoactive internal awareness. This unique pattern of brain activity may potentially be a prognostic marker for DOC. Copyright © 2014 John Wiley & Sons, Ltd.

  14. Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity

    Science.gov (United States)

    Weaver, Kurt E.; Wander, Jeremiah D.; Ko, Andrew L.; Casimo, Kaitlyn; Grabowski, Thomas J.; Ojemann, Jeffrey G.; Darvas, Felix

    2016-01-01

    Functional imaging investigations into the brain's resting state interactions have yielded a wealth of insight into the intrinsic and dynamic neural architecture supporting cognition and behavior. Electrophysiological studies however have highlighted the fact that synchrony across large-scale cortical systems is composed of spontaneous interactions occurring at timescales beyond the traditional resolution of fMRI, a feature that limits the capacity of fMRI to draw inference on the true directional relationship between network nodes. To approach the question of directionality in resting state signals, we recorded resting state functional MRI (rsfMRI) and electrocorticography (ECoG) from four human subjects undergoing invasive epilepsy monitoring. Using a seed-point based approach, we employed phase-amplitude coupling (PAC) and biPhase Locking Values (bPLV), two measures of cross-frequency coupling (CFC) to explore both outgoing and incoming connections between the seed and all non-seed, site electrodes. We observed robust PAC between a wide range of low-frequency phase and high frequency amplitude estimates. However, significant bPLV, a CFC measure of phase-phase synchrony, was only observed at specific narrow low and high frequency bandwidths. Furthermore, the spatial patterns of outgoing PAC connectivity were most closely associated with the rsfMRI connectivity maps. Our results support the hypothesis that PAC is relatively ubiquitous phenomenon serving as a mechanism for coordinating high-frequency amplitudes across distant neuronal assemblies even in absence of overt task structure. Additionally, we demonstrate that the spatial distribution of a seed-point rsfMRI sensorimotor network is strikingly similar to specific patterns of directional PAC. Specifically, the high frequency activities of distal patches of cortex owning membership in a rsfMRI sensorimotor network were most likely to be entrained to the phase of a low frequency rhythm engendered from the

  15. Altered spontaneous brain activity in patients with acute spinal cord injury revealed by resting-state functional MRI.

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    Ling Zhu

    Full Text Available Previous neuroimaging studies have provided evidence of structural and functional reorganization of brain in patients with chronic spinal cord injury (SCI. However, it remains unknown whether the spontaneous brain activity changes in acute SCI. In this study, we investigated intrinsic brain activity in acute SCI patients using a regional homogeneity (ReHo analysis based on resting-state functional magnetic resonance imaging.A total of 15 patients with acute SCI and 16 healthy controls participated in the study. The ReHo value was used to evaluate spontaneous brain activity, and voxel-wise comparisons of ReHo were performed to identify brain regions with altered spontaneous brain activity between groups. We also assessed the associations between ReHo and the clinical scores in brain regions showing changed spontaneous brain activity.Compared with the controls, the acute SCI patients showed decreased ReHo in the bilateral primary motor cortex/primary somatosensory cortex, bilateral supplementary motor area/dorsal lateral prefrontal cortex, right inferior frontal gyrus, bilateral dorsal anterior cingulate cortex and bilateral caudate; and increased ReHo in bilateral precuneus, the left inferior parietal lobe, the left brainstem/hippocampus, the left cingulate motor area, bilateral insula, bilateral thalamus and bilateral cerebellum. The average ReHo values of the left thalamus and right insula were negatively correlated with the international standards for the neurological classification of spinal cord injury motor scores.Our findings indicate that acute distant neuronal damage has an immediate impact on spontaneous brain activity. In acute SCI patients, the ReHo was prominently altered in brain regions involved in motor execution and cognitive control, default mode network, and which are associated with sensorimotor compensatory reorganization. Abnormal ReHo values in the left thalamus and right insula could serve as potential biomarkers for

  16. Altered task-based and resting-state amygdala functional connectivity following real-time fMRI amygdala neurofeedback training in major depressive disorder.

    Science.gov (United States)

    Young, Kymberly D; Siegle, Greg J; Misaki, Masaya; Zotev, Vadim; Phillips, Raquel; Drevets, Wayne C; Bodurka, Jerzy

    2018-01-01

    We have previously shown that in participants with major depressive disorder (MDD) trained to upregulate their amygdala hemodynamic response during positive autobiographical memory (AM) recall with real-time fMRI neurofeedback (rtfMRI-nf) training, depressive symptoms diminish. Here, we assessed the effect of rtfMRI-nf on amygdala functional connectivity during both positive AM recall and rest. The current manuscript consists of a secondary analysis on data from our published clinical trial of neurofeedback. Patients with MDD completed two rtfMRI-nf sessions (18 received amygdala rtfMRI-nf, 16 received control parietal rtfMRI-nf). One-week prior-to and following training participants also completed a resting-state fMRI scan. A GLM-based functional connectivity analysis was applied using a seed ROI in the left amygdala. We compared amygdala functional connectivity changes while recalling positive AMs from the baseline run to the final transfer run during rtfMRI-nf training, as well during rest from the baseline to the one-week follow-up visit. Finally, we assessed the correlation between change in depression scores and change in amygdala connectivity, as well as correlations between amygdala regulation success and connectivity changes. Following training, amygdala connectivity during positive AM recall increased with widespread regions in the frontal and limbic network. During rest, amygdala connectivity increased following training within the fronto-temporal-limbic network. During both task and resting-state analyses, amygdala-temporal pole connectivity decreased. We identified increased amygdala-precuneus and amygdala-inferior frontal gyrus connectivity during positive memory recall and increased amygdala-precuneus and amygdala-thalamus connectivity during rest as functional connectivity changes that explained significant variance in symptom improvement. Amygdala-precuneus connectivity changes also explain a significant amount of variance in neurofeedback

  17. Connectivity pattern differences bilaterally in the cerebellum posterior lobe in healthy subjects after normal sleep and sleep deprivation: a resting-state functional MRI study

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    Liu XM

    2015-05-01

    Full Text Available Xuming Liu,1 Zhihan Yan,2 Tingyu Wang,1 Xiaokai Yang,1 Feng Feng,3 Luping Fan,1 Jian Jiang4 1Department of Radiology, The Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou, 2Department of Radiology, The 2nd Affiliated Hospital of Wenzhou Medical University, Wenzhou, 3Peking Union Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 4Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, People’s Republic of China Objective: The aim of this study was to use functional magnetic resonance imaging (fMRI technique to explore the resting-state functional connectivity (rsFC differences of the bilaterial cerebellum posterior lobe (CPL after normal sleep (NS and after sleep deprivation (SD. Methods: A total of 16 healthy subjects (eight males, eight females underwent an fMRI scan twice at random: once following NS and the other following 24 hours’ SD, with an interval of 1 month between the two scans. The fMRI scanning included resting state and acupuncture stimulation. The special activated regions located during the acupuncture stimulation were selected as regions of interest for rsFC analysis. Results: Bilateral CPLs were positively activated by acupuncture stimulation. In the NS group, the left CPL showed rsFC with the bilateral CPL, bilateral frontal lobe (BFL, left precuneus and right inferior parietal lobule, while the right CPL showed rsFC with the bilateral temporal lobe, right cerebellum anterior lobe, right CPL, left frontal lobe, left anterior cingulate, right posterior cingulate, and bilateral inferior parietal lobule. In the SD group, the left CPL showed rsFC with the left posterior cingulate gyrus bilateral CPL, left precuneus, left precentral gyrus, BFL, and the left parietal lobe, while the right CPL showed rsFC with bilateral cerebellum anterior lobe, bilateral CPL, left frontal lobe and left temporal lobe. Compared with the NS group, the

  18. Identification and functional characterization of HIV-associated neurocognitive disorders with large-scale Granger causality analysis on resting-state functional MRI

    Science.gov (United States)

    Chockanathan, Udaysankar; DSouza, Adora M.; Abidin, Anas Z.; Schifitto, Giovanni; Wismüller, Axel

    2018-02-01

    Resting-state functional MRI (rs-fMRI), coupled with advanced multivariate time-series analysis methods such as Granger causality, is a promising tool for the development of novel functional connectivity biomarkers of neurologic and psychiatric disease. Recently large-scale Granger causality (lsGC) has been proposed as an alternative to conventional Granger causality (cGC) that extends the scope of robust Granger causal analyses to high-dimensional systems such as the human brain. In this study, lsGC and cGC were comparatively evaluated on their ability to capture neurologic damage associated with HIV-associated neurocognitive disorders (HAND). Functional brain network models were constructed from rs-fMRI data collected from a cohort of HIV+ and HIV- subjects. Graph theoretic properties of the resulting networks were then used to train a support vector machine (SVM) model to predict clinically relevant parameters, such as HIV status and neuropsychometric (NP) scores. For the HIV+/- classification task, lsGC, which yielded a peak area under the receiver operating characteristic curve (AUC) of 0.83, significantly outperformed cGC, which yielded a peak AUC of 0.61, at all parameter settings tested. For the NP score regression task, lsGC, with a minimum mean squared error (MSE) of 0.75, significantly outperformed cGC, with a minimum MSE of 0.84 (p < 0.001, one-tailed paired t-test). These results show that, at optimal parameter settings, lsGC is better able to capture functional brain connectivity correlates of HAND than cGC. However, given the substantial variation in the performance of the two methods at different parameter settings, particularly for the regression task, improved parameter selection criteria are necessary and constitute an area for future research.

  19. Disrupted functional connectivity of the anterior cingulate cortex in cirrhotic patients without overt hepatic encephalopathy: a resting state fMRI study.

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    Long Jiang Zhang

    Full Text Available BACKGROUND: To evaluate the changes of functional connectivity of the anterior cingulate cortex (ACC in patients with cirrhosis without overt hepatic encephalopathy (HE using resting state functional MRI. METHODOLOGY/PRINCIPAL FINDINGS: Participants included 67 cirrhotic patients (27 minimal hepatic encephalopathy (MHE and 40 cirrhotic patients without MHE (non-HE, and 40 age- and gender- matched healthy controls. rsfMRI were performed on 3 Telsa scanners. The pregenual ACC resting-state networks (RSNs were characterized by using a standard seed-based whole-brain correlation method and compared between cirrhotic patients and healthy controls. Pearson correlation analysis was performed between the ACC RSNs and venous blood ammonia levels, neuropsychological tests (number connection test type A [NCT-A] and digit symbol test [DST] scores in cirrhotic patients. All thresholds were set at P<0.05, with false discovery rate corrected. Compared with controls, non-HE and MHE patients showed significantly decreased functional connectivity in the bilateral ACC, bilateral middle frontal cortex (MFC, bilateral middle cingulate cortex (MCC, bilateral superior temporal gyri (STG/middle temporal gyri (MTG, bilateral thalami, bilateral putamen and bilateral insula, and increased functional connectivity of bilateral precuneus and left temporo-occipital lobe and bilateral lingual gyri. Compared with non-HE patients, MHE showed the decreased functional connectivity of right MCC, bilateral STG/MTG and right putamen. This indicates decreased ACC functional connectivity predominated with the increasing severity of HE. NCT-A scores negatively correlated with ACC functional connectivity in the bilateral MCC, right temporal lobe, and DST scores positively correlated with functional connectivity in the bilateral ACC and the right putamen. No correlation was found between venous blood ammonia levels and functional connectivity in ACC in cirrhotic patients. CONCLUSIONS

  20. Functional cortical changes in relapsing-remitting multiple sclerosis at amplitude configuration: a resting-state fMRI study

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    Liu H

    2016-11-01

    showed high degrees of sensitivity and specificity for distinguishing patients with RRMS from HCs. The EDSS score showed a significant negative Pearson correlation with the beta value of the caudate head (r=-0.474, P=0.047. Conclusion: RRMS is associated with disturbances in spontaneous regional brain activity in specific areas, and these specific abnormalities may provide important information about the neural mechanisms underlying behavioral impairment in RRMS. Keywords: multiple sclerosis, amplitude of low-frequency fluctuation, receiver operating characteristic, functional magnetic resonance imaging, blood oxygen level dependent, resting state

  1. [Aberrant topological properties of whole-brain functional network in chronic right-sided sensorineural hearing loss: a resting-state functional MRI study].

    Science.gov (United States)

    Zhang, Lingling; Liu, Bin; Xu, Yangwen; Yang, Ming; Feng, Yuan; Huang, Yaqing; Huan, Zhichun; Hou, Zhaorui

    2015-02-03

    To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients. In this study, we acquired resting-state BOLD- fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks. Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls. Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables. Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0. 1 - 0. 2 of sparsity. Compared to the controls, USNHL patients showed significant increase in characteristic path length and normalized characteristic path length, but significant decrease in global efficiency. Clustering coefficient, local efficiency and normalized clustering coefficient demonstrated no significant difference. Furthermore, USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss. Our results indicated the altered topological properties of whole brain functional networks in USNHL patients, which may help us to understand pathophysiologic mechanism of USNHL patients.

  2. The quest for EEG power band correlation with ICA derived fMRI resting state networks

    NARCIS (Netherlands)

    Meyer, M.C.; Janssen, R.J.; van Oort, E.S.B.; Beckmann, Christian; Barth, M.

    2013-01-01

    The neuronal underpinnings of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) resting state networks (RSNs) are still unclear. To investigate the underlying mechanisms, specifically the relation to the electrophysiological signal, we used simultaneous recordings of

  3. Distinct Neural Signatures Detected for ADHD Subtypes After Controlling for Micro-Movements in Resting State Functional Connectivity MRI Data

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    Damien eFair

    2013-02-01

    Full Text Available In recent years, there has been growing enthusiasm that functional MRI could achieve clinical utility for a broad range of neuropsychiatric disorders. However, several barriers remain. For example, the acquisition of large-scale datasets capable of clarifying the marked heterogeneity that exists in psychiatric illnesses will need to be realized. In addition, there continues to be a need for the development of image processing and analysis methods capable of separating signal from artifact. As a prototypical hyperkinetic disorder, and movement related artifact being a significant confound in functional imaging studies, ADHD offers a unique challenge. As part of the ADHD-200 Global Competition and this special edition of Frontiers, the ADHD-200 Consortium demonstrates the utility of an aggregate dataset pooled across five institutions in addressing these challenges. The work aimed to A examine the impact of emerging techniques for controlling for micro-movements, and B provide novel insights into the neural correlates of ADHD subtypes. Using SVM based MVPA we show that functional connectivity patterns in individuals are capable of differentiating the two most prominent ADHD subtypes. The application of graph-theory revealed that the Combined (ADHD-C and Inattentive (ADHD-I subtypes demonstrated some overlapping (particularly sensorimotor systems, but unique patterns of atypical connectivity. For ADHD-C, atypical connectivity was prominent in midline default network components, as well as insular cortex; in contrast, the ADHD-I group exhibited atypical patterns within the dlPFC regions and cerebellum. Systematic motion-related artifact was noted, and highlighted the need for stringent motion correction. Findings reported were robust to the specific motion correction strategy employed. These data suggest that rs-fcMRI data can be used to characterize individual patients with ADHD and to identify neural distinctions underlying the clinical

  4. Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

    Science.gov (United States)

    Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

    2012-01-01

    Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific

  5. Liver transplantation nearly normalizes brain spontaneous activity and cognitive function at 1 month: a resting-state functional MRI study.

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    Cheng, Yue; Huang, Lixiang; Zhang, Xiaodong; Zhong, Jianhui; Ji, Qian; Xie, Shuangshuang; Chen, Lihua; Zuo, Panli; Zhang, Long Jiang; Shen, Wen

    2015-08-01

    To investigate the short-term brain activity changes in cirrhotic patients with Liver transplantation (LT) using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Twenty-six cirrhotic patients as transplant candidates and 26 healthy controls were included in this study. The assessment was repeated for a sub-group of 12 patients 1 month after LT. ReHo values were calculated to evaluate spontaneous brain activity and whole brain voxel-wise analysis was carried to detect differences between groups. Correlation analyses were performed to explore the relationship between the change of ReHo with the change of clinical indexes pre- and post-LT. Compared to pre-LT, ReHo values increased in the bilateral inferior frontal gyrus (IFG), right inferior parietal lobule (IPL), right supplementary motor area (SMA), right STG and left middle frontal gyrus (MFG) in patients post-LT. Compared to controls, ReHo values of post-LT patients decreased in the right precuneus, right SMA and increased in bilateral temporal pole, left caudate, left MFG, and right STG. The changes of ReHo in the right SMA, STG and IFG were correlated with change of digit symbol test (DST) scores (P brain activity of most brain regions with decreased ReHo in pre-LT was substantially improved and nearly normalized, while spontaneous brain activity of some brain regions with increased ReHo in pre-LT continuously increased. ReHo may provide information on the neural mechanisms of LT' effects on brain function.

  6. Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression.

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    Kosuke Yoshida

    Full Text Available In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS regression to resting-state functional magnetic resonance imaging (rs-fMRI data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area.

  7. Hierarchical functional modularity in the resting-state human brain.

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    Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien

    2009-07-01

    Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc

  8. Effective artifact removal in resting state fMRI data improves detection of DMN functional connectivity alteration in Alzheimer’s disease

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    Ludovica eGriffanti

    2015-08-01

    Full Text Available Artefact removal from resting state fMRI data is an essential step for a better identification of the resting state networks and the evaluation of their functional connectivity (FC, especially in pathological conditions. There is growing interest in the development of cleaning procedures, especially those not requiring external recordings (data-driven, which are able to remove multiple sources of artefacts. It is important that only inter-subject variability due to the artefacts is removed, preserving the between-subject variability of interest - crucial in clinical applications using clinical scanners to discriminate different pathologies and monitor their staging. In Alzheimer’s disease (AD patients, decreased FC is usually observed in the posterior cingulate cortex within the default mode network (DMN, and this is becoming a possible biomarker for AD. The aim of this study was to compare four different data-driven cleaning procedures (regression of motion parameters; regression of motion parameters, mean white matter and cerebrospinal fluid signal; FMRIB's ICA-based X-noiseifier –FIX- cleanup with soft and aggressive options on data acquired at 1.5T. The approaches were compared using data from 20 elderly healthy subjects and 21 AD patients in a mild stage, in terms of their impact on within-group consistency in FC and ability to detect the typical FC alteration of the DMN in AD patients. Despite an increased within-group consistency across subjects after applying any of the cleaning approaches, only after cleaning with FIX the expected DMN FC alteration in AD was detectable. Our study validates the efficacy of artefact removal even in a relatively small clinical population, and supports the importance of cleaning fMRI data for sensitive detection of FC alterations in a clinical environment.

  9. Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study

    NARCIS (Netherlands)

    Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard Jack Anton; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F.

    2014-01-01

    The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state

  10. Phase-synchronization-based parcellation of resting state fMRI signals reveals topographically organized clusters in early visual cortex

    NARCIS (Netherlands)

    Gravel, Nicolás G; Harvey, Ben M; Renken, Remco K; Dumoulin, Serge O; Cornelissen, Frans W

    2018-01-01

    Resting-state fMRI is widely used to study brain function and connectivity. However, interpreting patterns of resting state (RS) fMRI activity remains challenging as they may arise from different neuronal mechanisms than those triggered by exogenous events. Currently, this limits the use of RS-fMRI

  11. Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

    Directory of Open Access Journals (Sweden)

    Xia Liang

    Full Text Available Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation, global signal presence (regressed or not and frequency band selection [slow-5 (0.01-0.027 Hz versus slow-4 (0.027-0.073 Hz] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR. The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics

  12. Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

    Science.gov (United States)

    Wen, Haiguang; Liu, Zhongming

    2016-06-01

    Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed

  13. Abnormal baseline brain activity in Parkinson's disease with and without REM sleep behavior disorder: A resting-state functional MRI study.

    Science.gov (United States)

    Li, Dan; Huang, Peiyu; Zang, Yufeng; Lou, Yuting; Cen, Zhidong; Gu, Quanquan; Xuan, Min; Xie, Fei; Ouyang, Zhiyuan; Wang, Bo; Zhang, Minming; Luo, Wei

    2017-09-01

    To investigate the differences in spontaneous brain activity between Parkinson's disease (PD) patients with rapid eye movement sleep behavior disorder (RBD), PD patients without RBD, and normal controls, which may shed new light on the neural mechanism of RBD. Eighteen PD patients with RBD, 16 patients without RBD, and 19 age- and gender-matched normal controls underwent clinical assessment and functional magnetic resonance imaging (fMRI) with a 3.0T scanner. Resting-state fMRI scans were collected using an echo planar imaging sequence. Amplitude of low-frequency fluctuations (ALFF) were calculated to measure spontaneous brain activity in each subject. Compared with PD patients without RBD, patients with RBD exhibited significantly decreased ALFF values (P abnormalities. Our findings provide additional insight into the neural mechanism of RBD and may drive future research to develop better treatment. 3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:697-703. © 2016 International Society for Magnetic Resonance in Medicine.

  14. Abnormal regional spontaneous neuronal activity associated with symptom severity in treatment-naive patients with obsessive-compulsive disorder revealed by resting-state functional MRI.

    Science.gov (United States)

    Qiu, Linlin; Fu, Xiangshuai; Wang, Shuai; Tang, Qunfeng; Chen, Xingui; Cheng, Lin; Zhang, Fuquan; Zhou, Zhenhe; Tian, Lin

    2017-02-15

    A large number of neuroimaging studies have revealed the dysfunction of brain activities in obsessive-compulsive disorder (OCD) during various tasks. However, regional spontaneous activity abnormalities in OCD are gradually being revealed. In this current study, we aimed to investigate cerebral regions with abnormal spontaneous activity using resting-state functional magnetic resonance imaging (fMRI) and further explored the relationship between the spontaneous neuronal activity and symptom severity of patients with OCD. Thirty-one patients with OCD and 32 age-and sex-matched normal controls received the fMRI scans and fractional amplitude of low-frequency fluctuation (fALFF) approach was applied to identify the abnormal brain activity. We found that patients with OCD showed decreased fALFF not only in the cortical-striato-thalamo-cortical (CSTC) circuits like the thalamus, but also in other cerebral systems like the cerebellum, the parietal cortex and the temporal cortex. Additionally, OCD patients demonstrated significant associations between decreased fALFF and obsessive-compulsive symptom severity in the thalamus, the paracentral lobule and the cerebellum. Our results provide evidence for abnormal spontaneous neuronal activity in distributed cerebral areas and support the notion that brain areas outside the CSTC circuits may also play an important role in the pathophysiology of OCD. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Comparative study of resting-state functional MRI and positron emission tomography-CT in the localization of temporal lobe epileptic focus

    International Nuclear Information System (INIS)

    Zhao Chunlei; Chen Ziqian; Wang Zhimin; Qian Gennian; Ni Ping; Tao Chaochao

    2013-01-01

    Objective: To evaluate the efficacy of PET-CT brain imaging and resting-state fMRI in preoperative localization of temporal lobe epileptic (TLE) focus. Methods: PET-CT and resting-state fMRI were performed in 17 patients with refractory TLE, who then underwent surgical treatment. Seventeen healthy volunteers matched with gender and age were recruited as the control group. The resting-state fMRI images were post processed by SPM5 software. Regional homogeneity (ReHo) values of the whole brain and bilateral hippocampus were obtained and analyzed. PET-CT images were analyzed by visual analysis method and asymmetry index method and the standardized uptake value (SUV) of bilateral hippocampus were obtained. The ReHo values and SUV of the bilateral hippocampus were compared by two independent samples t-test, and analyzed by receiver operating characteristic curve (ROC) for optimized diagnostic threshold. Pearson correlation analysis was employed for evaluating the correlation between the SUV and ReHo values of bilateral hippocampus. The consistency between the diagnostic accuracy of PET-CT and resting-state fMRI was assessed by Kappa consistency test. The outcome of the patient group was compared with that of the control group, and with the pathological results, to evaluate the diagnostic value of the two modalities for preoperative localization of temporal lobe epileptic focus. Results: Regional or comprehensive low metabolism of "1"8F-FDG in temporal lobes was presented in all 17 patients, and 11 patients out of 17 showed lateral decreased ReHo value. The diagnostic accuracy of the two examinations was 70.6% (12/17) and 64.7% (11/17) for PET-CT and resting-state fMRI respectively compared with pathological results, and could be increased to 76.5% (13/17) when the two methods were combined for diagnosis. The ReHo values of the TLE group (0.34 ± 0.12) were significantly lower than those of the control group (0.46 ± 0.07) (t = 3.230, P = 0.003). The sensitivity and

  16. Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

    Science.gov (United States)

    Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

    2015-12-01

    The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling.

  17. Altered Functional Connectivity of the Basal Nucleus of Meynert in Mild Cognitive Impairment: A Resting-State fMRI Study

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    Hui Li

    2017-05-01

    Full Text Available Background: Cholinergic dysfunction plays an important role in mild cognitive impairment (MCI. The basal nucleus of Meynert (BNM provides the main source of cortical cholinergic innervation. Previous studies have characterized structural changes of the cholinergic basal forebrain in individuals at risk of developing Alzheimer’s disease (AD. However, whether and how functional connectivity of the BNM (BNM-FC is altered in MCI remains unknown.Objective: The aim of this study was to identify alterations in BNM-FC in individuals with MCI as compared to healthy controls (HCs, and to examine the relationship between these alterations with neuropsychological measures in individuals with MCI.Method: One-hundred-and-one MCI patients and 103 HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI. Imaging data were processed with SPM8 and CONN software. BNM-FC was examined via correlation in low frequency fMRI signal fluctuations between the BNM and all other brain voxels. Group differences were examined with a covariance analysis with age, gender, education level, mean framewise displacement (FD and global correlation (GCOR as nuisance covariates. Pearson’s correlation was conducted to evaluate the relationship between the BNM-FC and clinical assessments.Result: Compared with HCs, individuals with MCI showed significantly decreased BNM-FC in the left insula extending into claustrum (insula/claustrum. Furthermore, greater decrease in BNM-FC with insula/claustrum was associated with more severe impairment in immediate recall during Auditory Verbal Learning Test (AVLT in MCI patients.Conclusion: MCI is associated with changes in BNM-FC to the insula/claustrum in relation to cognitive impairments. These new findings may advance research of the cholinergic bases of cognitive dysfunction during healthy aging and in individuals at risk of developing AD.

  18. The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study.

    Science.gov (United States)

    Sun, Yu; Lim, Julian; Dai, Zhongxiang; Wong, KianFoong; Taya, Fumihiko; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios

    2017-05-15

    Although rest breaks are commonly administered as a countermeasure to reduce mental fatigue and boost cognitive performance, the effects of taking a break on behavior are not consistent. Moreover, our understanding of the underlying neural mechanisms of rest breaks and how they modulate mental fatigue is still rudimentary. In this study, we investigated the effects of receiving a rest break on the topological properties of brain connectivity networks via a two-session experimental paradigm, in which one session comprised four successive blocks of a mentally demanding visual selective attention task (No-rest session), whereas the other contained a rest break between the second and third task blocks (Rest session). Functional brain networks were constructed using resting-state functional MRI data recorded from 20 healthy adults before and after the performance of the task blocks. Behaviorally, subjects displayed robust time-on-task (TOT) declines, as reflected by increasingly slower reaction time as the test progressed and lower post-task self-reported ratings of engagement. However, we did not find a significant effect on task performance due to administering a mid-task break. Compared to pre-task measurements, post-task functional brain networks demonstrated an overall decrease of optimal small-world properties together with lower global efficiency. Specifically, we found TOT-related reduced nodal efficiency in brain regions that mainly resided in the subcortical areas. More interestingly, a significant block-by-session interaction was revealed in local efficiency, attributing to a significant post-task decline in No-rest session and a preserved local efficiency when a mid-task break opportunity was introduced in the Rest session. Taken together, these findings augment our understanding of how the resting brain reorganizes following the accumulation of prolonged task, suggest dissociable processes between the neural mechanisms of fatigue and recovery, and provide

  19. Analysis of Altered Baseline Brain Activity in Drug-Naive Adult Patients with Social Anxiety Disorder Using Resting-State Functional MRI

    OpenAIRE

    Qiu, Changjian; Feng, Yuan; Meng, Yajing; Liao, Wei; Huang, Xiaoqi; Lui, Su; Zhu, Chunyan; Chen, Huafu; Gong, Qiyong; Zhang, Wei

    2015-01-01

    Objective We hypothesize that the amplitude of low-frequency fluctuations (ALFF) is involved in the altered regional baseline brain function in social anxiety disorder (SAD). The aim of the study was to analyze the altered baseline brain activity in drug-naive adult patients with SAD. Methods We investigated spontaneous and baseline brain activities by obtaining the resting-state functional magnetic resonance imaging data of 20 drug-na?ve adult SAD patients and 19 healthy controls. Voxels wer...

  20. Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

    Science.gov (United States)

    Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

    2018-04-18

    Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

  1. Altered pattern of spontaneous brain activity in the patients with end-stage renal disease: a resting-state functional MRI study with regional homogeneity analysis.

    Directory of Open Access Journals (Sweden)

    Xue Liang

    Full Text Available PURPOSE: To investigate the pattern of spontaneous neural activity in patients with end-stage renal disease (ESRD with and without neurocognitive dysfunction using resting-state functional magnetic resonance imaging (rs-fMRI with a regional homogeneity (ReHo algorithm. MATERIALS AND METHODS: rs-fMRI data were acquired in 36 ESRD patients (minimal nephro-encephalopathy [MNE], n = 19, 13 male, 37±12.07 years; non-nephro-encephalopathy [non-NE], n = 17, 11 male, 38±12.13 years and 20 healthy controls (13 male, 7 female, 36±10.27 years. Neuropsychological (number connection test type A [NCT-A], digit symbol test [DST] and laboratory tests were performed in all patients. The Kendall's coefficient of concordance (KCC was used to measure the regional homogeneity for each subject. The regional homogeneity maps were compared using ANOVA tests among MNE, non-NE, and healthy control groups and post hoc t -tests between each pair in a voxel-wise way. A multiple regression analysis was performed to evaluate the relationships between ReHo index and NCT-A, DST scores, serum creatinine and urea levels, disease and dialysis duration. RESULTS: Compared with healthy controls, both MNE and non-NE patients showed decreased ReHo in the multiple areas of bilateral frontal, parietal and temporal lobes. Compared with the non-NE, MNE patients showed decreased ReHo in the right inferior parietal lobe (IPL, medial frontal cortex (MFC and left precuneus (PCu. The NCT-A scores and serum urea levels of ESRD patients negatively correlated with ReHo values in the frontal and parietal lobes, while DST scores positively correlated with ReHo values in the bilateral PCC/precuneus, MFC and inferior parietal lobe (IPL (all P0.05, AlphaSim corrected. CONCLUSION: Diffused decreased ReHo values were found in both MNE and non-NE patients. The progressively decreased ReHo in the default mode network (DMN, frontal and parietal lobes might be trait-related in MNE. The Re

  2. Effect of scanner acoustic background noise on strict resting-state fMRI.

    Science.gov (United States)

    Rondinoni, C; Amaro, E; Cendes, F; dos Santos, A C; Salmon, C E G

    2013-04-01

    Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a 'resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced "silent" pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

  3. Effect of scanner acoustic background noise on strict resting-state fMRI

    Directory of Open Access Journals (Sweden)

    C. Rondinoni

    2013-04-01

    Full Text Available Functional MRI (fMRI resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a ‘resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs. Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced “silent” pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal, while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

  4. Abnormal functional connectivity of brain network hubs associated with symptom severity in treatment-naive patients with obsessive-compulsive disorder: A resting-state functional MRI study.

    Science.gov (United States)

    Tian, Lin; Meng, Chun; Jiang, Ying; Tang, Qunfeng; Wang, Shuai; Xie, Xiyao; Fu, Xiangshuai; Jin, Chunhui; Zhang, Fuquan; Wang, Jidong

    2016-04-03

    Abnormal brain networks have been observed in patients with obsessive-compulsive disorder (OCD). However, detailed network hub and connectivity changes remained unclear in treatment-naive patients with OCD. Here, we sought to determine whether patients show hub-related connectivity changes in their whole-brain functional networks. We used resting-state functional magnetic resonance imaging data and voxel-based graph-theoretic analysis to investigate functional connectivity strength and hubs of whole-brain networks in 29 treatment-naive patients with OCD and 29 age- and gender-matched healthy controls. Correlation analysis was applied for potential associations with OCD symptom severity. OCD selectively targeted brain regions of higher functional connectivity strength than the average including brain network hubs, mainly distributed in the cortico-striato-thalamo-cortical (CSTC) circuits and additionally parietal, occipital, temporal and cerebellar regions. Moreover, affected functional connectivity strength in the cerebellum, the medial orbitofrontal cortex and superior occipital cortex was significantly associated with global OCD symptom severity. Our results provide the evidence about OCD-related brain network hub changes, not only in the CSTC circuits but more distributed in whole brain networks. Data suggest that whole brain network hub analysis is useful for understanding the pathophysiology of OCD. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Brain regional homogeneity changes following transjugular intrahepatic portosystemic shunt in cirrhotic patients support cerebral adaptability theory—A resting-state functional MRI study

    Energy Technology Data Exchange (ETDEWEB)

    Ni, Ling; Qi, Rongfeng [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Zhang, Long Jiang, E-mail: kevinzhlj@163.com [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Zhong, Jianhui [Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang 310027 (China); Zheng, Gang [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Wu, Xingjiang; Fan, Xinxin [Department of General Surgery, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China); Lu, Guang Ming, E-mail: cjr.luguangming@vip.163.com [Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing 210002 (China)

    2014-03-15

    Purpose: The exact neuro-pathophysiological effect of transjugular intrahepatic portosystemic shunt (TIPS) on brain function remains unclear. The purpose of this study was to investigate the longitudinal brain activity changes in cirrhotic patients with TIPS insertion using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Methods: Fifteen cirrhotic patients without overt hepatic encephalopathy (OHE) planned for TIPS procedure and 15 age- and gender-matched healthy controls were included in this study. Eleven of the 15 patients underwent repeated fMRI examinations at median 7-day following TIPS, 8 patients in median 3-month, and 7 patients in median 1-year follow-up duration, respectively. Regional homogeneity was calculated by the Kendall's coefficient of concordance (KCC) and compared between patients before TIPS and healthy controls with two-sample t test as well as pre-and post-TIPS patients with paired t test. Correlations between the pre- and post-TIPS changes of ReHo and the changes of venous blood ammonia level and number connection test type A (NCT-A)/digit symbol test (DST) scores were calculated by crossing subjects. Results: Compared with healthy controls, 15 cirrhotic patients before TIPS procedure showed decreased ReHo in the bilateral frontal, parietal, temporal and occipital lobes and increased ReHo in the bilateral caudate. Compared with the pre-TIPS patients, 11 post-TIPS patients in the median 7-day follow-up examinations demonstrated decreased ReHo in the medial frontal gyrus (MFG), superior parietal gyrus (SPG), middle/superior temporal gyrus (M/STG), anterior cingulate cortex (ACC), caudate, and increased ReHo in the insula. Eight post-TIPS patients in the median 3-month follow-up examinations showed widespread decreased ReHo in the bilateral frontal and parietal lobes, ACC, caudate, and increased ReHo in the insula and precuneus/cuneus. In the median 1-year follow-up studies, seven post-TIPS patients displayed

  6. Brain regional homogeneity changes following transjugular intrahepatic portosystemic shunt in cirrhotic patients support cerebral adaptability theory—A resting-state functional MRI study

    International Nuclear Information System (INIS)

    Ni, Ling; Qi, Rongfeng; Zhang, Long Jiang; Zhong, Jianhui; Zheng, Gang; Wu, Xingjiang; Fan, Xinxin; Lu, Guang Ming

    2014-01-01

    Purpose: The exact neuro-pathophysiological effect of transjugular intrahepatic portosystemic shunt (TIPS) on brain function remains unclear. The purpose of this study was to investigate the longitudinal brain activity changes in cirrhotic patients with TIPS insertion using resting-state functional MRI (fMRI) with regional homogeneity (ReHo) method. Methods: Fifteen cirrhotic patients without overt hepatic encephalopathy (OHE) planned for TIPS procedure and 15 age- and gender-matched healthy controls were included in this study. Eleven of the 15 patients underwent repeated fMRI examinations at median 7-day following TIPS, 8 patients in median 3-month, and 7 patients in median 1-year follow-up duration, respectively. Regional homogeneity was calculated by the Kendall's coefficient of concordance (KCC) and compared between patients before TIPS and healthy controls with two-sample t test as well as pre-and post-TIPS patients with paired t test. Correlations between the pre- and post-TIPS changes of ReHo and the changes of venous blood ammonia level and number connection test type A (NCT-A)/digit symbol test (DST) scores were calculated by crossing subjects. Results: Compared with healthy controls, 15 cirrhotic patients before TIPS procedure showed decreased ReHo in the bilateral frontal, parietal, temporal and occipital lobes and increased ReHo in the bilateral caudate. Compared with the pre-TIPS patients, 11 post-TIPS patients in the median 7-day follow-up examinations demonstrated decreased ReHo in the medial frontal gyrus (MFG), superior parietal gyrus (SPG), middle/superior temporal gyrus (M/STG), anterior cingulate cortex (ACC), caudate, and increased ReHo in the insula. Eight post-TIPS patients in the median 3-month follow-up examinations showed widespread decreased ReHo in the bilateral frontal and parietal lobes, ACC, caudate, and increased ReHo in the insula and precuneus/cuneus. In the median 1-year follow-up studies, seven post-TIPS patients displayed

  7. Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

    Science.gov (United States)

    Cheng, Lin; Zhu, Yang; Sun, Junfeng; Deng, Lifu; He, Naying; Yang, Yang; Ling, Huawei; Ayaz, Hasan; Fu, Yi; Tong, Shanbao

    2018-01-25

    Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique

  8. Role of mitochondrial calcium uptake homeostasis in resting state fMRI brain networks.

    Science.gov (United States)

    Kannurpatti, Sridhar S; Sanganahalli, Basavaraju G; Herman, Peter; Hyder, Fahmeed

    2015-11-01

    Mitochondrial Ca(2+) uptake influences both brain energy metabolism and neural signaling. Given that brain mitochondrial organelles are distributed in relation to vascular density, which varies considerably across brain regions, we hypothesized different physiological impacts of mitochondrial Ca(2+) uptake across brain regions. We tested the hypothesis by monitoring brain "intrinsic activity" derived from the resting state functional MRI (fMRI) blood oxygen level dependent (BOLD) fluctuations in different functional networks spanning the somatosensory cortex, caudate putamen, hippocampus and thalamus, in normal and perturbed mitochondrial Ca(2+) uptake states. In anesthetized rats at 11.7 T, mitochondrial Ca(2+) uptake was inhibited or enhanced respectively by treatments with Ru360 or kaempferol. Surprisingly, mitochondrial Ca(2+) uptake inhibition by Ru360 and enhancement by kaempferol led to similar dose-dependent decreases in brain-wide intrinsic activities in both the frequency domain (spectral amplitude) and temporal domain (resting state functional connectivity; RSFC). The fact that there were similar dose-dependent decreases in the frequency and temporal domains of the resting state fMRI-BOLD fluctuations during mitochondrial Ca(2+) uptake inhibition or enhancement indicated that mitochondrial Ca(2+) uptake and its homeostasis may strongly influence the brain's functional organization at rest. Interestingly, the resting state fMRI-derived intrinsic activities in the caudate putamen and thalamic regions saturated much faster with increasing dosage of either drug treatment than the drug-induced trends observed in cortical and hippocampal regions. Regional differences in how the spectral amplitude and RSFC changed with treatment indicate distinct mitochondrion-mediated spontaneous neuronal activity coupling within the various RSFC networks determined by resting state fMRI. Copyright © 2015 John Wiley & Sons, Ltd.

  9. Graph Theoretical Analysis of Functional Brain Networks: Test-Retest Evaluation on Short- and Long-Term Resting-State Functional MRI Data

    Science.gov (United States)

    Wang, Jin-Hui; Zuo, Xi-Nian; Gohel, Suril; Milham, Michael P.; Biswal, Bharat B.; He, Yong

    2011-01-01

    Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest. PMID:21818285

  10. Resting State Functional Connectivity in Early Blind Humans

    Directory of Open Access Journals (Sweden)

    Harold eBurton

    2014-04-01

    Full Text Available Task-based neuroimaging studies in early blind humans (EB have demonstrated heightened visual cortex responses to non-visual paradigms. Several prior functional connectivity studies in EB have shown altered connections consistent with these task-based results. But these studies generally did not consider behavioral adaptations to lifelong blindness typically observed in EB. Enhanced cognitive abilities shown in EB include greater serial recall and attention to memory. Here, we address the question of the extent to which brain intrinsic activity in EB reflects such adaptations. We performed a resting-state functional magnetic resonance imaging study contrasting 14 EB with 14 age/gender matched normally sighted controls (NS. A principal finding was markedly greater functional connectivity in EB between visual cortex and regions typically associated with memory and cognitive control of attention. In contrast, correlations between visual cortex and non-deprived sensory cortices were significantly lower in EB. Thus, the available data, including that obtained in prior task-based and resting state fMRI studies, as well as the present results, indicate that visual cortex in EB becomes more heavily incorporated into functional systems instantiating episodic recall and attention to non-visual events. Moreover, EB appear to show a reduction in interactions between visual and non-deprived sensory cortices, possibly reflecting suppression of inter-sensory distracting activity.

  11. Aberrant brain regional homogeneity and functional connectivity in middle-aged T2DM patients: a resting-state functional MRI study

    Directory of Open Access Journals (Sweden)

    Daihong Liu

    2016-09-01

    Full Text Available Type 2 diabetes mellitus (T2DM has been associated with cognitive impairment. However, its neurological mechanism remains elusive. Combining regional homogeneity (ReHo and functional connectivity (FC analyses, the present study aimed to investigate brain functional alterations in middle-aged T2DM patients, which could provide complementary information for the neural substrates underlying T2DM-associated brain dysfunction. Twenty-five T2DM patients and 25 healthy controls were involved in neuropsychological testing and structural and resting-state functional magnetic resonance imaging data acquisition. ReHo analysis was conducted to determine the peak coordinates of brain regions with abnormal local brain activity synchronization. Then, the identified brain regions were considered as seeds, and FC between these brain regions and global voxels was computed. Finally, the potential correlations between the imaging indices and neuropsychological data were also explored. Compared with healthy controls, T2DM patients exhibited higher ReHo values in the anterior cingulate gyrus and lower ReHo in right fusiform gyrus, right precentral gyrus and right medial orbit of the superior frontal gyrus. Considering these areas as seed regions, T2DM patients displayed aberrant FC, mainly in the frontal and parietal lobes. The pattern of FC alterations in T2DM patients was characterized by decreased connectivity and positive to negative or negative to positive converted connectivity. Digital Span Test forward scores revealed significant correlations with the ReHo values of the right precentral gyrus (ρ = 0.527, p = 0.014 and FC between the right fusiform gyrus and middle temporal gyrus (ρ = -0.437, p = 0.048. Our findings suggest that T2DM patients suffer from cognitive dysfunction related to spatially local and remote brain activity synchronization impairment. The patterns of ReHo and FC alterations shed light on the mechanisms underlying T2DM-associated brain

  12. Resting-state functional connectivity differences in premature children

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    Eswar Damaraju

    2010-06-01

    Full Text Available We examine the coherence in the spontaneous brain activity of sleeping children as measured by the blood oxygenation level dependent (BOLD functional magnetic resonance imaging (fMRI signals. The results are described in terms of resting-state networks (RSN and their properties. More specifically, in this study we examine the effect of severe prematurity on the spatial location of the visual, temporal, motor, basal ganglia, and the default mode networks, the temporal response properties of each of these networks, and the functional connectivity between them. Our results suggest that the anatomical locations of the RSNs are well developed by 18 months of age and their spatial locations are not distinguishable between premature and term born infants at 18 months or at 36 months, with the exception of small spatial differences noted in the basal ganglia area and the visual cortex. The two major differences between term and preterm children were present at 36 but not 18 months and include: 1 increased spectral energy in the low frequency range (0.01 – 0.06 Hz for pre-term children in the basal ganglia component, and 2 stronger connectivity between RSNs in term children. We speculate that children born very prematurely are vulnerable to injury resulting in weaker connectivity between resting state networks by 36 months of age. Further work is required to determine whether this could be a clinically useful tool to identify children at risk of developmental delay related to premature birth.

  13. Progress in clinical research and application of resting state functional brain imaging

    International Nuclear Information System (INIS)

    Long Miaomiao; Ni Hongyan

    2013-01-01

    Resting state functional brain imaging experimental design is free of stimulus task and offers various parametric maps through different data-driven post processing methods with endogenous BOLD signal changes as the source of imaging. Mechanism of resting state brain activities could be extensively studied with improved patient compliance and clinical application compared with task related functional brain imaging. Also resting state functional brain imaging can be used as a method of data acquisition, with implicit neuronal activity as a kind of experimental design, to reveal characteristic brain activities of epileptic patient. Even resting state functional brain imaging data processing method can be used to analyze task related functional MRI data, opening new horizons of task related functional MRI study. (authors)

  14. Identification of Resting State Networks Involved in Executive Function.

    Science.gov (United States)

    Connolly, Joanna; McNulty, Jonathan P; Boran, Lorraine; Roche, Richard A P; Delany, David; Bokde, Arun L W

    2016-06-01

    The structural networks in the human brain are consistent across subjects, and this is reflected also in that functional networks across subjects are relatively consistent. These findings are not only present during performance of a goal oriented task but there are also consistent functional networks during resting state. It suggests that goal oriented activation patterns may be a function of component networks identified using resting state. The current study examines the relationship between resting state networks measured and patterns of neural activation elicited during a Stroop task. The association between the Stroop-activated networks and the resting state networks was quantified using spatial linear regression. In addition, we investigated if the degree of spatial association of resting state networks with the Stroop task may predict performance on the Stroop task. The results of this investigation demonstrated that the Stroop activated network can be decomposed into a number of resting state networks, which were primarily associated with attention, executive function, visual perception, and the default mode network. The close spatial correspondence between the functional organization of the resting brain and task-evoked patterns supports the relevance of resting state networks in cognitive function.

  15. Fast computation of voxel-level brain connectivity maps from resting-state functional MRI using l₁-norm as approximation of Pearson's temporal correlation: proof-of-concept and example vector hardware implementation.

    Science.gov (United States)

    Minati, Ludovico; Zacà, Domenico; D'Incerti, Ludovico; Jovicich, Jorge

    2014-09-01

    An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1(9)-1(11) links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l1-norm. Even though the adjacency matrices derived from correlation coefficients and l1-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l1-norm on an array of 4096 zero instruction-set processors. Calculation times correlation in very high-density resting-state functional connectivity analyses. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

  16. Resting-state fMRI and social cognition: An opportunity to connect.

    Science.gov (United States)

    Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

    2017-09-01

    Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

  17. Classification and Extraction of Resting State Networks Using Healthy and Epilepsy fMRI Data

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    Svyatoslav Vergun

    2016-09-01

    Full Text Available Functional magnetic resonance imaging studies have significantly expanded the field’s understanding of functional brain activity of healthy and patient populations. Resting state (rs- fMRI, which does not require subjects to perform a task, eliminating confounds of task difficulty, allows examination of neural activity and offers valuable functional mapping information. The purpose of this work was to develop an automatic resting state network (RNS labeling method which offers value in clinical workflow during rs-fMRI mapping by organizing and quickly labeling spatial maps into functional networks. Here independent component analysis (ICA and machine learning were applied to rs-fMRI data with the goal of developing a method for the clinically oriented task of extracting and classifying spatial maps into auditory, visual, default-mode, sensorimotor and executive control resting state networks from 23 epilepsy patients (and for general comparison, separately for 30 healthy subjects. ICA revealed distinct and consistent functional network components across patients and healthy subjects. Network classification was successful, achieving 88% accuracy for epilepsy patients with a naïve Bayes algorithm (and 90% accuracy for healthy subjects with a perceptron. The method’s utility to researchers and clinicians is the provided RSN spatial maps and their functional labeling which offer complementary functional information to clinicians’ expert interpretation.

  18. Altered Long- and Short-Range Functional Connectivity in Patients with Betel Quid Dependence: A Resting-State Functional MRI Study

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    Tao Liu

    2016-12-01

    Full Text Available Objective: Addiction is a chronic relapsing brain disease. Brain structural abnormalities may constitute an abnormal neural network that underlies the risk of drug dependence. We hypothesized that individuals with Betel Quid Dependence (BQD have functional connectivity alterations that can be described by long- and short-range functional connectivity density(FCD maps. Methods: We tested this hypothesis using functional magnetic resonance imaging (fMRI data from subjects of the Han ethnic group in Hainan, China. Here, we examined BQD individuals (n = 33 and age-, sex-, and education-matched healthy controls (HCs (n = 32 in a rs-fMRI study to observe FCD alterations associated with the severity of BQD. Results: Compared with HCs, long-range FCD was decreased in the right anterior cingulate cortex (ACC and increased in the left cerebellum posterior lobe (CPL and bilateral inferior parietal lobule (IPL in the BQD group. Short-range FCD was reduced in the right ACC and left dorsolateral prefrontal cortex (dlPFC, and increased in the left CPL. The short-range FCD alteration in the right ACC displayed a negative correlation with the Betel Quid Dependence Scale (BQDS (r=-0.432, P=0.012, and the long-range FCD alteration of left IPL showed a positive correlation with the duration of BQD(r=0.519, P=0.002 in BQD individuals. Conclusions: fMRI revealed differences in long- and short- range FCD in BQD individuals, and these alterations might be due to BQ chewing, BQ dependency, or risk factors for developing BQD.

  19. Functional alterations of fronto-limbic circuit and default mode network systems in first-episode, drug-naïve patients with major depressive disorder: A meta-analysis of resting-state fMRI data.

    Science.gov (United States)

    Zhong, Xue; Pu, Weidan; Yao, Shuqiao

    2016-12-01

    The neurobiological mechanisms of depression are increasingly being explored through resting-state brain imaging studies. However, resting-state fMRI findings have varied, perhaps because of differences between study populations, which included the disorder course and medication use. The aim of our study was to integrate studies of resting-state fMRI and explore the alterations of abnormal brain activity in first-episode, drug-naïve patients with major depressive disorder. Relevant imaging reports in English were searched, retrieved, selected and subjected to analysis by activation likelihood estimation, a coordinate-based meta-analysis technique (final sample, 31 studies). Coordinates extracted from the original reports were assigned to two categories based on effect directionality. Compared with healthy controls, the first-episode, medication-naïve major depressive disorder patients showed decreased brain activity in the dorsolateral prefrontal cortex, superior temporal gyrus, posterior precuneus, and posterior cingulate, as well as in visual areas within the occipital lobe, lingual gyrus, and fusiform gyrus, and increased activity in the putamen and anterior precuneus. Not every study that has reported relevant data met the inclusion criteria. Resting-state functional alterations were located mainly in the fronto-limbic system, including the dorsolateral prefrontal cortex and putamen, and in the default mode network, namely the precuneus and superior/middle temporal gyrus. Abnormal functional alterations of the fronto-limbic circuit and default mode network may be characteristic of first-episode, drug-naïve major depressive disorder patients. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Correspondent Functional Topography of the Human Left Inferior Parietal Lobule at Rest and Under Task Revealed Using Resting-State fMRI and Coactivation Based Parcellation.

    Science.gov (United States)

    Wang, Jiaojian; Xie, Sangma; Guo, Xin; Becker, Benjamin; Fox, Peter T; Eickhoff, Simon B; Jiang, Tianzi

    2017-03-01

    The human left inferior parietal lobule (LIPL) plays a pivotal role in many cognitive functions and is an important node in the default mode network (DMN). Although many previous studies have proposed different parcellation schemes for the LIPL, the detailed functional organization of the LIPL and the exact correspondence between the DMN and LIPL subregions remain unclear. Mounting evidence indicates that spontaneous fluctuations in the brain are strongly associated with cognitive performance at the behavioral level. However, whether a consistent functional topographic organization of the LIPL during rest and under task can be revealed remains unknown. Here, they used resting-state functional connectivity (RSFC) and task-related coactivation patterns separately to parcellate the LIPL and identified seven subregions. Four subregions were located in the supramarginal gyrus (SMG) and three subregions were located in the angular gyrus (AG). The subregion-specific networks and functional characterization revealed that the four anterior subregions were found to be primarily involved in sensorimotor processing, movement imagination and inhibitory control, audition perception and speech processing, and social cognition, whereas the three posterior subregions were mainly involved in episodic memory, semantic processing, and spatial cognition. The results revealed a detailed functional organization of the LIPL and suggested that the LIPL is a functionally heterogeneous area. In addition, the present study demonstrated that the functional architecture of the LIPL during rest corresponds with that found in task processing. Hum Brain Mapp 38:1659-1675, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  1. Resting-state fMRI study of patients with fragile X syndrome

    Science.gov (United States)

    Isanova, E.; Petrovskiy, E.; Savelov, A.; Yudkin, D.; Tulupov, A.

    2017-08-01

    The study aimed to assess the neural activity of different brain regions in patients with fragile X syndrome (FXS) and the healthy volunteers by resting-state functional magnetic resonance imaging (fMRI) on a 1.5 T MRI Achieva scanner (Philips). Results: The fMRI study showed a DMN of brain function in patients with FXS, as well as in the healthy volunteers. Furthermore, it was found that a default mode network of the brain in patients with FXS and healthy volunteers does not have statistically significant differences (p>0.05), which may indicate that the basal activity of neurons in patients with FXS is not reduced. In addition, we have found a significant (pright inferior parietal and right angular gyrus in the resting state in patients with FXS. Conclusion: New data of functional status of the brain in patients with FXS were received. The significant increase in the resting state functional connectivity within the right inferior parietal and right angular gyrus (p<0.001) in patients with FXS was found.

  2. Time of acquisition and network stability in pediatric resting-state functional magnetic resonance imaging

    NARCIS (Netherlands)

    T.J.H. White (Tonya); R.L. Muetzel (Ryan); M. Schmidt (Marcus); S.J.E. Langeslag (Sandra); V.W.V. Jaddoe (Vincent); A. Hofman (Albert); V.D. Calhoun Vince D. (V.); F.C. Verhulst (Frank); H.W. Tiemeier (Henning)

    2014-01-01

    textabstractResting-state functional magnetic resonance imaging (rs-fMRI) has been shown to elucidate reliable patterns of brain networks in both children and adults. Studies in adults have shown that rs-fMRI acquisition times of ∼5 to 6 min provide adequate sampling to produce stable spatial maps

  3. Identifying patients with Alzheimer's disease using resting-state fMRI and graph theory.

    Science.gov (United States)

    Khazaee, Ali; Ebrahimzadeh, Ata; Babajani-Feremi, Abbas

    2015-11-01

    Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. Graph theory can efficiently characterize different aspects of the brain network by calculating measures of integration and segregation. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. The data were preprocessed and each subject's graph was constructed by parcellation of the whole brain into 90 distinct regions using the automated anatomical labeling (AAL) atlas. The graph measures were then calculated and used as the discriminating features. Extracted network-based features were fed to different feature selection algorithms to choose most significant features. In addition to the machine learning approach, statistical analysis was performed on connectivity matrices to find altered connectivity patterns in patients with AD. Using the selected features, we were able to accurately classify patients with AD from healthy subjects with accuracy of 100%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD. Classification based on the resting-state fMRI can be used as a non-invasive and automatic tool to diagnosis of Alzheimer's disease. Copyright © 2015 International Federation of Clinical Neurophysiology. All rights reserved.

  4. Quantitative comparisons on hand motor functional areas determined by resting state and task BOLD fMRI and anatomical MRI for pre-surgical planning of patients with brain tumors

    Directory of Open Access Journals (Sweden)

    Bob L. Hou

    2016-01-01

    Full Text Available For pre-surgical planning we present quantitative comparison of the location of the hand motor functional area determined by right hand finger tapping BOLD fMRI, resting state BOLD fMRI, and anatomically using high resolution T1 weighted images. Data were obtained on 10 healthy subjects and 25 patients with left sided brain tumors. Our results show that there are important differences in the locations (i.e., >20 mm of the determined hand motor voxels by these three MR imaging methods. This can have significant effect on the pre-surgical planning of these patients depending on the modality used. In 13 of the 25 cases (i.e., 52% the distances between the task-determined and the rs-fMRI determined hand areas were more than 20 mm; in 13 of 25 cases (i.e., 52% the distances between the task-determined and anatomically determined hand areas were >20 mm; and in 16 of 25 cases (i.e., 64% the distances between the rs-fMRI determined and anatomically determined hand areas were more than 20 mm. In just three cases, the distances determined by all three modalities were within 20 mm of each other. The differences in the location or fingerprint of the hand motor areas, as determined by these three MR methods result from the different underlying mechanisms of these three modalities and possibly the effects of tumors on these modalities.

  5. Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI.

    Science.gov (United States)

    Dai, Weiying; Varma, Gopal; Scheidegger, Rachel; Alsop, David C

    2016-03-01

    Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to investigate spontaneous low-frequency signal fluctuations across brain resting state networks. However, BOLD only provides relative measures of signal fluctuations. Arterial Spin Labeling (ASL) MRI holds great potential for quantitative measurements of resting state network fluctuations. This study systematically quantified signal fluctuations of the large-scale resting state networks using ASL data from 20 healthy volunteers by separating them from global signal fluctuations and fluctuations caused by residual noise. Global ASL signal fluctuation was 7.59% ± 1.47% relative to the ASL baseline perfusion. Fluctuations of seven detected resting state networks vary from 2.96% ± 0.93% to 6.71% ± 2.35%. Fluctuations of networks and residual noise were 6.05% ± 1.18% and 6.78% ± 1.16% using 4-mm resolution ASL data applied with Gaussian smoothing kernel of 6mm. However, network fluctuations were reduced by 7.77% ± 1.56% while residual noise fluctuation was markedly reduced by 39.75% ± 2.90% when smoothing kernel of 12 mm was applied to the ASL data. Therefore, global and network fluctuations are the dominant structured noise sources in ASL data. Quantitative measurements of resting state networks may enable improved noise reduction and provide insights into the function of healthy and diseased brain. © The Author(s) 2015.

  6. Less head motion during MRI under task than resting-state conditions.

    Science.gov (United States)

    Huijbers, Willem; Van Dijk, Koene R A; Boenniger, Meta M; Stirnberg, Rüdiger; Breteler, Monique M B

    2017-02-15

    Head motion reduces data quality of neuroimaging data. In three functional magnetic resonance imaging (MRI) experiments we demonstrate that people make less head movements under task than resting-state conditions. In Experiment 1, we observed less head motion during a memory encoding task than during the resting-state condition. In Experiment 2, using publicly shared data from the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study, we again found less head motion during several active task conditions than during a resting-state condition, although some task conditions also showed comparable motion. In the healthy controls, we found more head motion in men than in women and more motion with increasing age. When comparing clinical groups, we found that patients with a clinical diagnosis of bipolar disorder, or schizophrenia, move more compared to healthy controls or patients with ADHD. Both these experiments had a fixed acquisition order across participants, and we could not rule out that a first or last scan during a session might be particularly prone to more head motion. Therefore, we conducted Experiment 3, in which we collected several task and resting-state fMRI runs with an acquisition order counter-balanced. The results of Experiment 3 show again less head motion during several task conditions than during rest. Together these experiments demonstrate that small head motions occur during MRI even with careful instruction to remain still and fixation with foam pillows, but that head motion is lower when participants are engaged in a cognitive task. These finding may inform the choice of functional runs when studying difficult-to-scan populations, such as children or certain patient populations. Our findings also indicate that differences in head motion complicate direct comparisons of measures of functional neuronal networks between task and resting-state fMRI because of potential differences in data quality. In practice, a task to reduce head motion

  7. Enhanced subject-specific resting-state network detection and extraction with fast fMRI.

    Science.gov (United States)

    Akin, Burak; Lee, Hsu-Lei; Hennig, Jürgen; LeVan, Pierre

    2017-02-01

    Resting-state networks have become an important tool for the study of brain function. An ultra-fast imaging technique that allows to measure brain function, called Magnetic Resonance Encephalography (MREG), achieves an order of magnitude higher temporal resolution than standard echo-planar imaging (EPI). This new sequence helps to correct physiological artifacts and improves the sensitivity of the fMRI analysis. In this study, EPI is compared with MREG in terms of capability to extract resting-state networks. Healthy controls underwent two consecutive resting-state scans, one with EPI and the other with MREG. Subject-level independent component analyses (ICA) were performed separately for each of the two datasets. Using Stanford FIND atlas parcels as network templates, the presence of ICA maps corresponding to each network was quantified in each subject. The number of detected individual networks was significantly higher in the MREG data set than for EPI. Moreover, using short time segments of MREG data, such as 50 seconds, one can still detect and track consistent networks. Fast fMRI thus results in an increased capability to extract distinct functional regions at the individual subject level for the same scan times, and also allow the extraction of consistent networks within shorter time intervals than when using EPI, which is notably relevant for the analysis of dynamic functional connectivity fluctuations. Hum Brain Mapp 38:817-830, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  8. Heritability estimates on resting state fMRI data using ENIGMA analysis pipeline.

    Science.gov (United States)

    Adhikari, Bhim M; Jahanshad, Neda; Shukla, Dinesh; Glahn, David C; Blangero, John; Reynolds, Richard C; Cox, Robert W; Fieremans, Els; Veraart, Jelle; Novikov, Dmitry S; Nichols, Thomas E; Hong, L Elliot; Thompson, Paul M; Kochunov, Peter

    2018-01-01

    Big data initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analysis consortium (ENIGMA), combine data collected by independent studies worldwide to achieve more generalizable estimates of effect sizes and more reliable and reproducible outcomes. Such efforts require harmonized image analyses protocols to extract phenotypes consistently. This harmonization is particularly challenging for resting state fMRI due to the wide variability of acquisition protocols and scanner platforms; this leads to site-to-site variance in quality, resolution and temporal signal-to-noise ratio (tSNR). An effective harmonization should provide optimal measures for data of different qualities. We developed a multi-site rsfMRI analysis pipeline to allow research groups around the world to process rsfMRI scans in a harmonized way, to extract consistent and quantitative measurements of connectivity and to perform coordinated statistical tests. We used the single-modality ENIGMA rsfMRI preprocessing pipeline based on modelfree Marchenko-Pastur PCA based denoising to verify and replicate resting state network heritability estimates. We analyzed two independent cohorts, GOBS (Genetics of Brain Structure) and HCP (the Human Connectome Project), which collected data using conventional and connectomics oriented fMRI protocols, respectively. We used seed-based connectivity and dual-regression approaches to show that the rsfMRI signal is consistently heritable across twenty major functional network measures. Heritability values of 20-40% were observed across both cohorts.

  9. Time course based artifact identification for independent components of resting state fMRI

    Directory of Open Access Journals (Sweden)

    Christian eRummel

    2013-05-01

    Full Text Available In functional magnetic resonance imaging (fMRI coherent oscillations of the blood oxygen level dependent (BOLD signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting state networks (RSN. Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82 and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

  10. Large-scale DCMs for resting-state fMRI

    Directory of Open Access Journals (Sweden)

    Adeel Razi

    2017-01-01

    Full Text Available This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity. This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI. We use spectral dynamic causal modeling (DCM to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of Bayesian model reduction to discover the most likely sparse graph (or model from a parent (e.g., fully connected graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM—with functional connectivity priors—is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

  11. A method to determine the necessity for global signal regression in resting-state fMRI studies.

    Science.gov (United States)

    Chen, Gang; Chen, Guangyu; Xie, Chunming; Ward, B Douglas; Li, Wenjun; Antuono, Piero; Li, Shi-Jiang

    2012-12-01

    In resting-state functional MRI studies, the global signal (operationally defined as the global average of resting-state functional MRI time courses) is often considered a nuisance effect and commonly removed in preprocessing. This global signal regression method can introduce artifacts, such as false anticorrelated resting-state networks in functional connectivity analyses. Therefore, the efficacy of this technique as a correction tool remains questionable. In this article, we establish that the accuracy of the estimated global signal is determined by the level of global noise (i.e., non-neural noise that has a global effect on the resting-state functional MRI signal). When the global noise level is low, the global signal resembles the resting-state functional MRI time courses of the largest cluster, but not those of the global noise. Using real data, we demonstrate that the global signal is strongly correlated with the default mode network components and has biological significance. These results call into question whether or not global signal regression should be applied. We introduce a method to quantify global noise levels. We show that a criteria for global signal regression can be found based on the method. By using the criteria, one can determine whether to include or exclude the global signal regression in minimizing errors in functional connectivity measures. Copyright © 2012 Wiley Periodicals, Inc.

  12. Asymmetrical hippocampal connectivity in mesial temporal lobe epilepsy: evidence from resting state fMRI

    Directory of Open Access Journals (Sweden)

    Castellano Gabriela

    2010-06-01

    Full Text Available Abstract Background Mesial temporal lobe epilepsy (MTLE, the most common type of focal epilepsy in adults, is often caused by hippocampal sclerosis (HS. Patients with HS usually present memory dysfunction, which is material-specific according to the hemisphere involved and has been correlated to the degree of HS as measured by postoperative histopathology as well as by the degree of hippocampal atrophy on magnetic resonance imaging (MRI. Verbal memory is mostly affected by left-sided HS, whereas visuo-spatial memory is more affected by right HS. Some of these impairments may be related to abnormalities of the network in which individual hippocampus takes part. Functional connectivity can play an important role to understand how the hippocampi interact with other brain areas. It can be estimated via functional Magnetic Resonance Imaging (fMRI resting state experiments by evaluating patterns of functional networks. In this study, we investigated the functional connectivity patterns of 9 control subjects, 9 patients with right MTLE and 9 patients with left MTLE. Results We detected differences in functional connectivity within and between hippocampi in patients with unilateral MTLE associated with ipsilateral HS by resting state fMRI. Functional connectivity resulted to be more impaired ipsilateral to the seizure focus in both patient groups when compared to control subjects. This effect was even more pronounced for the left MTLE group. Conclusions The findings presented here suggest that left HS causes more reduction of functional connectivity than right HS in subjects with left hemisphere dominance for language.

  13. Regional homogeneity changes in prelingually deafened patients: a resting-state fMRI study

    Science.gov (United States)

    Li, Wenjing; He, Huiguang; Xian, Junfang; Lv, Bin; Li, Meng; Li, Yong; Liu, Zhaohui; Wang, Zhenchang

    2010-03-01

    Resting-state functional magnetic resonance imaging (fMRI) is a technique that measures the intrinsic function of brain and has some advantages over task-induced fMRI. Regional homogeneity (ReHo) assesses the similarity of the time series of a given voxel with its nearest neighbors on a voxel-by-voxel basis, which reflects the temporal homogeneity of the regional BOLD signal. In the present study, we used the resting state fMRI data to investigate the ReHo changes of the whole brain in the prelingually deafened patients relative to normal controls. 18 deaf patients and 22 healthy subjects were scanned. Kendall's coefficient of concordance (KCC) was calculated to measure the degree of regional coherence of fMRI time courses. We found that regional coherence significantly decreased in the left frontal lobe, bilateral temporal lobes and right thalamus, and increased in the postcentral gyrus, cingulate gyrus, left temporal lobe, left thalamus and cerebellum in deaf patients compared with controls. These results show that the prelingually deafened patients have higher degree of regional coherence in the paleocortex, and lower degree in neocortex. Since neocortex plays an important role in the development of auditory, these evidences may suggest that the deaf persons reorganize the paleocortex to offset the loss of auditory.

  14. Resting-state functional magnetic resonance imaging for surgical planning in pediatric patients: a preliminary experience.

    Science.gov (United States)

    Roland, Jarod L; Griffin, Natalie; Hacker, Carl D; Vellimana, Ananth K; Akbari, S Hassan; Shimony, Joshua S; Smyth, Matthew D; Leuthardt, Eric C; Limbrick, David D

    2017-12-01

    OBJECTIVE Cerebral mapping for surgical planning and operative guidance is a challenging task in neurosurgery. Pediatric patients are often poor candidates for many modern mapping techniques because of inability to cooperate due to their immature age, cognitive deficits, or other factors. Resting-state functional MRI (rs-fMRI) is uniquely suited to benefit pediatric patients because it is inherently noninvasive and does not require task performance or significant cooperation. Recent advances in the field have made mapping cerebral networks possible on an individual basis for use in clinical decision making. The authors present their initial experience translating rs-fMRI into clinical practice for surgical planning in pediatric patients. METHODS The authors retrospectively reviewed cases in which the rs-fMRI analysis technique was used prior to craniotomy in pediatric patients undergoing surgery in their institution. Resting-state analysis was performed using a previously trained machine-learning algorithm for identification of resting-state networks on an individual basis. Network maps were uploaded to the clinical imaging and surgical navigation systems. Patient demographic and clinical characteristics, including need for sedation during imaging and use of task-based fMRI, were also recorded. RESULTS Twenty patients underwent rs-fMRI prior to craniotomy between December 2013 and June 2016. Their ages ranged from 1.9 to 18.4 years, and 12 were male. Five of the 20 patients also underwent task-based fMRI and one underwent awake craniotomy. Six patients required sedation to tolerate MRI acquisition, including resting-state sequences. Exemplar cases are presented including anatomical and resting-state functional imaging. CONCLUSIONS Resting-state fMRI is a rapidly advancing field of study allowing for whole brain analysis by a noninvasive modality. It is applicable to a wide range of patients and effective even under general anesthesia. The nature of resting-state

  15. Findings in resting-state fMRI by differences from K-means clustering.

    Science.gov (United States)

    Chyzhyk, Darya; Graña, Manuel

    2014-01-01

    Resting state fMRI has growing number of studies with diverse aims, always centered on some kind of functional connectivity biomarker obtained from correlation regarding seed regions, or by analytical decomposition of the signal towards the localization of the spatial distribution of functional connectivity patterns. In general, studies are computationally costly and very sensitive to noise and preprocessing of data. In this paper we consider clustering by K-means as a exploratory procedure which can provide some results with little computational effort, due to efficient implementations that are readily available. We demonstrate the approach on a dataset of schizophrenia patients, finding differences between patients with and without auditory hallucinations.

  16. Expanded functional coupling of subcortical nuclei with the motor resting-state network in multiple sclerosis

    DEFF Research Database (Denmark)

    Dogonowski, Anne-Marie; Siebner, Hartwig R; Sørensen, Per Soelberg

    2013-01-01

    controls underwent a 20-minute resting-state fMRI session at 3 Tesla. Independent component analysis was applied to the fMRI data to identify disease-related changes in motor resting-state connectivity. RESULTS: Patients with MS showed a spatial expansion of motor resting-state connectivity in deep...

  17. Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

    Science.gov (United States)

    Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

    2015-07-08

    When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

  18. Circulating androgens correlate with resting-state MRI in transgender men.

    Science.gov (United States)

    Mueller, Sven C; Wierckx, Katrien; Jackson, Kathryn; T'Sjoen, Guy

    2016-11-01

    Despite mounting evidence regarding the underlying neurobiology in transgender persons, information regarding resting-state activity, particularly after hormonal treatment, is lacking. The present study examined differences between transgender persons on long-term cross-sex hormone therapy and comparisons on two measures of local functional connectivity, intensity of spontaneous resting-state activity (low frequency fluctuations, LFF) and local synchronization of specific brain areas (regional homogeneity, ReHo). Nineteen transgender women (TW, male-to-female), 19 transgender men (TM, female-to-male), 21 non-transgender men (NTM) and 20 non-transgender women (NTW) underwent a resting-state MRI scan. The results showed differences between transgender persons and non-transgender comparisons on both LFF and ReHo measures in the frontal cortex, medial temporal lobe, and cerebellum. More interestingly, circulating androgens correlated for TM in the cerebellum and regions of the frontal cortex, an effect that was associated with treatment duration in the cerebellum. By comparison, no associations were found for TW with estrogens. These data provide first evidence for a potential masculinization of local functional connectivity in hormonally-treated transgender men. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Altered Brain Functional Activity in Infants with Congenital Bilateral Severe Sensorineural Hearing Loss: A Resting-State Functional MRI Study under Sedation

    Directory of Open Access Journals (Sweden)

    Shuang Xia

    2017-01-01

    Full Text Available Early hearing deprivation could affect the development of auditory, language, and vision ability. Insufficient or no stimulation of the auditory cortex during the sensitive periods of plasticity could affect the function of hearing, language, and vision development. Twenty-three infants with congenital severe sensorineural hearing loss (CSSHL and 17 age and sex matched normal hearing subjects were recruited. The amplitude of low frequency fluctuations (ALFF and regional homogeneity (ReHo of the auditory, language, and vision related brain areas were compared between deaf infants and normal subjects. Compared with normal hearing subjects, decreased ALFF and ReHo were observed in auditory and language-related cortex. Increased ALFF and ReHo were observed in vision related cortex, which suggest that hearing and language function were impaired and vision function was enhanced due to the loss of hearing. ALFF of left Brodmann area 45 (BA45 was negatively correlated with deaf duration in infants with CSSHL. ALFF of right BA39 was positively correlated with deaf duration in infants with CSSHL. In conclusion, ALFF and ReHo can reflect the abnormal brain function in language, auditory, and visual information processing in infants with CSSHL. This demonstrates that the development of auditory, language, and vision processing function has been affected by congenital severe sensorineural hearing loss before 4 years of age.

  20. Resting-State Functional Magnetic Resonance Imaging for Language Preoperative Planning

    Science.gov (United States)

    Branco, Paulo; Seixas, Daniela; Deprez, Sabine; Kovacs, Silvia; Peeters, Ronald; Castro, São L.; Sunaert, Stefan

    2016-01-01

    Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way. PMID:26869899

  1. Abnormal regional homogeneity in Parkinson's disease: a resting state fMRI study

    International Nuclear Information System (INIS)

    Li, Y.; Liang, P.; Jia, X.; Li, K.

    2016-01-01

    Aim: To examine the functional brain alterations in Parkinson's disease (PD) by measuring blood oxygenation level dependent (BOLD) functional MRI (fMRI) signals at rest while controlling for the structural atrophy. Materials and methods: Twenty-three PD patients and 20 age, gender, and education level matched normal controls (NC) were included in this study. Resting state fMRI and structural MRI data were acquired. The resting state brain activity was measured by the regional homogeneity (ReHo) method and the grey matter (GM) volume was attained by the voxel-based morphology (VBM) analysis. Two-sample t-test was then performed to detect the group differences with structural atrophy as a covariate. Results: VBM analysis showed GM volume reductions in the left superior frontal gyrus, left paracentral lobule, and left middle frontal gyrus in PD patients as compared to NC. There were widespread ReHo differences between NC and PD patients. Compared to NC, PD patients showed significant alterations in the motor network, including decreased ReHo in the right primary sensory cortex (S1), while increased ReHo in the left premotor area (PMA) and left dorsolateral prefrontal cortex (DLPFC). In addition, a cluster in the left superior occipital gyrus (SOG) also showed increased ReHo in PD patients. Conclusion: The current findings indicate that significant changes of ReHo in the motor and non-motor cortices have been detected in PD patients, independent of age, gender, education level, and structural atrophy. The present study thus suggests ReHo abnormalities as a potential biomarker for the diagnosis of PD and further provides insights into the biological mechanism of the disease. - Highlights: • Functional changes were found in PD patients independent of structural atrophy. • Both increased and decreased ReHo were observed in motor network regions in PD. • Increased ReHo was detected in visual association cortex for PD patients.

  2. Rapid geodesic mapping of brain functional connectivity: implementation of a dedicated co-processor in a field-programmable gate array (FPGA) and application to resting state functional MRI.

    Science.gov (United States)

    Minati, Ludovico; Cercignani, Mara; Chan, Dennis

    2013-10-01

    Graph theory-based analyses of brain network topology can be used to model the spatiotemporal correlations in neural activity detected through fMRI, and such approaches have wide-ranging potential, from detection of alterations in preclinical Alzheimer's disease through to command identification in brain-machine interfaces. However, due to prohibitive computational costs, graph-based analyses to date have principally focused on measuring connection density rather than mapping the topological architecture in full by exhaustive shortest-path determination. This paper outlines a solution to this problem through parallel implementation of Dijkstra's algorithm in programmable logic. The processor design is optimized for large, sparse graphs and provided in full as synthesizable VHDL code. An acceleration factor between 15 and 18 is obtained on a representative resting-state fMRI dataset, and maps of Euclidean path length reveal the anticipated heterogeneous cortical involvement in long-range integrative processing. These results enable high-resolution geodesic connectivity mapping for resting-state fMRI in patient populations and real-time geodesic mapping to support identification of imagined actions for fMRI-based brain-machine interfaces. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  3. Gender Differences in Cerebral Regional Homogeneity of Adult Healthy Volunteers: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Chunsheng Xu

    2015-01-01

    Full Text Available Objective. We sought to use the regional homogeneity (ReHo approach as an index in the resting-state functional MRI to investigate the gender differences of spontaneous brain activity within cerebral cortex and resting-state networks (RSNs in young adult healthy volunteers. Methods. One hundred and twelve healthy volunteers (56 males, 56 females participated in the resting-state fMRI scan. The ReHo mappings in the cerebral cortex and twelve RSNs of the male and female groups were compared. Results. We found statistically significant gender differences in the primary visual network (PVN (P<0.004, with Bonferroni correction and left attention network (LAtN, default mode network (DMN, sensorimotor network (SMN, executive network (EN, and dorsal medial prefrontal network (DMPFC as well (P<0.05, uncorrected. The male group showed higher ReHo in the left precuneus, while the female group showed higher ReHo in the right middle cingulate gyrus, fusiform gyrus, left inferior parietal lobule, precentral gyrus, supramarginal gyrus, and postcentral gyrus. Conclusions. Our results suggested that men and women had regional specific differences during the resting-state. The findings may improve our understanding of the gender differences in behavior and cognition from the perspective of resting-state brain function.

  4. Improving the Test-Retest Reliability of Resting State fMRI by Removing the Impact of Sleep.

    Science.gov (United States)

    Wang, Jiahui; Han, Junwei; Nguyen, Vinh T; Guo, Lei; Guo, Christine C

    2017-01-01

    Resting state functional magnetic resonance imaging (rs-fMRI) provides a powerful tool to examine large-scale neural networks in the human brain and their disturbances in neuropsychiatric disorders. Thanks to its low demand and high tolerance, resting state paradigms can be easily acquired from clinical population. However, due to the unconstrained nature, resting state paradigm is associated with excessive head movement and proneness to sleep. Consequently, the test-retest reliability of rs-fMRI measures is moderate at best, falling short of widespread use in the clinic. Here, we characterized the effect of sleep on the test-retest reliability of rs-fMRI. Using measures of heart rate variability (HRV) derived from simultaneous electrocardiogram (ECG) recording, we identified portions of fMRI data when subjects were more alert or sleepy, and examined their effects on the test-retest reliability of functional connectivity measures. When volumes of sleep were excluded, the reliability of rs-fMRI is significantly improved, and the improvement appears to be general across brain networks. The amount of improvement is robust with the removal of as much as 60% volumes of sleepiness. Therefore, test-retest reliability of rs-fMRI is affected by sleep and could be improved by excluding volumes of sleepiness as indexed by HRV. Our results suggest a novel and practical method to improve test-retest reliability of rs-fMRI measures.

  5. Improving the Test-Retest Reliability of Resting State fMRI by Removing the Impact of Sleep

    Directory of Open Access Journals (Sweden)

    Jiahui Wang

    2017-05-01

    Full Text Available Resting state functional magnetic resonance imaging (rs-fMRI provides a powerful tool to examine large-scale neural networks in the human brain and their disturbances in neuropsychiatric disorders. Thanks to its low demand and high tolerance, resting state paradigms can be easily acquired from clinical population. However, due to the unconstrained nature, resting state paradigm is associated with excessive head movement and proneness to sleep. Consequently, the test-retest reliability of rs-fMRI measures is moderate at best, falling short of widespread use in the clinic. Here, we characterized the effect of sleep on the test-retest reliability of rs-fMRI. Using measures of heart rate variability (HRV derived from simultaneous electrocardiogram (ECG recording, we identified portions of fMRI data when subjects were more alert or sleepy, and examined their effects on the test-retest reliability of functional connectivity measures. When volumes of sleep were excluded, the reliability of rs-fMRI is significantly improved, and the improvement appears to be general across brain networks. The amount of improvement is robust with the removal of as much as 60% volumes of sleepiness. Therefore, test-retest reliability of rs-fMRI is affected by sleep and could be improved by excluding volumes of sleepiness as indexed by HRV. Our results suggest a novel and practical method to improve test-retest reliability of rs-fMRI measures.

  6. Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

    Science.gov (United States)

    Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

    2014-01-01

    The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

  7. Low frequency fluctuations in resting-state functional magnetic resonance imaging and their applications

    International Nuclear Information System (INIS)

    Küblböck, M.

    2015-01-01

    Over the course of the last two decades, functional magnetic resonance imaging (fMRI) has emerged as a widely used, highly accepted and very popular method for the assessment of neuronal activity in the human brain. It is a completely non-invasive imaging technique with high temporal resolution, which relies on the measurement of local differences in magnetic susceptibility between oxygenated and deoxygenated blood. Therefore, fMRI can be regarded as an indirect measure of neuronal activity via measurement of localised changes in cerebral blood flow and cerebral oxygen consumption. Maps of neuronal activity are calculated from fMRI data acquired either in the presence of an explicit task (task-based fMRI) or in absence of a task (resting-state fMRI). While in task-based fMRI task-specific patterns of brain activity are subject to research, resting-state fMRI reveals fundamental networks of intrinsic brain activity. These networks are characterized by low-frequency oscillations in the power spectrum of resting-state fMRI data. In the present work, we first introduce the physical principles and the technical background that allow us to measure these changes in blood oxygenation, followed by an introduction to the blood oxygenation level dependent (BOLD) effect and to analysis methods for both task-based and resting-state fMRI data. We also analyse the temporal signal-to-noise ratio (tSNR) of a novel 2D-EPI sequence, which allows the experimenter to acquire several slices simultaneously in order to assess the optimal parameter settings for this sequence at 3T. We then proceed to investigate the temporal properties of measures for the amplitude of low-frequency oscillations in resting-state fMRI data, which are regarded as potential biomarkers for a wide range of mental diseases in various clinical studies and show the high stability and robustness of these data, which are important prerequisites for application as a biomarker as well as their dependency on head motion

  8. The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI.

    Science.gov (United States)

    Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

    2018-01-01

    Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg) . Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

  9. The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

    Directory of Open Access Journals (Sweden)

    Fatma Gargouri

    2018-02-01

    Full Text Available Resting state functional MRI (rs-fMRI is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step and the scr (where we applied realignment, tCompCor and smoothing as a final step strategies had the highest mean values of global efficiency (eg. Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step, had the highest mean local efficiency (el values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

  10. The Influence of Preprocessing Steps on Graph Theory Measures Derived from Resting State fMRI

    Science.gov (United States)

    Gargouri, Fatma; Kallel, Fathi; Delphine, Sebastien; Ben Hamida, Ahmed; Lehéricy, Stéphane; Valabregue, Romain

    2018-01-01

    Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg). Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency. PMID:29497372

  11. Love-related changes in the brain: A resting-state functional magnetic resonance imaging study

    OpenAIRE

    Hongwen eSong; Zhiling eZou; Juan eKou; Yang eLiu; LiZhuang eYang; Anna ezilverstand; Federicod’Oleire eUquillas; Xiaochu eZhang; Xiaochu eZhang; Xiaochu eZhang

    2015-01-01

    Romantic love is a motivational state associated with a desire to enter or maintain a close relationship with a specific other person. Studies with functional magnetic resonance imaging (fMRI) have found activation increases in brain regions involved in processing of reward, emotion, motivation when romantic lovers view photographs of their partners. However, not much is known on whether romantic love affects the brain’s functional architecture during rest. In the present study, resting state...

  12. Regional homogeneity and resting state functional connectivity: associations with exposure to early life stress.

    Science.gov (United States)

    Philip, Noah S; Kuras, Yuliya I; Valentine, Thomas R; Sweet, Lawrence H; Tyrka, Audrey R; Price, Lawrence H; Carpenter, Linda L

    2013-12-30

    Early life stress (ELS) confers risk for psychiatric illness. Previous literature suggests ELS is associated with decreased resting-state functional connectivity (rs-FC) in adulthood, but there are no studies of resting-state neuronal activity in this population. This study investigated whether ELS-exposed individuals demonstrate resting-state activity patterns similar to those found in PTSD. Twenty-seven adults (14 with at least moderate ELS), who were medication-free and without psychiatric or medical illness, underwent MRI scans during two 4-minute rest periods. Resting-state activity was examined using regional homogeneity (ReHo), which estimates regional activation patterns through indices of localized concordance. ReHo values were compared between groups, followed by rs-FC analyses utilizing ReHo-localized areas as seeds to identify other involved regions. Relative to controls, ELS subjects demonstrated diminished ReHo in the inferior parietal lobule (IPL) and superior temporal gyrus (STG). ReHo values were inversely correlated with ELS severity. Secondary analyses revealed decreased rs-FC between the IPL and right precuneus/posterior cingulate, left fusiform gyrus, cerebellum and caudate in ELS subjects. These findings indicate that ELS is associated with altered resting-state activity and connectivity in brain regions involved in trauma-related psychiatric disorders. Future studies are needed to evaluate whether these associations represent potential imaging biomarkers of stress exposure. Published by Elsevier Ireland Ltd.

  13. Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment.

    Directory of Open Access Journals (Sweden)

    Chi Wah Wong

    Full Text Available In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment.

  14. Different Resting-State Functional Connectivity Alterations in Smokers and Nonsmokers with Internet Gaming Addiction

    Directory of Open Access Journals (Sweden)

    Xue Chen

    2014-01-01

    Full Text Available This study investigated changes in resting-state functional connectivity (rsFC of posterior cingulate cortex (PCC in smokers and nonsmokers with Internet gaming addiction (IGA. Twenty-nine smokers with IGA, 22 nonsmokers with IGA, and 30 healthy controls (HC group underwent a resting-state fMRI scan. PCC connectivity was determined in all subjects by investigating synchronized low-frequency fMRI signal fluctuations using a temporal correlation method. Compared with the nonsmokers with IGA, the smokers with IGA exhibited decreased rsFC with PCC in the right rectus gyrus. Left middle frontal gyrus exhibited increased rsFC. The PCC connectivity with the right rectus gyrus was found to be negatively correlated with the CIAS scores in the smokers with IGA before correction. Our results suggested that smokers with IGA had functional changes in brain areas related to motivation and executive function compared with the nonsmokers with IGA.

  15. A computational study of whole-brain connectivity in resting state and task fMRI

    Science.gov (United States)

    Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

    2014-01-01

    Background We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition. PMID:24947491

  16. Caffeine reduces resting-state BOLD functional connectivity in the motor cortex.

    Science.gov (United States)

    Rack-Gomer, Anna Leigh; Liau, Joy; Liu, Thomas T

    2009-05-15

    In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N=9). We found that caffeine significantly (pcaffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

  17. Changes in community structure of resting state functional connectivity in unipolar depression.

    Directory of Open Access Journals (Sweden)

    Anton Lord

    Full Text Available Major depression is a prevalent disorder that imposes a significant burden on society, yet objective laboratory-style tests to assist in diagnosis are lacking. We employed network-based analyses of "resting state" functional neuroimaging data to ascertain group differences in the endogenous cortical activity between healthy and depressed subjects.We additionally sought to use machine learning techniques to explore the ability of these network-based measures of resting state activity to provide diagnostic information for depression. Resting state fMRI data were acquired from twenty two depressed outpatients and twenty two healthy subjects matched for age and gender. These data were anatomically parcellated and functional connectivity matrices were then derived using the linear correlations between the BOLD signal fluctuations of all pairs of cortical and subcortical regions.We characterised the hierarchical organization of these matrices using network-based matrics, with an emphasis on their mid-scale "modularity" arrangement. Whilst whole brain measures of organization did not differ between groups, a significant rearrangement of their community structure was observed. Furthermore we were able to classify individuals with a high level of accuracy using a support vector machine, primarily through the use of a modularity-based metric known as the participation index.In conclusion, the application of machine learning techniques to features of resting state fMRI network activity shows promising potential to assist in the diagnosis of major depression, now suggesting the need for validation in independent data sets.

  18. Neural correlate of resting-state functional connectivity under α2 adrenergic receptor agonist, medetomidine.

    Science.gov (United States)

    Nasrallah, Fatima A; Lew, Si Kang; Low, Amanda Si-Min; Chuang, Kai-Hsiang

    2014-01-01

    Correlative fluctuations in functional MRI (fMRI) signals across the brain at rest have been taken as a measure of functional connectivity, but the neural basis of this resting-state MRI (rsMRI) signal is not clear. Previously, we found that the α2 adrenergic agonist, medetomidine, suppressed the rsMRI correlation dose-dependently but not the stimulus evoked activation. To understand the underlying electrophysiology and neurovascular coupling, which might be altered due to the vasoconstrictive nature of medetomidine, somatosensory evoked potential (SEP) and resting electroencephalography (EEG) were measured and correlated with corresponding BOLD signals in rat brains under three dosages of medetomidine. The SEP elicited by electrical stimulation to both forepaws was unchanged regardless of medetomidine dosage, which was consistent with the BOLD activation. Identical relationship between the SEP and BOLD signal under different medetomidine dosages indicates that the neurovascular coupling was not affected. Under resting state, EEG power was the same but a depression of inter-hemispheric EEG coherence in the gamma band was observed at higher medetomidine dosage. Different from medetomidine, both resting EEG power and BOLD power and coherence were significantly suppressed with increased isoflurane level. Such reduction was likely due to suppressed neural activity as shown by diminished SEP and BOLD activation under isoflurane, suggesting different mechanisms of losing synchrony at resting-state. Even though, similarity between electrophysiology and BOLD under stimulation and resting-state implicates a tight neurovascular coupling in both medetomidine and isoflurane. Our results confirm that medetomidine does not suppress neural activity but dissociates connectivity in the somatosensory cortex. The differential effect of medetomidine and its receptor specific action supports the neuronal origin of functional connectivity and implicates the mechanism of its sedative

  19. Changes in thalamus connectivity in mild cognitive impairment: Evidence from resting state fMRI

    International Nuclear Information System (INIS)

    Wang Zhiqun; Jia Xiuqin; Liang Peipeng; Qi Zhigang; Yang Yanhui; Zhou Weidong; Li Kuncheng

    2012-01-01

    Purpose: The subcortical region such as thalamus was believed to have close relationship with many cerebral cortexes which made it especially interesting in the study of functional connectivity. Here, we used resting state functional MRI (fMRI) to examine changes in thalamus connectivity in mild cognitive impairment (MCI), which presented a neuro-disconnection syndrome. Materials and methods: Data from 14 patients and 14 healthy age-matched controls were analyzed. Thalamus connectivity was investigated by examination of the correlation between low frequency fMRI signal fluctuations in the thalamus and those in all other brain regions. Results: We found that functional connectivity between the left thalamus and a set of regions was decreased in MCI; these regions are: bilateral cuneus, middle occipital gyrus (MOG), superior frontal gyrus (SFG), medial prefrontal cortex (MPFC), precuneus, inferior frontal gyrus (IFG) and precentral gyrus (PreCG). There are also some regions showed reduced connectivity to right thalamus; these regions are bilateral cuneus, MOG, fusiform gyrus (FG), MPFC, paracentral lobe (PCL), precuneus, superior parietal lobe (SPL) and IFG. We also found increased functional connectivity between the left thalamus and the right thalamus in MCI. Conclusion: The decreased connectivity between the thalamus and the other brain regions might indicate reduced integrity of thalamus-related cortical networks in MCI. Furthermore, the increased connectivity between the left and right thalamus suggest compensation for the loss of cognitive function. Briefly, impairment and compensation of thalamus connectivity coexist in the MCI patients.

  20. The resting state fMRI study of patients with Parkinson's disease associated with cognitive dysfunction

    International Nuclear Information System (INIS)

    Feng Jieying; Huang Biao

    2013-01-01

    Parkinson's disease (PD) is the most common neurodegenerative cause of Parkinsonism, but the high morbidity of PD accompanied cognitive dysfunction hasn't drawn enough attention by the clinicians. With the rapid development of the resting state functional MRI (fMRI) technique, the cause of PD patients with cognitive dysfunction may be associated with the damage of functional connectivity of the motor networks and the cognitive networks. The relationship between neuropathologic mechanism of PD patients with cognitive dysfunction and impaired cognitive circuits will be disclosed by building the changes of brain topological structure in patients. The resting state fMRI study can provide the rationale for prevention, diagnosis and treatment of PD. (authors)

  1. Snack food as a modulator of human resting-state functional connectivity.

    Science.gov (United States)

    Mendez-Torrijos, Andrea; Kreitz, Silke; Ivan, Claudiu; Konerth, Laura; Rösch, Julie; Pischetsrieder, Monika; Moll, Gunther; Kratz, Oliver; Dörfler, Arnd; Horndasch, Stefanie; Hess, Andreas

    2018-04-04

    To elucidate the mechanisms of how snack foods may induce non-homeostatic food intake, we used resting state functional magnetic resonance imaging (fMRI), as resting state networks can individually adapt to experience after short time exposures. In addition, we used graph theoretical analysis together with machine learning techniques (support vector machine) to identifying biomarkers that can categorize between high-caloric (potato chips) vs. low-caloric (zucchini) food stimulation. Seventeen healthy human subjects with body mass index (BMI) 19 to 27 underwent 2 different fMRI sessions where an initial resting state scan was acquired, followed by visual presentation of different images of potato chips and zucchini. There was then a 5-minute pause to ingest food (day 1=potato chips, day 3=zucchini), followed by a second resting state scan. fMRI data were further analyzed using graph theory analysis and support vector machine techniques. Potato chips vs. zucchini stimulation led to significant connectivity changes. The support vector machine was able to accurately categorize the 2 types of food stimuli with 100% accuracy. Visual, auditory, and somatosensory structures, as well as thalamus, insula, and basal ganglia were found to be important for food classification. After potato chips consumption, the BMI was associated with the path length and degree in nucleus accumbens, middle temporal gyrus, and thalamus. The results suggest that high vs. low caloric food stimulation in healthy individuals can induce significant changes in resting state networks. These changes can be detected using graph theory measures in conjunction with support vector machine. Additionally, we found that the BMI affects the response of the nucleus accumbens when high caloric food is consumed.

  2. Resting States Are Resting Traits – An fMRI Study of Sex Differences and Menstrual Cycle Effects in Resting State Cognitive Control Networks

    OpenAIRE

    Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten

    2014-01-01

    To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the c...

  3. Localized reductions in resting-state functional connectivity in children with prenatal alcohol exposure.

    Science.gov (United States)

    Fan, Jia; Taylor, Paul A; Jacobson, Sandra W; Molteno, Christopher D; Gohel, Suril; Biswal, Bharat B; Jacobson, Joseph L; Meintjes, Ernesta M

    2017-10-01

    Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting-state functional MRI (rs-fMRI), which examines the low-frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low-functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting-state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting-state functional connectivity within these RSNs in FASD. Rs-fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting-state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose-dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra-RSN connections. Hum Brain Mapp 38:5217-5233, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. ALFF Value in Right Parahippocampal Gyrus Acts as a Potential Marker Monitoring Amyotrophic Lateral Sclerosis Progression: a Neuropsychological, Voxel-Based Morphometry, and Resting-State Functional MRI Study.

    Science.gov (United States)

    Zhu, Wenjia; Fu, Xiaoling; Cui, Fang; Yang, Fei; Ren, Yuting; Zhang, Xiaoyun; Zhang, Xiaolan; Chen, Zhaohui; Ling, Li; Huang, Xusheng

    2015-09-01

    The aim of this study is to analyze cognitive impairment in amyotrophic lateral sclerosis (ALS). Forty-four participants matched for age, sex, and educational background were enrolled as the sporadic ALS group (n = 22) and the control group (n = 22). All participants completed comprehensive neuropsychological tests, including the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Stroop Color-Word Interference Test (SCWT), the Wisconsin Card Sorting Test (WCST), and the Frontal Assessment Battery. The participants underwent a series of 3.0 Tesla magnetic resonance imaging (MRI) scans. Resting-state functional MRI (Rs-fMRI) using the amplitude of low-frequency fluctuation (ALFF) was performed. Three-dimensional T1-weighted anatomical images obtained by voxel-based morphometry (VBM) were used to conduct correlation analyses and group comparisons with the demographic and neuropsychological characteristics. The results indicated that the decreased gray matter (GM) volume in the bilateral precentral gyri and increased ALFF values in the right parahippocampal gyrus, left inferior temporal gyrus, left anterior cingulate gyrus, right superior frontal gyrus, and left middle occipital gyrus were identified in the sporadic ALS group. The increased ALFF value in the right parahippocampal gyrus was positively correlated with ALS progression rate. The ALS patients exhibited poor performances on cognitive and executive tests, which were significantly or marginally significantly correlated with the ALFF values in the anterior cingulate gyrus and the frontal, temporal, and parahippocampal cortices. In conclusion, these findings provide evidence of an extramotor involvement and suggest that the ALFF value in the right parahippocampal gyrus could represent a potential marker to monitor disease progression.

  5. Non-parametric Bayesian graph models reveal community structure in resting state fMRI

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Madsen, Kristoffer H.; Siebner, Hartwig Roman

    2014-01-01

    Modeling of resting state functional magnetic resonance imaging (rs-fMRI) data using network models is of increasing interest. It is often desirable to group nodes into clusters to interpret the communication patterns between nodes. In this study we consider three different nonparametric Bayesian...... models for node clustering in complex networks. In particular, we test their ability to predict unseen data and their ability to reproduce clustering across datasets. The three generative models considered are the Infinite Relational Model (IRM), Bayesian Community Detection (BCD), and the Infinite...... between clusters. BCD restricts the between-cluster link probabilities to be strictly lower than within-cluster link probabilities to conform to the community structure typically seen in social networks. IDM only models a single between-cluster link probability, which can be interpreted as a background...

  6. Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

    Directory of Open Access Journals (Sweden)

    Emilia Sbardella

    2015-01-01

    Full Text Available Brain functional connectivity (FC is defined as the coherence in the activity between cerebral areas under a task or in the resting-state (RS. By applying functional magnetic resonance imaging (fMRI, RS FC shows several patterns which define RS brain networks (RSNs involved in specific functions, because brain function is known to depend not only on the activity within individual regions, but also on the functional interaction of different areas across the whole brain. Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation. Multiple sclerosis (MS is characterized by multiple lesions mainly affecting the white matter, determining both structural and functional disconnection between various areas of the central nervous system. The study of RS FC in MS is mainly aimed at understanding alterations in the intrinsic functional architecture of the brain and their role in disease progression and clinical impairment. In this paper, we will examine the results obtained by the application of RS fMRI in different multiple sclerosis (MS phenotypes and the correlations of FC changes with clinical features in this pathology. The knowledge of RS FC changes may represent a substantial step forward in the MS research field, both for clinical and therapeutic purposes.

  7. Decreased resting-state interhemispheric functional connectivity in unaffected siblings of schizophrenia patients.

    Science.gov (United States)

    Guo, Wenbin; Jiang, Jiajing; Xiao, Changqing; Zhang, Zhikun; Zhang, Jian; Yu, Liuyu; Liu, Jianrong; Liu, Guiying

    2014-01-01

    Neuroimaging studies in unaffected siblings of schizophrenia patients can provide clues to the pathophysiology for the development of schizophrenia. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (FC) in siblings, although the dysconnectivity hypothesis is prevailing in schizophrenia for years. In the present study, we used a newly validated voxel-mirrored homotopic connectivity (VMHC) method to identify whether aberrant interhemispheric FC was present in unaffected siblings at increased risk of developing schizophrenia at rest. Forty-six unaffected siblings of schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI). Automated VMHC was used to analyze the data. The sibling group had lower VMHC than the control group in the angular gyrus (AG) and the lingual gyrus/cerebellum lobule VI. No region exhibited higher VMHC in the sibling group than in the control group. There was no significant sex difference of the VMHC values between male siblings and female siblings or between male controls and female controls, although evidence has been accumulated that size and shape of the corpus callosum, and functional homotopy differ between men and women. Our results first suggest that interhemispheric resting-state FC of VMHC is disrupted in unaffected siblings of schizophrenia patients, and add a new clue of abnormal interhemispheric resting-state FC to the pathophysiology for the development of schizophrenia. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. Frequency-Specific Abnormalities of Intrinsic Functional Connectivity Strength among Patients with Amyotrophic Lateral Sclerosis: A Resting-State fMRI Study

    OpenAIRE

    Li, Fangjun; Zhou, Fuqing; Huang, Muhua; Gong, Honghan; Xu, Renshi

    2017-01-01

    The classical concept that amyotrophic lateral sclerosis (ALS) is a degenerative disorder characterized by the loss of upper and lower motor neurons is agreed. However, more and more studies have suggested the involvement of some extra-motor regions. The aim of this study is to investigate the frequency-related alteration pattern of intrinsic functional connectivity strength (FCS) at the voxel-wise level in the relatively early-stage of ALS on a whole brain scale. In this study, 21 patients w...

  9. Resting-state fMRI study of acute migraine treatment with kinetic oscillation stimulation in nasal cavity

    Directory of Open Access Journals (Sweden)

    Tie-Qiang Li

    2016-01-01

    The result of this study confirms the efficacy of KOS treatment for relieving acute migraine symptoms and reducing attack frequency. Resting-state fMRI measurements demonstrate that migraine is associated with aberrant intrinsic functional activity in the limbic and primary sensory systems. KOS in the nasal cavity gives rise to the adjustment of the intrinsic functional activity in the limbic and primary sensory networks and restores the physiological homeostasis in the autonomic nervous system.

  10. A task-related and resting state realistic fMRI simulator for fMRI data validation

    Science.gov (United States)

    Hill, Jason E.; Liu, Xiangyu; Nutter, Brian; Mitra, Sunanda

    2017-02-01

    After more than 25 years of published functional magnetic resonance imaging (fMRI) studies, careful scrutiny reveals that most of the reported results lack fully decisive validation. The complex nature of fMRI data generation and acquisition results in unavoidable uncertainties in the true estimation and interpretation of both task-related activation maps and resting state functional connectivity networks, despite the use of various statistical data analysis methodologies. The goal of developing the proposed STANCE (Spontaneous and Task-related Activation of Neuronally Correlated Events) simulator is to generate realistic task-related and/or resting-state 4D blood oxygenation level dependent (BOLD) signals, given the experimental paradigm and scan protocol, by using digital phantoms of twenty normal brains available from BrainWeb (http://brainweb.bic.mni.mcgill.ca/brainweb/). The proposed simulator will include estimated system and modelled physiological noise as well as motion to serve as a reference to measured brain activities. In its current form, STANCE is a MATLAB toolbox with command line functions serving as an open-source add-on to SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). The STANCE simulator has been designed in a modular framework so that the hemodynamic response (HR) and various noise models can be iteratively improved to include evolving knowledge about such models.

  11. Frequency-Specific Abnormalities of Intrinsic Functional Connectivity Strength among Patients with Amyotrophic Lateral Sclerosis: A Resting-State fMRI Study.

    Science.gov (United States)

    Li, Fangjun; Zhou, Fuqing; Huang, Muhua; Gong, Honghan; Xu, Renshi

    2017-01-01

    The classical concept that amyotrophic lateral sclerosis (ALS) is a degenerative disorder characterized by the loss of upper and lower motor neurons is agreed. However, more and more studies have suggested the involvement of some extra-motor regions. The aim of this study is to investigate the frequency-related alteration pattern of intrinsic functional connectivity strength (FCS) at the voxel-wise level in the relatively early-stage of ALS on a whole brain scale. In this study, 21 patients with ALS and 21 well-matched healthy control subjects were enrolled to examine the intrinsic FCS in the different frequencies (slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz, and typical band: 0.01-0.1 Hz). Compared with the control subjects, the ALS patients showed a significantly decreased FCS in the left prefrontal cortex (PFC) and the bilateral superior frontal gyrus. In the slow-5 band, the patients with ALS showed decreased FCS in the left lingual gyrus, as well as increased FCS in the left postcentral gyrus/paracentral lobule (PoCG/PARC). In the slow-4 band, the ALS patients presented decreased FCS in the left and right ventrolateral PFC. Moreover, the increased FCS in the left PoCG/PARC in the slow-5 band was positively correlated with the ALSFRS-r score ( P = 0.015). Our results demonstrated that the FCS changes in ALS were wide spread and frequency dependent. These findings may provide some evidences that ALS patients have the consistent impairment in some extra-motor regions at a relatively early-stage.

  12. Frequency-Specific Abnormalities of Intrinsic Functional Connectivity Strength among Patients with Amyotrophic Lateral Sclerosis: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Fangjun Li

    2017-11-01

    Full Text Available The classical concept that amyotrophic lateral sclerosis (ALS is a degenerative disorder characterized by the loss of upper and lower motor neurons is agreed. However, more and more studies have suggested the involvement of some extra-motor regions. The aim of this study is to investigate the frequency-related alteration pattern of intrinsic functional connectivity strength (FCS at the voxel-wise level in the relatively early-stage of ALS on a whole brain scale. In this study, 21 patients with ALS and 21 well-matched healthy control subjects were enrolled to examine the intrinsic FCS in the different frequencies (slow-4: 0.027–0.073 Hz; slow-5: 0.01–0.027 Hz, and typical band: 0.01–0.1 Hz. Compared with the control subjects, the ALS patients showed a significantly decreased FCS in the left prefrontal cortex (PFC and the bilateral superior frontal gyrus. In the slow-5 band, the patients with ALS showed decreased FCS in the left lingual gyrus, as well as increased FCS in the left postcentral gyrus/paracentral lobule (PoCG/PARC. In the slow-4 band, the ALS patients presented decreased FCS in the left and right ventrolateral PFC. Moreover, the increased FCS in the left PoCG/PARC in the slow-5 band was positively correlated with the ALSFRS-r score (P = 0.015. Our results demonstrated that the FCS changes in ALS were wide spread and frequency dependent. These findings may provide some evidences that ALS patients have the consistent impairment in some extra-motor regions at a relatively early-stage.

  13. Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

    Energy Technology Data Exchange (ETDEWEB)

    Liu Yaou [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Liang Peipeng [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); International WIC institute, Beijing University of Technology, Beijing 100024 (China); Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Dong Huiqing; Ye Jing [Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Li Kuncheng, E-mail: likuncheng1955@yahoo.com.cn [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China)

    2011-11-15

    Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

  14. Abnormal baseline brain activity in patients with neuromyelitis optica: A resting-state fMRI study

    International Nuclear Information System (INIS)

    Liu Yaou; Liang Peipeng; Duan Yunyun; Jia Xiuqin; Wang Fei; Yu Chunshui; Qin Wen; Dong Huiqing; Ye Jing; Li Kuncheng

    2011-01-01

    Purpose: Recent immunopathologic and MRI findings suggest that tissue damage in neuromyelitis optica (NMO) is not limited to spinal cord and optic nerve, but also in brain. Baseline brain activity can reveal the brain functional changes to the tissue damages and give clues to the pathophysiology of NMO, however, it has never been explored by resting-state functional MRI (fMRI). We used regional amplitude of low frequency fluctuation (ALFF) as an index in resting-state fMRI to investigate how baseline brain activity changes in patients with NMO. Methods: Resting-state fMRIs collected from seventeen NMO patients and seventeen age- and sex-matched normal controls were compared to investigate the ALFF difference between the two groups. The relationships between ALFF in regions with significant group differences and the EDSS (Expanded Disability Status Scale), disease duration were further explored. Results: Our results showed that NMO patients had significantly decreased ALFF in precuneus, posterior cingulate cortex (PCC) and lingual gyrus; and increased ALFF in middle frontal gyrus, caudate nucleus and thalamus, compared to normal controls. Moderate negative correlations were found between the EDSS and ALFF in the left middle frontal gyrus (r = -0.436, p = 0.040) and the left caudate (r = -0.542, p = 0.012). Conclusion: The abnormal baseline brain activity shown by resting-state fMRI in NMO is relevant to cognition, visual and motor systems. It implicates a complex baseline brain status of both functional impairments and adaptations caused by tissue damages in these systems, which gives clues to the pathophysiology of NMO.

  15. [Resting state fMRI study of emotional network in patients with postconcussion syndrome].

    Science.gov (United States)

    Zhang, X; Qian, R B; Fu, X M; Lin, B; Zhang, D; Xia, C S; Wei, X P; Niu, C S; Wang, Y H

    2017-07-04

    Objective: To discuss functional connectivity changes in the emotional network of patients with post-concussion syndrome (PCS) and their clinical significance by resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Twenty-seven patients with PCS were recruited from the Department of Neurosurgery of Anhui provincial hospital affiliated to Anhui medical university from October 2015 to April 2016, and 27 healthy subjects were recruited as the controls. The Hamilton Anxiety Scale (HAMA) and The Hamilton Depression Scale (HAMD) were used to evaluate the emotional state of two groups of subjects. All fMRI data were preprocessed after RS-fMRI scanning, the left and right amygdala were selected as region of interest (ROI) to make functional connectivity (FC) calculation with the whole brain and then the results were did statistical analysis in order to obtain the altered brain areas of amygdala and whole brain functional connectivity in the PCS patient, to understand the functional changes of emotional network. Results: HAMA and HAMD scores of PCS group and the health controls had significant statistical difference (HAMA: the PCS group 9.8±1.5, the health controls 4.5±1.2, P =0.044; HAMD: the PCS group 12±1.2, the health controls was 4.2±1.5, P =0.024). Compared with the health controls, the left amygdala in PCS patients showed decreased FC with left insula, left putamen, left anterior cingulate gyrus, left inferior orbital frontal gyrus, left medial superior frontal gyrus, bilateral superior temporal gyrus, left superior temporal pole, bilateral supramarginal gyrus et al, on the contrary with the increased FC with right superior orbital frontal gyrus, right middle frontal lobe, right orbital frontal lobe, right middle frontal gyrus. The right amygdala in PCS patients showed decreased FC with bilateral putamen, right inferior orbital frontal gyrus, left insula, bilateral precuneus, bilateral superior temporal pole, right superior temporal gyrus

  16. Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.

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    Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

    2014-01-01

    Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

  17. Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

    Science.gov (United States)

    Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

    2014-01-01

    Background Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. Methodology/Principal Findings We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. Conclusions/Significance These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning. PMID:24465577

  18. Functional Disconnectivity during Inter-Task Resting State in Dementia with Lewy Bodies.

    Science.gov (United States)

    Chabran, Eléna; Roquet, Daniel; Gounot, Daniel; Sourty, Marion; Armspach, Jean-Paul; Blanc, Frédéric

    2018-05-03

    Limited research has been done on the functional connectivity in visuoperceptual regions in dementia with Lewy bodies (DLB) patients. This study aimed to investigate the functional connectivity differences between a task condition and an inter-task resting state condition within a visuoperceptual paradigm, in DLB patients compared with Alzheimer disease (AD) patients and healthy elderly control subjects. Twenty-six DLB, 29 AD, and 22 healthy subjects underwent a detailed clinical and neuropsychological examination along with a functional MRI during the different conditions of a visuoperceptual paradigm. Functional images were analyzed using group-level spatial independent component analysis and seed-based connectivity analyses. While the DLB patients scored well and did not differ from the control and AD groups in terms of functional activity and connectivity during the task conditions, they showed decreased functional connectivity in visuoperceptual regions during the resting state condition, along with a temporal impairment of the default-mode network activity. Functional connectivity disturbances were also found within two attentional-executive networks and between these networks and visuoperceptual regions. We found a specific functional profile in the switching between task and resting state conditions in DLB patients. This result could help better characterize functional impairments in DLB and their contribution to several core symptoms of this pathology such as visual hallucinations and cognitive fluctuations. © 2018 S. Karger AG, Basel.

  19. REST: a toolkit for resting-state functional magnetic resonance imaging data processing.

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    Xiao-Wei Song

    Full Text Available Resting-state fMRI (RS-fMRI has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST. REST was developed in MATLAB with graphical user interface (GUI. After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF, and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.. REST is an open-source package and is freely available at http://www.restfmri.net.

  20. Neuroplastic changes in resting-state functional connectivity after stroke rehabilitation

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    Yang-teng eFan

    2015-10-01

    Full Text Available Most neuroimaging research in stroke rehabilitation mainly focuses on the neural mechanisms underlying the natural history of post-stroke recovery. However, connectivity mapping from resting-state fMRI is well suited for different neurological conditions and provides a promising method to explore plastic changes for treatment-induced recovery from stroke. We examined the changes in resting-state functional connectivity (RS-FC of the ipsilesional primary motor cortex (M1 in 10 post-acute stroke patients before and immediately after 4 weeks of robot-assisted bilateral arm therapy (RBAT. Motor performance, functional use of the affected arm, and daily function improved in all participants. Reduced interhemispheric RS-FC between the ipsilesional and contralesional M1 (M1-M1 and the contralesional-lateralized connections were noted before treatment. In contrast, greater M1-M1 functional connectivity and disturbed resting-state networks were observed after RBAT relative to pre-treatment. Increased changes in M1-M1 RS-FC after RBAT were coupled with better motor and functional improvements. Mediation analysis showed the pre-to-post difference in M1-M1 RS-FC was a significant mediator for the relationship between motor and functional recovery. These results show neuroplastic changes and functional recoveries induced by RBAT in post-acute stroke survivors and suggest that interhemispheric functional connectivity in the motor cortex may be a neurobiological marker for recovery after stroke rehabilitation.

  1. Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

    Science.gov (United States)

    Zhou, Yuan; Wang, Yun; Rao, Li-Lin; Liang, Zhu-Yuan; Chen, Xiao-Ping; Zheng, Dang; Tan, Cheng; Tian, Zhi-Qiang; Wang, Chun-Hui; Bai, Yan-Qiang; Chen, Shan-Guang; Li, Shu

    2014-01-01

    Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI) to study whether the functional architecture of the brain is altered after 45 days of −6° head-down tilt (HDT) bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of −6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC), to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC) analysis. We found decreased DC in two regions, the left anterior insula (aINS) and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies), in the male volunteers after 45 days of −6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function, and central neural activity. PMID:24926242

  2. Disrutpted resting-state functional architecture of the brain after 45-day simulated microgravity

    Directory of Open Access Journals (Sweden)

    Yuan eZhou

    2014-06-01

    Full Text Available Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI to study whether the functional architecture of the brain is altered after 45 days of -6° head-down tilt (HDT bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of -6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC, to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC analysis. We found decreased DC in two regions, the left anterior insula (aINS and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies, in the male volunteers after 45 days of -6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function and central neural activity.

  3. Establishing the resting state default mode network derived from functional magnetic resonance imaging tasks as an endophenotype: A twins study.

    Science.gov (United States)

    Korgaonkar, Mayuresh S; Ram, Kaushik; Williams, Leanne M; Gatt, Justine M; Grieve, Stuart M

    2014-08-01

    The resting state default mode network (DMN) has been shown to characterize a number of neurological and psychiatric disorders. Evidence suggests an underlying genetic basis for this network and hence could serve as potential endophenotype for these disorders. Heritability is a defining criterion for endophenotypes. The DMN is measured either using a resting-state functional magnetic resonance imaging (fMRI) scan or by extracting resting state activity from task-based fMRI. The current study is the first to evaluate heritability of this task-derived resting activity. 250 healthy adult twins (79 monozygotic and 46 dizygotic same sex twin pairs) completed five cognitive and emotion processing fMRI tasks. Resting state DMN functional connectivity was derived from these five fMRI tasks. We validated this approach by comparing connectivity estimates from task-derived resting activity for all five fMRI tasks, with those obtained using a dedicated task-free resting state scan in an independent cohort of 27 healthy individuals. Structural equation modeling using the classic twin design was used to estimate the genetic and environmental contributions to variance for the resting-state DMN functional connectivity. About 9-41% of the variance in functional connectivity between the DMN nodes was attributed to genetic contribution with the greatest heritability found for functional connectivity between the posterior cingulate and right inferior parietal nodes (P<0.001). Our data provide new evidence that functional connectivity measures from the intrinsic DMN derived from task-based fMRI datasets are under genetic control and have the potential to serve as endophenotypes for genetically predisposed psychiatric and neurological disorders. Copyright © 2014 Wiley Periodicals, Inc.

  4. Automatic selection of resting-state networks with functional magnetic resonance imaging

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    Silvia Francesca eStorti

    2013-05-01

    Full Text Available Functional magnetic resonance imaging (fMRI during a resting-state condition can reveal the co-activation of specific brain regions in distributed networks, called resting-state networks, which are selected by independent component analysis (ICA of the fMRI data. One of the major difficulties with component analysis is the automatic selection of the ICA features related to brain activity. In this study we describe a method designed to automatically select networks of potential functional relevance, specifically, those regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the default-mode network. To do this, image analysis was based on probabilistic ICA as implemented in FSL software. After decomposition, the optimal number of components was selected by applying a novel algorithm which takes into account, for each component, Pearson's median coefficient of skewness of the spatial maps generated by FSL, followed by clustering, segmentation, and spectral analysis. To evaluate the performance of the approach, we investigated the resting-state networks in 25 subjects. For each subject, three resting-state scans were obtained with a Siemens Allegra 3 T scanner (NYU data set. Comparison of the visually and the automatically identified neuronal networks showed that the algorithm had high accuracy (first scan: 95%, second scan: 95%, third scan: 93% and precision (90%, 90%, 84%. The reproducibility of the networks for visual and automatic selection was very close: it was highly consistent in each subject for the default-mode network (≥ 92% and the occipital network, which includes the medial visual cortical areas (≥ 94%, and consistent for the attention network (≥ 80%, the right and/or left lateralized frontoparietal attention networks, and the temporal-motor network (≥ 80%. The automatic selection method may be used to detect neural networks and reduce subjectivity in ICA

  5. Resting state cerebral blood flow with arterial spin labeling MRI in developing human brains.

    Science.gov (United States)

    Liu, Feng; Duan, Yunsuo; Peterson, Bradley S; Asllani, Iris; Zelaya, Fernando; Lythgoe, David; Kangarlu, Alayar

    2018-07-01

    The development of brain circuits is coupled with changes in neurovascular coupling, which refers to the close relationship between neural activity and cerebral blood flow (CBF). Studying the characteristics of CBF during resting state in developing brain can be a complementary way to understand the functional connectivity of the developing brain. Arterial spin labeling (ASL), as a noninvasive MR technique, is particularly attractive for studying cerebral perfusion in children and even newborns. We have collected pulsed ASL data in resting state for 47 healthy subjects from young children to adolescence (aged from 6 to 20 years old). In addition to studying the developmental change of static CBF maps during resting state, we also analyzed the CBF time series to reveal the dynamic characteristics of CBF in differing age groups. We used the seed-based correlation analysis to examine the temporal relationship of CBF time series between the selected ROIs and other brain regions. We have shown the developmental patterns in both static CBF maps and dynamic characteristics of CBF. While higher CBF of default mode network (DMN) in all age groups supports that DMN is the prominent active network during the resting state, the CBF connectivity patterns of some typical resting state networks show distinct patterns of metabolic activity during the resting state in the developing brains. Copyright © 2018 European Paediatric Neurology Society. All rights reserved.

  6. Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping

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    Bin Wang

    2017-11-01

    Full Text Available Alzheimer's disease (AD is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs, 33 early MCI (EMCI, 32 late MCI (LMCI, and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ scores and global Clinical Dementia Rating (CDR scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE

  7. Habenula functional resting-state connectivity in pediatric CRPS.

    Science.gov (United States)

    Erpelding, Nathalie; Sava, Simona; Simons, Laura E; Lebel, Alyssa; Serrano, Paul; Becerra, Lino; Borsook, David

    2014-01-01

    The habenula (Hb) is a small brain structure located in the posterior end of the medial dorsal thalamus and through medial (MHb) and lateral (LHb) Hb connections, it acts as a conduit of information between forebrain and brainstem structures. The role of the Hb in pain processing is well documented in animals and recently also in acute experimental pain in humans. However, its function remains unknown in chronic pain disorders. Here, we investigated Hb resting-state functional connectivity (rsFC) in patients with complex regional pain syndrome (CRPS) compared with healthy controls. Twelve pediatric patients with unilateral lower-extremity CRPS (9 females; 10-17 yr) and 12 age- and sex-matched healthy controls provided informed consent to participate in the study. In healthy controls, Hb functional connections largely overlapped with previously described anatomical connections in cortical, subcortical, and brainstem structures. Compared with controls, patients exhibited an overall Hb rsFC reduction with the rest of the brain and, specifically, with the anterior midcingulate cortex, dorsolateral prefrontal cortex, supplementary motor cortex, primary motor cortex, and premotor cortex. Our results suggest that Hb rsFC parallels anatomical Hb connections in the healthy state and that overall Hb rsFC is reduced in patients, particularly connections with forebrain areas. Patients' decreased Hb rsFC to brain regions implicated in motor, affective, cognitive, and pain inhibitory/modulatory processes may contribute to their symptomatology.

  8. Altered thalamo-cortical resting state functional connectivity in smokers.

    Science.gov (United States)

    Wang, Chaoyan; Bai, Jie; Wang, Caihong; von Deneen, Karen M; Yuan, Kai; Cheng, Jingliang

    2017-07-13

    The thalamus has widespread connections with the prefrontal cortex (PFC) and modulates communication between the striatum and PFC, which is crucial to the neural mechanisms of smoking. However, relatively few studies focused on the thalamic resting state functional connectivity (RSFC) patterns and their association with smoking behaviors in smokers. 24 young male smokers and 24 non-smokers were enrolled in our study. Fagerström Test for Nicotine Dependence (FTND) was used to assess the nicotine dependence level. The bilateral thalamic RSFC patterns were compared between smokers and non-smokers. The relationship between neuroimaging findings and smoking behaviors (FTND and pack-years) were also investigated in smokers. Relative to nonsmokers, smokers showed reduced RSFC strength between the left thalamus and several brain regions, i.e. the right dorsolateral prefrontal cortex (dlPFC), the anterior cingulate cortex (ACC) and the bilateral caudate. In addition, the right thalamus showed reduced RSFC with the right dlPFC as well as the bilateral insula in smokers. Therefore, the findings in the current study revealed the reduced RSFC of the thalamus with the dlPFC, the ACC, the insula and the caudate in smokers, which provided new insights into the roles of the thalamus in nicotine addiction from a function integration perspective. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Impairments of thalamic resting-state functional connectivity in patients with chronic tinnitus

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    Zhang, Jian [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Chen, Yu-Chen [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Center for Hearing and Deafness, University at Buffalo, State University of New York, Buffalo, NY (United States); Feng, Xu [Department of Otolaryngology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Yang, Ming; Liu, Bin; Qian, Cheng [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China); Wang, Jian [Department of Physiology, Southeast University, Nanjing (China); School of Human Communication Disorders, Dalhousie University, Halifax, NS (Canada); Salvi, Richard [Center for Hearing and Deafness, University at Buffalo, State University of New York, Buffalo, NY (United States); Teng, Gao-Jun, E-mail: gjteng@vip.sina.com [Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing (China)

    2015-07-15

    Highlights: • Tinnitus patients have aberrant thalamic connectivity to many brain regions. • Decreased thalamic connectivity is linked with tinnitus characteristics. • Thalamocortical connectivity disturbances can reflect tinnitus-related networks. - Abstract: Purpose: The phantom sound of tinnitus is believed to arise from abnormal functional coupling between the thalamus and cerebral cortex. To explore this hypothesis, we used resting-state functional magnetic resonance imaging (fMRI) to compare the degree of thalamocortical functional connectivity in chronic tinnitus patients and controls. Materials and methods: Resting-state fMRI scans were obtained from 31 chronic tinnitus patients and 33 well-matched healthy controls. Thalamocortical functional connectivity was characterized using a seed-based whole-brain correlation method. The resulting thalamic functional connectivity measures were correlated with other clinical data. Results: We found decreased functional connectivity between the seed region in left thalamus and right middle temporal gyrus (MTG), right middle orbitofrontal cortex, left middle frontal gyrus, right precentral gyrus, and bilateral calcarine cortex. Decreased functional connectivity was detected between the seed in the right thalamus and the left superior temporal gyrus (STG), left amygdala, right superior frontal gyrus, left precentral gyrus, and left middle occipital gyrus. Tinnitus distress correlated negatively with thalamic functional connectivity in right MTG; tinnitus duration correlated negatively with thalamic functional connectivity in left STG. Increased functional connectivity between the bilateral thalamus and a set of regions were also observed. Conclusions: Chronic tinnitus patients have disrupted thalamocortical functional connectivity to selected brain regions which is associated with specific tinnitus characteristics. Resting-state thalamic functional connectivity disturbances may play an important role in

  10. Impairments of thalamic resting-state functional connectivity in patients with chronic tinnitus

    International Nuclear Information System (INIS)

    Zhang, Jian; Chen, Yu-Chen; Feng, Xu; Yang, Ming; Liu, Bin; Qian, Cheng; Wang, Jian; Salvi, Richard; Teng, Gao-Jun

    2015-01-01

    Highlights: • Tinnitus patients have aberrant thalamic connectivity to many brain regions. • Decreased thalamic connectivity is linked with tinnitus characteristics. • Thalamocortical connectivity disturbances can reflect tinnitus-related networks. - Abstract: Purpose: The phantom sound of tinnitus is believed to arise from abnormal functional coupling between the thalamus and cerebral cortex. To explore this hypothesis, we used resting-state functional magnetic resonance imaging (fMRI) to compare the degree of thalamocortical functional connectivity in chronic tinnitus patients and controls. Materials and methods: Resting-state fMRI scans were obtained from 31 chronic tinnitus patients and 33 well-matched healthy controls. Thalamocortical functional connectivity was characterized using a seed-based whole-brain correlation method. The resulting thalamic functional connectivity measures were correlated with other clinical data. Results: We found decreased functional connectivity between the seed region in left thalamus and right middle temporal gyrus (MTG), right middle orbitofrontal cortex, left middle frontal gyrus, right precentral gyrus, and bilateral calcarine cortex. Decreased functional connectivity was detected between the seed in the right thalamus and the left superior temporal gyrus (STG), left amygdala, right superior frontal gyrus, left precentral gyrus, and left middle occipital gyrus. Tinnitus distress correlated negatively with thalamic functional connectivity in right MTG; tinnitus duration correlated negatively with thalamic functional connectivity in left STG. Increased functional connectivity between the bilateral thalamus and a set of regions were also observed. Conclusions: Chronic tinnitus patients have disrupted thalamocortical functional connectivity to selected brain regions which is associated with specific tinnitus characteristics. Resting-state thalamic functional connectivity disturbances may play an important role in

  11. The neural correlates of risk propensity in males and females using resting-state fMRI

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    Yuan eZhou

    2014-01-01

    Full Text Available Men are more risk prone than women, but the underlying basis remains unclear. To investigate this question, we developed a trait-like measure of risk propensity which we correlated with resting-state functional connectivity to identify sex differences. Specifically, we used short- and long-range functional connectivity densities to identify associated brain regions and examined their functional connectivities in resting-state functional magnetic resonance imaging (fMRI data collected from a large sample of healthy young volunteers. We found that men had a higher level of general risk propensity (GRP than women. At the neural level, although they shared a common neural correlate of GRP in a network centered at the right inferior frontal gyrus, men and women differed in a network centered at the right secondary somatosensory cortex, which included the bilateral dorsal anterior/middle insular cortices and the dorsal anterior cingulate cortex. In addition, men and women differed in a local network centered at the left inferior orbitofrontal cortex. Most of the regions identified by this resting-state fMRI study have been previously implicated in risk processing when people make risky decisions. This study provides a new perspective on the brain-behavioral relationships in risky decision making and contributes to our understanding of sex differences in risk propensity.

  12. Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan

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    Jianxin Dong

    2018-02-01

    Full Text Available Exploring functional information among various brain regions across time enables understanding of healthy aging process and holds great promise for age-related brain disease diagnosis. This paper proposed a method to explore fractal complexity of the resting-state functional magnetic resonance imaging (rs-fMRI signal in the human brain across the adult lifespan using Hurst exponent (HE. We took advantage of the examined rs-fMRI data from 116 adults 19 to 85 years of age (44.3 ± 19.4 years, 49 females from NKI/Rockland sample. Region-wise and voxel-wise analyses were performed to investigate the effects of age, gender, and their interaction on complexity. In region-wise analysis, we found that the healthy aging is accompanied by a loss of complexity in frontal and parietal lobe and increased complexity in insula, limbic, and temporal lobe. Meanwhile, differences in HE between genders were found to be significant in parietal lobe (p = 0.04, corrected. However, there was no interaction between gender and age. In voxel-wise analysis, the significant complexity decrease with aging was found in frontal and parietal lobe, and complexity increase was found in insula, limbic lobe, occipital lobe, and temporal lobe with aging. Meanwhile, differences in HE between genders were found to be significant in frontal, parietal, and limbic lobe. Furthermore, we found age and sex interaction in right parahippocampal gyrus (p = 0.04, corrected. Our findings reveal HE variations of the rs-fMRI signal across the human adult lifespan and show that HE may serve as a new parameter to assess healthy aging process.

  13. Is fMRI ?noise? really noise? Resting state nuisance regressors remove variance with network structure

    OpenAIRE

    Bright, Molly G.; Murphy, Kevin

    2015-01-01

    Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed ...

  14. Whole brain resting-state analysis reveals decreased functional connectivity in major depression

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    Ilya M. Veer

    2010-09-01

    Full Text Available Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within six months before inclusion and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxelwise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: 1 decreased bilateral amygdala and left anterior insula connectivity in an affective network, 2 reduced connectivity of the left frontal pole in a network associated with attention and working memory, and 3 decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or grey matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

  15. Complex network analysis of resting-state fMRI of the brain.

    Science.gov (United States)

    Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

    2016-08-01

    Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

  16. Test-retest reliability of fMRI-based graph theoretical properties during working memory, emotion processing, and resting state.

    Science.gov (United States)

    Cao, Hengyi; Plichta, Michael M; Schäfer, Axel; Haddad, Leila; Grimm, Oliver; Schneider, Michael; Esslinger, Christine; Kirsch, Peter; Meyer-Lindenberg, Andreas; Tost, Heike

    2014-01-01

    The investigation of the brain connectome with functional magnetic resonance imaging (fMRI) and graph theory analyses has recently gained much popularity, but little is known about the robustness of these properties, in particular those derived from active fMRI tasks. Here, we studied the test-retest reliability of brain graphs calculated from 26 healthy participants with three established fMRI experiments (n-back working memory, emotional face-matching, resting state) and two parcellation schemes for node definition (AAL atlas, functional atlas proposed by Power et al.). We compared the intra-class correlation coefficients (ICCs) of five different data processing strategies and demonstrated a superior reliability of task-regression methods with condition-specific regressors. The between-task comparison revealed significantly higher ICCs for resting state relative to the active tasks, and a superiority of the n-back task relative to the face-matching task for global and local network properties. While the mean ICCs were typically lower for the active tasks, overall fair to good reliabilities were detected for global and local connectivity properties, and for the n-back task with both atlases, smallworldness. For all three tasks and atlases, low mean ICCs were seen for the local network properties. However, node-specific good reliabilities were detected for node degree in regions known to be critical for the challenged functions (resting-state: default-mode network nodes, n-back: fronto-parietal nodes, face-matching: limbic nodes). Between-atlas comparison demonstrated significantly higher reliabilities for the functional parcellations for global and local network properties. Our findings can inform the choice of processing strategies, brain atlases and outcome properties for fMRI studies using active tasks, graph theory methods, and within-subject designs, in particular future pharmaco-fMRI studies. © 2013 Elsevier Inc. All rights reserved.

  17. Changes in resting-state functionally connected parietofrontal networks after videogame practice.

    Science.gov (United States)

    Martínez, Kenia; Solana, Ana Beatriz; Burgaleta, Miguel; Hernández-Tamames, Juan Antonio; Alvarez-Linera, Juan; Román, Francisco J; Alfayate, Eva; Privado, Jesús; Escorial, Sergio; Quiroga, María A; Karama, Sherif; Bellec, Pierre; Colom, Roberto

    2013-12-01

    Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions. Copyright © 2012 Wiley Periodicals, Inc.

  18. Changes in resting-state fMRI in vestibular neuritis.

    Science.gov (United States)

    Helmchen, Christoph; Ye, Zheng; Sprenger, Andreas; Münte, Thomas F

    2014-11-01

    Vestibular neuritis (VN) is a sudden peripheral unilateral vestibular failure with often persistent head movement-related dizziness and unsteadiness. Compensation of asymmetrical activity in the primary peripheral vestibular afferents is accomplished by restoration of impaired brainstem vestibulo-ocular and vestibulo-spinal reflexes, but presumably also by changing cortical vestibular tone imbalance subserving, e.g., spatial perception and orientation. The aim of this study was to elucidate (i) whether there are changes of cerebral resting-state networks with respect to functional interregional connectivity (resting-state activity) in VN patients and (ii) whether these are related to neurophysiological, perceptual and functional parameters of vestibular-induced disability. Using independent component analysis (ICA), we compared resting-state networks between 20 patients with unilateral VN and 20 age- and gender-matched healthy control subjects. Patients were examined in the acute VN stage and after 3 months. A neural network (component 50) comprising the parietal lobe, medial aspect of the superior parietal lobule, posterior cingulate cortex, middle frontal gyrus, middle temporal gyrus, parahippocampal gyrus, anterior cingulate cortex, insular cortex, caudate nucleus, thalamus and midbrain was modulated between acute VN patients and healthy controls and in patients over time. Within this network, acute VN patients showed decreased resting-state activity (ICA) in the contralateral intraparietal sulcus (IPS), in close vicinity to the supramarginal gyrus (SMG), which increased after 3 months. Resting-state activity in IPS tended to increase over 3 months in VN patients who improved with respect to functional parameters of vestibular-induced disability (VADL). Resting-state activity in the IPS was not related to perceptual (subjective visual vertical) or neurophysiological parameters of vestibular-induced disability (e.g., gain of vestibulo-ocular reflex, caloric

  19. Potential pitfalls when denoising resting state fMRI data using nuisance regression.

    Science.gov (United States)

    Bright, Molly G; Tench, Christopher R; Murphy, Kevin

    2017-07-01

    In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Altered default network resting-state functional connectivity in adolescents with Internet gaming addiction.

    Directory of Open Access Journals (Sweden)

    Wei-na Ding

    Full Text Available Excessive use of the Internet has been linked to a variety of negative psychosocial consequences. This study used resting-state functional magnetic resonance imaging (fMRI to investigate whether functional connectivity is altered in adolescents with Internet gaming addiction (IGA.Seventeen adolescents with IGA and 24 normal control adolescents underwent a 7.3 minute resting-state fMRI scan. Posterior cingulate cortex (PCC connectivity was determined in all subjects by investigating synchronized low-frequency fMRI signal fluctuations using a temporal correlation method. To assess the relationship between IGA symptom severity and PCC connectivity, contrast images representing areas correlated with PCC connectivity were correlated with the scores of the 17 subjects with IGA on the Chen Internet Addiction Scale (CIAS and Barratt Impulsiveness Scale-11 (BIS-11 and their hours of Internet use per week.There were no significant differences in the distributions of the age, gender, and years of education between the two groups. The subjects with IGA showed longer Internet use per week (hours (p<0.0001 and higher CIAS (p<0.0001 and BIS-11 (p = 0.01 scores than the controls. Compared with the control group, subjects with IGA exhibited increased functional connectivity in the bilateral cerebellum posterior lobe and middle temporal gyrus. The bilateral inferior parietal lobule and right inferior temporal gyrus exhibited decreased connectivity. Connectivity with the PCC was positively correlated with CIAS scores in the right precuneus, posterior cingulate gyrus, thalamus, caudate, nucleus accumbens, supplementary motor area, and lingual gyrus. It was negatively correlated with the right cerebellum anterior lobe and left superior parietal lobule.Our results suggest that adolescents with IGA exhibit different resting-state patterns of brain activity. As these alterations are partially consistent with those in patients with substance addiction, they support the

  1. A Longitudinal Study on Resting State Functional Connectivity in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease.

    Science.gov (United States)

    Hafkemeijer, Anne; Möller, Christiane; Dopper, Elise G P; Jiskoot, Lize C; van den Berg-Huysmans, Annette A; van Swieten, John C; van der Flier, Wiesje M; Vrenken, Hugo; Pijnenburg, Yolande A L; Barkhof, Frederik; Scheltens, Philip; van der Grond, Jeroen; Rombouts, Serge A R B

    2017-01-01

    Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are the most common types of early-onset dementia. We applied longitudinal resting state functional magnetic resonance imaging (fMRI) to delineate functional brain connections relevant for disease progression and diagnostic accuracy. We used two-center resting state fMRI data of 20 AD patients (65.1±8.0 years), 12 bvFTD patients (64.7±5.4 years), and 22 control subjects (63.8±5.0 years) at baseline and 1.8-year follow-up. We used whole-network and voxel-based network-to-region analyses to study group differences in functional connectivity at baseline and follow-up, and longitudinal changes in connectivity within and between groups. At baseline, connectivity between paracingulate gyrus and executive control network, between cuneal cortex and medial visual network, and between paracingulate gyrus and salience network was higher in AD compared with controls. These differences were also present after 1.8 years. At follow-up, connectivity between angular gyrus and right frontoparietal network, and between paracingulate gyrus and default mode network was lower in bvFTD compared with controls, and lower compared with AD between anterior cingulate gyrus and executive control network, and between lateral occipital cortex and medial visual network. Over time, connectivity decreased in AD between precuneus and right frontoparietal network and in bvFTD between inferior frontal gyrus and left frontoparietal network. Longitudinal changes in connectivity between supramarginal gyrus and right frontoparietal network differ between both patient groups and controls. We found disease-specific brain regions with longitudinal connectivity changes. This suggests the potential of longitudinal resting state fMRI to delineate regions relevant for disease progression and for diagnostic accuracy, although no group differences in longitudinal changes in the direct comparison of AD and bvFTD were found.

  2. Experimentally induced thyrotoxicosis leads to increased connectivity in temporal lobe structures: a resting state fMRI study.

    Science.gov (United States)

    Göttlich, Martin; Heldmann, Marcus; Göbel, Anna; Dirk, Anna-Luise; Brabant, Georg; Münte, Thomas F

    2015-06-01

    Adult onset hyperthyroidism may impact on different cognitive domains, including attention and concentration, memory, perceptual function, language and executive function. Previous PET studies implicated changed functionality of limbic regions, the temporal and frontal lobes in hyperthyroidism, whereas it is unknown whether cognitive effects of hyperthyroidism may be due to changed brain connectivity. This study aimed to investigate the effect of experimentally induced short-term hyperthyroidism thyrotoxicosis on resting-state functional connectivity using functional magnetic resonance imaging. Twenty-nine healthy male right-handed subjects were examined twice, once prior and once after 8 weeks of oral administration of 250 μg levothyroxine per day. Resting-state fMRI was subjected to graph-theory based analysis methods to investigate whole-brain intrinsic functional connectivity. Despite a lack of subjective changes noticed by the subjects significant thyrotoxicosis was confirmed in all subjects. This induced a significant increase in resting-state functional connectivity specifically in the rostral temporal lobes (0.05 FDR corrected at the cluster level), which is caused by an increased connectivity to the cognitive control network. The increased connectivity between temporal poles and the cognitive control network shown here under experimental conditions supports an important function of thyroid hormones in the regulation of paralimbic structures. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure.

    Science.gov (United States)

    Bright, Molly G; Murphy, Kevin

    2015-07-01

    Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. Copyright © 2015. Published by Elsevier Inc.

  4. Effects of taurine on resting-state fMRI activity in spontaneously hypertensive rats.

    Science.gov (United States)

    Chen, Vincent Chin-Hung; Hsu, Tsai-Ching; Chen, Li-Jeng; Chou, Hong-Chun; Weng, Jun-Cheng; Tzang, Bor-Show

    2017-01-01

    Attention deficit hyperactivity disorder (ADHD) is a global behavior illness among children and adults. To investigate the effects of taurine on resting-state fMRI activity in ADHD, a spontaneously hypertensive rat (SHR) animal model was adopted. Significantly decreased serum C-reactive protein (CRP) was detected in rats of Wistar Kyoto (WKY) high-taurine group and significantly decreased interleukin (IL)-1β and CRP were detected in rats of SHR low-taurine and high-taurine groups. Moreover, significantly higher horizontal locomotion was detected in rats of WKY low-taurine and SHR low-taurine groups than in those of controls. In contrast, significantly lower horizontal locomotion was detected in rats of the SHR high-taurine group than in those of the SHR control group. Additionally, significantly lower functional connectivity (FC) and mean amplitude of low-frequency fluctuation (mALFF) in the bilateral hippocampus in rats of WKY high-taurine and SHR high-taurine groups was detected. Notably, the mALFF in rats of the SHR low-taurine and high-taurine groups was significantly lower than in those of the SHR control group. These findings suggest that the administration of a high-dose taurine probably improves hyperactive behavior in SHR rats by ameliorating the inflammatory cytokines and modulating brain functional signals in SHR rats.

  5. Altered default network resting-state functional connectivity in adolescents with Internet gaming addiction.

    Science.gov (United States)

    Ding, Wei-na; Sun, Jin-hua; Sun, Ya-wen; Zhou, Yan; Li, Lei; Xu, Jian-rong; Du, Ya-song

    2013-01-01

    Excessive use of the Internet has been linked to a variety of negative psychosocial consequences. This study used resting-state functional magnetic resonance imaging (fMRI) to investigate whether functional connectivity is altered in adolescents with Internet gaming addiction (IGA). Seventeen adolescents with IGA and 24 normal control adolescents underwent a 7.3 minute resting-state fMRI scan. Posterior cingulate cortex (PCC) connectivity was determined in all subjects by investigating synchronized low-frequency fMRI signal fluctuations using a temporal correlation method. To assess the relationship between IGA symptom severity and PCC connectivity, contrast images representing areas correlated with PCC connectivity were correlated with the scores of the 17 subjects with IGA on the Chen Internet Addiction Scale (CIAS) and Barratt Impulsiveness Scale-11 (BIS-11) and their hours of Internet use per week. There were no significant differences in the distributions of the age, gender, and years of education between the two groups. The subjects with IGA showed longer Internet use per week (hours) (paddiction, they support the hypothesis that IGA as a behavioral addiction that may share similar neurobiological abnormalities with other addictive disorders.

  6. Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture.

    Science.gov (United States)

    Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Cabanban, Romeo; Crosson, Bruce A

    2015-06-01

    A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.

  7. Resting state functional connectivity magnetic resonance imaging integrated with intraoperative neuronavigation for functional mapping after aborted awake craniotomy

    Science.gov (United States)

    Batra, Prag; Bandt, S. Kathleen; Leuthardt, Eric C.

    2016-01-01

    Background: Awake craniotomy is currently the gold standard for aggressive tumor resections in eloquent cortex. However, a significant subset of patients is unable to tolerate this procedure, particularly the very young or old or those with psychiatric comorbidities, cardiopulmonary comorbidities, or obesity, among other conditions. In these cases, typical alternative procedures include biopsy alone or subtotal resection, both of which are associated with diminished surgical outcomes. Case Description: Here, we report the successful use of a preoperatively obtained resting state functional connectivity magnetic resonance imaging (MRI) integrated with intraoperative neuronavigation software in order to perform functional cortical mapping in the setting of an aborted awake craniotomy due to loss of airway. Conclusion: Resting state functional connectivity MRI integrated with intraoperative neuronavigation software can provide an alternative option for functional cortical mapping in the setting of an aborted awake craniotomy. PMID:26958419

  8. ADHD-200 Global Competition: Diagnosing ADHD using personal characteristic data can outperform resting state fMRI measurements

    Directory of Open Access Journals (Sweden)

    Matthew R G Brown

    2012-09-01

    Full Text Available Neuroimaging-based diagnostics could potentially assist clinicians to make more accurate diagnoses resulting in faster, more effective treatment. We participated in the 2011 ADHD-200 Global Competition which involved analyzing a large dataset of 973 participants including ADHD patients and healthy controls. Each participant's data included a resting state functional magnetic resonance imaging (fMRI scan as well as personal characteristic and diagnostic data. The goal was to learn a machine learning classifier that used a participant's resting state fMRI scan to diagnose (classify that individual into one of three categories: healthy control, ADHD combined type, or ADHD inattentive type. We used participants' personal characteristic data (site of data collection, age, gender, handedness, performance IQ, verbal IQ, and full scale IQ, without any fMRI data, as input to a logistic classifier to generate diagnostic predictions. Surprisingly, this approach achieved the highest diagnostic accuracy (62.52% as well as the highest score (124 of 195 of any of the 21 teams participating in the competition. These results demonstrate the importance of accounting for differences in age, gender, and other personal characteristics in imaging diagnostics research. We discuss further implications of these results for fMRI-based diagnosis as well as fMRI-based clinical research. We also document our tests with a variety of imaging-based diagnostic methods, none of which performed as well as the logistic classifier using only personal characteristic data.

  9. Structure-function relationships in elderly resting-state-networks : influence of age and cognitive performance

    OpenAIRE

    Jockwitz, Christiane

    2016-01-01

    The aim of this work was to investigate the structure-function relationship in cognitive resting state networks in a large population-based elderly sample. The first study characterized the functional connectivity in four cognitive resting state networks with respect to age, gender and cognitive performance: Default Mode Network (DMN), executive, and left and right frontoparietal resting state networks. The second study assessed the structural correlates of the functional reorganization of th...

  10. Resting state functional connectivity differences between behavioral variant frontotemporal dementia and Alzheimer’s disease

    Directory of Open Access Journals (Sweden)

    Anne eHafkemeijer

    2015-09-01

    Full Text Available Alzheimer’s disease (AD and behavioral variant frontotemporal dementia (bvFTD are the most common types of early-onset dementia. Here, we apply resting state functional magnetic resonance imaging (fMRI to study functional brain connectivity differences between AD and bvFTD.We used resting state fMRI data of 31 AD patients, 25 bvFTD patients, and 29 controls. We studied functional connectivity throughout the entire brain, applying two different analysis techniques, studying network-to-region and region-to-region connectivity. A general linear model approach was used to study group differences, while controlling for physiological noise, age, gender, study center, and regional gray matter volume. Given gray matter differences, we observed decreased network-to-region connectivity in bvFTD between a lateral visual cortical network and lateral occipital and cuneal cortex, and b auditory system network and angular gyrus. In AD, we found decreased network-to-region connectivity between the dorsal visual stream network and lateral occipital and parietal opercular cortex. Region-to-region connectivity was decreased in bvFTD between superior temporal gyrus and cuneal, supracalcarine, intracalcarine cortex, and lingual gyrus. We showed that the pathophysiology of functional brain connectivity is different between AD and bvFTD. However, the group differences in functional connectivity are less abundant than has been shown in previous studies.

  11. Abnormal Resting-State Functional Connectivity in Progressive Supranuclear Palsy and Corticobasal Syndrome

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    Komal Bharti

    2017-06-01

    Full Text Available BackgroundPathological and MRI-based evidence suggests that multiple brain structures are likely to be involved in functional disconnection between brain areas. Few studies have investigated resting-state functional connectivity (rsFC in progressive supranuclear palsy (PSP and corticobasal syndrome (CBS. In this study, we investigated within- and between-network rsFC abnormalities in these two conditions.MethodsTwenty patients with PSP, 11 patients with CBS, and 16 healthy subjects (HS underwent a resting-state fMRI study. Resting-state networks (RSNs were extracted to evaluate within- and between-network rsFC using the Melodic and FSLNets software packages.ResultsIncreased within-network rsFC was observed in both PSP and CBS patients, with a larger number of RSNs being involved in CBS. Within-network cerebellar rsFC positively correlated with mini-mental state examination scores in patients with PSP. Compared to healthy volunteers, PSP and CBS patients exhibit reduced functional connectivity between the lateral visual and auditory RSNs, with PSP patients additionally showing lower functional connectivity between the cerebellar and insular RSNs. Moreover, rsFC between the salience and executive-control RSNs was increased in patients with CBS compared to HS.ConclusionThis study provides evidence of functional brain reorganization in both PSP and CBS. Increased within-network rsFC could represent a higher degree of synchronization in damaged brain areas, while between-network rsFC abnormalities may mainly reflect degeneration of long-range white matter fibers.

  12. Pain Perception Can Be Modulated by Mindfulness Training: A Resting-state fMRI Study

    Directory of Open Access Journals (Sweden)

    I-Wen Su

    2016-11-01

    Full Text Available The multi-dimensional nature of pain renders difficult a holistic understanding of it. The conceptual framework of pain is said to be cognitive-evaluative, in addition to being sensory-discriminative and affective-motivational. To compare participants’ brain-behavior response before and after a six-week mindfulness-based stress reduction (MBSR training course on mindfulness in relation to pain modulation, three questionnaires (the Dallas Pain Questionnaire, Short Form McGill Pain Questionnaire-SFMPQ, and Kentucky Inventory of Mindfulness as well as resting-state functional magnetic resonance imaging (fMRI were administered to participants, divided into a pain-afflicted group (N=18 and a control group (N=16. Our results showed that the pain-afflicted group experienced significantly less pain after the mindfulness treatment than before, as measured by the SFMPQ. In conjunction, an increased connection from the anterior insular cortex (AIC to the dorsal anterior midcingulate cortex (daMCC was observed in the post-training pain-afflicted group and a significant correlation was found between AIC-daMCC connectivity and SFMPQ scores. The results suggest that mindfulness training can modulate the brain network dynamics underlying the subjective experience of pain.

  13. Brain entropy and human intelligence: A resting-state fMRI study.

    Science.gov (United States)

    Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

    2018-01-01

    Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

  14. Brain entropy and human intelligence: A resting-state fMRI study

    Science.gov (United States)

    Calderone, Daniel; Morales, Leah J.

    2018-01-01

    Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

  15. Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

    Science.gov (United States)

    Dong, Xiaojuan; Qin, Haixia; Wu, Taoyu; Hu, Hua; Liao, Keren; Cheng, Fei; Gao, Dong; Lei, Xu

    2018-02-01

    One classical hypothesis among many models to explain the etiology and maintenance of insomnia disorder (ID) is hyperarousal. Aberrant functional connectivity among resting-state large-scale brain networks may be the underlying neurological mechanisms of this hypothesis. The aim of current study was to investigate the functional network connectivity (FNC) among large-scale brain networks in patients with insomnia disorder (ID) during resting state. In the present study, the resting-state fMRI was used to evaluate whether patients with ID showed aberrant FNC among dorsal attention network (DAN), frontoparietal control network (FPC), anterior default mode network (aDMN), and posterior default mode network (pDMN) compared with healthy good sleepers (HGSs). The Pearson's correlation analysis was employed to explore whether the abnormal FNC observed in patients with ID was associated with sleep parameters, cognitive and emotional scores, and behavioral performance assessed by questionnaires and tasks. Patients with ID had worse subjective thought control ability measured by Thought Control Ability Questionnaire (TCAQ) and more negative affect than HGSs. Intriguingly, relative to HGSs, patients with ID showed a significant increase in FNC between DAN and FPC, but a significant decrease in FNC between aDMN and pDMN. Exploratory analysis in patients with ID revealed a significantly positive correlation between the DAN-FPC FNC and reaction time (RT) of psychomotor vigilance task (PVT). The current study demonstrated that even during the resting state, the task-activated and task-deactivated large-scale brain networks in insomniacs may still maintain a hyperarousal state, looking quite similar to the pattern in a task condition with external stimuli. Those results support the hyperarousal model of insomnia.

  16. Ketamine changes the local resting-state functional properties of anesthetized-monkey brain.

    Science.gov (United States)

    Rao, Jia-Sheng; Liu, Zuxiang; Zhao, Can; Wei, Rui-Han; Zhao, Wen; Tian, Peng-Yu; Zhou, Xia; Yang, Zhao-Yang; Li, Xiao-Guang

    2017-11-01

    Ketamine is a well-known anesthetic. 'Recreational' use of ketamine common induces psychosis-like symptoms and cognitive impairments. The acute and chronic effects of ketamine on relevant brain circuits have been studied, but the effects of single-dose ketamine administration on the local resting-state functional properties of the brain remain unknown. In this study, we aimed to assess the effects of single-dose ketamine administration on the brain local intrinsic properties. We used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the ketamine-induced alterations of brain intrinsic properties. Seven adult rhesus monkeys were imaged with rs-fMRI to examine the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) in the brain before and after ketamine injection. Paired comparisons were used to detect the significantly altered regions. Results showed that the fALFF of the prefrontal cortex (p=0.046), caudate nucleus (left side, p=0.018; right side, p=0.025), and putamen (p=0.020) in post-injection stage significantly increased compared with those in pre-injection period. The ReHo of nucleus accumbens (p=0.049), caudate nucleus (p=0.037), and hippocampus (p=0.025) increased after ketamine injection, but that of prefrontal cortex decreased (pketamine administration can change the regional intensity and synchronism of brain activity, thereby providing evidence of ketamine-induced abnormal resting-state functional properties in primates. This evidence may help further elucidate the effects of ketamine on the cerebral resting status. Copyright © 2017. Published by Elsevier Inc.

  17. Resting State fMRI in the moving fetus: a robust framework for motion, bias field and spin history correction.

    Science.gov (United States)

    Ferrazzi, Giulio; Kuklisova Murgasova, Maria; Arichi, Tomoki; Malamateniou, Christina; Fox, Matthew J; Makropoulos, Antonios; Allsop, Joanna; Rutherford, Mary; Malik, Shaihan; Aljabar, Paul; Hajnal, Joseph V

    2014-11-01

    There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

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    Chandler R. L. Mongerson

    2017-08-01

    Full Text Available Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1 present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA, such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2 review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3 discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

  19. Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality.

    Science.gov (United States)

    Mongerson, Chandler R L; Jennings, Russell W; Borsook, David; Becerra, Lino; Bajic, Dusica

    2017-01-01

    Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.

  20. Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

    Science.gov (United States)

    von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

    2018-02-01

    Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which

  1. A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

    Science.gov (United States)

    Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

    2015-10-01

    In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

  2. Altered Default Mode Network on Resting-State fMRI in Children with Infantile Spasms

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    Ya Wang

    2017-05-01

    Full Text Available Infantile spasms (IS syndrome is an age-dependent epileptic encephalopathy, which occurs in children characterized by spasms, impaired consciousness, and hypsarrhythmia. Abnormalities in default mode network (DMN might contribute to the loss of consciousness during seizures and cognitive deficits in children with IS. The purpose of the present study was to investigate the changes in DMN with functional connectivity (FC and amplitude of low-frequency fluctuation (ALFF, the two methods to discover the potential neuronal underpinnings of IS. The consistency of the two calculate methods of DMN abnormalities in IS patients was also our main focus. To avoid the disturbance of interictal epileptic discharge, our testing was performed within the interictal durations without epileptic discharges. Resting-state fMRI data were collected from 13 patients with IS and 35 sex- and age-matched healthy controls. FC analysis with seed in posterior cingulate cortex (PCC was used to compare the differences between two groups. We chose PCC as the seed region because PCC is the only node in the DMN that directly interacts with virtually all other nodes according to previous studies. Furthermore, the ALFF values within the DMN were also calculated and compared between the two groups. The FC results showed that IS patients exhibited markedly reduced connectivity between posterior seed region and other areas within DMN. In addition, part of the brain areas within the DMN showing significant difference of FC had significantly lower ALFF signal in the patient group than that in the healthy controls. The observed disruption in DMN through the two methods showed that the coherence of brain signal fluctuation in DMN during rest was broken in IS children. Neuronal functional impairment or altered integration in DMN would be one neuroimaging characteristic, which might help us to understand the underlying neural mechanism of IS. Further studies are needed to determine whether

  3. Classification of schizophrenia patients based on resting-state functional network connectivity

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    Mohammad Reza Arbabshirani

    2013-07-01

    Full Text Available There is a growing interest in automatic classification of mental disorders based on neuroimaging data. Small training data sets (subjects and very large amount of high dimensional data make it a challenging task to design robust and accurate classifiers for heterogeneous disorders such as schizophrenia. Most previous studies considered structural MRI, diffusion tensor imaging and task-based fMRI for this purpose. However, resting-state data has been rarely used in discrimination of schizophrenia patients from healthy controls. Resting data are of great interest, since they are relatively easy to collect, and not confounded by behavioral performance on a task. Several linear and non-linear classification methods were trained using a training dataset and evaluate with a separate testing dataset. Results show that classification with high accuracy is achievable using simple non-linear discriminative methods such as k-nearest neighbors which is very promising. We compare and report detailed results of each classifier as well as statistical analysis and evaluation of each single feature. To our knowledge our effects represent the first use of resting-state functional network connectivity features to classify schizophrenia.

  4. ICA-based artifact removal diminishes scan site differences in multi-center resting-state fMRI

    NARCIS (Netherlands)

    R.A. Feis (Rogier A.); S.M. Smith (Stephen); N. Filippini (Nicola); G. Douaud (Gwenaëlle); E.G.P. Dopper (Elise); V. Heise (Verena); A.J. Trachtenberg (Aaron J.); J.C. van Swieten (John); M.A. van Buchem (Mark); S.A.R.B. Rombouts (Serge); C.E. Mackay (Clare E.)

    2015-01-01

    textabstractResting-state fMRI (R-fMRI) has shown considerable promise in providing potential biomarkers for diagnosis, prognosis and drug response across a range of diseases. Incorporating R-fMRI into multi-center studies is becoming increasingly popular, imposing technical challenges on data

  5. A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data.

    Science.gov (United States)

    James, George Andrew; Hazaroglu, Onder; Bush, Keith A

    2016-02-01

    The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all pRest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory

  6. Comparison of spontaneous brain activity revealed by regional homogeneity in AQP4-IgG neuromyelitis optica-optic neuritis versus MOG-IgG optic neuritis patients: a resting-state functional MRI study

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    Wang J

    2017-10-01

    Ho values in the posterior lobe of the right cerebellum.AQP4-Ig+NMO-ON subjects showed higher ReHo values in the left precentral/postcentral gyrus and right superior temporal gyrus. Conclusion: AQP4-IgG+NMO-ON and MOG-IgG+ON subjects showed abnormal synchronized neuronal activity in many brain regions, which is consistent with deficits in visual, motor, and cognitive function. Furthermore, different patterns of synchronized neuronal activity occurred in the AQP4-IgG+NMO-ON and MOG-IgG+ON. Keywords: neuromyelitis optica-optic neuritis, MOG-IgG, AQP4-IgG, regional homogeneity, resting state, functional magnetic resonance imaging

  7. Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

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    Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C

    2017-06-01

    Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.

  8. Classification of fMRI resting-state maps using machine learning techniques: A comparative study

    Science.gov (United States)

    Gallos, Ioannis; Siettos, Constantinos

    2017-11-01

    We compare the efficiency of Principal Component Analysis (PCA) and nonlinear learning manifold algorithms (ISOMAP and Diffusion maps) for classifying brain maps between groups of schizophrenia patients and healthy from fMRI scans during a resting-state experiment. After a standard pre-processing pipeline, we applied spatial Independent component analysis (ICA) to reduce (a) noise and (b) spatial-temporal dimensionality of fMRI maps. On the cross-correlation matrix of the ICA components, we applied PCA, ISOMAP and Diffusion Maps to find an embedded low-dimensional space. Finally, support-vector-machines (SVM) and k-NN algorithms were used to evaluate the performance of the algorithms in classifying between the two groups.

  9. Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

    Science.gov (United States)

    Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland-Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean-Flory Luaba; Schiff, Nicholas D; Laureys, Steven

    2016-01-01

    The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.

  10. Altered Coupling Between Resting-State Cerebral Blood Flow and Functional Connectivity in Schizophrenia.

    Science.gov (United States)

    Zhu, Jiajia; Zhuo, Chuanjun; Xu, Lixue; Liu, Feng; Qin, Wen; Yu, Chunshui

    2017-10-21

    Respective changes in resting-state cerebral blood flow (CBF) and functional connectivity in schizophrenia have been reported. However, their coupling alterations in schizophrenia remain largely unknown. 89 schizophrenia patients and 90 sex- and age-matched healthy controls underwent resting-state functional MRI to calculate functional connectivity strength (FCS) and arterial spin labeling imaging to compute CBF. The CBF-FCS coupling of the whole gray matter and the CBF/FCS ratio (the amount of blood supply per unit of connectivity strength) of each voxel were compared between the 2 groups. Whole gray matter CBF-FCS coupling was decreased in schizophrenia patients relative to healthy controls. In schizophrenia patients, the decreased CBF/FCS ratio was predominantly located in cognitive- and emotional-related brain regions, including the dorsolateral prefrontal cortex, insula, hippocampus and thalamus, whereas an increased CBF/FCS ratio was mainly identified in the sensorimotor regions, including the putamen, and sensorimotor, mid-cingulate and visual cortices. These findings suggest that the neurovascular decoupling in the brain may be a possible neuropathological mechanism of schizophrenia. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com

  11. Altered resting-state functional connectivity in patients with chronic bilateral vestibular failure.

    Science.gov (United States)

    Göttlich, Martin; Jandl, Nico M; Wojak, Jann F; Sprenger, Andreas; von der Gablentz, Janina; Münte, Thomas F; Krämer, Ulrike M; Helmchen, Christoph

    2014-01-01

    Patients with bilateral vestibular failure (BVF) suffer from gait unsteadiness, oscillopsia and impaired spatial orientation. Brain imaging studies applying caloric irrigation to patients with BVF have shown altered neural activity of cortical visual-vestibular interaction: decreased bilateral neural activity in the posterior insula and parietal operculum and decreased deactivations in the visual cortex. It is unknown how this affects functional connectivity in the resting brain and how changes in connectivity are related to vestibular impairment. We applied a novel data driven approach based on graph theory to investigate altered whole-brain resting-state functional connectivity in BVF patients (n= 22) compared to age- and gender-matched healthy controls (n= 25) using resting-state fMRI. Changes in functional connectivity were related to subjective (vestibular scores) and objective functional parameters of vestibular impairment, specifically, the adaptive changes during active (self-guided) and passive (investigator driven) head impulse test (HIT) which reflects the integrity of the vestibulo-ocular reflex (VOR). BVF patients showed lower bilateral connectivity in the posterior insula and parietal operculum but higher connectivity in the posterior cerebellum compared to controls. Seed-based analysis revealed stronger connectivity from the right posterior insula to the precuneus, anterior insula, anterior cingulate cortex and the middle frontal gyrus. Excitingly, functional connectivity in the supramarginal gyrus (SMG) of the inferior parietal lobe and posterior cerebellum correlated with the increase of VOR gain during active as compared to passive HIT, i.e., the larger the adaptive VOR changes the larger was the increase in regional functional connectivity. Using whole brain resting-state connectivity analysis in BVF patients we show that enduring bilateral deficient or missing vestibular input leads to changes in resting-state connectivity of the brain. These

  12. Resting-state functional magnetic resonance imaging: the impact of regression analysis.

    Science.gov (United States)

    Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

    2015-01-01

    To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

  13. Resting-state functional connectivity and pitch identification ability in non-musicians

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    Jiancheng eHou

    2015-02-01

    Full Text Available Previous studies have used task-related fMRI to investigate the neural basis of pitch identification (PI, but no study has examined the associations between resting-state functional connectivity (RSFC and PI ability. Using a large sample of Chinese non-musicians (N = 320, with 56 having prior musical training, the current study examined the associations among musical training, PI ability, and RSFC. Results showed that musical training was associated with increased RSFC within the networks for multiple cognitive functions (such as vision, phonology, semantics, auditory encoding, and executive functions. PI ability was associated with RSFC with regions for perceptual and auditory encoding for participants with musical training, and with RSFC with regions for short-term memory, semantics, and phonology for participants without musical training.

  14. Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

    Science.gov (United States)

    Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

    2012-01-01

    The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

  15. Love-related changes in the brain: A resting-state functional magnetic resonance imaging study

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    Hongwen eSong

    2015-02-01

    Full Text Available Romantic love is a motivational state associated with a desire to enter or maintain a close relationship with a specific other person. Studies with functional magnetic resonance imaging (fMRI have found activation increases in brain regions involved in processing of reward, emotion, motivation when romantic lovers view photographs of their partners. However, not much is known on whether romantic love affects the brain’s functional architecture during rest. In the present study, resting state functional magnetic resonance imaging (rsfMRI data was collected to compare the regional homogeneity (ReHo and functional connectivity (FC across a lover group (LG, N=34, currently intensely in love, ended-love group (ELG, N=34, romantic relationship ended recently, and single group (SG, N=32, never fallen in love.The results showed that:1 ReHo of the left dorsal anterior cingulate cortex (dACC was significantly increased in the LG (in comparison to the ELG and the SG; 2 ReHo of the left dACC was positively correlated with length of time in love in the LG, and negatively correlated with the lovelorn duration since breakup in the ELG; 3 functional connectivity (FC within the reward, motivation, and emotion network (dACC, insula, caudate, amygdala and nucleus accumbens and the social cognition network (temporo-parietal junction (TPJ, posterior cingulate cortex (PCC, medial prefrontal cortex (MPFC, inferior parietal, precuneus and temporal lobe was significantly increased in the LG (in comparison to the ELG and SG; 4 in most regions within both networks FC was positively correlated with the love duration in the LG but negatively correlated with the lovelorn duration in the ELG. This study provides first empirical evidence of love-related alterations of brain functional architecture. The results shed light on the underlying neural mechanisms of romantic love, and demonstrate the possibility of applying a resting state approach for investigating romantic love.

  16. Altered resting-state whole-brain functional networks of neonates with intrauterine growth restriction.

    Science.gov (United States)

    Batalle, Dafnis; Muñoz-Moreno, Emma; Tornador, Cristian; Bargallo, Nuria; Deco, Gustavo; Eixarch, Elisenda; Gratacos, Eduard

    2016-04-01

    The feasibility to use functional MRI (fMRI) during natural sleep to assess low-frequency basal brain activity fluctuations in human neonates has been demonstrated, although its potential to characterise pathologies of prenatal origin has not yet been exploited. In the present study, we used intrauterine growth restriction (IUGR) as a model of altered neurodevelopment due to prenatal condition to show the suitability of brain networks to characterise functional brain organisation at neonatal age. Particularly, we analysed resting-state fMRI signal of 20 neonates with IUGR and 13 controls, obtaining whole-brain functional networks based on correlations of blood oxygen level-dependent (BOLD) signal in 90 grey matter regions of an anatomical atlas (AAL). Characterisation of the networks obtained with graph theoretical features showed increased network infrastructure and raw efficiencies but reduced efficiency after normalisation, demonstrating hyper-connected but sub-optimally organised IUGR functional brain networks. Significant association of network features with neurobehavioral scores was also found. Further assessment of spatiotemporal dynamics displayed alterations into features associated to frontal, cingulate and lingual cortices. These findings show the capacity of functional brain networks to characterise brain reorganisation from an early age, and their potential to develop biomarkers of altered neurodevelopment. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Alterations in Cortical Sensorimotor Connectivity following Complete Cervical Spinal Cord Injury: A Prospective Resting-State fMRI Study.

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    Akinwunmi Oni-Orisan

    Full Text Available Functional magnetic resonance imaging (fMRI studies have demonstrated alterations during task-induced brain activation in spinal cord injury (SCI patients. The interruption to structural integrity of the spinal cord and the resultant disrupted flow of bidirectional communication between the brain and the spinal cord might contribute to the observed dynamic reorganization (neural plasticity. However, the effect of SCI on brain resting-state connectivity patterns remains unclear. We undertook a prospective resting-state fMRI (rs-fMRI study to explore changes to cortical activation patterns following SCI. With institutional review board approval, rs-fMRI data was obtained in eleven patients with complete cervical SCI (>2 years post injury and nine age-matched controls. The data was processed using the Analysis of Functional Neuroimages software. Region of interest (ROI based analysis was performed to study changes in the sensorimotor network using pre- and post-central gyri as seed regions. Two-sampled t-test was carried out to check for significant differences between the two groups. SCI patients showed decreased functional connectivity in motor and sensory cortical regions when compared to controls. The decrease was noted in ipsilateral, contralateral, and interhemispheric regions for left and right precentral ROIs. Additionally, the left postcentral ROI demonstrated increased connectivity with the thalamus bilaterally in SCI patients. Our results suggest that cortical activation patterns in the sensorimotor network undergo dynamic reorganization following SCI. The presence of these changes in chronic spinal cord injury patients is suggestive of the inherent neural plasticity within the central nervous system.

  18. [Functional connectivity of temporal parietal junction in online game addicts:a resting-state functional magnetic resonance imaging study].

    Science.gov (United States)

    Yuan, Ji; Qian, Ruobing; Lin, Bin; Fu, Xianming; Wei, Xiangpin; Weng, Chuanbo; Niu, Chaoshi; Wang, Yehan

    2014-02-11

    To explore the functions of temporal parietal junction (TPJ) as parts of attention networks in the pathogenesis of online game addiction using resting-state functional magnetic resonance imaging (fMRI). A total of 17 online game addicts (OGA) were recruited as OGA group and 17 healthy controls during the same period were recruited as CON group. The neuropsychological tests were performed for all of them to compare the inter-group differences in the results of Internet Addiction Test (IAT) and attention functions. All fMRI data were preprocessed after resting-state fMRI scanning. Then left and right TPJ were selected as regions of interest (ROIs) to calculate the linear correlation between TPJ and entire brain to compare the inter-group differences. Obvious differences existed between OGA group (71 ± 5 scores) and CON group (19 ± 7 scores) in the IAT results and attention function (P online game addicts showed decreased functional connectivity with bilateral ventromedial prefrontal cortex (VMPFC), bilateral hippocampal gyrus and bilateral amygdaloid nucleus, but increased functional connectivity with right cuneus.However, left TPJ demonstrated decreased functional connectivity with bilateral superior frontal gyrus and bilateral middle frontal gyrus, but increased functional connectivity with bilateral cuneus (P online game addicts.It suggests that TPJ is an important component of attention networks participating in the generation of online game addiction.

  19. Brain resting-state networks in adolescents with high-functioning autism: Analysis of spatial connectivity and temporal neurodynamics.

    Science.gov (United States)

    Bernas, Antoine; Barendse, Evelien M; Aldenkamp, Albert P; Backes, Walter H; Hofman, Paul A M; Hendriks, Marc P H; Kessels, Roy P C; Willems, Frans M J; de With, Peter H N; Zinger, Svitlana; Jansen, Jacobus F A

    2018-02-01

    Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population. The aim of this study is to test whether high-functioning adolescents with ASD (HFA) have an abnormal resting-state functional connectivity. We performed spatial and temporal analyses on resting-state networks (RSNs) in 13 HFA adolescents and 13 IQ- and age-matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics. Controls and HFA display very similar patterns and strengths of resting-state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting-state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices. The results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience-executive network: a pathway involving cognitive, executive, and emotion-related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state.

  20. Multivariate pattern analysis strategies in detection of remitted major depressive disorder using resting state functional connectivity

    Directory of Open Access Journals (Sweden)

    Runa Bhaumik

    2017-01-01

    Full Text Available Understanding abnormal resting-state functional connectivity of distributed brain networks may aid in probing and targeting mechanisms involved in major depressive disorder (MDD. To date, few studies have used resting state functional magnetic resonance imaging (rs-fMRI to attempt to discriminate individuals with MDD from individuals without MDD, and to our knowledge no investigations have examined a remitted (r population. In this study, we examined the efficiency of support vector machine (SVM classifier to successfully discriminate rMDD individuals from healthy controls (HCs in a narrow early-adult age range. We empirically evaluated four feature selection methods including multivariate Least Absolute Shrinkage and Selection Operator (LASSO and Elastic Net feature selection algorithms. Our results showed that SVM classification with Elastic Net feature selection achieved the highest classification accuracy of 76.1% (sensitivity of 81.5% and specificity of 68.9% by leave-one-out cross-validation across subjects from a dataset consisting of 38 rMDD individuals and 29 healthy controls. The highest discriminating functional connections were between the left amygdala, left posterior cingulate cortex, bilateral dorso-lateral prefrontal cortex, and right ventral striatum. These appear to be key nodes in the etiopathophysiology of MDD, within and between default mode, salience and cognitive control networks. This technique demonstrates early promise for using rs-fMRI connectivity as a putative neurobiological marker capable of distinguishing between individuals with and without rMDD. These methods may be extended to periods of risk prior to illness onset, thereby allowing for earlier diagnosis, prevention, and intervention.

  1. Multivariate pattern analysis strategies in detection of remitted major depressive disorder using resting state functional connectivity.

    Science.gov (United States)

    Bhaumik, Runa; Jenkins, Lisanne M; Gowins, Jennifer R; Jacobs, Rachel H; Barba, Alyssa; Bhaumik, Dulal K; Langenecker, Scott A

    2017-01-01

    Understanding abnormal resting-state functional connectivity of distributed brain networks may aid in probing and targeting mechanisms involved in major depressive disorder (MDD). To date, few studies have used resting state functional magnetic resonance imaging (rs-fMRI) to attempt to discriminate individuals with MDD from individuals without MDD, and to our knowledge no investigations have examined a remitted (r) population. In this study, we examined the efficiency of support vector machine (SVM) classifier to successfully discriminate rMDD individuals from healthy controls (HCs) in a narrow early-adult age range. We empirically evaluated four feature selection methods including multivariate Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net feature selection algorithms. Our results showed that SVM classification with Elastic Net feature selection achieved the highest classification accuracy of 76.1% (sensitivity of 81.5% and specificity of 68.9%) by leave-one-out cross-validation across subjects from a dataset consisting of 38 rMDD individuals and 29 healthy controls. The highest discriminating functional connections were between the left amygdala, left posterior cingulate cortex, bilateral dorso-lateral prefrontal cortex, and right ventral striatum. These appear to be key nodes in the etiopathophysiology of MDD, within and between default mode, salience and cognitive control networks. This technique demonstrates early promise for using rs-fMRI connectivity as a putative neurobiological marker capable of distinguishing between individuals with and without rMDD. These methods may be extended to periods of risk prior to illness onset, thereby allowing for earlier diagnosis, prevention, and intervention.

  2. Migraine classification using magnetic resonance imaging resting-state functional connectivity data.

    Science.gov (United States)

    Chong, Catherine D; Gaw, Nathan; Fu, Yinlin; Li, Jing; Wu, Teresa; Schwedt, Todd J

    2017-08-01

    Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging ( rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

  3. Aberrant functional connectivity of resting state networks in transient ischemic attack.

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    Rong Li

    Full Text Available BACKGROUND: Transient ischemic attack (TIA is usually defined as a neurologic ischemic disorder without permanent cerebral infarction. Studies have showed that patients with TIA can have lasting cognitive functional impairment. Inherent brain activity in the resting state is spatially organized in a set of specific coherent patterns named resting state networks (RSNs, which epitomize the functional architecture of memory, language, attention, visual, auditory and somato-motor networks. Here, we aimed to detect differences in RSNs between TIA patients and healthy controls (HCs. METHODS: Twenty one TIA patients suffered an ischemic event and 21 matched HCs were enrolled in the study. All subjects were investigated using cognitive tests, psychiatric tests and functional magnetic resonance imaging (fMRI. Independent component analysis (ICA was adopted to acquire the eight brain RSNs. Then one-sample t-tests were calculated in each group to gather the spatial maps of each RSNs, followed by second level analysis to investigate statistical differences on RSNs between twenty one TIA patients and 21 controls. Furthermore, a correlation analysis was performed to explore the relationship between functional connectivity (FC and cognitive and psychiatric scales in TIA group. RESULTS: Compared with the controls, TIA patients exhibited both decreased and increased functional connectivity in default mode network (DMN and self-referential network (SRN, and decreased functional connectivity in dorsal attention network (DAN, central-executive network (CEN, core network (CN, somato-motor network (SMN, visual network (VN and auditory network (AN. There was no correlation between neuropsychological scores and functional connectivity in regions of RSNs. CONCLUSIONS: We observed selective impairments of RSN intrinsic FC in TIA patients, whose all eight RSNs had aberrant functional connectivity. These changes indicate that TIA is a disease with widely abnormal brain

  4. High spatial correspondence at a columnar level between activation and resting state fMRI signals and local field potentials.

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    Shi, Zhaoyue; Wu, Ruiqi; Yang, Pai-Feng; Wang, Feng; Wu, Tung-Lin; Mishra, Arabinda; Chen, Li Min; Gore, John C

    2017-05-16

    Although blood oxygenation level-dependent (BOLD) fMRI has been widely used to map brain responses to external stimuli and to delineate functional circuits at rest, the extent to which BOLD signals correlate spatially with underlying neuronal activity, the spatial relationships between stimulus-evoked BOLD activations and local correlations of BOLD signals in a resting state, and whether these spatial relationships vary across functionally distinct cortical areas are not known. To address these critical questions, we directly compared the spatial extents of stimulated activations and the local profiles of intervoxel resting state correlations for both high-resolution BOLD at 9.4 T and local field potentials (LFPs), using 98-channel microelectrode arrays, in functionally distinct primary somatosensory areas 3b and 1 in nonhuman primates. Anatomic images of LFP and BOLD were coregistered within 0.10 mm accuracy. We found that the point spread functions (PSFs) of BOLD and LFP responses were comparable in the stimulus condition, and both estimates of activations were slightly more spatially constrained than local correlations at rest. The magnitudes of stimulus responses in area 3b were stronger than those in area 1 and extended in a medial to lateral direction. In addition, the reproducibility and stability of stimulus-evoked activation locations within and across both modalities were robust. Our work suggests that the intrinsic resolution of BOLD is not a limiting feature in practice and approaches the intrinsic precision achievable by multielectrode electrophysiology.

  5. Impaired insight into illness and cognitive insight in schizophrenia spectrum disorders: Resting state functional connectivity

    Science.gov (United States)

    Gerretsen, Philip; Menon, Mahesh; Mamo, David C.; Fervaha, Gagan; Remington, Gary; Pollock, Bruce G.; Graff-Guerrero, Ariel

    2015-01-01

    Background Impaired insight into illness (clinical insight) in schizophrenia has negative effects on treatment adherence and clinical outcomes. Schizophrenia is described as a disorder of disrupted brain connectivity. In line with this concept, resting state networks (RSNs) appear differentially affected in persons with schizophrenia. Therefore, impaired clinical, or the related construct of cognitive insight (which posits that impaired clinical insight is a function of metacognitive deficits), may reflect alterations in RSN functional connectivity (fc). Based on our previous research, which showed that impaired insight into illness was associated with increased left hemisphere volume relative to right, we hypothesized that impaired clinical insight would be associated with increased connectivity in the DMN with specific left hemisphere brain regions. Methods Resting state MRI scans were acquired for participants with schizophrenia or schizoaffective disorder (n = 20). Seed-to-voxel and ROI-to-ROI fc analyses were performed using the CONN-fMRI fc toolbox v13 for established RSNs. Clinical and cognitive insight were measured with the Schedule for the Assessment of Insight—Expanded Version and Beck Cognitive Insight Scale, respectively, and included as the regressors in fc analyses. Results As hypothesized, impaired clinical insight was associated with increased connectivity in the default mode network (DMN) with the left angular gyrus, and also in the self-referential network (SRN) with the left insula. Cognitive insight was associated with increased connectivity in the dorsal attention network (DAN) with the right inferior frontal cortex (IFC) and left anterior cingulate cortex (ACC). Conclusion Increased connectivity in DMN and SRN with the left angular gyrus and insula, respectively, may represent neural correlates of impaired clinical insight in schizophrenia spectrum disorders, and is consistent with the literature attributing impaired insight to left

  6. Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys.

    Science.gov (United States)

    Wu, Ruiqi; Yang, Pai-Feng; Chen, Li Min

    2017-11-15

    This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened

  7. Normalization of aberrant resting state functional connectivity in fibromyalgia patients following a three month physical exercise therapy

    OpenAIRE

    P. Flodin; S. Martinsen; K. Mannerkorpi; M. Löfgren; I. Bileviciute-Ljungar; E. Kosek; P. Fransson

    2015-01-01

    Physical exercise is one of the most efficient interventions to mitigate chronic pain symptoms in fibromyalgia (FM). However, little is known about the neurophysiological mechanisms mediating these effects. In this study we investigated resting-state connectivity using functional magnetic resonance imaging (fMRI) before and after a 15 week standardized exercise program supervised by physical therapists. Our aim was to gain an understanding of how physical exercise influences previously shown ...

  8. Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

    Science.gov (United States)

    Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

    2015-01-01

    Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

  9. Resting-State Functional Connectivity Predicts Cognitive Impairment Related to Alzheimer's Disease

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    Qi Lin

    2018-04-01

    Full Text Available Resting-state functional connectivity (rs-FC is a promising neuromarker for cognitive decline in aging population, based on its ability to reveal functional differences associated with cognitive impairment across individuals, and because rs-fMRI may be less taxing for participants than task-based fMRI or neuropsychological tests. Here, we employ an approach that uses rs-FC to predict the Alzheimer's Disease Assessment Scale (11 items; ADAS11 scores, which measure overall cognitive functioning, in novel individuals. We applied this technique, connectome-based predictive modeling, to a heterogeneous sample of 59 subjects from the Alzheimer's Disease Neuroimaging Initiative, including normal aging, mild cognitive impairment, and AD subjects. First, we built linear regression models to predict ADAS11 scores from rs-FC measured with Pearson's r correlation. The positive network model tested with leave-one-out cross validation (LOOCV significantly predicted individual differences in cognitive function from rs-FC. In a second analysis, we considered other functional connectivity features, accordance and discordance, which disentangle the correlation and anticorrelation components of activity timecourses between brain areas. Using partial least square regression and LOOCV, we again built models to successfully predict ADAS11 scores in novel individuals. Our study provides promising evidence that rs-FC can reveal cognitive impairment in an aging population, although more development is needed for clinical application.

  10. A resting-state fMRI study of obese females between pre- and postprandial states before and after bariatric surgery.

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    Wiemerslage, Lyle; Zhou, Wei; Olivo, Gaia; Stark, Julia; Hogenkamp, Pleunie S; Larsson, Elna-Marie; Sundbom, Magnus; Schiöth, Helgi B

    2017-02-01

    Past studies utilizing resting-state functional MRI (rsfMRI), have shown that obese humans exhibit altered activity in brain areas related to reward compared to normal-weight controls. However, to what extent bariatric surgery-induced weight loss alters resting-state brain activity in obese humans is less well-studied. Thus, we measured the fractional amplitude of low-frequency fluctuations from eyes-closed, rsfMRI in obese females (n = 11, mean age = 42 years, mean BMI = 41 kg/m 2 ) in both a pre- and postprandial state at two time points: four weeks before, and four weeks after bariatric surgery. Several brain areas showed altered resting-state activity following bariatric surgery, including the putamen, insula, cingulate, thalamus and frontal regions. Activity augmented by surgery was also dependent on prandial state. For example, in the fasted state, activity in the middle frontal and pre- and postcentral gyri was found to be decreased after surgery. In the sated state, activity within the insula was increased before, but not after surgery. Collectively, our results suggest that resting-state neural functions are rapidly affected following bariatric surgery and the associated weight loss and change in diet. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  11. A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data

    KAUST Repository

    Kang, Hakmook

    2017-03-20

    Current approaches separately analyze concurrently acquired diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data. The primary limitation of these approaches is that they do not take advantage of the information from DTI that could potentially enhance estimation of resting-state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatiotemporal model that incorporates structural connectivity (SC) into estimating FC. In our proposed approach, SC based on DTI data is used to construct an informative prior for FC based on resting-state fMRI data through the Cholesky decomposition. Simulation studies showed that incorporating the two data produced significantly reduced mean squared errors compared to the standard approach of separately analyzing the two data from different modalities. We applied our model to analyze the resting state DTI and fMRI data collected to estimate FC between the brain regions that were hypothetically important in the origination and spread of temporal lobe epilepsy seizures. Our analysis concludes that the proposed model achieves smaller false positive rates and is much robust to data decimation compared to the conventional approach.

  12. Love-related changes in the brain: a resting-state functional magnetic resonance imaging study.

    Science.gov (United States)

    Song, Hongwen; Zou, Zhiling; Kou, Juan; Liu, Yang; Yang, Lizhuang; Zilverstand, Anna; d'Oleire Uquillas, Federico; Zhang, Xiaochu

    2015-01-01

    Romantic love is a motivational state associated with a desire to enter or maintain a close relationship with a specific other person. Functional magnetic resonance imaging (fMRI) studies have found activation increases in brain regions involved in the processing of reward, motivation and emotion regulation, when romantic lovers view photographs of their partners. However, not much is known about whether romantic love affects the brain's functional architecture during rest. In the present study, resting state functional magnetic resonance imaging (rsfMRI) data was collected to compare the regional homogeneity (ReHo) and functional connectivity (FC) across an "in-love" group (LG, N = 34, currently intensely in love), an "ended-love" group (ELG, N = 34, ended romantic relationship recently), and a "single" group (SG, N = 32, never fallen in love). Results show that: (1) ReHo of the left dorsal anterior cingulate cortex (dACC) was significantly increased in the LG (in comparison to the ELG and the SG); (2) ReHo of the left dACC was positively correlated with length of time in love in the LG, and negatively correlated with the lovelorn duration since breakup in the ELG; (3) FC within the reward, motivation, and emotion regulation network (dACC, insula, caudate, amygdala, and nucleus accumbens) as well as FC in the social cognition network [temporo-parietal junction (TPJ), posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC), inferior parietal, precuneus, and temporal lobe] was significantly increased in the LG (in comparison to the ELG and SG); (4) in most regions within both networks FC was positively correlated with the duration of love in the LG but negatively correlated with the lovelorn duration of time since breakup in the ELG. This study provides first empirical evidence of love-related alterations in brain functional architecture. Furthermore, the results shed light on the underlying neural mechanisms of romantic love, and demonstrate the

  13. Abnormalities of resting state functional connectivity are related to sustained attention deficits in MS.

    Directory of Open Access Journals (Sweden)

    Marisa Loitfelder

    Full Text Available OBJECTIVES: Resting state (RS functional MRI recently identified default network abnormalities related to cognitive impairment in MS. fMRI can also be used to map functional connectivity (FC while the brain is at rest and not adhered to a specific task. Given the importance of the anterior cingulate cortex (ACC for higher executive functioning in MS, we here used the ACC as seed-point to test for differences and similarities in RS-FC related to sustained attention between MS patients and controls. DESIGN: Block-design rest phases of 3 Tesla fMRI data were analyzed to assess RS-FC in 31 patients (10 clinically isolated syndromes, 16 relapsing-remitting, 5 secondary progressive MS and 31 age- and gender matched healthy controls (HC. Participants underwent extensive cognitive testing. OBSERVATIONS: In both groups, signal changes in several brain areas demonstrated significant correlation with RS-activity in the ACC. These comprised the posterior cingulate cortex (PCC, insular cortices, the right caudate, right middle temporal gyrus, angular gyri, the right hippocampus, and the cerebellum. Compared to HC, patients showed increased FC between the ACC and the left angular gyrus, left PCC, and right postcentral gyrus. Better cognitive performance in the patients was associated with increased FC to the cerebellum, middle temporal gyrus, occipital pole, and the angular gyrus. CONCLUSION: We provide evidence for adaptive changes in RS-FC in MS patients compared to HC in a sustained attention network. These results extend and partly mirror findings of task-related fMRI, suggesting FC may increase our understanding of cognitive dysfunction in MS.

  14. fMRI resting state networks and their association with cognitive fluctuations in dementia with Lewy bodies

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    Luis R. Peraza

    2014-01-01

    Full Text Available Cognitive fluctuations are a core symptom in dementia with Lewy bodies (DLB and may relate to pathological alterations in distributed brain networks. To test this we analysed resting state fMRI changes in a cohort of fluctuating DLB patients (n = 16 compared with age matched controls (n = 17 with the aim of finding functional connectivity (FC differences between these two groups and whether these associate with cognitive fluctuations in DLB. Resting state networks (RSNs were estimated using independent component analysis and FC between the RSN maps and the entirety of the brain was assessed using dual regression. The default mode network (DMN appeared unaffected in DLB compared to controls but significant cluster differences between DLB and controls were found for the left fronto-parietal, temporal, and sensory–motor networks. Desynchronization of a number of cortical and subcortical areas related to the left fronto-parietal network was associated with the severity and frequency of cognitive fluctuations. Our findings provide empirical evidence for the potential role of attention–executive networks in the aetiology of this core symptom in DLB.

  15. Resting-state functional connectivity remains unaffected by preceding exposure to aversive visual stimuli.

    Science.gov (United States)

    Geissmann, Léonie; Gschwind, Leo; Schicktanz, Nathalie; Deuring, Gunnar; Rosburg, Timm; Schwegler, Kyrill; Gerhards, Christiane; Milnik, Annette; Pflueger, Marlon O; Mager, Ralph; de Quervain, Dominique J F; Coynel, David

    2018-02-15

    While much is known about immediate brain activity changes induced by the confrontation with emotional stimuli, the subsequent temporal unfolding of emotions has yet to be explored. To investigate whether exposure to emotionally aversive pictures affects subsequent resting-state networks differently from exposure to neutral pictures, a resting-state fMRI study implementing a two-group repeated-measures design in healthy young adults (N = 34) was conducted. We focused on investigating (i) patterns of amygdala whole-brain and hippocampus connectivity in both a seed-to-voxel and seed-to-seed approach, (ii) whole-brain resting-state networks with an independent component analysis coupled with dual regression, and (iii) the amygdala's fractional amplitude of low frequency fluctuations, all while EEG recording potential fluctuations in vigilance. In spite of the successful emotion induction, as demonstrated by stimuli rating and a memory-facilitating effect of negative emotionality, none of the resting-state measures was differentially affected by picture valence. In conclusion, resting-state networks connectivity as well as the amygdala's low frequency oscillations appear to be unaffected by preceding exposure to widely used emotionally aversive visual stimuli in healthy young adults. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data.

    Science.gov (United States)

    Sharaev, Maksim G; Zavyalova, Viktoria V; Ushakov, Vadim L; Kartashov, Sergey I; Velichkovsky, Boris M

    2016-01-01

    The Default Mode Network (DMN) is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of Blood-oxygen-level dependent (BOLD) activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e., effective connectivity), however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex (mPFC), the posterior cingulate cortex (PCC), left and right intraparietal cortex (LIPC and RIPC). For this purpose functional magnetic resonance imaging (fMRI) data from 30 healthy subjects (1000 time points from each one) was acquired and spectral dynamic causal modeling (DCM) on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078-0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain's functioning at resting state.

  17. Effective connectivity within the default mode network: dynamic causal modeling of resting-state fMRI data

    Directory of Open Access Journals (Sweden)

    Maksim eSharaev

    2016-02-01

    Full Text Available The Default Mode Network (DMN is a brain system that mediates internal modes of cognitive activity, showing higher neural activation when one is at rest. Nowadays, there is a lot of interest in assessing functional interactions between its key regions, but in the majority of studies only association of BOLD (Blood-oxygen-level dependent activation patterns is measured, so it is impossible to identify causal influences. There are some studies of causal interactions (i.e. effective connectivity, however often with inconsistent results. The aim of the current work is to find a stable pattern of connectivity between four DMN key regions: the medial prefrontal cortex mPFC, the posterior cingulate cortex PCC, left and right intraparietal cortex LIPC and RIPC. For this purpose fMRI (functional magnetic resonance imaging data from 30 healthy subjects (1000 time points from each one was acquired and spectral dynamic causal modeling (DCM on a resting-state fMRI data was performed. The endogenous brain fluctuations were explicitly modeled by Discrete Cosine Set at the low frequency band of 0.0078–0.1 Hz. The best model at the group level is the one where connections from both bilateral IPC to mPFC and PCC are significant and symmetrical in strength (p<0.05. Connections between mPFC and PCC are bidirectional, significant in the group and weaker than connections originating from bilateral IPC. In general, all connections from LIPC/RIPC to other DMN regions are much stronger. One can assume that these regions have a driving role within the DMN. Our results replicate some data from earlier works on effective connectivity within the DMN as well as provide new insights on internal DMN relationships and brain’s functioning at resting state.

  18. Effects of Early and Late Bilingualism on Resting-State Functional Connectivity.

    Science.gov (United States)

    Berken, Jonathan A; Chai, Xiaoqian; Chen, Jen-Kai; Gracco, Vincent L; Klein, Denise

    2016-01-27

    Of current interest is how variations in early language experience shape patterns of functional connectivity in the human brain. In the present study, we compared simultaneous (two languages from birth) and sequential (second language learned after age 5 years) bilinguals using a seed-based resting-state MRI approach. We focused on the inferior frontal gyrus (IFG) as our ROI, as recent studies have demonstrated both neurofunctional and neurostructural changes related to age of second language acquisition in bilinguals in this cortical area. Stronger functional connectivity was observed for simultaneous bilinguals between the left and right IFG, as well as between the inferior frontal gyrus and brain areas involved in language control, including the dorsolateral prefrontal cortex, inferior parietal lobule, and cerebellum. Functional connectivity between the left IFG and the right IFG and right inferior parietal lobule was also significantly correlated with age of acquisition for sequential bilinguals; the earlier the second language was acquired, the stronger was the functional connectivity. In addition, greater functional connectivity between homologous regions of the inferior frontal gyrus was associated with reduced neural activation in the left IFG during speech production. The increased connectivity at rest and reduced neural activation during task performance suggests enhanced neural efficiency in this important brain area involved in both speech production and domain-general cognitive processing. Together, our findings highlight how the brain's intrinsic functional patterns are influenced by the developmental timeline in which second language acquisition occurs. Of current interest is how early life experience leaves its footprint on brain structure and function. In this regard, bilingualism provides an optimal way to determine the effects of the timing of language learning because a second language can be learned from birth or later in life. We used resting-state

  19. Investigation of True High Frequency Electrical Substrates of fMRI-Based Resting State Networks Using Parallel Independent Component Analysis of Simultaneous EEG/fMRI Data.

    Science.gov (United States)

    Kyathanahally, Sreenath P; Wang, Yun; Calhoun, Vince D; Deshpande, Gopikrishna

    2017-01-01

    Previous work using simultaneously acquired electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data has shown that the slow temporal dynamics of resting state brain networks (RSNs), e.g., default mode network (DMN), visual network (VN), obtained from fMRI are correlated with smoothed and down sampled versions of various EEG features such as microstates and band-limited power envelopes. Therefore, even though the down sampled and smoothed envelope of EEG gamma band power is correlated with fMRI fluctuations in the RSNs, it does not mean that the electrical substrates of the RSNs fluctuate with periods state fMRI fluctuations in the RSNs, researchers have speculated that truly high frequency electrical substrates may exist for the RSNs, which would make resting fluctuations obtained from fMRI more meaningful to typically occurring fast neuronal processes in the sub-100 ms time scale. In this study, we test this critical hypothesis using an integrated framework involving simultaneous EEG/fMRI acquisition, fast fMRI sampling ( TR = 200 ms) using multiband EPI (MB EPI), and EEG/fMRI fusion using parallel independent component analysis (pICA) which does not require the down sampling of EEG to fMRI temporal resolution . Our results demonstrate that with faster sampling, high frequency electrical substrates (fluctuating with periods <100 ms time scale) of the RSNs can be observed. This provides a sounder neurophysiological basis for the RSNs.

  20. Disrupted thalamic resting-state functional connectivity in patients with minimal hepatic encephalopathy

    International Nuclear Information System (INIS)

    Qi, Rongfeng; Zhang, Long Jiang; Zhong, Jianhui; Zhang, Zhiqiang; Ni, Ling; Zheng, Gang; Lu, Guang Ming

    2013-01-01

    Background and purpose: Little is known about the role of thalamus in the pathophysiology of minimal hepatic encephalopathy (MHE). The purpose of this study was to investigate whether the thalamic functional connectivity was disrupted in cirrhotic patients with MHE by using resting-state functional magnetic resonance imaging (rs-fMRI). Materials and Methods: Twenty seven MHE patients and twenty seven age- and gender- matched healthy controls participated in the rs-fMRI scans. The functional connectivity of 11 thalamic nuclei were characterized by using a standard seed-based whole-brain correlation method and compared between MHE patients and healthy controls. Pearson correlation analysis was performed between the thalamic functional connectivity and venous blood ammonia levels/neuropsychological tests scores of patients. Results: The ventral anterior nucleus (VAN) and the ventral posterior medial nucleus (VPMN) in each side of thalamus showed abnormal functional connectivities in MHE. Compared with healthy controls, MHE patients demonstrated significant decreased functional connectivity between the right/left VAN and the bilateral putamen/pallidum, inferior frontal gyri, insula, supplementary motor area, right middle frontal gyrus, medial frontal gyrus. In addition, MHE patients showed significantly decreased functional connectivity with the right/left VPMN in the bilateral middle temporal gyri (MTG), temporal lobe, and right superior temporal gyrus. The venous blood ammonia levels of MHE patients negatively correlated with the functional connectivity between the VAN and the insula. Number connecting test scores showed negative correlation with the functional connectivity between the VAN and the insula, and between the VPMN and the MTG. Conclusion: MHE patients had disrupted thalamic functional connectivity, which mainly located in the bilateral ventral anterior nuclei and ventral posterior medial nuclei. The decreased connectivity between thalamus and many

  1. Disrupted thalamic resting-state functional connectivity in patients with minimal hepatic encephalopathy

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    Qi, Rongfeng [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China); Zhang, Long Jiang, E-mail: kevinzhanglongjiang@yahoo.com.cn [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China); Zhong, Jianhui [Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang 310027 (China); Zhang, Zhiqiang; Ni, Ling; Zheng, Gang [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China); Lu, Guang Ming, E-mail: cjr.luguangming@vip.163.com [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing 210002 (China)

    2013-05-15

    Background and purpose: Little is known about the role of thalamus in the pathophysiology of minimal hepatic encephalopathy (MHE). The purpose of this study was to investigate whether the thalamic functional connectivity was disrupted in cirrhotic patients with MHE by using resting-state functional magnetic resonance imaging (rs-fMRI). Materials and Methods: Twenty seven MHE patients and twenty seven age- and gender- matched healthy controls participated in the rs-fMRI scans. The functional connectivity of 11 thalamic nuclei were characterized by using a standard seed-based whole-brain correlation method and compared between MHE patients and healthy controls. Pearson correlation analysis was performed between the thalamic functional connectivity and venous blood ammonia levels/neuropsychological tests scores of patients. Results: The ventral anterior nucleus (VAN) and the ventral posterior medial nucleus (VPMN) in each side of thalamus showed abnormal functional connectivities in MHE. Compared with healthy controls, MHE patients demonstrated significant decreased functional connectivity between the right/left VAN and the bilateral putamen/pallidum, inferior frontal gyri, insula, supplementary motor area, right middle frontal gyrus, medial frontal gyrus. In addition, MHE patients showed significantly decreased functional connectivity with the right/left VPMN in the bilateral middle temporal gyri (MTG), temporal lobe, and right superior temporal gyrus. The venous blood ammonia levels of MHE patients negatively correlated with the functional connectivity between the VAN and the insula. Number connecting test scores showed negative correlation with the functional connectivity between the VAN and the insula, and between the VPMN and the MTG. Conclusion: MHE patients had disrupted thalamic functional connectivity, which mainly located in the bilateral ventral anterior nuclei and ventral posterior medial nuclei. The decreased connectivity between thalamus and many

  2. Altered regional homogeneity in pediatric bipolar disorder during manic state: a resting-state fMRI study.

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    Qian Xiao

    Full Text Available UNLABELLED: Pediatric bipolar disorder (PBD is a severely debilitating illness, which is characterized by episodes of mania and depression separated by periods of remission. Previous fMRI studies investigating PBD were mainly task-related. However, little is known about the abnormalities in PBD, especially during resting state. Resting state brain activity measured by fMRI might help to explore neurobiological biomarkers of the disorder. METHODS: Regional homogeneity (ReHo was examined with resting-state fMRI (RS-fMRI on 15 patients with PBD in manic state, with 15 age-and sex-matched healthy youth subjects as controls. RESULTS: Compared with the healthy controls, the patients with PBD showed altered ReHo in the cortical and subcortical structures. The ReHo measurement of the PBD group was negatively correlated with the score of Young Mania Rating Scale (YMRS in the superior frontal gyrus. Positive correlations between the ReHo measurement and the score of YMRS were found in the hippocampus and the anterior cingulate cortex in the PBD group. CONCLUSIONS: Altered regional brain activity is present in patients with PBD during manic state. This study presents new evidence for abnormal ventral-affective and dorsal-cognitive circuits in PBD during resting state and may add fresh insights into the pathophysiological mechanisms underlying PBD.

  3. Whole brain, high resolution spin-echo resting state fMRI using PINS multiplexing at 7 T

    NARCIS (Netherlands)

    Koopmans, P.J.; Boyacioglu, R.; Barth, M.; Norris, David Gordon

    2012-01-01

    This article demonstrates the application of spin-echo EPI for resting state fMRI at 7 T. A short repetition time of 1860 ms was made possible by the use of slice multiplexing which permitted whole brain coverage at high spatial resolution (84 slices of 1.6 mm thickness). Radiofrequency power

  4. Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

    Science.gov (United States)

    2017-10-13

    psychological therapies or pharmacological drugs. 2. KEYWORDS: fMRI (functional magnetic resonance imaging), tinnitus, brain imaging, cluster analysis...9/2016). Details in next section.  6-9 months: • Task 2: Participant recruitment, participant evaluation, MRI and behavioral data acquisition 3...WHASC: N = 40 patients and 20 controls o For year 2 (at end of first 24 months) details see next section. • Task 4: Behavioral and MRI data

  5. Cerebro-cerebellar resting state functional connectivity in children and adolescents with autism spectrum disorder

    Science.gov (United States)

    Khan, Amanda J.; Nair, Aarti; Keown, Christopher L.; Datko, Michael C.; Lincoln, Alan J.; Müller, Ralph-Axel

    2017-01-01

    Background The cerebellum plays important roles in both sensorimotor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. Methods We used resting-state functional connectivity MRI in 56 children and adolescents (28 ASD, 28 typically developing [TD]) aged 8–17 years. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensorimotor (premotor/primary motor, somatosensory, superior temporal, occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). Results There were three main findings: (i) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; (ii) partial correlation analyses that emphasized domain-specificity (sensorimotor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared to the TD group) for sensorimotor ROIs, but predominantly reduced connectivity for supramodal ROIs; (iii) this atypical pattern of connectivity was supported by significantly increased non-canonical connections (between sensorimotor cerebral and supramodal cerebellar ROIs, and vice versa) in the ASD group. Conclusions Our findings indicate that sensorimotor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. PMID:25959247

  6. Abnormal resting-state functional connectivity of the left caudate nucleus in obsessive-compulsive disorder.

    Science.gov (United States)

    Chen, Yunhui; Juhás, Michal; Greenshaw, Andrew J; Hu, Qiang; Meng, Xin; Cui, Hongsheng; Ding, Yongzhuo; Kang, Lu; Zhang, Yubo; Wang, Yuhua; Cui, Guangcheng; Li, Ping

    2016-06-03

    Altered brain activities in the cortico-striato-thalamocortical (CSTC) circuitry are implicated in the pathophysiology of obsessive-compulsive disorder (OCD). However, whether the underlying changes occur only within this circuitry or in large-scale networks is still not thoroughly understood. This study performed voxel-based functional connectivity analysis on resting-state functional magnetic resonance imaging (fMRI) data from thirty OCD patients and thirty healthy controls to investigate whole-brain intrinsic functional connectivity patterns in OCD. Relative to the healthy controls, OCD patients showed decreased functional connectivity within the CSTC circuitry but increased functional connectivity in other brain regions. Furthermore, decreased left caudate nucleus-thalamus connectivity within the CSTC circuitry was positively correlated with the illness duration of OCD. This study provides additional evidence that CSTC circuitry may play an essential role and alteration of large-scale brain networks may be involved in the pathophysiology of OCD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  7. Identifying the default mode network structure using dynamic causal modeling on resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Di, Xin; Biswal, Bharat B

    2014-02-01

    The default mode network is part of the brain structure that shows higher neural activity and energy consumption when one is at rest. The key regions in the default mode network are highly interconnected as conveyed by both the white matter fiber tracing and the synchrony of resting-state functional magnetic resonance imaging signals. However, the causal information flow within the default mode network is still poorly understood. The current study used the dynamic causal modeling on a resting-state fMRI data set to identify the network structure underlying the default mode network. The endogenous brain fluctuations were explicitly modeled by Fourier series at the low frequency band of 0.01-0.08Hz, and those Fourier series were set as driving inputs of the DCM models. Model comparison procedures favored a model wherein the MPFC sends information to the PCC and the bilateral inferior parietal lobule sends information to both the PCC and MPFC. Further analyses provide evidence that the endogenous connectivity might be higher in the right hemisphere than in the left hemisphere. These data provided insight into the functions of each node in the DMN, and also validate the usage of DCM on resting-state fMRI data. © 2013.

  8. Identifying the Neural Substrates of Procrastination: a Resting-State fMRI Study.

    Science.gov (United States)

    Zhang, Wenwen; Wang, Xiangpeng; Feng, Tingyong

    2016-09-12

    Procrastination is a prevalent problematic behavior that brings serious consequences to individuals who suffer from it. Although this phenomenon has received increasing attention from researchers, the underpinning neural substrates of it is poorly studied. To examine the neural bases subserving procrastination, the present study employed resting-state fMRI. The main results were as follows: (1) the behavioral procrastination was positively correlated with the regional activity of the ventromedial prefrontal cortex (vmPFC) and the parahippocampal cortex (PHC), while negatively correlated with that of the anterior prefrontal cortex (aPFC). (2) The aPFC-seed connectivity with the anterior medial prefrontal cortex and the posterior cingulate cortex was positively associated with procrastination. (3) The connectivity between vmPFC and several other regions, such as the dorsomedial prefrontal cortex, the bilateral inferior prefrontal cortex showed a negative association with procrastination. These results suggested that procrastination could be attributed to, on the one hand, hyper-activity of the default mode network (DMN) that overrides the prefrontal control signal; while on the other hand, the failure of top-down control exerted by the aPFC on the DMN. Therefore, the present study unravels the biomarkers of procrastination and provides treatment targets for procrastination prevention.

  9. Resting-state functional connectivity of the default mode network associated with happiness.

    Science.gov (United States)

    Luo, Yangmei; Kong, Feng; Qi, Senqing; You, Xuqun; Huang, Xiting

    2016-03-01

    Happiness refers to people's cognitive and affective evaluation of their life. Why are some people happier than others? One reason might be that unhappy people are prone to ruminate more than happy people. The default mode network (DMN) is normally active during rest and is implicated in rumination. We hypothesized that unhappiness may be associated with increased default-mode functional connectivity during rest, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC) and inferior parietal lobule (IPL). The hyperconnectivity of these areas may be associated with higher levels of rumination. One hundred forty-eight healthy participants underwent a resting-state fMRI scan. A group-independent component analysis identified the DMNs. Results indicated increased functional connectivity in the DMN was associated with lower levels of happiness. Specifically, relative to happy people, unhappy people exhibited greater functional connectivity in the anterior medial cortex (bilateral MPFC), posterior medial cortex regions (bilateral PCC) and posterior parietal cortex (left IPL). Moreover, the increased functional connectivity of the MPFC, PCC and IPL, correlated positively with the inclination to ruminate. These results highlight the important role of the DMN in the neural correlates of happiness, and suggest that rumination may play an important role in people's perceived happiness. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  10. Altered resting state functional connectivity of fear and reward circuitry in comorbid PTSD and major depression.

    Science.gov (United States)

    Zhu, Xi; Helpman, Liat; Papini, Santiago; Schneier, Franklin; Markowitz, John C; Van Meter, Page E; Lindquist, Martin A; Wager, Tor D; Neria, Yuval

    2017-07-01

    Individuals with comorbid posttraumatic stress disorder and major depressive disorder (PTSD-MDD) often exhibit greater functional impairment and poorer treatment response than individuals with PTSD alone. Research has not determined whether PTSD-MDD is associated with different network connectivity abnormalities than PTSD alone. We used functional magnetic resonance imaging (fMRI) to measure resting state functional connectivity (rs-FC) patterns of brain regions involved in fear and reward processing in three groups: patients with PTSD-alone (n = 27), PTSD-MDD (n = 21), and trauma-exposed healthy controls (TEHCs, n = 34). Based on previous research, seeds included basolateral amygdala (BLA), centromedial amygdala (CMA), and nucleus accumbens (NAcc). Regardless of MDD comorbidity, PTSD was associated with decreased connectivity of BLA-orbitalfrontal cortex (OFC) and CMA-thalamus pathways, key to fear processing, and fear expression, respectively. PTSD-MDD, compared to PTSD-alone and TEHC, was associated with decreased connectivity across multiple amygdala and striatal-subcortical pathways: BLA-OFC, NAcc-thalamus, and NAcc-hippocampus. Further, while both the BLA-OFC and the NAcc-thalamus pathways were correlated with MDD symptoms, PTSD symptoms correlated with the amygdala pathways (BLA-OFC; CMA-thalamus) only. Comorbid PTSD-MDD may be associated with multifaceted functional connectivity alterations in both fear and reward systems. Clinical implications are discussed. © 2016 Wiley Periodicals, Inc.

  11. A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series

    Science.gov (United States)

    Patel, Ameera X.; Kundu, Prantik; Rubinov, Mikail; Jones, P. Simon; Vértes, Petra E.; Ersche, Karen D.; Suckling, John; Bullmore, Edward T.

    2014-01-01

    The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N = 22) and a new dataset on adults with stimulant drug dependence (N = 40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www

  12. A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series.

    Science.gov (United States)

    Patel, Ameera X; Kundu, Prantik; Rubinov, Mikail; Jones, P Simon; Vértes, Petra E; Ersche, Karen D; Suckling, John; Bullmore, Edward T

    2014-07-15

    The impact of in-scanner head movement on functional magnetic resonance imaging (fMRI) signals has long been established as undesirable. These effects have been traditionally corrected by methods such as linear regression of head movement parameters. However, a number of recent independent studies have demonstrated that these techniques are insufficient to remove motion confounds, and that even small movements can spuriously bias estimates of functional connectivity. Here we propose a new data-driven, spatially-adaptive, wavelet-based method for identifying, modeling, and removing non-stationary events in fMRI time series, caused by head movement, without the need for data scrubbing. This method involves the addition of just one extra step, the Wavelet Despike, in standard pre-processing pipelines. With this method, we demonstrate robust removal of a range of different motion artifacts and motion-related biases including distance-dependent connectivity artifacts, at a group and single-subject level, using a range of previously published and new diagnostic measures. The Wavelet Despike is able to accommodate the substantial spatial and temporal heterogeneity of motion artifacts and can consequently remove a range of high and low frequency artifacts from fMRI time series, that may be linearly or non-linearly related to physical movements. Our methods are demonstrated by the analysis of three cohorts of resting-state fMRI data, including two high-motion datasets: a previously published dataset on children (N=22) and a new dataset on adults with stimulant drug dependence (N=40). We conclude that there is a real risk of motion-related bias in connectivity analysis of fMRI data, but that this risk is generally manageable, by effective time series denoising strategies designed to attenuate synchronized signal transients induced by abrupt head movements. The Wavelet Despiking software described in this article is freely available for download at www

  13. Resting-state functional connectivity of ventral parietal regions associated with attention reorienting and episodic recollection

    Directory of Open Access Journals (Sweden)

    Sander M Daselaar

    2013-02-01

    Full Text Available In functional neuroimaging studies, ventral parietal cortex (VPC is recruited by very different cognitive tasks. Explaining the contributions VPC to these tasks has become a topic of intense study and lively debate. Perception studies frequently find VPC activations during tasks involving attention-reorienting, and memory studies frequently find them during tasks involving episodic recollection. According to the Attention to Memory (AtoM model, both phenomena can be explained by the same VPC function: bottom-up attention. Yet, a recent functional MRI (fMRI meta-analysis suggested that attention-reorienting activations are more frequent in anterior VPC, whereas recollection activations are more frequent in posterior VPC. Also, there is evidence that anterior and posterior VPC regions have different functional connectivity patterns. To investigate these issues, we conducted a resting-state functional connectivity analysis using as seeds the center-of-mass of attention-reorienting and recollection activations in the meta-analysis, which were located in the supramarginal gyrus (SMG, around the temporo-parietal junction—TPJ and in the angular gyrus (AG, respectively. The SMG seed showed stronger connectivity with ventrolateral prefrontal cortex (VLPFC and occipito-temporal cortex, whereas the AG seed showed stronger connectivity with the hippocampus and default network regions. To investigate whether these connectivity differences were graded or sharp, VLPFC and hippocampal connectivity was measured in VPC regions traversing through the SMG and AG seeds. The results showed a graded pattern: VLPFC connectivity gradually decreases from SMG to AG, whereas hippocampal connectivity gradually increases from SMG to AG. Importantly, both gradients showed an abrupt break when extended beyond VPC borders. This finding suggests that functional differences between SMG and AG are more subtle than previously thought. These connectivity differences can be

  14. Disrupted resting-state functional connectivity in minimally treated chronic schizophrenia.

    Science.gov (United States)

    Wang, Xijin; Xia, Mingrui; Lai, Yunyao; Dai, Zhengjia; Cao, Qingjiu; Cheng, Zhang; Han, Xue; Yang, Lei; Yuan, Yanbo; Zhang, Yong; Li, Keqing; Ma, Hong; Shi, Chuan; Hong, Nan; Szeszko, Philip; Yu, Xin; He, Yong

    2014-07-01

    The pathophysiology of chronic schizophrenia may reflect long term brain changes related to the disorder. The effect of chronicity on intrinsic functional connectivity patterns in schizophrenia without the potentially confounding effect of antipsychotic medications, however, remains largely unknown. We collected resting-state fMRI data in 21 minimally treated chronic schizophrenia patients and 20 healthy controls. We computed regional functional connectivity strength for each voxel in the brain, and further divided regional functional connectivity strength into short-range regional functional connectivity strength and long-range regional functional connectivity strength. General linear models were used to detect between-group differences in these regional functional connectivity strength metrics and to further systematically investigate the relationship between these differences and clinical/behavioral variables in the patients. Compared to healthy controls, the minimally treated chronic schizophrenia patients showed an overall reduced regional functional connectivity strength especially in bilateral sensorimotor cortex, right lateral prefrontal cortex, left insula and right lingual gyrus, and these regional functional connectivity strength decreases mainly resulted from disruption of short-range regional functional connectivity strength. The minimally treated chronic schizophrenia patients also showed reduced long-range regional functional connectivity strength in the bilateral posterior cingulate cortex/precuneus, and increased long-range regional functional connectivity strength in the right lateral prefrontal cortex and lingual gyrus. Notably, disrupted short-range regional functional connectivity strength mainly correlated with duration of illness and negative symptoms, whereas disrupted long-range regional functional connectivity strength correlated with neurocognitive performance. All of the results were corrected using Monte-Carlo simulation. This

  15. Aberrant Resting-State Functional Connectivity in the Salience Network of Adolescent Chronic Fatigue Syndrome.

    Directory of Open Access Journals (Sweden)

    Laura Anne Wortinger

    Full Text Available Neural network investigations are currently absent in adolescent chronic fatigue syndrome (CFS. In this study, we examine whether the core intrinsic connectivity networks (ICNs are altered in adolescent CFS patients. Eighteen adolescent patients with CFS and 18 aged matched healthy adolescent control subjects underwent resting-state functional magnetic resonance imaging (rfMRI. Data was analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic connectivity was evaluated in the default mode network (DMN, salience network (SN, and central executive network (CEN. Associations between network characteristics and symptoms of CFS were also explored. Adolescent CFS patients displayed a significant decrease in SN functional connectivity to the right posterior insula compared to healthy comparison participants, which was related to fatigue symptoms. Additionally, there was an association between pain intensity and SN functional connectivity to the left middle insula and caudate that differed between adolescent patients and healthy comparison participants. Our findings of insula dysfunction and its association with fatigue severity and pain intensity in adolescent CFS demonstrate an aberration of the salience network which might play a role in CFS pathophysiology.

  16. Resting-state functional connectivity of the amygdala in suicide attempters with major depressive disorder.

    Science.gov (United States)

    Kang, Seung-Gul; Na, Kyoung-Sae; Choi, Jae-Won; Kim, Jeong-Hee; Son, Young-Don; Lee, Yu Jin

    2017-07-03

    In this study, we investigated the difference in resting-state functional connectivity (RSFC) of the amygdala between suicide attempters and non-suicide attempters with major depressive disorder (MDD) using functional magnetic resonance imaging (fMRI). This study included 19 suicide attempters with MDD and 19 non-suicide attempters with MDD. RSFC was compared between the two groups and the regression analyses were conducted to identify the correlation between RSFC and Scale for Suicide Ideation (SSI) scores in the suicide attempt group. Statistical significance was set at p-value (uncorrected) suicide attempters, suicide attempters showed significantly increased RSFC of the left amygdala with the right insula and left superior orbitofrontal area, and increased RSFC of the right amygdala with the left middle temporal area. The regression analysis showed a significant correlation between the SSI total score and RSFC of the right amygdala with the right parahippocampal area in the suicide attempt group. The present RSFC findings provide evidence of a functional neural basis and will help reveal the pathophysiology underlying suicidality in subjects with MDD. Copyright © 2017. Published by Elsevier Inc.

  17. Ketamine decreases resting state functional network connectivity in healthy subjects: implications for antidepressant drug action.

    Directory of Open Access Journals (Sweden)

    Milan Scheidegger

    Full Text Available Increasing preclinical and clinical evidence underscores the strong and rapid antidepressant properties of the glutamate-modulating NMDA receptor antagonist ketamine. Targeting the glutamatergic system might thus provide a novel molecular strategy for antidepressant treatment. Since glutamate is the most abundant and major excitatory neurotransmitter in the brain, pathophysiological changes in glutamatergic signaling are likely to affect neurobehavioral plasticity, information processing and large-scale changes in functional brain connectivity underlying certain symptoms of major depressive disorder. Using resting state functional magnetic resonance imaging (rsfMRI, the "dorsal nexus "(DN was recently identified as a bilateral dorsal medial prefrontal cortex region showing dramatically increased depression-associated functional connectivity with large portions of a cognitive control network (CCN, the default mode network (DMN, and a rostral affective network (AN. Hence, Sheline and colleagues (2010 proposed that reducing increased connectivity of the DN might play a critical role in reducing depression symptomatology and thus represent a potential therapy target for affective disorders. Here, using a randomized, placebo-controlled, double-blind, crossover rsfMRI challenge in healthy subjects we demonstrate that ketamine decreases functional connectivity of the DMN to the DN and to the pregenual anterior cingulate (PACC and medioprefrontal cortex (MPFC via its representative hub, the posterior cingulate cortex (PCC. These findings in healthy subjects may serve as a model to elucidate potential biomechanisms that are addressed by successful treatment of major depression. This notion is further supported by the temporal overlap of our observation of subacute functional network modulation after 24 hours with the peak of efficacy following an intravenous ketamine administration in treatment-resistant depression.

  18. A resting state functional magnetic resonance imaging study of concussion in collegiate athletes.

    Science.gov (United States)

    Czerniak, Suzanne M; Sikoglu, Elif M; Liso Navarro, Ana A; McCafferty, Joseph; Eisenstock, Jordan; Stevenson, J Herbert; King, Jean A; Moore, Constance M

    2015-06-01

    Sports-related concussions are currently diagnosed through multi-domain assessment by a medical professional and may utilize neurocognitive testing as an aid. However, these tests have only been able to detect differences in the days to week post-concussion. Here, we investigate a measure of brain function, namely resting state functional connectivity, which may detect residual brain differences in the weeks to months after concussion. Twenty-one student athletes (9 concussed within 6 months of enrollment; 12 non-concussed; between ages 18 and 22 years) were recruited for this study. All participants completed the Wisconsin Card Sorting Task and the Color-Word Interference Test. Neuroimaging data, specifically resting state functional Magnetic Resonance Imaging data, were acquired to examine resting state functional connectivity. Two sample t-tests were used to compare the neurocognitive scores and resting state functional connectivity patterns among concussed and non-concussed participants. Correlations between neurocognitive scores and resting state functional connectivity measures were also determined across all subjects. There were no significant differences in neurocognitive performance between concussed and non-concussed groups. Concussed subjects had significantly increased connections between areas of the brain that underlie executive function. Across all subjects, better neurocognitive performance corresponded to stronger brain connectivity. Even at rest, brains of concussed athletes may have to 'work harder' than their healthy peers to achieve similar neurocognitive results. Resting state brain connectivity may be able to detect prolonged brain differences in concussed athletes in a more quantitative manner than neurocognitive test scores.

  19. Abnormal amygdala connectivity in patients with primary insomnia: Evidence from resting state fMRI

    International Nuclear Information System (INIS)

    Huang Zhaoyang; Liang Peipeng; Jia Xiuqin; Zhan Shuqin; Li Ning; Ding Yan; Lu Jie; Wang Yuping; Li Kuncheng

    2012-01-01

    Background: Neurobiological mechanisms underlying insomnia are poorly understood. Previous findings indicated that dysfunction of the emotional circuit might contribute to the neurobiological mechanisms underlying insomnia. The present study will test this hypothesis by examining alterations in functional connectivity of the amygdala in patients with primary insomnia (PI). Methods: Resting-state functional connectivity analysis was used to examine the temporal correlation between the amygdala and whole-brain regions in 10 medication-naive PI patients and 10 age- and sex-matched healthy controls. Additionally, the relationship between the abnormal functional connectivity and insomnia severity was investigated. Results: We found decreased functional connectivity mainly between the amygdala and insula, striatum and thalamus, and increased functional connectivity mainly between the amygdala and premotor cortex, sensorimotor cortex in PI patients as compared to healthy controls. The connectivity of the amygdala with the premotor cortex in PI patients showed significant positive correlation with the total score of the Pittsburgh Sleep Quality Index (PSQI). Conclusions: The decreased functional connectivity between the amygdala and insula, striatum, and thalamus suggests that dysfunction in the emotional circuit might contribute to the neurobiological mechanisms underlying PI. The increased functional connectivity of the amygdala with the premotor and sensorimotor cortex demonstrates a compensatory mechanism to overcome the negative effects of sleep deficits and maintain the psychomotor performances in PI patients.

  20. Abnormal amygdala connectivity in patients with primary insomnia: evidence from resting state fMRI.

    Science.gov (United States)

    Huang, Zhaoyang; Liang, Peipeng; Jia, Xiuqin; Zhan, Shuqin; Li, Ning; Ding, Yan; Lu, Jie; Wang, Yuping; Li, Kuncheng

    2012-06-01

    Neurobiological mechanisms underlying insomnia are poorly understood. Previous findings indicated that dysfunction of the emotional circuit might contribute to the neurobiological mechanisms underlying insomnia. The present study will test this hypothesis by examining alterations in functional connectivity of the amygdala in patients with primary insomnia (PI). Resting-state functional connectivity analysis was used to examine the temporal correlation between the amygdala and whole-brain regions in 10 medication-naive PI patients and 10 age- and sex-matched healthy controls. Additionally, the relationship between the abnormal functional connectivity and insomnia severity was investigated. We found decreased functional connectivity mainly between the amygdala and insula, striatum and thalamus, and increased functional connectivity mainly between the amygdala and premotor cortex, sensorimotor cortex in PI patients as compared to healthy controls. The connectivity of the amygdala with the premotor cortex in PI patients showed significant positive correlation with the total score of the Pittsburgh Sleep Quality Index (PSQI). The decreased functional connectivity between the amygdala and insula, striatum, and thalamus suggests that dysfunction in the emotional circuit might contribute to the neurobiological mechanisms underlying PI. The increased functional connectivity of the amygdala with the premotor and sensorimotor cortex demonstrates a compensatory mechanism to overcome the negative effects of sleep deficits and maintain the psychomotor performances in PI patients. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  1. How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

    Science.gov (United States)

    Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J

    2017-02-15

    Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed

  2. Sex Differences in the Default Mode Network with Regard to Autism Spectrum Traits: A Resting State fMRI Study.

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    Minyoung Jung

    Full Text Available Autism spectrum traits exist on a continuum and are more common in males than in females, but the basis for this sex difference is unclear. To this end, the present study draws on the extreme male brain theory, investigating the relationship between sex difference and the default mode network (DMN, both known to be associated with autism spectrum traits. Resting-state functional magnetic resonance imaging (MRI was carried out in 42 females (mean age ± standard deviation, 22.4 ± 4.2 years and 43 males (mean age ± standard deviation, 23.8 ± 3.9 years with typical development. Using a combination of different analyses (viz., independent component analysis (ICA, fractional amplitude of low-frequency fluctuation (fALFF, regional homogeneity (ReHo, and seed-based analyses, we examined sex differences in the DMN and the relationship to autism spectrum traits as measured by autism-spectrum quotient (AQ scores. We found significant differences between female and male subjects in DMN brain regions, with seed-based analysis revealing a significant negative correlation between default-mode resting state functional connectivity of the anterior medial prefrontal cortex seed (aMPFC and AQ scores in males. However, there were no relationships between DMN sex differences and autism spectrum traits in females. Our findings may provide important insight into the skewed balance of functional connectivity in males compared to females that could serve as a potential biomarker of the degree of autism spectrum traits in line with the extreme male brain theory.

  3. Spontaneous Brain Activity Did Not Show the Effect of Violent Video Games on Aggression: A Resting-State fMRI Study

    OpenAIRE

    Wei Pan; Wei Pan; Wei Pan; Xuemei Gao; Shuo Shi; Fuqu Liu; Chao Li

    2018-01-01

    A great many of empirical researches have proved that longtime exposure to violent video game can lead to a series of negative effects. Although research has focused on the neural basis of the correlation between violent video game and aggression, little is known whether the spontaneous brain activity is associated with violent video game exposure. To address this question, we measured the spontaneous brain activity using resting-state functional magnetic resonance imaging (fMRI). We used the...

  4. Regional homogeneity changes between heroin relapse and non-relapse patients under methadone maintenance treatment: a resting-state fMRI study

    OpenAIRE

    Chang, Haifeng; Li, Wei; Li, Qiang; Chen, Jiajie; Zhu, Jia; Ye, Jianjun; Liu, Jierong; Li, Zhe; Li, Yongbin; Shi, Ming; Wang, Yarong; Wang, Wei

    2016-01-01

    Background Methadone maintenance treatment (MMT) is recognized as one of the most effective treatments for heroin addiction but its effect is dimmed by the high incidence of heroin relapse. However, underlying neurobiology mechanism of heroin relapse under MMT is still largely unknown. Here, we took advantage of a resting-state fMRI technique by analysis of regional homogeneity (ReHo), and tried to explore the difference of brain function between heroin relapsers and non-relapsers in MMT. Met...

  5. Altered resting-state functional connectivity of the frontal-striatal reward system in social anxiety disorder.

    Science.gov (United States)

    Manning, Joshua; Reynolds, Gretchen; Saygin, Zeynep M; Hofmann, Stefan G; Pollack, Mark; Gabrieli, John D E; Whitfield-Gabrieli, Susan

    2015-01-01

    We investigated differences in the intrinsic functional brain organization (functional connectivity) of the human reward system between healthy control participants and patients with social anxiety disorder. Functional connectivity was measured in the resting-state via functional magnetic resonance imaging (fMRI). 53 patients with social anxiety disorder and 33 healthy control participants underwent a 6-minute resting-state fMRI scan. Functional connectivity of the reward system was analyzed by calculating whole-brain temporal correlations with a bilateral nucleus accumbens seed and a ventromedial prefrontal cortex seed. Patients with social anxiety disorder, relative to the control group, had (1) decreased functional connectivity between the nucleus accumbens seed and other regions associated with reward, including ventromedial prefrontal cortex; (2) decreased functional connectivity between the ventromedial prefrontal cortex seed and lateral prefrontal regions, including the anterior and dorsolateral prefrontal cortices; and (3) increased functional connectivity between both the nucleus accumbens seed and the ventromedial prefrontal cortex seed with more posterior brain regions, including anterior cingulate cortex. Social anxiety disorder appears to be associated with widespread differences in the functional connectivity of the reward system, including markedly decreased functional connectivity between reward regions and between reward regions and lateral prefrontal cortices, and markedly increased functional connectivity between reward regions and posterior brain regions.

  6. Regional homogeneity changes between heroin relapse and non-relapse patients under methadone maintenance treatment: a resting-state fMRI study.

    Science.gov (United States)

    Chang, Haifeng; Li, Wei; Li, Qiang; Chen, Jiajie; Zhu, Jia; Ye, Jianjun; Liu, Jierong; Li, Zhe; Li, Yongbin; Shi, Ming; Wang, Yarong; Wang, Wei

    2016-08-18

    Methadone maintenance treatment (MMT) is recognized as one of the most effective treatments for heroin addiction but its effect is dimmed by the high incidence of heroin relapse. However, underlying neurobiology mechanism of heroin relapse under MMT is still largely unknown. Here, we took advantage of a resting-state fMRI technique by analysis of regional homogeneity (ReHo), and tried to explore the difference of brain function between heroin relapsers and non-relapsers in MMT. Forty MMT patients were included and received a 12-month follow-up. All patients were given baseline resting-state fMRI scans by using a 3.0 T GE Signa Excite HD whole-body MRI system. Monthly self-report and urine test were used to assess heroin relapse or non-relapse. Subjective craving was measured with visual analog scale. The correlation between ReHo and the degree of heroin relapse was analyzed. Compared with the non-relapsers, ReHo values were increased in the bilateral medial orbitofrontal cortex, right caudate, and right cerebellum of the heroin relapsers while those in the left parahippocampal gyrus, left middle temporal gyrus, right lingual gyrus, and precuneus were decreased in heroin relapsers. Importantly, altered ReHo in the right caudate were positively correlated with heroin relapse rates or subjective craving response. Using the resting-state fMRI technique by analysis of ReHo, we provided the first resting-state fMRI evidence that right caudate may serve as a potential biomarker for heroin relapse prediction and also as a promising target for reducing relapse risk.

  7. Age related changes in striatal resting state functional connectivity in autism

    Directory of Open Access Journals (Sweden)

    Aarthi ePadmanabhan

    2013-11-01

    Full Text Available Characterizing the nature of developmental change is critical to understanding the mechanisms that are impaired in complex neurodevelopment disorders such as autism spectrum disorder (ASD and, pragmatically, may allow us to pinpoint periods of plasticity when interventions are particularly useful. Although aberrant brain development has long been theorized as a characteristic feature of ASD, the neural substrates have been difficult to characterize, in part due to a lack of developmental data and to performance confounds. To address these issues, we examined the development of intrinsic functional connectivity with resting state fMRI from late childhood to early adulthood (8-36 years, using a seed based functional connectivity method with the striatum. Overall, we found that both groups show decreases in cortico-striatal circuits over age. However, when controlling for age, ASD participants showed increased connectivity with parietal cortex and decreased connectivity with prefrontal cortex relative to TD participants. In addition, ASD participants showed aberrant age-related changes in connectivity with anterior aspects of cerebellum, and posterior temporal regions (e.g. fusiform gyrus, inferior and superior temporal gyri. In sum, we found prominent differences in the development of striatal connectivity in ASD, most notably, atypical development of connectivity in striatal networks that may underlie cognitive and social reward processing. Our findings highlight the need to identify the biological mechanisms of perturbations in brain reorganization over development, which also may help clarify discrepant findings in the literature.

  8. Whole brain resting-state analysis reveals decreased functional connectivity in major depression

    NARCIS (Netherlands)

    Veer, I.M.; Beckmann, C.F.; van Tol, M.J.; Ferrarini, L.; Milles, J.; Veltman, D.J.; Aleman, A.; van Buchem, M.A.; van der Wee, N.J.; Rombouts, S.A.R.B.

    2010-01-01

    Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always

  9. Brain Structure and Resting-State Functional Connectivity in University Professors with High Academic Achievement

    Science.gov (United States)

    Li, Weiwei; Yang, Wenjing; Li, Wenfu; Li, Yadan; Wei, Dongtao; Li, Huimin; Qiu, Jiang; Zhang, Qinglin

    2015-01-01

    Creative persons play an important role in technical innovation and social progress. There is little research on the neural correlates with researchers with high academic achievement. We used a combined structural (regional gray matter volume, rGMV) and functional (resting-state functional connectivity analysis, rsFC) approach to examine the…

  10. Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T.

    Science.gov (United States)

    San Emeterio Nateras, Oscar; Yu, Fang; Muir, Eric R; Bazan, Carlos; Franklin, Crystal G; Li, Wei; Li, Jinqi; Lancaster, Jack L; Duong, Timothy Q

    2016-04-01

    To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P 3, P 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

  11. Sex differences in associations of arginine vasopressin and oxytocin with resting-state functional brain connectivity.

    Science.gov (United States)

    Rubin, Leah H; Yao, Li; Keedy, Sarah K; Reilly, James L; Bishop, Jeffrey R; Carter, C Sue; Pournajafi-Nazarloo, Hossein; Drogos, Lauren L; Tamminga, Carol A; Pearlson, Godfrey D; Keshavan, Matcheri S; Clementz, Brett A; Hill, Scot K; Liao, Wei; Ji, Gong-Jun; Lui, Su; Sweeney, John A

    2017-01-02

    Oxytocin (OT) and arginine vasopressin (AVP) exert robust and sexually dimorphic influences on cognition and emotion. How these hormones regulate relevant functional brain systems is not well understood. OT and AVP serum concentrations were assayed in 60 healthy individuals (36 women). Brain functional networks assessed with resting-state functional magnetic resonance imaging (rs-fMRI) were constructed with graph theory-based approaches that characterize brain networks as connected nodes. Sex differences were demonstrated in rs-fMRI. Men showed higher nodal degree (connectedness) and efficiency (information propagation capacity) in left inferior frontal gyrus (IFG) and bilateral superior temporal gyrus (STG) and higher nodal degree in left rolandic operculum. Women showed higher nodal betweenness (being part of paths between nodes) in right putamen and left inferior parietal gyrus (IPG). Higher hormone levels were associated with less intrinsic connectivity. In men, higher AVP was associated with lower nodal degree and efficiency in left IFG (pars orbitalis) and left STG and less efficiency in left IFG (pars triangularis). In women, higher AVP was associated with lower betweenness in left IPG, and higher OT was associated with lower nodal degree in left IFG (pars orbitalis). Hormones differentially correlate with brain networks that are important for emotion processing and cognition in men and women. AVP in men and OT in women may regulate orbital frontal cortex connectivity, which is important in emotion processing. Hormone associations with STG and pars triangularis in men and parietal cortex in women may account for well-established sex differences in verbal and visuospatial abilities, respectively. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  12. Resting-State Functional Connectivity and Cognitive Impairment in Children with Perinatal Stroke

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    Nigul Ilves

    2016-01-01

    Full Text Available Perinatal stroke is a leading cause of congenital hemiparesis and neurocognitive deficits in children. Dysfunctions in the large-scale resting-state functional networks may underlie cognitive and behavioral disability in these children. We studied resting-state functional connectivity in patients with perinatal stroke collected from the Estonian Pediatric Stroke Database. Neurodevelopment of children was assessed by the Pediatric Stroke Outcome Measurement and the Kaufman Assessment Battery. The study included 36 children (age range 7.6–17.9 years: 10 with periventricular venous infarction (PVI, 7 with arterial ischemic stroke (AIS, and 19 controls. There were no differences in severity of hemiparesis between the PVI and AIS groups. A significant increase in default mode network connectivity (FDR 0.1 and lower cognitive functions (p<0.05 were found in children with AIS compared to the controls and the PVI group. The children with PVI had no significant differences in the resting-state networks compared to the controls and their cognitive functions were normal. Our findings demonstrate impairment in cognitive functions and neural network profile in hemiparetic children with AIS compared to children with PVI and controls. Changes in the resting-state networks found in children with AIS could possibly serve as the underlying derangements of cognitive brain functions in these children.

  13. Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

    Science.gov (United States)

    Deco, Gustavo; Hagmann, Patric; Hudetz, Anthony G; Tononi, Giulio

    2014-12-01

    The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Reduced topological efficiency in cortical-basal Ganglia motor network of Parkinson's disease: a resting state fMRI study.

    Science.gov (United States)

    Wei, Luqing; Zhang, Jiuquan; Long, Zhiliang; Wu, Guo-Rong; Hu, Xiaofei; Zhang, Yanling; Wang, Jian

    2014-01-01

    Parkinson's disease (PD) is mainly characterized by dopamine depletion of the cortico-basal ganglia (CBG) motor circuit. Given that dopamine dysfunction could affect functional brain network efficiency, the present study utilized resting-state fMRI (rs-fMRI) and graph theoretical approach to investigate the topological efficiency changes of the CBG motor network in patients with PD during a relatively hypodopaminergic state (12 hours after a last dose of dopamimetic treatment). We found that PD compared with controls had remarkable decreased efficiency in the CBG motor network, with the most pronounced changes observed in rostral supplementary motor area (pre-SMA), caudal SMA (SMA-proper), primary motor cortex (M1), primary somatosensory cortex (S1), thalamus (THA), globus pallidus (GP), and putamen (PUT). Furthermore, reduced efficiency in pre-SMA, M1, THA and GP was significantly correlated with Unified Parkinson's Disease Rating Scale (UPDRS) motor scores in PD patients. Together, our results demonstrate that individuals with PD appear to be less effective at information transfer within the CBG motor pathway, which provides a novel perspective on neurobiological explanation for the motor symptoms in patients. These findings are in line with the pathophysiology of PD, suggesting that network efficiency metrics may be used to identify and track the pathology of PD.

  15. Correlation of BOLD Signal with Linear and Nonlinear Patterns of EEG in Resting State EEG-Informed fMRI

    Directory of Open Access Journals (Sweden)

    Galina V. Portnova

    2018-01-01

    Full Text Available Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived from EEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20 Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.

  16. Resting state functional connectivity changes in adults with developmental stuttering: an initial sLORETA study.

    Directory of Open Access Journals (Sweden)

    Kathleen eJoos

    2014-10-01

    Full Text Available Introduction: Stuttering is defined as speech characterized by verbal dysfluencies, but should not be seen as an isolated speech disorder, but as a generalized sensorimotor timing deficit due to impaired communication between speech related brain areas. Therefore we focused on resting state brain activity and functional connectivity.Method: We included 11 patients with developmental stuttering and 11 age matched controls. To objectify stuttering severity and the impact on the quality of life (QoL, we used the Dutch validated Test for Stuttering Severity-Readers (TSS-R and the Overall Assessment of the Speaker’s Experience of Stuttering (OASES, respectively. Furthermore, we used standardized low resolution brain electromagnetic tomography (sLORETA analyses to look at resting state activity and functional connectivity differences and their correlations with the TSS-R and OASES.Results: No resting state activity differences were identified in comparison to fluently speaking controls or in correlation with stuttering severity or QoL measures. Significant alterations in resting state functional connectivity were found, predominantly interhemispheric, i.e. a decreased functional connectivity for high frequency oscillations (beta and gamma between motor speech areas (BA44 and 45 and the contralateral premotor (BA 6 and motor (BA 4 areas. A positive correlation was found between functional connectivity at low frequency oscillations (theta and alpha and stuttering severity, while a mixed increased and decreased functional connectivity at low and high frequency oscillations correlated with QoL.Discussion: PWS are characterized by decreased high frequency interhemispheric functional connectivity between motor speech, premotor and motor areas in the resting state, while higher functional connectivity in the low frequency bands indicates more severe speech disturbances, suggesting that increased interhemispheric and right sided functional connectivity is

  17. Altered resting-state functional connectivity in women with chronic fatigue syndrome.

    Science.gov (United States)

    Kim, Byung-Hoon; Namkoong, Kee; Kim, Jae-Jin; Lee, Seojung; Yoon, Kang Joon; Choi, Moonjong; Jung, Young-Chul

    2015-12-30

    The biological underpinnings of the psychological factors characterizing chronic fatigue syndrome (CFS) have not been extensively studied. Our aim was to evaluate alterations of resting-state functional connectivity in CFS patients. Participants comprised 18 women with CFS and 18 age-matched female healthy controls who were recruited from the local community. Structural and functional magnetic resonance images were acquired during a 6-min passive-viewing block scan. Posterior cingulate cortex seeded resting-state functional connectivity was evaluated, and correlation analyses of connectivity strength were performed. Graph theory analysis of 90 nodes of the brain was conducted to compare the global and local efficiency of connectivity networks in CFS patients with that in healthy controls. The posterior cingulate cortex in CFS patients showed increased resting-state functional connectivity with the dorsal and rostral anterior cingulate cortex. Connectivity strength of the posterior cingulate cortex to the dorsal anterior cingulate cortex significantly correlated with the Chalder Fatigue Scale score, while the Beck Depression Inventory (BDI) score was controlled. Connectivity strength to the rostral anterior cingulate cortex significantly correlated with the Chalder Fatigue Scale score. Global efficiency of the posterior cingulate cortex was significantly lower in CFS patients, while local efficiency showed no difference from findings in healthy controls. The findings suggest that CFS patients show inefficient increments in resting-state functional connectivity that are linked to the psychological factors observed in the syndrome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Altered Amygdala Resting-State Functional Connectivity and Hemispheric Asymmetry in Patients With Social Anxiety Disorder

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    Ye-Ha Jung

    2018-04-01

    Full Text Available Background: The amygdala plays a key role in emotional hyperreactivity in response to social threat in patients with social anxiety disorder (SAD. We investigated resting-state functional connectivity (rs-FCN of the left and right amygdala with various brain regions and functional lateralization in patients with SAD.Methods: A total of 36 patients with SAD and 42 matched healthy controls underwent functional magnetic resonance imaging (fMRI at rest. Using the left and right amygdala as seed regions, we compared the strength of the rs-FCN in the patient and control groups. Furthermore, we investigated group differences in the hemispheric asymmetry of the functional connectivity maps of the left and right amygdala.Results: Compared with healthy controls, the rs-FCN between the left amygdala and the dorsolateral prefrontal cortex was reduced in patients with SAD, whereas left amygdala connectivity with the fusiform gyrus, anterior insula, supramarginal gyrus, and precuneus was increased or positively deflected in the patient group. Additionally, the strength rs-FCN between the left amygdala and anterior insula was positively associated with the severity of the fear of negative evaluation in patients with SAD (r = 0.338, p = 0.044. The rs-FCN between the right amygdala and medial frontal gyrus was decreased in patients with SAD compared with healthy controls, whereas connectivity with the parahippocampal gyrus was greater in the patient group than in the control group. The hemispheric asymmetry patterns in the anterior insula, intraparietal sulcus (IPS, and inferior frontal gyrus of the patient group were opposite those of the control group, and functional lateralization of the connectivity between the amygdala and the IPS was associated with the severity of social anxiety symptoms (r = 0.365, p = 0.037.Conclusion: Our findings suggest that in addition to impaired fronto-amygdala communication, the functional lateralization of amygdala function

  19. Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Tijn M. Schouten

    2016-01-01

    Full Text Available Magnetic resonance imaging (MRI is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD, and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N=77 from the prospective registry on dementia study and controls (N=173 from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC of 0.760 (full correlations between functional networks to 0.909 (grey matter density. When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.

  20. Moral competence and brain connectivity: a resting-state fMRI study

    Science.gov (United States)

    Jung, Wi Hoon; Prehn, Kristin; Fang, Zhuo; Korczykowski, Marc; Kable, Joseph W.; Rao, Hengyi; Robertson, Diana C.

    2016-01-01

    Moral competence (MC) refers to the ability to apply certain moral orientations in a consistent and differentiated manner when judging moral issues. People greatly differ in terms of MC, however, little is known about how these differences are implemented in the brain. To investigate this question, we used functional magnetic resonance imaging and examined resting-state functional connectivity (RSFC) in n=31 individuals with MC scores in the highest 15% of the population and n=33 individuals with MC scores in the lowest 15%, selected from a large sample of 730 Master of Business Administration (MBA) students. Compared to individuals with lower MC, individuals with higher MC showed greater amygdala-ventromedial prefrontal connectivity, which may reflect better ability to cope with emotional conflicts elicited by moral dilemmas. Moreover, individuals with higher MC showed less inter-network connectivity between the amygdalar and fronto-parietal networks, suggesting a more independent operation of these networks. Our findings provide novel insights into how individual differences in moral judgment are associated with RSFC in brain circuits related to emotion processing and cognitive control. PMID:27456537

  1. Moral competence and brain connectivity: A resting-state fMRI study.

    Science.gov (United States)

    Jung, Wi Hoon; Prehn, Kristin; Fang, Zhuo; Korczykowski, Marc; Kable, Joseph W; Rao, Hengyi; Robertson, Diana C

    2016-11-01

    Moral competence (MC) refers to the ability to apply certain moral orientations in a consistent and differentiated manner when judging moral issues. People greatly differ in terms of MC, however, little is known about how these differences are implemented in the brain. To investigate this question, we used functional magnetic resonance imaging and examined resting-state functional connectivity (RSFC) in n=31 individuals with MC scores in the highest 15% of the population and n=33 individuals with MC scores in the lowest 15%, selected from a large sample of 730 Master of Business Administration (MBA) students. Compared to individuals with lower MC, individuals with higher MC showed greater amygdala-ventromedial prefrontal connectivity, which may reflect better ability to cope with emotional conflicts elicited by moral dilemmas. Moreover, individuals with higher MC showed less inter-network connectivity between the amygdalar and fronto-parietal networks, suggesting a more independent operation of these networks. Our findings provide novel insights into how individual differences in moral judgment are associated with RSFC in brain circuits related to emotion processing and cognitive control. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Abnormal Baseline Brain Activity in Drug-Naïve Patients with Tourette Syndrome: A Resting-state fMRI Study

    Directory of Open Access Journals (Sweden)

    Yonghua eCui

    2014-01-01

    Full Text Available Tourette Syndrome (TS is a childhood-onset chronic disorder characterized by the presence of multiple motor and vocal tics. This study investigated spontaneous low-frequency fluctuations in TS patients during resting-state functional magnetic resonance imaging (fMRI scans. We obtained resting-state fMRI scans from seventeen drug-naïve TS children and fifteen demographically matched healthy children. We computed the amplitude of low frequency fluctuation (ALFF and fractional ALFF (fALFF of resting-state fMRI data to measure spontaneous brain activity, and assessed the between-group differences in ALFF/fALFF and the relationship between ALFF/fALFF and tic severity scores. Our results showed that the children with TS exhibited significantly decreased ALFF in the posterior cingulate gyrus/precuneus and bilateral parietal gyrus. fALFF was decreased in TS children in the anterior cingulated cortex, bilateral middle and superior frontal cortices and superior parietal lobule, and increased in the left putamen and bilateral thalamus. Moreover, we found significantly positive correlations between fALFF and tic severity scores in the right thalamus. Our study provides empirical evidence for abnormal spontaneous neuronal activity in TS patients, which may implicate the underlying neurophysiological mechanism in TS and demonstrate the possibility of applying ALFF/fALFF for clinical TS studies.

  3. Resting-state fMRI revealed different brain activities responding to valproic acid and levetiracetam in benign epilepsy with central-temporal spikes

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qirui; Zhang, Zhiqiang; Xu, Qiang; Wu, Han; Li, Zhipeng; Lu, Guangming [Nanjing University School of Medicine, Department of Medical Imaging, Jinling Hospital, Nanjing (China); Yang, Fang; Li, Qian [Nanjing University School of Medicine, Department of Neurology, Jinling Hospital, Nanjing (China); Hu, Zheng [Nanjing Children' s Hospital, Department of Neurology, Nanjing (China); Dante, Mantini [Faculty of Kinesiology and Rehabilitation Sciences, KU Leuven (Belgium); Li, Kai [Suzhou University, Laboratory of Molecular Medicine, Suzhou (China)

    2017-05-15

    Our aim was to investigate regional difference in brain activities in response to antiepileptic drug (AED) medications in benign epilepsy with central-temporal spikes (BECTS) using resting-state functional magnetic resonance imaging (fMRI). Fifty-seven patients with BECTS underwent resting-state fMRI scans after receiving either valproic acid (VPA) (n = 15), levetiracetam (LEV) (n = 21), or no medication (n = 21). fMRI regional homogeneity (ReHo) parameter among the three groups of patients were compared and were correlated with total doses of AED in the two medicated groups. Compared with patients on no-medication, patients receiving either VPA or LEV showed decreased ReHo in the central-temporal region, frontal cortex, and thalamus. In particular, the VPA group showed greater ReHo decrease in the thalamus and milder in cortices and caudate heads compared with the LEV group. In addition, the VPA group demonstrated a negative correlation between ReHo values in the central-temporal region and medication dose. Both VPA and LEV inhibit resting-state neural activity in the central-temporal region, which is the main epileptogenic focus of BECTS. VPA reduced brain activity in the cortical epileptogenic regions and thalamus evenly, whereas LEV reduced brain activity predominantly in the cortices. Interestingly, VPA showed a cumulative effect on inhibiting brain activity in the epileptogenic regions in BECTS. (orig.)

  4. Resting-state fMRI revealed different brain activities responding to valproic acid and levetiracetam in benign epilepsy with central-temporal spikes

    International Nuclear Information System (INIS)

    Zhang, Qirui; Zhang, Zhiqiang; Xu, Qiang; Wu, Han; Li, Zhipeng; Lu, Guangming; Yang, Fang; Li, Qian; Hu, Zheng; Dante, Mantini; Li, Kai

    2017-01-01

    Our aim was to investigate regional difference in brain activities in response to antiepileptic drug (AED) medications in benign epilepsy with central-temporal spikes (BECTS) using resting-state functional magnetic resonance imaging (fMRI). Fifty-seven patients with BECTS underwent resting-state fMRI scans after receiving either valproic acid (VPA) (n = 15), levetiracetam (LEV) (n = 21), or no medication (n = 21). fMRI regional homogeneity (ReHo) parameter among the three groups of patients were compared and were correlated with total doses of AED in the two medicated groups. Compared with patients on no-medication, patients receiving either VPA or LEV showed decreased ReHo in the central-temporal region, frontal cortex, and thalamus. In particular, the VPA group showed greater ReHo decrease in the thalamus and milder in cortices and caudate heads compared with the LEV group. In addition, the VPA group demonstrated a negative correlation between ReHo values in the central-temporal region and medication dose. Both VPA and LEV inhibit resting-state neural activity in the central-temporal region, which is the main epileptogenic focus of BECTS. VPA reduced brain activity in the cortical epileptogenic regions and thalamus evenly, whereas LEV reduced brain activity predominantly in the cortices. Interestingly, VPA showed a cumulative effect on inhibiting brain activity in the epileptogenic regions in BECTS. (orig.)

  5. Resting state functional connectivity: its physiological basis and application in neuropharmacology.

    Science.gov (United States)

    Lu, Hanbing; Stein, Elliot A

    2014-09-01

    Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Systems-level network activity can be investigated by resting state magnetic resonance imaging (rsMRI), an emerging neuroimaging technique that assesses the synchrony of the brain's ongoing spontaneous activity. Converging evidence reveals that rsMRI is able to consistently identify distinct spatiotemporal patterns of large-scale brain networks. Dysregulation within and between these networks has been implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer's disease and drug addiction. Despite wide application of this approach in systems neuroscience, the physiological basis of these fluctuations remains incompletely understood. Here we review physiological studies in electrical, metabolic and hemodynamic fluctuations that are most pertinent to the rsMRI signal. We also review recent applications to neuropharmacology - specifically drug effects on resting state fluctuations. We speculate that the mechanisms governing spontaneous fluctuations in regional oxygenation availability likely give rise to the observed rsMRI signal. We conclude by identifying several open questions surrounding this technique. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Published by Elsevier Ltd.

  6. Network Centrality of Resting-State fMRI in Primary Angle-Closure Glaucoma Before and After Surgery.

    Directory of Open Access Journals (Sweden)

    Fengqin Cai

    Full Text Available Using voxel-wise degree centrality (DC, as measured by resting-state fMRI, we aimed to study alterations in the brain functional networks in patients with primary angle-closure glaucoma (PACG and to reveal the plastic trajectories of surgery.A total of 23 preoperative PACG patients (49.48 ± 14.37 years old were recruited to undergo a resting-state fMRI scan, and 9 of them were rescanned 3 months after surgery. All PACG patients underwent a complete ophthalmologic examination, including intraocular pressure (IOP, retinal nerve fiber layer (RNFL thickness, vertical cup to disc ratio (V C/D, and average cup to disc ratio (A C/D. Another 23 gender- and age-matched healthy controls (48.18 ± 9.40 years old underwent scanning once for comparison. The group difference in DC was calculated in each voxel, and the correlations between the DC value and each of the clinical variables were analyzed in the PACG patients.Preoperative PACG (pre-PACG patients showed significantly decreased DC in the bilateral visual cortices but increased DC in the left anterior cingulate cortex (ACC and caudate (p < 0.05, corrected compared with the controls. Statistical analysis showed a significantly negative correlation between DC in the bilateral visual cortices and the IOP score and between DC in the anterior cingulate cortex (ACC and both the A C/D and V C/D scores in the pre-PACG patients. Three months after surgery, these postoperative PACG (post-PACG patients showed a significantly increased DC in both the bilateral visual cortices and the left precentral gyrus compared with the pre-PACG patients.Our results suggest that PACG may contribute to decreased functional centrality in the visual system and to increased degree centrality in cognition-emotional processing regions. Alterations in visual areas seem to parallel the cup to disc ratio, but not the duration of angle closure. The changes of functional centrality in PACG patients after operation may reveal the

  7. Resting state fMRI entropy probes complexity of brain activity in adults with ADHD.

    Science.gov (United States)

    Sokunbi, Moses O; Fung, Wilson; Sawlani, Vijay; Choppin, Sabine; Linden, David E J; Thome, Johannes

    2013-12-30

    In patients with attention deficit hyperactivity disorder (ADHD), quantitative neuroimaging techniques have revealed abnormalities in various brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Nonlinear signal processing techniques such as sample entropy have been used to probe the regularity of brain magnetoencephalography signals in patients with ADHD. In the present study, we extend this technique to analyse the complex output patterns of the 4 dimensional resting state functional magnetic resonance imaging signals in adult patients with ADHD. After adjusting for the effect of age, we found whole brain entropy differences (P=0.002) between groups and negative correlation (r=-0.45) between symptom scores and mean whole brain entropy values, indicating lower complexity in patients. In the regional analysis, patients showed reduced entropy in frontal and occipital regions bilaterally and a significant negative correlation between the symptom scores and the entropy maps at a family-wise error corrected cluster level of Pentropy is a useful tool in revealing abnormalities in the brain dynamics of patients with psychiatric disorders. © 2013 Elsevier Ireland Ltd. All rights reserved.

  8. Mentalizing and Microblog Repost through Social Network: Evidence from a Resting-state-fMRI study

    Directory of Open Access Journals (Sweden)

    Huijun Zhang

    2016-11-01

    Full Text Available Microblogs is one of the main social networking channels by which information is spread. Among them, Sina Weibo is one of the largest social networking channel in China. Millions of users repost information from Sina Weibo and share embedded emotion at the same time. The present study investigated participants’ propensity to repost microblog messages of positive, negative or neutral valence, and studied the neural correlates during resting state with the reposting rate of each type microblog messages. Participants preferred to repost negative messages relative to positive and neutral messages. Reposting rate of negative messages was positively correlated to the functional connectivity of temporoparietal junction (TPJ with insula, and TPJ with dorsolateral prefrontal cortex (DLPFC. These results indicate that reposting negative messages is related to conflict resolution between the feeling of pain/ disgust and the intention to repost significant information. Thus, resposting emotional microblog messages might be attributed to participants’ appraisal of personal and recipient’s interest, as well as their cognitive process for decision making.

  9. Mentalizing and Information Propagation through Social Network: Evidence from a Resting-State-fMRI Study.

    Science.gov (United States)

    Zhang, Huijun; Mo, Lei

    2016-01-01

    Microblogs is one of the main social networking channels by which information is spread. Among them, Sina Weibo is one of the largest social networking channels in China. Millions of users repost information from Sina Weibo and share embedded emotion at the same time. The present study investigated participants' propensity to repost microblog messages of positive, negative, or neutral valence, and studied the neural correlates during resting state with the reposting rate of each type microblog messages. Participants preferred to repost negative messages relative to positive and neutral messages. Reposting rate of negative messages was positively correlated to the functional connectivity of temporoparietal junction (TPJ) with insula, and TPJ with dorsolateral prefrontal cortex. These results indicate that reposting negative messages is related to conflict resolution between the feeling of pain/disgust and the intention to repost significant information. Thus, resposting emotional microblog messages might be attributed to participants' appraisal of personal and recipient's interest, as well as their cognitive process for decision making.

  10. Comparing consistency of R2* and T2*-weighted BOLD analysis of resting state fetal fMRI

    Science.gov (United States)

    Seshamani, Sharmishtaa; Blazejewska, Anna I.; Gatenby, Christopher; Mckown, Susan; Caucutt, Jason; Dighe, Manjiri; Studholme, Colin

    2015-03-01

    Understanding when and how resting state brain functional activity begins in the human brain is an increasing area of interest in both basic neuroscience and in the clinical evaluation of the brain during pregnancy and after premature birth. Although fMRI studies have been carried out on pregnant women since the 1990's, reliable mapping of brain function in utero is an extremely challenging problem due to the unconstrained fetal head motion. Recent studies have employed scrubbing to exclude parts of the time series and whole subjects from studies in order to control the confounds of motion. Fundamentally, even after correction of the location of signals due to motion, signal intensity variations are a fundamental limitation, due to coil sensitivity and spin history effects. An alternative technique is to use a more parametric MRI signal derived from multiple echoes that provides a level of independence from basic MRI signal variation. Here we examine the use of R2* mapping combined with slice based multi echo geometric distortion correction for in-utero studies. The challenges for R2* mapping arise from the relatively low signal strength of in-utero data. In this paper we focus on comparing activation detection in-utero using T2W and R2* approaches. We make use a subset of studies with relatively limited motion to compare the activation patterns without the additional confound of significant motion. Results at different gestational ages indicate comparable agreement in many activation patterns when limited motion is present, and the detection of some additional networks in the R2* data, not seen in the T2W results.

  11. Bupropion Administration Increases Resting-State Functional Connectivity in Dorso-Medial Prefrontal Cortex.

    Science.gov (United States)

    Rzepa, Ewelina; Dean, Zola; McCabe, Ciara

    2017-06-01

    Patients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown. Using a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity. Relative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network. These results are opposite to that which we found with 7 days treatment of citalopram in healthy volunteers. These results reflect a different mechanism of action of bupropion compared with selective serotonergic reuptake inhibitors. These results help explain the apparent lack of emotional blunting caused by bupropion in depressed patients. © The Author 2017. Published by Oxford University Press on behalf of CINP.

  12. High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain

    OpenAIRE

    Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Quentin; Culver, Joseph P.; Wang, Lihong V.

    2013-01-01

    The increasing use of mouse models for human brain disease studies presents an emerging need for a new functional imaging modality. Using optical excitation and acoustic detection, we developed a functional connectivity photoacoustic tomography system, which allows noninvasive imaging of resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight functional regions, including the olfactory bu...

  13. Attentional control underlies the perceptual load effect: Evidence from voxel-wise degree centrality and resting-state functional connectivity.

    Science.gov (United States)

    Yin, Shouhang; Liu, Lu; Tan, Jinfeng; Ding, Cody; Yao, Dezhong; Chen, Antao

    2017-10-24

    The fact that interference from peripheral distracting information can be reduced in high perceptual load tasks has been widely demonstrated in previous research. The modulation from the perceptual load is known as perceptual load effect (PLE). Previous functional magnetic resonance imaging (fMRI) studies on perceptual load have reported the brain areas implicated in attentional control. To date, the contribution of attentional control to PLE and the relationship between the organization of functional connectivity and PLE are still poorly understood. In the present study, we used resting-state fMRI to explore the association between the voxel-wise degree centrality (DC) and PLE in an individual differences design and further investigated the potential resting-state functional connectivity (RSFC) contributing to individual's PLE. DC-PLE correlation analysis revealed that PLE was positively associated with the right middle temporal visual area (MT)-one of dorsal attention network (DAN) nodes. Furthermore, the right MT functionally connected to the conventional DAN and the RSFCs between right MT and DAN nodes were also positively associated with individual difference in PLE. The results suggest an important role of attentional control in perceptual load tasks and provide novel insights into the understanding of the neural correlates underlying PLE. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  14. Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

    Science.gov (United States)

    Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

    2011-01-01

    The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti

  15. Abnormal Baseline Brain Activity in Patients with Pulsatile Tinnitus: A Resting-State fMRI Study

    Directory of Open Access Journals (Sweden)

    Lv Han

    2014-01-01

    Full Text Available Numerous investigations studying the brain functional activity of the tinnitus patients have indicated that neurological changes are important findings of this kind of disease. However, the pulsatile tinnitus (PT patients were excluded in previous studies because of the totally different mechanisms of the two subtype tinnitus. The aim of this study is to investigate whether altered baseline brain activity presents in patients with PT using resting-state functional magnetic resonance imaging (rs-fMRI technique. The present study used unilateral PT patients (n=42 and age-, sex-, and education-matched normal control subjects (n=42 to investigate the changes in structural and amplitude of low-frequency (ALFF of the brain. Also, we analyzed the relationships between these changes with clinical data of the PT patients. Compared with normal controls, PT patients did not show any structural changes. PT patients showed significant increased ALFF in the bilateral precuneus, and bilateral inferior frontal gyrus (IFG and decreased ALFF in multiple occipital areas. Moreover, the increased THI score and PT duration was correlated with increased ALFF in precuneus and bilateral IFG. The abnormalities of spontaneous brain activity reflected by ALFF measurements in the absence of structural changes may provide insights into the neural reorganization in PT patients.

  16. Is fMRI “noise” really noise? Resting state nuisance regressors remove variance with network structure

    Science.gov (United States)

    Bright, Molly G.; Murphy, Kevin

    2015-01-01

    Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured “signal” as well as “noise.” Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. PMID:25862264

  17. Effect of phase-encoding direction on group analysis of resting-state functional magnetic resonance imaging.

    Science.gov (United States)

    Mori, Yasuo; Miyata, Jun; Isobe, Masanori; Son, Shuraku; Yoshihara, Yujiro; Aso, Toshihiko; Kouchiyama, Takanori; Murai, Toshiya; Takahashi, Hidehiko

    2018-05-17

    Echo-planar imaging is a common technique used in functional magnetic resonance imaging (fMRI), however it suffers from image distortion and signal loss because of large susceptibility effects that are related to the phase-encoding direction of the scan. Despite this relationship, the majority of neuroimaging studies have not considered the influence of phase-encoding direction. Here, we aimed to clarify how phase-encoding direction can affect the outcome of an fMRI connectivity study of schizophrenia. Resting-state fMRI using anterior to posterior (A-P) and posterior to anterior (P-A) directions was used to examine 25 patients with schizophrenia (SC) and 37 matched healthy controls (HC). We conducted a functional connectivity analysis using independent component analysis and performed three group comparisons: A-P vs. P-A (all participants), SC vs. HC for the A-P and P-A datasets, and the interaction between phase-encoding direction and participant group. The estimated functional connectivity differed between the two phase-encoding directions in areas that were more extensive than those where signal loss has been reported. Although functional connectivity in the SC group was lower than that in the HC group for both directions, the A-P and P-A conditions did not exhibit the same specific pattern of differences. Further, we observed an interaction between participant group and the phase-encoding direction in the left temporo-parietal junction and left fusiform gyrus. Phase-encoding direction can influence the results of functional connectivity studies. Thus, appropriate selection and documentation of phase-encoding direction will be important in future resting-state fMRI studies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  18. Altered fractional amplitude of low frequency fluctuation in premenstrual syndrome: A resting state fMRI study.

    Science.gov (United States)

    Liao, Hai; Duan, Gaoxiong; Liu, Peng; Liu, Yanfei; Pang, Yong; Liu, Huimei; Tang, Lijun; Tao, Jien; Wen, Danhong; Li, Shasha; Liang, Lingyan; Deng, Demao

    2017-08-15

    Premenstrual syndrome (PMS) is becoming highly prevalent among female and is characterized by emotional, physical and behavior symptoms. Previous evidence suggested functional dysregulation of female brain was expected to be involved in the etiology of PMS. The aim of present study was to evaluate the alterations of spontaneous brain activity in PMS patients based on functional magnetic resonance imaging (fMRI). 20 PMS patients and 21 healthy controls underwent resting-state fMRI scanning during luteal phase. All participants were asked to complete a prospective daily record of severity of problems (DRSP) questionnaire. Compared with healthy controls, the results showed that PMS patients had increased fALFF in bilateral precuneus, left hippocampus and left inferior temporal cortex, and decreased fALFF in bilateral anterior cingulate cortex (ACC) and cerebellum at luteal phase. Moreover, the DRSP scores of PMS patients were negatively correlated with the mean fALFF in ACC and positively correlated with the fALFF in precuneus. (1) the study did not investigate whether or not abnormal brain activity differences between groups in mid-follicular phase, and within-group changes. between phases.(2) it was relatively limited sample size and the participants were young; (3) fALFF could not provide us with more holistic information of brain network;(4) the comparisons of PMS and premenstrual dysphoric disorder (PMDD) were not involved in the study. The present study shows abnormal spontaneous brain activity in PMS patients revealed by fALFF, which could provide neuroimaging evidence to further improve our understanding of the underlying neural mechanism of PMS. Copyright © 2017. Published by Elsevier B.V.

  19. Resting-State Functional MR Imaging for Determining Language Laterality in Intractable Epilepsy.

    Science.gov (United States)

    DeSalvo, Matthew N; Tanaka, Naoaki; Douw, Linda; Leveroni, Catherine L; Buchbinder, Bradley R; Greve, Douglas N; Stufflebeam, Steven M

    2016-10-01

    Purpose To measure the accuracy of resting-state functional magnetic resonance (MR) imaging in determining hemispheric language dominance in patients with medically intractable focal epilepsies against the results of an intracarotid amobarbital procedure (IAP). Materials and Methods This study was approved by the institutional review board, and all subjects gave signed informed consent. Data in 23 patients with medically intractable focal epilepsy were retrospectively analyzed. All 23 patients were candidates for epilepsy surgery and underwent both IAP and resting-state functional MR imaging as part of presurgical evaluation. Language dominance was determined from functional MR imaging data by calculating a laterality index (LI) after using independent component analysis. The accuracy of this method was assessed against that of IAP by using a variety of thresholds. Sensitivity and specificity were calculated by using leave-one-out cross validation. Spatial maps of language components were qualitatively compared among each hemispheric language dominance group. Results Measurement of hemispheric language dominance with resting-state functional MR imaging was highly concordant with IAP results, with up to 96% (22 of 23) accuracy, 96% (22 of 23) sensitivity, and 96% (22 of 23) specificity. Composite language component maps in patients with typical language laterality consistently included classic language areas such as the inferior frontal gyrus, the posterior superior temporal gyrus, and the inferior parietal lobule, while those of patients with atypical language laterality also included non-classical language areas such as the superior and middle frontal gyri, the insula, and the occipital cortex. Conclusion Resting-state functional MR imaging can be used to measure language laterality in patients with medically intractable focal epilepsy. (©) RSNA, 2016 Online supplemental material is available for this article.

  20. ICA-based artifact removal diminishes scan site differences in multi-center resting-state fMRI.

    Directory of Open Access Journals (Sweden)

    Rogier Alexander Feis

    2015-10-01

    Full Text Available Resting-state fMRI (R-fMRI has shown considerable promise in providing potential biomarkers for diagnosis, prognosis and drug response across a range of diseases. Incorporating R-fMRI into multi-center studies is becoming increasingly popular, imposing technical challenges on data acquisition and analysis, as fMRI data is particularly sensitive to structured noise resulting from hardware, software and environmental differences. Here, we investigated whether a novel clean up tool for structured noise was capable of reducing center-related R-fMRI differences between healthy subjects.We analyzed 3 Tesla R-fMRI data from 72 subjects, half of whom were scanned with eyes closed in a Philips Achieva system in The Netherlands, and half of whom were scanned with eyes open in a Siemens Trio system in the UK. After pre-statistical processing and individual Independent Component Analysis (ICA, FMRIB’s ICA-based X-noiseifier (FIX was used to remove noise components from the data. GICA and dual regression were run and non-parametric statistics were used to compare spatial maps between groups before and after applying FIX.Large significant differences were found in all resting-state networks between study sites before using FIX, most of which were reduced to non-significant after applying FIX. The between-center difference in the medial/primary visual network, presumably reflecting a between-center difference in protocol, remained statistically different.FIX helps facilitate multi-center R-fMRI research by diminishing structured noise from R-fMRI data. In doing so, it improves combination of existing data from different centers in new settings and comparison of rare diseases and risk genes for which adequate sample size remains a challenge.

  1. Repetitive tactile stimulation changes resting-state functional connectivity – implications for treatment of sensorimotor decline

    Directory of Open Access Journals (Sweden)

    Frank eFreyer

    2012-05-01

    Full Text Available Neurological disorders and physiological aging can lead to a decline of perceptual abilities. In contrast to the conventional therapeutic approach that comprises intensive training and practicing, passive repetitive sensory stimulation (RSS has recently gained increasing attention as an alternative to countervail the sensory decline by improving perceptual abilities without the need of active participation. A particularly effective type of high-frequency RSS, utilizing Hebbian learning principles, improves perceptual acuity as well as sensorimotor functions and has been successfully applied to treat chronic stroke patients and elderly subjects. High-frequency RSS has been shown to induce plastic changes of somatosensory cortex such as representational map reorganization, but its impact on the brain’s ongoing network activity and resting-state functional connectivity has not been investigated so far. Here, we applied high-frequency RSS in healthy human subjects and analyzed resting state Electroencephalography (EEG functional connectivity patterns before and after RSS by means of imaginary coherency (ImCoh, a frequency-specific connectivity measure which is known to reduce overestimation biases due to volume conduction and common reference. Thirty minutes of passive high-frequency RSS lead to significant ImCoh-changes of the resting state mu-rhythm in the individual upper alpha frequency band within distributed sensory and motor cortical areas. These stimulation induced distributed functional connectivity changes likely underlie the previously observed improvement in sensorimotor integration.

  2. Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing.

    Science.gov (United States)

    McGregor, Heather R; Gribble, Paul L

    2015-07-01

    Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153-160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493-1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289-2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989-994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400-404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526-2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769-771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning. Copyright © 2015 the American Physiological Society.

  3. Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing

    Science.gov (United States)

    McGregor, Heather R.

    2015-01-01

    Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153–160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493–1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289–2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989–994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400–404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526–2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769–771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning. PMID:25995349

  4. Mentalizing and Information Propagation through Social Network: Evidence from a Resting-State-fMRI Study

    OpenAIRE

    Zhang, Huijun; Mo, Lei

    2016-01-01

    Microblogs is one of the main social networking channels by which information is spread. Among them, Sina Weibo is one of the largest social networking channels in China. Millions of users repost information from Sina Weibo and share embedded emotion at the same time. The present study investigated participants’ propensity to repost microblog messages of positive, negative, or neutral valence, and studied the neural correlates during resting state with the reposting rate of each type microblo...

  5. Mentalizing and Microblog Repost through Social Network: Evidence from a Resting-state-fMRI study

    OpenAIRE

    Huijun Zhang; Lei Mo

    2016-01-01

    Microblogs is one of the main social networking channels by which information is spread. Among them, Sina Weibo is one of the largest social networking channel in China. Millions of users repost information from Sina Weibo and share embedded emotion at the same time. The present study investigated participants’ propensity to repost microblog messages of positive, negative or neutral valence, and studied the neural correlates during resting state with the reposting rate of each type microblog ...

  6. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

    Science.gov (United States)

    Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

    2015-03-01

    Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

  7. Regional homogeneity within the default mode network in bipolar depression: a resting-state functional magnetic resonance imaging study.

    Directory of Open Access Journals (Sweden)

    Chun-Hong Liu

    Full Text Available AIM: We sought to use a regional homogeneity (ReHo approach as an index in resting-state functional magnetic resonance imaging (fMRI to investigate the features of spontaneous brain activity within the default mode network (DMN in patients suffering from bipolar depression (BD. METHODS: Twenty-six patients with BD and 26 gender-, age-, and education-matched healthy subjects participated in the resting-state fMRI scans. We compared the differences in ReHo between the two groups within the DMN and investigated the relationships between sex, age, years of education, disease duration, the Hamilton Rating Scale for Depression (HAMD total score, and ReHo in regions with significant group differences. RESULTS: Our results revealed that bipolar depressed patients had increased ReHo in the left medial frontal gyrus and left inferior parietal lobe compared to healthy controls. No correlations were found between regional ReHo values and sex, age, and clinical features within the BD group. CONCLUSIONS: Our findings indicate that abnormal brain activity is mainly distributed within prefrontal-limbic circuits, which are believed to be involved in the pathophysiological mechanisms underlying bipolar depression.

  8. Replicability of time-varying connectivity patterns in large resting state fMRI samples.

    Science.gov (United States)

    Abrol, Anees; Damaraju, Eswar; Miller, Robyn L; Stephen, Julia M; Claus, Eric D; Mayer, Andrew R; Calhoun, Vince D

    2017-12-01

    The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Transdiagnostic differences in the resting-state functional connectivity of the prefrontal cortex in depression and schizophrenia.

    Science.gov (United States)

    Chen, Xi; Liu, Chang; He, Hui; Chang, Xin; Jiang, Yuchao; Li, Yingjia; Duan, Mingjun; Li, Jianfu; Luo, Cheng; Yao, Dezhong

    2017-08-01

    Depression and schizophrenia are two of the most serious psychiatric disorders. They share similar symptoms but the pathology-specific commonalities and differences remain unknown. This study was conducted to acquire a full picture of the functional alterations in schizophrenia and depression patients. The resting-state fMRI data from 20 patients with schizophrenia, 20 patients with depression and 20 healthy control subjects were collected. A data-driven approach that included local functional connectivity density (FCD) analysis combined with multivariate pattern analysis (MVPA) was used to compare the three groups. Based on the results of the MVPA, the local FCD value in the orbitofrontal cortex (OFC) can differentiate depression patients from schizophrenia patients. The patients with depression had a higher local FCD value in the medial and anterior parts of the OFC than the subjects in the other two groups, which suggested altered abstract and reward reinforces processing in depression patients. Subsequent functional connectivity analysis indicated that the connection in the prefrontal cortex was significantly lower in people with schizophrenia compared to people with depression and healthy controls. The systematically different medications for schizophrenia and depression may have different effects on functional connectivity. These results suggested that the resting-state functional connectivity pattern in the prefrontal cortex may be a transdiagnostic difference between depression and schizophrenia patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Amygdala-prefrontal cortex resting-state functional connectivity varies with first depressive or manic episode in bipolar disorder.

    Science.gov (United States)

    Wei, Shengnan; Geng, Haiyang; Jiang, Xiaowei; Zhou, Qian; Chang, Miao; Zhou, Yifang; Xu, Ke; Tang, Yanqing; Wang, Fei

    2017-02-22

    Bipolar disorder (BD) is one of the most complex mental illnesses, characterized by interactive depressive and manic states that are 2 contrary symptoms of disease states. The bilateral amygdala and prefrontal cortex (PFC) appear to play critical roles in BD; however, abnormalities seem to manifest differently in the 2 states and may provide further insight into underlying mechanisms. Sixteen participants with first-episode depressive and 13 participants with first-episode manic states of bipolar disorder as well as 30 healthy control (HC) participants underwent resting-state functional magnetic resonance imaging (fMRI). Resting-state functional connectivity (rsFC) between the bilateral amygdala and PFC was compared among the 3 groups. Compared with depressive state participants of the BD group, manic state participants of the BD group showed a significant decrease in rsFC between the amygdala and right orbital frontal cortex (pamygdala and left middle frontal cortex was significantly decreased in depressive and manic state participants of the BD group when compared with the HC group (pamygdala- left PFC functional connectivity might present the trait feature for BD, while deficits in amygdala- right PFC functional connectivity might be specific to manic episode, compared to depressive episode. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Resting-state Functional Connectivity is an Age-dependent Predictor of Motor Learning Abilities.

    Science.gov (United States)

    Mary, Alison; Wens, Vincent; Op de Beeck, Marc; Leproult, Rachel; De Tiège, Xavier; Peigneux, Philippe

    2017-10-01

    This magnetoencephalography study investigates how ageing modulates the relationship between pre-learning resting-state functional connectivity (rsFC) and subsequent learning. Neuromagnetic resting-state activity was recorded 5 min before motor sequence learning in 14 young (19-30 years) and 14 old (66-70 years) participants. We used a seed-based beta-band power envelope correlation approach to estimate rsFC maps, with the seed located in the right primary sensorimotor cortex. In each age group, the relation between individual rsFC and learning performance was investigated using Pearson's correlation analyses. Our results show that rsFC is predictive of subsequent motor sequence learning but involves different cross-network interactions in the two age groups. In young adults, decreased coupling between the sensorimotor network and the cortico-striato-cerebellar network is associated with better motor learning, whereas a similar relation is found in old adults between the sensorimotor, the dorsal-attentional and the DMNs. Additionally, age-related correlational differences were found in the dorsolateral prefrontal cortex, known to subtend attentional and controlled processes. These findings suggest that motor skill learning depends-in an age-dependent manner-on subtle interactions between resting-state networks subtending motor activity on the one hand, and controlled and attentional processes on the other hand. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. A method for independent component graph analysis of resting-state fMRI

    DEFF Research Database (Denmark)

    de Paula, Demetrius Ribeiro; Ziegler, Erik; Abeyasinghe, Pubuditha M.

    2017-01-01

    Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non-contiguou......Introduction Independent component analysis (ICA) has been extensively used for reducing task-free BOLD fMRI recordings into spatial maps and their associated time-courses. The spatially identified independent components can be considered as intrinsic connectivity networks (ICNs) of non......-contiguous regions. To date, the spatial patterns of the networks have been analyzed with techniques developed for volumetric data. Objective Here, we detail a graph building technique that allows these ICNs to be analyzed with graph theory. Methods First, ICA was performed at the single-subject level in 15 healthy...... parcellated regions. Third, between-node functional connectivity was established by building edge weights for each networks. Group-level graph analysis was finally performed for each network and compared to the classical network. Results Network graph comparison between the classically constructed network...

  13. Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy

    Science.gov (United States)

    Zhang, Yu-Jin; Lu, Chun-Ming; Biswal, Bharat B.; Zang, Yu-Feng; Peng, Dan-Lin; Zhu, Chao-Zhe

    2010-07-01

    Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high-level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach.

  14. Imbalance in resting state functional connectivity is associated with eating behaviors and adiposity in children

    Directory of Open Access Journals (Sweden)

    BettyAnn A. Chodkowski

    2016-01-01

    Conclusions: In the absence of any explicit eating-related stimuli, the developing brain is primed toward food approach and away from food avoidance behavior with increasing adiposity. Imbalance in resting state functional connectivity that is associated with non-homeostatic eating develops during childhood, as early as 8–13 years of age. Our results indicate the importance of identifying children at risk for obesity for earlier intervention. In addition to changing eating habits and physical activity, strategies that normalize neural functional connectivity imbalance are needed to maintain healthy weight. Mindfulness may be one such approach as it is associated with increased response inhibition and decreased impulsivity.

  15. Resting-State Functional Connectivity and Network Analysis of Cerebellum with Respect to IQ and Gender

    Directory of Open Access Journals (Sweden)

    Vasileios C. Pezoulas

    2017-04-01

    Full Text Available During the last years, it has been established that the prefrontal and posterior parietal brain lobes, which are mostly related to intelligence, have many connections to cerebellum. However, there is a limited research investigating cerebellum's relationship with cognitive processes. In this study, the network of cerebellum was analyzed in order to investigate its overall organization in individuals with low and high fluid Intelligence Quotient (IQ. Functional magnetic resonance imaging (fMRI data were selected from 136 subjects in resting-state from the Human Connectome Project (HCP database and were further separated into two IQ groups composed of 69 low-IQ and 67 high-IQ subjects. Cerebellum was parcellated into 28 lobules/ROIs (per subject using a standard cerebellum anatomical atlas. Thereafter, correlation matrices were constructed by computing Pearson's correlation coefficients between the average BOLD time-series for each pair of ROIs inside the cerebellum. By computing conventional graph metrics, small-world network properties were verified using the weighted clustering coefficient and the characteristic path length for estimating the trade-off between segregation and integration. In addition, a connectivity metric was computed for extracting the average cost per network. The concept of the Minimum Spanning Tree (MST was adopted and implemented in order to avoid methodological biases in graph comparisons and retain only the strongest connections per network. Subsequently, six global and three local metrics were calculated in order to retrieve useful features concerning the characteristics of each MST. Moreover, the local metrics of degree and betweenness centrality were used to detect hubs, i.e., nodes with high importance. The computed set of metrics gave rise to extensive statistical analysis in order to examine differences between low and high-IQ groups, as well as between all possible gender-based group combinations. Our results

  16. Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

    Science.gov (United States)

    Wang, J; Hao, Z; Wang, H

    2018-01-01

    The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

  17. Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation

    Directory of Open Access Journals (Sweden)

    J. Wang

    2018-05-01

    Full Text Available The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC. The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

  18. Detecting bilateral motor associated areas with resting state functional magnetic resonance: the effect of different seed points selection on the results

    International Nuclear Information System (INIS)

    Yi Huiming; Yang Mingming; Meng Liangliang; Zhang Jing

    2011-01-01

    Objective: To investigate the effect of different seed points selection on localizing bilateral hand motor associated areas in resting state functional magnetic resonance. Methods: Thirty -one subjects were recruited (male 15, female 16), all of them underwent both block-designed fMRI scan during performing bilateral hand motor task and resting-state fMRI scan. DPARSA V2.0 and SPM8 were used to process the data. The peak voxels in the activity map of the task scan were selected as seeds to compute functional connectivity map of the resting-state scan. Spatial correlation analysis was performed to compare the activity map of the task scan and the connectivity map of the resting- state scan. Results: Fifteen isolated clusters were picked to generate the peak voxels, which were selected as seeds to compute functional connectivity maps. Among all the functional connectivity maps, those generated by motor area (SMA) presented the most consistent spatial distribution with task associated activity map, and the functional connectivity maps generated by primary motor cortex (M1) and dorsal premotor cortex (PMd) consisted of bilateral Ml and SMA. the functional connectivity maps generated by putamen (Pu), thalamus (Th), cerebellum anterior lobe (CbAL) and cerebellum posterior lobe (CbPL) consisted of the areas around the seeds and the mirror areas in the contralateral cortex. Conclusion: Using SMA as seed to compute resting-state functional connectivity map may produce the best spatial coherence with the activity map generated by bilateral hand motor task, and selecting M1 and PMd as seeds may present the best primary motor cortex in the connectivity map. (authors)

  19. Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

    Science.gov (United States)

    Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

    2017-11-01

    Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Music reduces pain and increases resting state fMRI BOLD signal amplitude in the left angular gyrus in fibromyalgia patients

    DEFF Research Database (Denmark)

    Garza-Villarreal, Eduardo A; Jiang, Zhiguo; Vuust, Peter

    2015-01-01

    , correlated to the analgesia reports. The post-hoc seed-based functional connectivity analysis of the lAnG showed found higher connectivity after listening to music with right dorsolateral prefrontal cortex (rdlPFC), the left caudate (lCau), and decreased connectivity with right anterior cingulate cortex (r......Music reduces pain in fibromyalgia (FM), a chronic pain disease, but the functional neural correlates of music-induced analgesia (MIA) are still largely unknown. We recruited FM patients (n = 22) who listened to their preferred relaxing music and an auditory control (pink noise) for 5 min without...... external noise from fMRI image acquisition. Resting state fMRI was then acquired before and after the music and control conditions. A significant increase in the amplitude of low frequency fluctuations of the BOLD signal was evident in the left angular gyrus (lAnG) after listening to music, which in turn...

  1. Concurrent tACS-fMRI Reveals Causal Influence of Power Synchronized Neural Activity on Resting State fMRI Connectivity.

    Science.gov (United States)

    Bächinger, Marc; Zerbi, Valerio; Moisa, Marius; Polania, Rafael; Liu, Quanying; Mantini, Dante; Ruff, Christian; Wenderoth, Nicole

    2017-05-03

    Resting state fMRI (rs-fMRI) is commonly used to study the brain's intrinsic neural coupling, which reveals specific spatiotemporal patterns in the form of resting state networks (RSNs). It has been hypothesized that slow rs-fMRI oscillations (5 Hz); however, causal evidence for this relationship is currently lacking. Here we measured rs-fMRI in humans while applying transcranial alternating current stimulation (tACS) to entrain brain rhythms in left and right sensorimotor cortices. The two driving tACS signals were tailored to the individual's α rhythm (8-12 Hz) and fluctuated in amplitude according to a 1 Hz power envelope. We entrained the left versus right hemisphere in accordance to two different coupling modes where either α oscillations were synchronized between hemispheres (phase-synchronized tACS) or the slower oscillating power envelopes (power-synchronized tACS). Power-synchronized tACS significantly increased rs-fMRI connectivity within the stimulated RSN compared with phase-synchronized or no tACS. This effect outlasted the stimulation period and tended to be more effective in individuals who exhibited a naturally weak interhemispheric coupling. Using this novel approach, our data provide causal evidence that synchronized power fluctuations contribute to the formation of fMRI-based RSNs. Moreover, our findings demonstrate that the brain's intrinsic coupling at rest can be selectively modulated by choosing appropriate tACS signals, which could lead to new interventions for patients with altered rs-fMRI connectivity. SIGNIFICANCE STATEMENT Resting state fMRI (rs-fMRI) has become an important tool to estimate brain connectivity. However, relatively little is known about how slow hemodynamic oscillations measured with fMRI relate to electrophysiological processes. It was suggested that slowly fluctuating power envelopes of electrophysiological signals synchronize across brain areas and that the topography of this activity is spatially correlated to

  2. High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain

    Science.gov (United States)

    Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Quentin; Culver, Joseph P.; Wang, Lihong V.

    2014-01-01

    The increasing use of mouse models for human brain disease studies presents an emerging need for a new functional imaging modality. Using optical excitation and acoustic detection, we developed a functional connectivity photoacoustic tomography system, which allows noninvasive imaging of resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight functional regions, including the olfactory bulb, limbic, parietal, somatosensory, retrosplenial, visual, motor, and temporal regions, as well as in several subregions. The borders and locations of these regions agreed well with the Paxinos mouse brain atlas. By subjecting the mouse to alternating hyperoxic and hypoxic conditions, strong and weak functional connectivities were observed, respectively. In addition to connectivity images, vascular images were simultaneously acquired. These studies show that functional connectivity photoacoustic tomography is a promising, noninvasive technique for functional imaging of the mouse brain. PMID:24367107

  3. Exploring difference and overlap between schizophrenia, schizoaffective and bipolar disorders using resting-state brain functional networks.

    Science.gov (United States)

    Du, Yuhui; Liu, Jingyu; Sui, Jing; He, Hao; Pearlson, Godfrey D; Calhoun, Vince D

    2014-01-01

    Schizophrenia, schizoaffective and bipolar disorders share some common symptoms. However, the biomarkers underlying those disorders remain unclear. In fact, there is still controversy about the schizoaffective disorder with respect to its validity of independent category and its relationship with schizophrenia and bipolar disorders. In this paper, based on brain functional networks extracted from resting-state fMRI using a recently proposed group information guided ICA (GIG-ICA) method, we explore the biomarkers for discriminating healthy controls, schizophrenia patients, bipolar patients, and patients with two symptom defined subsets of schizoaffective disorder, and then investigate the relationship between different groups. The results demonstrate that the discriminating regions mainly including frontal, parietal, precuneus, cingulate, supplementary motor, cerebellar, insular and supramarginal cortices perform well in distinguishing the different diagnostic groups. The results also suggest that schizoaffective disorder may be an independent disorder, although its subtype characterized by depressive episodes shares more similarity with schizophrenia.

  4. Altered Amygdala Resting-State Functional Connectivity in Maintenance Hemodialysis End-Stage Renal Disease Patients with Depressive Mood.

    Science.gov (United States)

    Chen, Hui Juan; Wang, Yun Fei; Qi, Rongfeng; Schoepf, U Joseph; Varga-Szemes, Akos; Ball, B Devon; Zhang, Zhe; Kong, Xiang; Wen, Jiqiu; Li, Xue; Lu, Guang Ming; Zhang, Long Jiang

    2017-04-01

    The purpose of this study was to investigate patterns in the amygdala-based emotional processing circuit of hemodialysis patients using resting-state functional MR imaging (rs-fMRI). Fifty hemodialysis patients (25 with depressed mood and 25 without depressed mood) and 26 healthy controls were included. All subjects underwent neuropsychological tests and rs-fMRI, and patients also underwent laboratory tests. Functional connectivity of the bilateral amygdala was compared among the three groups. The relationship between functional connectivity and clinical markers was investigated. Depressed patients showed increased positive functional connectivity of the left amygdala with the left superior temporal gyrus and right parahippocampal gyrus (PHG) but decreased amygdala functional connectivity with the left precuneus, angular gyrus, posterior cingulate cortex (PCC), and left inferior parietal lobule compared with non-depressed patients (P amygdala with bilateral supplementary motor areas and PHG but decreased amygdala functional connectivity with the right superior frontal gyrus, superior parietal lobule, bilateral precuneus, and PCC (P amygdala (P amygdala-prefrontal-PCC-limbic circuits was impaired in depressive hemodialysis patients, with a gradual decrease in ACC between controls, non-depressed, and depressed patients for the right amygdala. This indicates that ACC plays a role in amygdala-based emotional regulatory circuits in these patients.

  5. A Bayesian Double Fusion Model for Resting-State Brain Connectivity Using Joint Functional and Structural Data

    KAUST Repository

    Kang, Hakmook; Ombao, Hernando; Fonnesbeck, Christopher; Ding, Zhaohua; Morgan, Victoria L.

    2017-01-01

    DTI that could potentially enhance estimation of resting-state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatiotemporal model that incorporates structural connectivity (SC

  6. Extraversion modulates functional connectivity hubs of resting-state brain networks.

    Science.gov (United States)

    Pang, Yajing; Cui, Qian; Duan, Xujun; Chen, Heng; Zeng, Ling; Zhang, Zhiqiang; Lu, Guangming; Chen, Huafu

    2017-09-01

    Personality dimension extraversion describes individual differences in social behaviour and socio-emotional functioning. The intrinsic functional connectivity patterns of the brain are reportedly associated with extraversion. However, whether or not extraversion is associated with functional hubs warrants clarification. Functional hubs are involved in the rapid integration of neural processing, and their dysfunction contributes to the development of neuropsychiatric disorders. In this study, we employed the functional connectivity density (FCD) method for the first time to distinguish the energy-efficient hubs associated with extraversion. The resting-state functional magnetic resonance imaging data of 71 healthy subjects were used in the analysis. Short-range FCD was positively correlated with extraversion in the left cuneus, revealing a link between the local functional activity of this region and extraversion in risk-taking. Long-range FCD was negatively correlated with extraversion in the right superior frontal gyrus and the inferior frontal gyrus. Seed-based resting-state functional connectivity (RSFC) analyses revealed that a decreased long-range FCD in individuals with high extraversion scores showed a low long-range functional connectivity pattern between the medial and dorsolateral prefrontal cortex, middle temporal gyrus, and anterior cingulate cortex. This result suggests that decreased RSFC patterns are responsible for self-esteem, self-evaluation, and inhibitory behaviour system that account for the modulation and shaping of extraversion. Overall, our results emphasize specific brain hubs, and reveal long-range functional connections in relation to extraversion, thereby providing a neurobiological basis of extraversion. © 2015 The British Psychological Society.

  7. Early Changes in Alpha Band Power and DMN BOLD Activity in Alzheimer’s Disease: A Simultaneous Resting State EEG-fMRI Study

    Directory of Open Access Journals (Sweden)

    Katharina Brueggen

    2017-10-01

    Full Text Available Simultaneous resting state functional magnetic resonance imaging (rsfMRI–resting state electroencephalography (rsEEG studies in healthy adults showed robust positive associations of signal power in the alpha band with BOLD signal in the thalamus, and more heterogeneous associations in cortical default mode network (DMN regions. Negative associations were found in occipital regions. In Alzheimer’s disease (AD, rsfMRI studies revealed a disruption of the DMN, while rsEEG studies consistently reported a reduced power within the alpha band. The present study is the first to employ simultaneous rsfMRI-rsEEG in an AD sample, investigating the association of alpha band power and BOLD signal, compared to healthy controls (HC. We hypothesized to find reduced positive associations in DMN regions and reduced negative associations in occipital regions in the AD group. Simultaneous resting state fMRI–EEG was recorded in 14 patients with mild AD and 14 HC, matched for age and gender. Power within the EEG alpha band (8–12 Hz, 8–10 Hz, and 10–12 Hz was computed from occipital electrodes and served as regressor in voxel-wise linear regression analyses, to assess the association with the BOLD signal. Compared to HC, the AD group showed significantly decreased positive associations between BOLD signal and occipital alpha band power in clusters in the superior, middle and inferior frontal cortex, inferior temporal lobe and thalamus (p < 0.01, uncorr., cluster size ≥ 50 voxels. This group effect was more pronounced in the upper alpha sub-band, compared to the lower alpha sub-band. Notably, we observed a high inter-individual heterogeneity. Negative associations were only reduced in the lower alpha range in the hippocampus, putamen and cerebellum. The present study gives first insights into the relationship of resting-state EEG and fMRI characteristics in an AD sample. The results suggest that positive associations between alpha band power and BOLD

  8. Effects of Methylphenidate on Resting-State Functional Connectivity of the Mesocorticolimbic Dopamine Pathways in Cocaine Addiction

    Energy Technology Data Exchange (ETDEWEB)

    Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo; Volkow, Nora D.; Goldstein, Rita Z.

    2013-08-01

    Cocaine addiction is associated with altered resting-state functional connectivity among regions of the mesocorticolimbic dopamine pathways. Methylphenidate hydrochloride, an indirect dopamine agonist, normalizes task-related regional brain activity and associated behavior in cocaine users; however, the neural systems–level effects of methylphenidate in this population have not yet been described. To use resting-state functional magnetic resonance imaging to examine changes in mesocorticolimbic connectivity with methylphenidate and how connectivity of affected pathways relates to severity of cocaine addiction.

  9. Study on resting-state fMRI based on amplitude of low-frequency fluctuation in patients with major depression

    Directory of Open Access Journals (Sweden)

    Meng-jie PAN

    2018-04-01

    Full Text Available Objective To observe characteristics of resting-state functional magnetic resonance imaging (rs-fMRI in patients with major depression and explore the possible pathogenesis. Methods A total of 24 major depression patients and 26 sex-, age- and education-matched healthy controls were scanned with rs-fMRI based on amplitude of low-frequency fluctuation (ALFF. The correlation between mALFF values of brain regions and Hamilton Depression Rating Scale-17 (HAMD-17 score was analyzed by Spearman rank correlation analysis. Results Compared with control group, mALFF values in bilateral dorsolateral prefrontal cortex (DLPFC, right orbital superior frontal gyrus, right inferior temporal gyrus, left operculum inferior frontal gyrus, left medial superior frontal gyrus and left gyrus rectus in major depression group were significantly increased (P 0.05, for all. Conclusions Abnormal brain spontaneous activity within default mode network (DMN and limbic system could emerge in major depression patients during resting-state, which may be neurobiological substrate of major depression. DOI: 10.3969/j.issn.1672-6731.2018.03.005

  10. How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI

    Directory of Open Access Journals (Sweden)

    Julia Leonard

    2017-03-01

    Full Text Available A constant problem developmental neuroimagers face is in-scanner head motion. Children move more than adults and this has led to concerns that developmental changes in resting-state connectivity measures may be artefactual. Furthermore, children are challenging to recruit into studies and therefore researchers have tended to take a permissive stance when setting exclusion criteria on head motion. The literature is not clear regarding our central question: How much motion is too much? Here, we systematically examine the effects of multiple motion exclusion criteria at different sample sizes and age ranges in a large openly available developmental cohort (ABIDE; http://preprocessed-connectomes-project.org/abide. We checked 1 the reliability of resting-state functional magnetic resonance imaging (rs-fMRI pairwise connectivity measures across the brain and 2 the accuracy with which we can separate participants with autism spectrum disorder from typically developing controls based on their rs-fMRI scans using machine learning. We find that reliability on average is primarily sensitive to the number of participants considered, but that increasingly permissive motion thresholds lower case-control prediction accuracy for all sample sizes.

  11. Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning.

    Science.gov (United States)

    Kesler, Shelli R; Rao, Arvind; Blayney, Douglas W; Oakley-Girvan, Ingrid A; Karuturi, Meghan; Palesh, Oxana

    2017-01-01

    We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34-65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( p breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.

  12. A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia.

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    Castellazzi, Gloria; Palesi, Fulvia; Casali, Stefano; Vitali, Paolo; Sinforiani, Elena; Wheeler-Kingshott, Claudia A M; D'Angelo, Egidio

    2014-01-01

    In resting state fMRI (rs-fMRI), only functional connectivity (FC) reductions in the default mode network (DMN) are normally reported as a biomarker for Alzheimer's disease (AD). In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI), compared to healthy controls (HC). Resting state networks (RSNs) were studied in 14 AD (70 ± 6 years), 12 MCI (74 ± 6 years), and 16 HC (69 ± 5 years). RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC), putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN), lateral visual network (LVN), basal ganglia network (BGN), cerebellar network (CBLN), and the anterior insula network (AIN). Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.

  13. Resting-state functional connectivity differentiates anxious apprehension and anxious arousal.

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    Burdwood, Erin N; Infantolino, Zachary P; Crocker, Laura D; Spielberg, Jeffrey M; Banich, Marie T; Miller, Gregory A; Heller, Wendy

    2016-10-01

    Brain regions in the default mode network (DMN) display greater functional connectivity at rest or during self-referential processing than during goal-directed tasks. The present study assessed resting-state connectivity as a function of anxious apprehension and anxious arousal, independent of depressive symptoms, in order to understand how these dimensions disrupt cognition. Whole-brain, seed-based analyses indicated differences between anxious apprehension and anxious arousal in DMN functional connectivity. Lower connectivity associated with higher anxious apprehension suggests decreased adaptive, inner-focused thought processes, whereas higher connectivity at higher levels of anxious arousal may reflect elevated monitoring of physiological responses to threat. These findings further the conceptualization of anxious apprehension and anxious arousal as distinct psychological dimensions with distinct neural instantiations. © 2016 Society for Psychophysiological Research.

  14. Mindfulness Meditation Training and Executive Control Network Resting State Functional Connectivity: A Randomized Controlled Trial.

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    Taren, Adrienne A; Gianaros, Peter J; Greco, Carol M; Lindsay, Emily K; Fairgrieve, April; Brown, Kirk Warren; Rosen, Rhonda K; Ferris, Jennifer L; Julson, Erica; Marsland, Anna L; Creswell, J David

    Mindfulness meditation training has been previously shown to enhance behavioral measures of executive control (e.g., attention, working memory, cognitive control), but the neural mechanisms underlying these improvements are largely unknown. Here, we test whether mindfulness training interventions foster executive control by strengthening functional connections between dorsolateral prefrontal cortex (dlPFC)-a hub of the executive control network-and frontoparietal regions that coordinate executive function. Thirty-five adults with elevated levels of psychological distress participated in a 3-day randomized controlled trial of intensive mindfulness meditation or relaxation training. Participants completed a resting state functional magnetic resonance imaging scan before and after the intervention. We tested whether mindfulness meditation training increased resting state functional connectivity (rsFC) between dlPFC and frontoparietal control network regions. Left dlPFC showed increased connectivity to the right inferior frontal gyrus (T = 3.74), right middle frontal gyrus (MFG) (T = 3.98), right supplementary eye field (T = 4.29), right parietal cortex (T = 4.44), and left middle temporal gyrus (T = 3.97, all p < .05) after mindfulness training relative to the relaxation control. Right dlPFC showed increased connectivity to right MFG (T = 4.97, p < .05). We report that mindfulness training increases rsFC between dlPFC and dorsal network (superior parietal lobule, supplementary eye field, MFG) and ventral network (right IFG, middle temporal/angular gyrus) regions. These findings extend previous work showing increased functional connectivity among brain regions associated with executive function during active meditation by identifying specific neural circuits in which rsFC is enhanced by a mindfulness intervention in individuals with high levels of psychological distress. Clinicaltrials.gov,NCT01628809.

  15. Longitudinal changes in resting-state fMRI from age 5 to age 6years covary with language development.

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    Xiao, Yaqiong; Friederici, Angela D; Margulies, Daniel S; Brauer, Jens

    2016-03-01

    Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i.e., left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI

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    Nathan W. Churchill

    Full Text Available Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70 university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1 a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings; and (2 a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks. Keywords: fMRI, Functional connectivity, Concussion, Brain injury, Symptoms

  17. A compact and realistic cerebral cortical layout derived from prewhitened resting-state fMRI time series: Cherniak's adjacency rule, size law, and metamodule grouping upheld.

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    Lewis, Scott M; Christova, Peka; Jerde, Trenton A; Georgopoulos, Apostolos P

    2012-01-01

    We used hierarchical tree clustering to derive a functional organizational chart of 52 human cortical areas (26 per hemisphere) from zero-lag correlations calculated between single-voxel, prewhitened, resting-state BOLD fMRI time series in 18 subjects. No special "resting-state networks" were identified. There were four major features in the resulting tree (dendrogram). First, there was a strong clustering of homotopic, left-right hemispheric areas. Second, cortical areas were concatenated in multiple, partially overlapping clusters. Third, the arrangement of the areas revealed a layout that closely resembled the actual layout of the cerebral cortex, namely an orderly progression from anterior to posterior. And fourth, the layout of the cortical areas in the tree conformed to principles of efficient, compact layout of components proposed by Cherniak. Since the tree was derived on the basis of the strength of neural correlations, these results document an orderly relation between functional interactions and layout, i.e., between structure and function.

  18. A compact and realistic cerebral cortical layout derived from prewhitened resting-state fMRI time series: Cherniak's adjacency rule, size law, and metamodule grouping upheld

    Science.gov (United States)

    Lewis, Scott M.; Christova, Peka; Jerde, Trenton A.; Georgopoulos, Apostolos P.

    2012-01-01

    We used hierarchical tree clustering to derive a functional organizational chart of 52 human cortical areas (26 per hemisphere) from zero-lag correlations calculated between single-voxel, prewhitened, resting-state BOLD fMRI time series in 18 subjects. No special “resting-state networks” were identified. There were four major features in the resulting tree (dendrogram). First, there was a strong clustering of homotopic, left-right hemispheric areas. Second, cortical areas were concatenated in multiple, partially overlapping clusters. Third, the arrangement of the areas revealed a layout that closely resembled the actual layout of the cerebral cortex, namely an orderly progression from anterior to posterior. And fourth, the layout of the cortical areas in the tree conformed to principles of efficient, compact layout of components proposed by Cherniak. Since the tree was derived on the basis of the strength of neural correlations, these results document an orderly relation between functional interactions and layout, i.e., between structure and function. PMID:22973198

  19. Abnormal prefrontal cortex resting state functional connectivity and severity of internet gaming disorder.

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    Jin, Chenwang; Zhang, Ting; Cai, Chenxi; Bi, Yanzhi; Li, Yangding; Yu, Dahua; Zhang, Ming; Yuan, Kai

    2016-09-01

    Internet Gaming Disorder (IGD) among adolescents has become an important public concern and gained more and more attention internationally. Recent studies focused on IGD and revealed brain abnormalities in the IGD group, especially the prefrontal cortex (PFC). However, the role of PFC-striatal circuits in pathology of IGD remains unknown. Twenty-five adolescents with IGD and 21 age- and gender-matched healthy controls were recruited in our study. Voxel-based morphometric (VBM) and functional connectivity analysis were employed to investigate the abnormal structural and resting-state properties of several frontal regions in individuals with online gaming addiction. Relative to healthy comparison subjects, IGD subjects showed significant decreased gray matter volume in PFC regions including the bilateral dorsolateral prefrontal cortex (DLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC) and the right supplementary motor area (SMA) after controlling for age and gender effects. We chose these regions as the seeding areas for the resting-state analysis and found that IGD subjects showed decreased functional connectivity between several cortical regions and our seeds, including the insula, and temporal and occipital cortices. Moreover, significant decreased functional connectivity between some important subcortical regions, i.e., dorsal striatum, pallidum, and thalamus, and our seeds were found in the IGD group and some of those changes were associated with the severity of IGD. Our results revealed the involvement of several PFC regions and related PFC-striatal circuits in the process of IGD and suggested IGD may share similar neural mechanisms with substance dependence at the circuit level.

  20. Dynamic Functional Connectivity States Between the Dorsal and Ventral Sensorimotor Networks Revealed by Dynamic Conditional Correlation Analysis of Resting-State Functional Magnetic Resonance Imaging.

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    Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I

    2017-12-01

    Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.

  1. Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.

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    Hojjati, Seyed Hani; Ebrahimzadeh, Ata; Khazaee, Ali; Babajani-Feremi, Abbas

    2017-04-15

    We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI). Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73.0 years, 28 male) were included in this study. We trained and tested a support vector machine (SVM) to classify MCI-C from MCI-NC using features constructed based on the local and global graph measures. A novel feature selection algorithm was developed and utilized to select an optimal subset of features. Using subset of optimal features in SVM, we classified MCI-C from MCI-NC with an accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve of 91.4%, 83.24%, 90.1%, and 0.95, respectively. Furthermore, results of our statistical analyses were used to identify the affected brain regions in AD. To the best of our knowledge, this is the first study that combines the graph measures (constructed based on rs-fMRI) with machine learning approach and accurately classify MCI-C from MCI-NC. Results of this study demonstrate potential of the proposed approach for early AD diagnosis and demonstrate capability of rs-fMRI to predict conversion from MCI to AD by identifying affected brain regions underlying this conversion. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. White Matter Structural Connectivity Is Not Correlated to Cortical Resting-State Functional Connectivity over the Healthy Adult Lifespan

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    Adrian Tsang

    2017-05-01

    Full Text Available Structural connectivity (SC of white matter (WM and functional connectivity (FC of cortical regions undergo changes in normal aging. As WM tracts form the underlying anatomical architecture that connects regions within resting state networks (RSNs, it is intuitive to expect that SC and FC changes with age are correlated. Studies that investigated the relationship between SC and FC in normal aging are rare, and have mainly compared between groups of elderly and younger subjects. The objectives of this work were to investigate linear SC and FC changes across the healthy adult lifespan, and to define relationships between SC and FC measures within seven whole-brain large scale RSNs. Diffusion tensor imaging (DTI and resting-state functional MRI (rs-fMRI data were acquired from 177 healthy participants (male/female = 69/108; aged 18–87 years. Forty cortical regions across both hemispheres belonging to seven template-defined RSNs were considered. Mean diffusivity (MD, fractional anisotropy (FA, mean tract length, and number of streamlines derived from DTI data were used as SC measures, delineated using deterministic tractography, within each RSN. Pearson correlation coefficients of rs-fMRI-obtained BOLD signal time courses between cortical regions were used as FC measure. SC demonstrated significant age-related changes in all RSNs (decreased FA, mean tract length, number of streamlines; and increased MD, and significant FC decrease was observed in five out of seven networks. Among the networks that showed both significant age related changes in SC and FC, however, SC was not in general significantly correlated with FC, whether controlling for age or not. The lack of observed relationship between SC and FC suggests that measures derived from DTI data that are commonly used to infer the integrity of WM microstructure are not related to the corresponding changes in FC within RSNs. The possible temporal lag between SC and FC will need to be addressed

  3. Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis

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    Yuanyuan Chen

    2017-06-01

    Full Text Available Normal aging is typically characterized by abnormal resting-state functional connectivity (FC, including decreasing connectivity within networks and increasing connectivity between networks, under the assumption that the FC over the scan time was stationary. In fact, the resting-state FC has been shown in recent years to vary over time even within minutes, thus showing the great potential of intrinsic interactions and organization of the brain. In this article, we assumed that the dynamic FC consisted of an intrinsic dynamic balance in the resting brain and was altered with increasing age. Two groups of individuals (N = 36, ages 20–25 for the young group; N = 32, ages 60–85 for the senior group were recruited from the public data of the Nathan Kline Institute. Phase randomization was first used to examine the reliability of the dynamic FC. Next, the variation in the dynamic FC and the energy ratio of the dynamic FC fluctuations within a higher frequency band were calculated and further checked for differences between groups by non-parametric permutation tests. The results robustly showed modularization of the dynamic FC variation, which declined with aging; moreover, the FC variation of the inter-network connections, which mainly consisted of the frontal-parietal network-associated and occipital-associated connections, decreased. In addition, a higher energy ratio in the higher FC fluctuation frequency band was observed in the senior group, which indicated the frequency interactions in the FC fluctuations. These results highly supported the basis of abnormality and compensation in the aging brain and might provide new insights into both aging and relevant compensatory mechanisms.

  4. Resting-state functional connectivity predicts the strength of hemispheric lateralization for language processing in temporal lobe epilepsy and normals.

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    Doucet, Gaëlle E; Pustina, Dorian; Skidmore, Christopher; Sharan, Ashwini; Sperling, Michael R; Tracy, Joseph I

    2015-01-01

    In temporal lobe epilepsy (TLE), determining the hemispheric specialization for language before surgery is critical to preserving a patient's cognitive abilities post-surgery. To date, the major techniques utilized are limited by the capacity of patients to efficiently realize the task. We determined whether resting-state functional connectivity (rsFC) is a reliable predictor of language hemispheric dominance in right and left TLE patients, relative to controls. We chose three subregions of the inferior frontal cortex (pars orbitalis, pars triangularis, and pars opercularis) as the seed regions. All participants performed both a verb generation task and a resting-state fMRI procedure. Based on the language task, we computed a laterality index (LI) for the resulting network. This revealed that 96% of the participants were left-hemisphere dominant, although there remained a large degree of variability in the strength of left lateralization. We tested whether LI correlated with rsFC values emerging from each seed. We revealed a set of regions that was specific to each group. Unique correlations involving the epileptic mesial temporal lobe were revealed for the right and left TLE patients, but not for the controls. Importantly, for both TLE groups, the rsFC emerging from a contralateral seed was the most predictive of LI. Overall, our data depict the broad patterns of rsFC that support strong versus weak left hemisphere language laterality. This project provides the first evidence that rsFC data may potentially be used on its own to verify the strength of hemispheric dominance for language in impaired or pathologic populations. © 2014 Wiley Periodicals, Inc.

  5. Contribution of the resting-state functional connectivity of the contralesional primary sensorimotor cortex to motor recovery after subcortical stroke.

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    Huijuan Xu

    Full Text Available It remains uncertain if the contralesional primary sensorimotor cortex (CL_PSMC contributes to motor recovery after stroke. Here we investigated longitudinal changes in the resting-state functional connectivity (rsFC of the CL_PSMC and their association with motor recovery. Thirteen patients who had experienced subcortical stroke underwent a series of resting-state fMRI and clinical assessments over a period of 1 year at 5 time points, i.e., within the first week, at 2 weeks, 1 month, 3 months, and 1 year after stroke onset. Thirteen age- and gender-matched healthy subjects were recruited as controls. The CL_PSMC was defined as a region centered at the voxel that had greatest activation during hand motion task. The dynamic changes in the rsFCs of the CL_PSMC within the whole brain were evaluated and correlated with the Motricity Index (MI scores. Compared with healthy controls, the rsFCs of the CL_PSMC with the bilateral PSMC were initially decreased, then gradually increased, and finally restored to the normal level 1 year later. Moreover, the dynamic change in the inter-hemispheric rsFC between the bilateral PSMC in these patients was positively correlated with the MI scores. However, the intra-hemispheric rsFC of the CL_PSMC was not correlated with the MI scores. This study shows dynamic changes in the rsFCs of the CL_PSMC after stroke and suggests that the increased inter-hemispheric rsFC between the bilateral PSMC may facilitate motor recovery in stroke patients. However, generalization of our findings is limited by the small sample size of our study and needs to be confirmed.

  6. [Resting-state functional magnetic resonance study of brain function changes after TIPS operation in patients with liver cirrhosis].

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    Liu, C; Wang, H B; Yu, Y Q; Wang, M Q; Zhang, G B; Xu, L Y; Wu, J M

    2016-12-20

    Objective: To investigate the brain function changes in cirrhosis patients after transjugular intrahepatic portosystemic shunt (TIPS), resting-state functional MRI (rs-fMRI) performed and fractional amplitude of low frequency fluctuation (fALFF) was analyzed. Methods: From January 2014 to February 2016, a total of 96 cirrhotic patients from invasive technology department and infection department in the First Affiliated Hospital of Anhui Medical University were selected , the blood ammonia data of 96 cirrhotic patients with TIPS operation in four groups were collected after 1, 3, 6 and 12 month, and all subjects performed rs-fMRI scans. The rs-fMRI data processed with DPARSF and SPM12 softwares, whole-brain fALFF values were calculated, and One-Way analysis of variance , multiple comparison analysis and correlation analysis were performed. Results: There were brain regions with significant function changes in four groups patients with TIPS operation after 1, 3, 6 and 12 month, including bilateral superior temporal gyrus, right middle temportal gyrus , right hippocampus, right island of inferior frontal gyrus, left fusiform gyrus, left olfactory cortex, left orbital superior frontal gyrus (all P brain function areas increased in left olfactory cortex, left inferior temporal gyrus, left fusiform gyrus, left orbital middle frontal gyrus, left putamen, left cerebelum, and decreased in left lingual gyrus; patients in the 6-month follow-up showed that brain function areas increased in left middle temportal gyrus, right supramarginal gyrus, right temporal pole, right central operculum, and decreased in left top edge of angular gyrus, left postcentral gyrus; patients in the 12-month follow-up showed that brain function areas increased in right hippocampus, right middle cingulate gyrus, and decreased in right middle temportal gyrus.Compared with patients in the 3-month follow-up, patients in the 6-month follow-up showed that brain function areas increased in left superior

  7. Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

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    Guihua Jiang

    Full Text Available Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs and 15 age-, gender-matched normal controls (NCs were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

  8. Disrupted topological organization in whole-brain functional networks of heroin-dependent individuals: a resting-state FMRI study.

    Science.gov (United States)

    Jiang, Guihua; Wen, Xue; Qiu, Yingwei; Zhang, Ruibin; Wang, Junjing; Li, Meng; Ma, Xiaofen; Tian, Junzhang; Huang, Ruiwang

    2013-01-01

    Neuroimaging studies have shown that heroin addiction is related to abnormalities in widespread local regions and in the functional connectivity of the brain. However, little is known about whether heroin addiction changes the topological organization of whole-brain functional networks. Seventeen heroin-dependent individuals (HDIs) and 15 age-, gender-matched normal controls (NCs) were enrolled, and the resting-state functional magnetic resonance images (RS-fMRI) were acquired from these subjects. We constructed the brain functional networks of HDIs and NCs, and compared the between-group differences in network topological properties using graph theory method. We found that the HDIs showed decreases in the normalized clustering coefficient and in small-worldness compared to the NCs. Furthermore, the HDIs exhibited significantly decreased nodal centralities primarily in regions of cognitive control network, including the bilateral middle cingulate gyrus, left middle frontal gyrus, and right precuneus, but significantly increased nodal centralities primarily in the left hippocampus. The between-group differences in nodal centralities were not corrected by multiple comparisons suggesting these should be considered as an exploratory analysis. Moreover, nodal centralities in the left hippocampus were positively correlated with the duration of heroin addiction. Overall, our results indicated that disruptions occur in the whole-brain functional networks of HDIs, findings which may be helpful in further understanding the mechanisms underlying heroin addiction.

  9. EEG resting state functional connectivity analysis in children with benign epilepsy with centrotemporal spikes

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    Azeez eAdebimpe

    2016-03-01

    Full Text Available In this study, we investigated changes in functional connectivity of the brain networks in patients with benign epilepsy with centrotemporal spikes compared to healthy controls using high-density EEG data collected under eyes-closed resting state condition. EEG source reconstruction was performed with exact Low Resolution Electromagnetic Tomography (eLORETA. We investigated functional connectivity (FC between 84 Brodmann areas using lagged phase synchronization (LPS in four frequency bands (δ, θ, α, and β. We further computed the network degree, clustering coefficient and efficiency. Compared to controls, patients displayed higher θ and α and lower β lagged phase synchronization values. In these frequency bands, patients were also characterized by less well ordered brain networks exhibiting higher global degrees and efficiencies and lower clustering coefficients. In the beta band, patients exhibited reduced functional segregation and integration due to loss of both local and long-distance functional connections. These findings suggest that benign epileptic brain networks might be functionally disrupted due to their altered functional organization especially in the α and β frequency bands.

  10. Resting-state subcortical functional connectivity in HIV-infected patients on long-term cART

    NARCIS (Netherlands)

    Janssen, M.A.M.; Hinne, M.; Janssen, R.J.; Gerven, M.A.J. van; Steens, S.C.; Góraj, B.M.; Koopmans, P.P.; Kessels, R.P.C.

    2017-01-01

    Despite long-term successful treatment with cART, impairments in cognitive functioning are still being reported in HIV-infected patients. Since changes in cognitive function may be preceded by subtle changes in brain function, neuroimaging techniques, such as resting-state functional magnetic

  11. Abnormal cerebral functional connectivity in esophageal cancer patients with theory of mind deficits in resting state.

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    Cao, Yin; Xiang, JianBo; Qian, Nong; Sun, SuPing; Hu, LiJun; Yuan, YongGui

    2015-01-01

    To explore the function of the default mode network (DMN) in the psychopathological mechanisms of theory of mind deficits in patients with an esophageal cancer concomitant with depression in resting the state. Twenty-five cases of esophageal cancer with theory of mind deficits (test group) that meet the diagnostic criteria of esophageal cancer and neuropsychological tests, including Beck depression inventory, reading the mind in the eyes, and Faux pas, were included, Another 25 cases of esophageal cancer patients but without theory of mind deficits (control group) were enrolled. Each patient completed a resting-state functional magnetic resonance imaging. The functional connectivity intensities within the cerebral regions in the DMN of all the enrolled patients were analyzed. The results of each group were compared. The functional connectivity of the bilateral prefrontal central region with the precuneus, bilateral posterior cingulate gyrus and bilateral ventral anterior cingulate gyrus in the patients of the test group were all reduced significantly (P theory of mind deficits. The theory of mind deficits might have an important function in the pathogenesis of esophageal cancer.

  12. Cerebro-cerebellar Resting-State Functional Connectivity in Children and Adolescents with Autism Spectrum Disorder.

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    Khan, Amanda J; Nair, Aarti; Keown, Christopher L; Datko, Michael C; Lincoln, Alan J; Müller, Ralph-Axel

    2015-11-01

    The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available. We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal). There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group. Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  13. Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment.

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    Yi, Li-Ye; Liang, Xia; Liu, Da-Ming; Sun, Bo; Ying, Sun; Yang, Dong-Bo; Li, Qing-Bin; Jiang, Chuan-Lu; Han, Ying

    2015-10-01

    Neuroimaging studies have demonstrated both structural and functional abnormalities in widespread brain regions in patients with subcortical vascular mild cognitive impairment (svMCI). However, whether and how these changes alter functional brain network organization remains largely unknown. We recruited 21 patients with svMCI and 26 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging scans. Graph theory-based network analyses were used to investigate alterations in the topological organization of functional brain networks. Compared with the HC individuals, the patients with svMCI showed disrupted global network topology with significantly increased path length and modularity. Modular structure was also impaired in the svMCI patients with a notable rearrangement of the executive control module, where the parietal regions were split out and grouped as a separate module. The svMCI patients also revealed deficits in the intra- and/or intermodule connectivity of several brain regions. Specifically, the within-module degree was decreased in the middle cingulate gyrus while it was increased in the left anterior insula, medial prefrontal cortex and cuneus. Additionally, increased intermodule connectivity was observed in the inferior and superior parietal gyrus, which was associated with worse cognitive performance in the svMCI patients. Together, our results indicate that svMCI patients exhibit dysregulation of the topological organization of functional brain networks, which has important implications for understanding the pathophysiological mechanism of svMCI. © 2015 John Wiley & Sons Ltd.

  14. Gender differences in brain regional homogeneity of healthy subjects after normal sleep and after sleep deprivation: a resting-state fMRI study.

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    Dai, Xi-Jian; Gong, Hong-Han; Wang, Yi-Xiang; Zhou, Fu-Qing; Min, You-Jiang; Zhao, Feng; Wang, Si-Yong; Liu, Bi-Xia; Xiao, Xiang-Zuo

    2012-06-01

    To explore the gender differences of brain regional homogeneity (ReHo) in healthy subjects during the resting-state, after normal sleep, and after sleep deprivation (SD) using functional magnetic resonance imaging (fMRI) and the ReHo method. Sixteen healthy subjects (eight males and eight females) each underwent the resting-state fMRI exams twice, i.e., once after normal sleep and again after 24h's SD. According to the gender and sleep, 16 subjects were all measured twice and divided into four groups: the male control group (MC), female control group (FC), male SD group (MSD), and female SD group (FSD). The ReHo method was used to calculate and analyze the data, SPM5 software was used to perform a two-sample T-test and a two-pair T-test with a P value right paracentral lobule (BA3/6), but in no obviously lower regions. Compared with the FC, the FSD showed significantly higher ReHo in bilateral parietal lobes (BA2/3), bilateral vision-related regions of occipital lobes (BA17/18/19), right frontal lobe (BA4/6), and lower ReHo in the right frontal lobe. Compared with the FC, the MC showed significantly higher ReHo in the left occipital lobe (BA18/19), and left temporal lobe (BA21), left frontal lobe, and lower ReHo in the right insula and in the left parietal lobe. Compared with the FSD, the MSD showed significantly higher ReHo in the left cerebellum posterior lobe (uvula/declive of vermis), left parietal lobe, and bilateral frontal lobes, and lower ReHo in the right occipital lobe (BA17) and right frontal lobe (BA4). The differences of brain activity in the resting state can be widely found not only between the control and SD group in a same gender group, but also between the male group and female group. Thus, we should take the gender differences into consideration in future fMRI studies, especially the treatment of brain-related diseases (e.g., depression). Copyright © 2012 Elsevier B.V. All rights reserved.

  15. Alteration in intrinsic and extrinsic functional connectivity of resting state networks associated with subclinical hypothyroid.

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    Kumar, Mukesh; Modi, Shilpi; Rana, Poonam; Kumar, Pawan; Kanwar, Ratnesh; Sekhri, Tarun; D'souza, Maria; Khushu, Subash

    2018-03-05

    Subclinical hypothyroidism (SCH) is characterized by mild elevation of thyroid stimulating hormone (TSH) (range 5-10 μIU/ml) and normal free triiodothyronine (FT3) and free thyroxine (FT4). The cognitive function impairment is well known in thyroid disorders such as hypothyroidism and hyperthyroidism, but little is known about deficits in brain functions in SCH subjects. Also, whether hormone-replacement treatment is necessary or not in SCH subjects is still debatable. In order to have an insight into the cognition of SCH subjects, intrinsic and extrinsic functional connectivity (FC) of the resting state networks (RSNs) was studied. For resting state data analysis we used an unbiased, data-driven approach based on Independent Component Analysis (ICA) and dual-regression that can emphasize widespread changes in FC without restricting to a set of predefined seeds. 28 SCH subjects and 28 matched healthy controls (HC) participated in the study. RSN analysis showed significantly decreased intrinsic FC in somato-motor network (SMN) and right fronto-parietal attention network (RAN) and increased intrinsic FC in default mode network (DMN) in SCH subjects as compared to control subjects. The reduced intrinsic FC in the SMN and RAN suggests neuro-cognitive alterations in SCH subjects in the corresponding functions which were also evident from the deficit in the neuropsychological performance of the SCH subjects on behavioural tests such as digit span, delayed recall, visual retention, recognition, Bender Gestalt and Mini-Mental State Examination (MMSE). We also found a significant reduction in extrinsic network FC between DMN and RAN; SMN and posterior default mode network (PDMN); and increased extrinsic FC between SMN and anterior default mode network (ADMN) in SCH subjects as compared to controls. An altered extrinsic FC in SCH suggests functional reorganization in response to neurological disruption. The partial correlation analysis between intrinsic and extrinsic RSNs

  16. Exercise alters resting state functional connectivity of motor circuits in Parkinsonian rats

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    Wang, Zhuo; Guo, Yumei; Myers, Kalisa G.; Heintz, Ryan; Peng, Yu-Hao; Maarek, Jean-Michel I.; Holschneider, Daniel P.

    2014-01-01

    Few studies have examined changes in functional connectivity after long-term aerobic exercise. We examined the effects of 4 weeks of forced running wheel exercise on the resting-state functional connectivity (rsFC) of motor circuits of rats subjected to bilateral 6-hydroxydopamine lesion of the dorsal striatum. Our results showed substantial similarity between lesion-induced changes in rsFC in the rats and alterations in rsFC reported in Parkinson’s disease subjects, including disconnection of the dorsolateral striatum. Exercise in lesioned rats resulted in: (a) normalization of many of the lesion-induced alterations in rsFC, including reintegration of the dorsolateral striatum into the motor network; (b) emergence of the ventrolateral striatum as a new broadly connected network hub; (c) increased rsFC among the motor cortex, motor thalamus, basal ganglia, and cerebellum. Our results showed for the first time that long-term exercise training partially reversed lesion-induced alterations in rsFC of the motor circuits, and in addition enhanced functional connectivity in specific motor pathways in the Parkinsonian rats, which could underlie recovery in motor functions observed in these rats. PMID:25219465

  17. Connectomic markers of symptom severity in sport-related concussion: Whole-brain analysis of resting-state fMRI.

    Science.gov (United States)

    Churchill, Nathan W; Hutchison, Michael G; Graham, Simon J; Schweizer, Tom A

    2018-01-01

    Concussion is associated with significant adverse effects within the first week post-injury, including physical complaints and altered cognition, sleep and mood. It is currently unknown whether these subjective disturbances have reliable functional brain correlates. Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to measure functional connectivity of individuals after traumatic brain injury, but less is known about the relationship between functional connectivity and symptom assessments after a sport concussion. In this study, rs-fMRI was used to evaluate whole-brain functional connectivity for seventy (70) university-level athletes, including 35 with acute concussion and 35 healthy matched controls. Univariate analyses showed that greater symptom severity was mainly associated with lower pairwise connectivity in frontal, temporal and insular regions, along with higher connectivity in a sparser set of cerebellar regions. A novel multivariate approach also extracted two components that showed reliable covariation with symptom severity: (1) a network of frontal, temporal and insular regions where connectivity was negatively correlated with symptom severity (replicating the univariate findings); and (2) a network with anti-correlated elements of the default-mode network and sensorimotor system, where connectivity was positively correlated with symptom severity. These findings support the presence of connectomic signatures of symptom complaints following a sport-related concussion, including both increased and decreased functional connectivity within distinct functional brain networks.

  18. A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia

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    Jessica A Turner

    2013-08-01

    Full Text Available Background. This multi-site study compares resting state fMRI amplitude of low frequency fluctuations (ALFF and fractional ALFF (fALFF between patients with schizophrenia (SZ and healthy controls (HC. Methods. Eyes-closed resting fMRI scans (5:38 minutes; n=306, 146 SZ were collected from 6 Siemens 3T scanners and one GE 3T scanner. Imaging data were pre-processed using an SPM pipeline. Power in the low frequency band (0.01 to 0.08 Hz was calculated both for the original pre-processed data as well as for the pre-processed data after regressing out the six rigid-body motion parameters, mean white matter and CSF signals. Both original and regressed ALFF and fALFF measures were modeled with site, diagnosis, age, and diagnosis × age interactions. Results. Regressing out motion and non-gray matter signals significantly decreased fALFF throughout the brain as well as ALFF in the cortical edge, but significantly increased ALFF in subcortical regions. Regression had little effect on site, age, and diagnosis effects on ALFF, other than to reduce diagnosis effects in subcortical regions. There were significant effects of site across the brain in all the analyses, largely due to vendor differences. HC showed greater ALFF in the occipital, posterior parietal, and superior temporal lobe, while SZ showed smaller clusters of greater ALFF in the frontal and temporal/insular regions as well as in the caudate, putamen, and hippocampus. HC showed greater fALFF compared with SZ in all regions, though subcortical differences were only significant for original fALFF. Conclusions. SZ show greater eyes-closed resting state low frequency power in frontal cortex, and less power in posterior lobes than do HC; fALFF, however, is lower in SZ than HC throughout the cortex. These effects are robust to multi-site variability. Regressing out physiological noise signals significantly affects both total and fractional ALFF measures, but does not affect the pattern of case

  19. Visibility graphs for fMRI data: Multiplex temporal graphs and their modulations across resting-state networks

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    Speranza Sannino

    2017-10-01

    Full Text Available Visibility algorithms are a family of methods that map time series into graphs, such that the tools of graph theory and network science can be used for the characterization of time series. This approach has proved a convenient tool, and visibility graphs have found applications across several disciplines. Recently, an approach has been proposed to extend this framework to multivariate time series, allowing a novel way to describe collective dynamics. Here we test their application to fMRI time series, following two main motivations, namely that (a this approach allows vs to simultaneously capture and process relevant aspects of both local and global dynamics in an easy and intuitive way, and (b this provides a suggestive bridge between time series and network theory that nicely fits the consolidating field of network neuroscience. Our application to a large open dataset reveals differences in the similarities of temporal networks (and thus in correlated dynamics across resting-state networks, and gives indications that some differences in brain activity connected to psychiatric disorders could be picked up by this approach. Here we present the first application of multivariate visibility graphs to fMRI data. Visibility graphs are a way to represent a time series as a temporal network, evidencing specific aspects of its dynamics, such as extreme events. Multivariate time series, as those encountered in neuroscience, and in fMRI in particular, can be seen as a multiplex network, in which each layer represents a time series (a region of interest in the brain in our case. Here we report the method, we describe some relevant aspects of its application to BOLD time series, and we discuss the analogies and differences with existing methods. Finally, we present an application to a high-quality, publicly available dataset, containing healthy subjects and psychotic patients, and we discuss our findings. All the code to reproduce the analyses and the

  20. Differences in hemispherical thalamo-cortical causality analysis during resting-state fMRI.

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    Anwar, Abdul Rauf; Muthalib, Makii; Perrey, Stephane; Wolff, Stephan; Deuschl, Guunther; Heute, Ulrich; Muthuraman, Muthuraman

    2014-01-01

    Thalamus is a very important part of the human brain. It has been reported to act as a relay for the messaging taking place between the cortical and sub-cortical regions of the brain. In the present study, we analyze the functional network between both hemispheres of the brain with the focus on thalamus. We used conditional Granger causality (CGC) and time-resolved partial directed coherence (tPDC) to investigate the functional connectivity. Results of CGC analysis revealed the asymmetry between connection strengths of the bilateral thalamus. Upon testing the functional connectivity of the default-mode network (DMN) at low-frequency fluctuations (LFF) and comparing coherence vectors using Spearman's rank correlation, we found that thalamus is a better source for the signals directed towards the contralateral regions of the brain, however, when thalamus acts as sink, it is a better sink for signals generated from ipsilateral regions of the brain.

  1. A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia

    Directory of Open Access Journals (Sweden)

    Gloria eCastellazzi

    2014-07-01

    Full Text Available In resting state fMRI (rs-fMRI, only functional connectivity (FC reductions in the default mode network (DMN are normally reported as a biomarker for Alzheimer's disease (AD. In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI, compared to healthy controls (HC. Resting state networks (RSNs were studied in 14 AD (70±6 years, 12 MCI (74±6 years and 16 HC (69±5 years. RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC, putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN, lateral visual network (LVN, basal ganglia network (BGN, cerebellar network (CBLN, and the anterior insula network (AIN. Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p< 0.001 with psychological scores, in particular MMSE and attention/memory tasks. In conclusion, this analysis revealed that the DMN was affected by remarkable FC increases, that FC alterations extended over several RSNs, that derangement of functional relationships between multiple areas occurred already in the early stages of dementia. These results warrant future work to verify whether these represent compensatory mechanisms that exploit a pre-existing neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.

  2. Abnormal Functional Connectivity of Resting State Network Detection Based on Linear ICA Analysis in Autism Spectrum Disorder.