Altered brain connectivity in sagittal craniosynostosis.

Science.gov (United States)

Beckett, Joel S; Brooks, Eric D; Lacadie, Cheryl; Vander Wyk, Brent; Jou, Roger J; Steinbacher, Derek M; Constable, R Todd; Pelphrey, Kevin A; Persing, John A

2014-06-01

Sagittal nonsyndromic craniosynostosis (sNSC) is the most common form of NSC. The condition is associated with a high prevalence (> 50%) of deficits in executive function. The authors employed diffusion tensor imaging (DTI) and functional MRI to evaluate whether hypothesized structural and functional connectivity differences underlie the observed neurocognitive morbidity of sNSC. Using a 3-T Siemens Trio MRI system, the authors collected DTI and resting-state functional connectivity MRI data in 8 adolescent patients (mean age 12.3 years) with sNSC that had been previously corrected via total vault cranioplasty and 8 control children (mean age 12.3 years) without craniosynostosis. Data were analyzed using the FMRIB Software Library and BioImageSuite. Analyses of the DTI data revealed white matter alterations approaching statistical significance in all supratentorial lobes. Statistically significant group differences (sNSC right supramarginal gyrus. Analysis of the resting-state seed in relation to whole-brain data revealed significant increases in negative connectivity (anticorrelations) of Brodmann area 8 to the prefrontal cortex (Montreal Neurological Institute [MNI] center of mass coordinates [x, y, z]: -6, 53, 6) and anterior cingulate cortex (MNI coordinates 6, 43, 14) in the sNSC group relative to controls. Furthermore, in the sNSC patients versus controls, the Brodmann area 7, 39, and 40 seed had decreased connectivity to left angular gyrus (MNI coordinates -31, -61, 34), posterior cingulate cortex (MNI coordinates 13, -52, 18), precuneus (MNI coordinates 10, -55, 54), left and right parahippocampus (MNI coordinates -13, -52, 2 and MNI coordinates 11, -50, 2, respectively), lingual (MNI coordinates -11, -86, -10), and fusiform gyri (MNI coordinates -30, -79, -18). Intrinsic connectivity analysis also revealed altered connectivity between central nodes in the default mode network in sNSC relative to controls; the left and right posterior cingulate cortices

Brain Connectivity and Visual Attention

Science.gov (United States)

Parks, Emily L.

2013-01-01

Abstract Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures. PMID:23597177

Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

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Ni Shu

2015-01-01

Full Text Available The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain.

Financial literacy is associated with medial brain region functional connectivity in old age.

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Han, S Duke; Boyle, Patricia A; Yu, Lei; Fleischman, Debra A; Arfanakis, Konstantinos; Leurgans, Sue; Bennett, David A

2014-01-01

Financial literacy refers to the ability to access and utilize financial information in ways that promote better outcomes. In old age, financial literacy has been associated with a wide range of positive characteristics; however, the neural correlates remain unclear. Recent work has suggested greater co-activity between anterior-posterior medial brain regions is associated with better brain functioning. We hypothesized financial literacy would be associated with this pattern. We assessed whole-brain functional connectivity to a posterior cingulate cortex (PCC) seed region of interest (ROI) in 138 participants of the Rush Memory and Aging Project. Results revealed financial literacy was associated with greater functional connectivity between the PCC and three regions: the right ventromedial prefrontal cortex (vmPFC), the left postcentral gyrus, and the right precuneus. Results also revealed financial literacy was associated negatively with functional connectivity between the PCC and left caudate. Post hoc analyses showed the PCC-vmPFC relationship accounted for the most variance in a regression model adjusted for all four significant functional connectivity relationships, demographic factors, and global cognition. These findings provide information on the neural mechanisms associated with financial literacy in old age. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

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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

Violence-related content in video game may lead to functional connectivity changes in brain networks as revealed by fMRI-ICA in young men.

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Zvyagintsev, M; Klasen, M; Weber, R; Sarkheil, P; Esposito, F; Mathiak, K A; Schwenzer, M; Mathiak, K

2016-04-21

In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players' behavior. In a previous study, a violence-related version of the racing game "Carmageddon TDR2000" increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game. Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks. The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network. Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Laterality patterns of brain functional connectivity: gender effects.

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Tomasi, Dardo; Volkow, Nora D

2012-06-01

Lateralization of brain connectivity may be essential for normal brain function and may be sexually dimorphic. Here, we study the laterality patterns of short-range (implicated in functional specialization) and long-range (implicated in functional integration) connectivity and the gender effects on these laterality patterns. Parallel computing was used to quantify short- and long-range functional connectivity densities in 913 healthy subjects. Short-range connectivity was rightward lateralized and most asymmetrical in areas around the lateral sulcus, whereas long-range connectivity was rightward lateralized in lateral sulcus and leftward lateralizated in inferior prefrontal cortex and angular gyrus. The posterior inferior occipital cortex was leftward lateralized (short- and long-range connectivity). Males had greater rightward lateralization of brain connectivity in superior temporal (short- and long-range), inferior frontal, and inferior occipital cortices (short-range), whereas females had greater leftward lateralization of long-range connectivity in the inferior frontal cortex. The greater lateralization of the male's brain (rightward and predominantly short-range) may underlie their greater vulnerability to disorders with disrupted brain asymmetries (schizophrenia, autism).

Multivariate Heteroscedasticity Models for Functional Brain Connectivity

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Christof Seiler

2017-12-01

Full Text Available Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI. We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Brain connectivity in normally developing children and adolescents.

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Khundrakpam, Budhachandra S; Lewis, John D; Zhao, Lu; Chouinard-Decorte, François; Evans, Alan C

2016-07-01

The developing human brain undergoes an astonishing sequence of events that continuously shape the structural and functional brain connectivity. Distinct regional variations in the timelines of maturational events (synaptogenesis and synaptic pruning) occurring at the synaptic level are reflected in brain measures at macroscopic resolution (cortical thickness and gray matter density). Interestingly, the observed brain changes coincide with cognitive milestones suggesting that the changing scaffold of brain circuits may subserve cognitive development. Recent advances in connectivity analysis propelled by graph theory have allowed, on one hand, the investigation of maturational changes in global organization of structural and functional brain networks; and on the other hand, the exploration of specific networks within the context of global brain networks. An emerging picture from several connectivity studies is a system-level rewiring that constantly refines the connectivity of the developing brain. Copyright © 2016 Elsevier Inc. All rights reserved.

Structural Graphical Lasso for Learning Mouse Brain Connectivity

KAUST Repository

Yang, Sen; Sun, Qian; Ji, Shuiwang; Wonka, Peter; Davidson, Ian; Ye, Jieping

2015-01-01

Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability

Neuroinformatics of the Allen Mouse Brain Connectivity Atlas.

Science.gov (United States)

Kuan, Leonard; Li, Yang; Lau, Chris; Feng, David; Bernard, Amy; Sunkin, Susan M; Zeng, Hongkui; Dang, Chinh; Hawrylycz, Michael; Ng, Lydia

2015-02-01

The Allen Mouse Brain Connectivity Atlas is a mesoscale whole brain axonal projection atlas of the C57Bl/6J mouse brain. Anatomical trajectories throughout the brain were mapped into a common 3D space using a standardized platform to generate a comprehensive and quantitative database of inter-areal and cell-type-specific projections. This connectivity atlas has several desirable features, including brain-wide coverage, validated and versatile experimental techniques, a single standardized data format, a quantifiable and integrated neuroinformatics resource, and an open-access public online database (http://connectivity.brain-map.org/). Meaningful informatics data quantification and comparison is key to effective use and interpretation of connectome data. This relies on successful definition of a high fidelity atlas template and framework, mapping precision of raw data sets into the 3D reference framework, accurate signal detection and quantitative connection strength algorithms, and effective presentation in an integrated online application. Here we describe key informatics pipeline steps in the creation of the Allen Mouse Brain Connectivity Atlas and include basic application use cases. Copyright © 2014 Elsevier Inc. All rights reserved.

A Multimodal Approach for Determining Brain Networks by Jointly Modeling Functional and Structural Connectivity

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Wenqiong eXue

2015-02-01

Full Text Available Recent innovations in neuroimaging technology have provided opportunities for researchers to investigate connectivity in the human brain by examining the anatomical circuitry as well as functional relationships between brain regions. Existing statistical approaches for connectivity generally examine resting-state or task-related functional connectivity (FC between brain regions or separately examine structural linkages. As a means to determine brain networks, we present a unified Bayesian framework for analyzing FC utilizing the knowledge of associated structural connections, which extends an approach by Patel et al.(2006a that considers only functional data. We introduce an FC measure that rests upon assessments of functional coherence between regional brain activity identified from functional magnetic resonance imaging (fMRI data. Our structural connectivity (SC information is drawn from diffusion tensor imaging (DTI data, which is used to quantify probabilities of SC between brain regions. We formulate a prior distribution for FC that depends upon the probability of SC between brain regions, with this dependence adhering to structural-functional links revealed by our fMRI and DTI data. We further characterize the functional hierarchy of functionally connected brain regions by defining an ascendancy measure that compares the marginal probabilities of elevated activity between regions. In addition, we describe topological properties of the network, which is composed of connected region pairs, by performing graph theoretic analyses. We demonstrate the use of our Bayesian model using fMRI and DTI data from a study of auditory processing. We further illustrate the advantages of our method by comparisons to methods that only incorporate functional information.

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.

Voxel Scale Complex Networks of Functional Connectivity in the Rat Brain: Neurochemical State Dependence of Global and Local Topological Properties

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Adam J. Schwarz

2012-01-01

Full Text Available Network analysis of functional imaging data reveals emergent features of the brain as a function of its topological properties. However, the brain is not a homogeneous network, and the dependence of functional connectivity parameters on neuroanatomical substrate and parcellation scale is a key issue. Moreover, the extent to which these topological properties depend on underlying neurochemical changes remains unclear. In the present study, we investigated both global statistical properties and the local, voxel-scale distribution of connectivity parameters of the rat brain. Different neurotransmitter systems were stimulated by pharmacological challenge (d-amphetamine, fluoxetine, and nicotine to discriminate between stimulus-specific functional connectivity and more general features of the rat brain architecture. Although global connectivity parameters were similar, mapping of local connectivity parameters at high spatial resolution revealed strong neuroanatomical dependence of functional connectivity in the rat brain, with clear differentiation between the neocortex and older brain regions. Localized foci of high functional connectivity independent of drug challenge were found in the sensorimotor cortices, consistent with the high neuronal connectivity in these regions. Conversely, the topological properties and node roles in subcortical regions varied with neurochemical state and were dependent on the specific dynamics of the different functional processes elicited.

Whole-brain functional connectivity predicted by indirect structural connections

DEFF Research Database (Denmark)

Røge, Rasmus; Ambrosen, Karen Marie Sandø; Albers, Kristoffer Jon

2017-01-01

Modern functional and diffusion magnetic resonance imaging (fMRI and dMRI) provide data from which macro-scale networks of functional and structural whole brain connectivity can be estimated. Although networks derived from these two modalities describe different properties of the human brain, the...

Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

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Jin, Changfeng; Jia, Hao; Lanka, Pradyumna; Rangaprakash, D; Li, Lingjiang; Liu, Tianming; Hu, Xiaoping; Deshpande, Gopikrishna

2017-09-01

Using resting-state functional magnetic resonance imaging, we test the hypothesis that subjects with post-traumatic stress disorder (PTSD) are characterized by reduced temporal variability of brain connectivity compared to matched healthy controls. Specifically, we test whether PTSD is characterized by elevated static connectivity, coupled with decreased temporal variability of those connections, with the latter providing greater sensitivity toward the pathology than the former. Static functional connectivity (FC; nondirectional zero-lag correlation) and static effective connectivity (EC; directional time-lagged relationships) were obtained over the entire brain using conventional models. Dynamic FC and dynamic EC were estimated by letting the conventional models to vary as a function of time. Statistical separation and discriminability of these metrics between the groups and their ability to accurately predict the diagnostic label of a novel subject were ascertained using separate support vector machine classifiers. Our findings support our hypothesis that PTSD subjects have stronger static connectivity, but reduced temporal variability of connectivity. Further, machine learning classification accuracy obtained with dynamic FC and dynamic EC was significantly higher than that obtained with static FC and static EC, respectively. Furthermore, results also indicate that the ease with which brain regions engage or disengage with other regions may be more sensitive to underlying pathology than the strength with which they are engaged. Future studies must examine whether this is true only in the case of PTSD or is a general organizing principle in the human brain. Hum Brain Mapp 38:4479-4496, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

On development of functional brain connectivity in the young brain

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G.E. Anna-Jasmijn eHoff

2013-10-01

Full Text Available Our brain is a complex network of structurally and functionally interconnected regions, shaped to efficiently process and integrate information. The development from a brain equipped with basic functionalities to an efficient network facilitating complex behavior starts during gestation and continues into adulthood. Resting-state functional MRI (rs-fMRI enables the examination of developmental aspects of functional connectivity and functional brain networks. This review will discuss changes observed in the developing brain on the level of network functional connectivity (FC from a gestational age of 20 weeks onwards. We discuss findings of resting-state fMRI studies showing that functional network development starts during gestation, creating a foundation for each of the resting-state networks to be established. Visual and sensorimotor areas are reported to develop first, with other networks, at different rates, increasing both in network connectivity and size over time. Reaching childhood, marked fine-tuning and specialization takes place in the regions necessary for higher-order cognitive functions.

Supervised hub-detection for brain connectivity

DEFF Research Database (Denmark)

Kasenburg, Niklas; Liptrot, Matthew George; Reislev, Nina Linde

2016-01-01

, but can smooth discriminative signals in the population, degrading predictive performance. We present a novel hub-detection optimized for supervised learning that both clusters network nodes based on population level variation in connectivity and also takes the learning problem into account. The found......A structural brain network consists of physical connections between brain regions. Brain network analysis aims to find features associated with a parameter of interest through supervised prediction models such as regression. Unsupervised preprocessing steps like clustering are often applied...... hubs are a low-dimensional representation of the network and are chosen based on predictive performance as features for a linear regression. We apply our method to the problem of finding age-related changes in structural connectivity. We compare our supervised hub-detection (SHD) to an unsupervised hub...

Measurements of brain microstructure and connectivity with diffusion MRI

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Ching-Po Lin

2011-12-01

Full Text Available By probing direction-dependent diffusivity of water molecules, diffusion MRI has shown its capability to reflect the microstructural tissue status and to estimate the neural orientation and pathways in the living brain. This approach has supplied novel insights into in-vivo human brain connections. By detecting the connection patterns, anatomical architecture and structural integrity between cortical regions or subcortical nuclei in the living human brain can be easily identified. It thus opens a new window on brain connectivity studies and disease processes. During the past years, there is a growing interest in exploring the connectivity patterns of the human brain. Specifically, the utilities of noninvasive neuroimaging data and graph theoretical analysis have provided important insights into the anatomical connections and topological pattern of human brain structural networks in vivo. Here, we review the progress of this important technique and the recent methodological and application studies utilizing graph theoretical approaches on brain structural networks with structural MRI and diffusion MRI.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback.

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Ramot, Michal; Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

2017-09-16

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants' awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

Science.gov (United States)

Kimmich, Sara; Gonzalez-Castillo, Javier; Roopchansingh, Vinai; Popal, Haroon; White, Emily; Gotts, Stephen J; Martin, Alex

2017-01-01

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity. Desired network connectivity patterns were reinforced in real-time, without participants’ awareness of the training taking place. This training regimen produced large, significant long-term changes in correlations at the network level, and whole brain analysis revealed that the greatest changes were focused on the areas being trained. These changes were not found in the control group. Moreover, changes in ASD resting state connectivity following the training were correlated to changes in behavior, suggesting that neurofeedback can be used to directly alter complex, clinically relevant network connectivity patterns. PMID:28917059

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

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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.

Decreased resting functional connectivity after traumatic brain injury in the rat.

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Asht Mangal Mishra

Full Text Available Traumatic brain injury (TBI contributes to about 10% of acquired epilepsy. Even though the mechanisms of post-traumatic epileptogenesis are poorly known, a disruption of neuronal networks predisposing to altered neuronal synchrony remains a viable candidate mechanism. We tested a hypothesis that resting state BOLD-fMRI functional connectivity can reveal network abnormalities in brain regions that are connected to the lesioned cortex, and that these changes associate with functional impairment, particularly epileptogenesis. TBI was induced using lateral fluid-percussion injury in seven adult male Sprague-Dawley rats followed by functional imaging at 9.4T 4 months later. As controls we used six sham-operated animals that underwent all surgical operations but were not injured. Electroencephalogram (EEG-functional magnetic resonance imaging (fMRI was performed to measure resting functional connectivity. A week after functional imaging, rats were implanted with bipolar skull electrodes. After recovery, rats underwent pentyleneterazol (PTZ seizure-susceptibility test under EEG. For image analysis, four pairs of regions of interests were analyzed in each hemisphere: ipsilateral and contralateral frontal and parietal cortex, hippocampus, and thalamus. High-pass and low-pass filters were applied to functional imaging data. Group statistics comparing injured and sham-operated rats and correlations over time between each region were calculated. In the end, rats were perfused for histology. None of the rats had epileptiform discharges during functional imaging. PTZ-test, however revealed increased seizure susceptibility in injured rats as compared to controls. Group statistics revealed decreased connectivity between the ipsilateral and contralateral parietal cortex and between the parietal cortex and hippocampus on the side of injury as compared to sham-operated animals. Injured animals also had abnormal negative connectivity between the ipsilateral and

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

Whole brain functional connectivity in clinically isolated syndrome without conventional brain MRI lesions

International Nuclear Information System (INIS)

Liu, Yaou; Dai, Zhengjia; Duan, Yunyun; Huang, Jing; Ren, Zhuoqiong; Li, Kuncheng; Liu, Zheng; Dong, Huiqing; Shu, Ni; He, Yong; Vrenken, Hugo; Wattjes, Mike P.; Barkhof, Frederik

2016-01-01

To investigate brain functional connectivity (FC) alterations in patients with clinically isolated syndromes (CIS) presenting without conventional brain MRI lesions, and to identify the FC differences between the CIS patients who converted to multiple sclerosis (MS) and those not converted during a 5-year follow-up. We recruited 20 CIS patients without conventional brain lesions, 28 patients with MS and 28 healthy controls (HC). Normalized voxel-based functional connectivity strength (nFCS) was determined using resting-state fMRI (R-fMRI) and compared among groups. Furthermore, 5-years clinical follow-up of the CIS patients was performed to examine the differences in nFCS between converters and non-converters. Compared to HC, CIS patients showed significantly decreased nFCS in the visual areas and increased nFCS in several brain regions predominately in the temporal lobes. MS patients revealed more widespread higher nFCS especially in deep grey matter (DGM), compared to CIS and HC. In the four CIS patients converting to MS, significantly higher nFCS was found in right anterior cingulate gyrus (ACC) and fusiform gyrus (FG), compared to non-converted patients. We demonstrated both functional impairment and compensation in CIS by R-fMRI. nFCS alteration in ACC and FG seems to occur in CIS patients at risk of developing MS. (orig.)

Altered whole-brain connectivity in albinism.

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Welton, Thomas; Ather, Sarim; Proudlock, Frank A; Gottlob, Irene; Dineen, Robert A

2017-02-01

Albinism is a group of congenital disorders of the melanin synthesis pathway. Multiple ocular, white matter and cortical abnormalities occur in albinism, including a greater decussation of nerve fibres at the optic chiasm, foveal hypoplasia and nystagmus. Despite this, visual perception is largely preserved. It was proposed that this may be attributable to reorganisation among cerebral networks, including an increased interhemispheric connectivity of the primary visual areas. A graph-theoretic model was applied to explore brain connectivity networks derived from resting-state functional and diffusion-tensor magnetic resonance imaging data in 23 people with albinism and 20 controls. They tested for group differences in connectivity between primary visual areas and in summary network organisation descriptors. Main findings were supplemented with analyses of control regions, brain volumes and white matter microstructure. Significant functional interhemispheric hyperconnectivity of the primary visual areas in the albinism group were found (P = 0.012). Tests of interhemispheric connectivity based on the diffusion-tensor data showed no significant group difference (P = 0.713). Second, it was found that a range of functional whole-brain network metrics were abnormal in people with albinism, including the clustering coefficient (P = 0.005), although this may have been driven partly by overall differences in connectivity, rather than reorganisation. Based on the results, it was suggested that changes occur in albinism at the whole-brain level, and not just within the visual processing pathways. It was proposed that their findings may reflect compensatory adaptations to increased chiasmic decussation, foveal hypoplasia and nystagmus. Hum Brain Mapp 38:740-752, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Brain functional connectivity and cognition in mild traumatic brain injury

International Nuclear Information System (INIS)

Xiong, K.L.; Zhang, Y.L.; Chen, H.; Zhang, J.N.; Zhang, Y.; Qiu, M.G.

2016-01-01

The aim of this study was to analyze brain functional connectivity and its relationship to cognition in patients with mild traumatic brain injury (mTBI). Twenty-five patients with mTBI and 25 healthy control subjects were studied using resting-state functional MRI (rs-fMRI). Amplitudes of low-frequency fluctuations (ALFFs) and functional connectivity (FC) were calculated and correlated with cognition. Compared with the normal control group, the mTBI patients showed a significant decrease in working memory index (WMI) and processing speed index (PSI), as well as significantly decreased ALFFs in the cingulate gyrus, the middle frontal gyrus and superior frontal gyrus. In contrast, the mTBI patients' ALFFs in the left middle occipital gyrus, the left precuneus, and lingual gyrus increased. Additionally, FC significantly decreased in the thalamus, caudate nucleus, and right hippocampus in the mTBI patients. Statistical analysis further showed a significant positive correlation between the ALFF in the cingulate gyrus and the WMI (R 2 = 0.423, P < 0.05) and a significant positive correlation between the FC in the left thalamus and left middle frontal gyrus and the WMI (R 2 = 0.381, P < 0.05). rs-fMRI can reveal the functional state of the brain in patients with mTBI. This finding differed from observations of the normal control group and was significantly associated with clinical cognitive dysfunction. Therefore, rs-fMRI offers an objective imaging modality for treatment planning and prognosis assessment in patients with mTBI. (orig.)

Brain functional connectivity changes in children that differ in impulsivity temperamental trait

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Alberto eInuggi

2014-05-01

Full Text Available Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents’ report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior.

Brain functional connectivity changes in children that differ in impulsivity temperamental trait.

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Inuggi, Alberto; Sanz-Arigita, Ernesto; González-Salinas, Carmen; Valero-García, Ana V; García-Santos, Jose M; Fuentes, Luis J

2014-01-01

Impulsivity is a core personality trait forming part of normal behavior and contributing to adaptive functioning. However, in typically developing children, altered patterns of impulsivity constitute a risk factor for the development of behavioral problems. Since both pathological and non-pathological states are commonly characterized by continuous transitions, we used a correlative approach to investigate the potential link between personality and brain dynamics. We related brain functional connectivity of typically developing children, measured with magnetic resonance imaging at rest, with their impulsivity scores obtained from a questionnaire completed by their parents. We first looked for areas within the default mode network (DMN) whose functional connectivity might be modulated by trait impulsivity. Then, we calculated the functional connectivity among these regions and the rest of the brain in order to assess if impulsivity trait altered their relationships. We found two DMN clusters located at the posterior cingulate cortex and the right angular gyrus which were negatively correlated with impulsivity scores. The whole-brain correlation analysis revealed the classic network of correlating and anti-correlating areas with respect to the DMN. The impulsivity trait modulated such pattern showing that the canonical anti-phasic relation between DMN and action-related network was reduced in high impulsive children. These results represent the first evidence that the impulsivity, measured as personality trait assessed through parents' report, exerts a modulatory influence over the functional connectivity of resting state brain networks in typically developing children. The present study goes further to connect developmental approaches, mainly based on data collected through the use of questionnaires, and behavioral neuroscience, interested in how differences in brain structure and functions reflect in differences in behavior.

Hyper-connectivity of functional networks for brain disease diagnosis.

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Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

2016-08-01

Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

Functional connectivity of the rodent brain using optical imaging

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Guevara Codina, Edgar

showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Graph analyses showed a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex ipsilateral to the treated carotid; however these changes are not reflected in differentiated metabolic estimates. Confounds remain due to the fact that carotid rigidification gives rise to neural decline in the hippocampus as well as unilateral alteration of vascular pulsatility; however the results support the need to look at several hemodynamic parameters when imaging the brain after arterial remodeling. The third article of this thesis studies a model of inflammatory injury on the newborn rat. Oxygen saturation and functional connectivity were assessed with photoacoustic tomography. Oxygen saturation was decreased in the site of the lesion and on the cortex ipsilateral to the injury; however this decrease is not fully explained by hypovascularization revealed by histology. Seed-based functional connectivity analysis showed that inter-hemispheric connectivity is not affected by inflammatory injury.

K -shell decomposition reveals hierarchical cortical organization of the human brain

International Nuclear Information System (INIS)

Lahav, Nir; Ksherim, Baruch; Havlin, Shlomo; Ben-Simon, Eti; Maron-Katz, Adi; Cohen, Reuven

2016-01-01

In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the different parts of the system and enables to examine how global and complex functions might emerge from network topology. Previous work revealed that the human brain features ‘small world’ characteristics and that cortical hubs tend to interconnect among themselves. However, in order to fully understand the topological structure of hubs, and how their profile reflect the brain’s global functional organization, one needs to go beyond the properties of a specific hub and examine the various structural layers that make up the network. To address this topic further, we applied an analysis known in statistical physics and network theory as k-shell decomposition analysis. The analysis was applied on a human cortical network, derived from MRI/DSI data of six participants. Such analysis enables us to portray a detailed account of cortical connectivity focusing on different neighborhoods of inter-connected layers across the cortex. Our findings reveal that the human cortex is highly connected and efficient, and unlike the internet network contains no isolated nodes. The cortical network is comprised of a nucleus alongside shells of increasing connectivity that formed one connected giant component, revealing the human brain’s global functional organization. All these components were further categorized into three hierarchies in accordance with their connectivity profile, with each hierarchy reflecting different functional roles. Such a model may explain an efficient flow of information from the lowest hierarchy to the highest one, with each step enabling increased data integration. At the top, the highest hierarchy (the nucleus) serves as a global interconnected collective and demonstrates high correlation with consciousness related regions, suggesting that the nucleus might serve as a

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

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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.

Altered structural connectivity of pain-related brain network in burning mouth syndrome-investigation by graph analysis of probabilistic tractography.

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Wada, Akihiko; Shizukuishi, Takashi; Kikuta, Junko; Yamada, Haruyasu; Watanabe, Yusuke; Imamura, Yoshiki; Shinozaki, Takahiro; Dezawa, Ko; Haradome, Hiroki; Abe, Osamu

2017-05-01

Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis. Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity. In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed. Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome.

Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox

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Andre Santos Ribeiro

2015-07-01

Full Text Available Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity.Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI and positron emission tomography (PET. It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also.Results. It was observed both a high inter

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

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Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

3D atlas of brain connections and functional circuits

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Pan, Jinghong; Nowinski, Wieslaw L.; Fock, Loe K.; Dow, Douglas E.; Chuan, Teh H.

1997-05-01

This work aims at the construction of an extendable brain atlas system which contains: (i) 3D models of cortical and subcortical structures along with their connections; (ii) visualization and exploration tools; and (iii) structures and connections editors. A 3D version of the Talairach- Tournoux brain atlas along with 3D Brodmann's areas are developed, co-registered, and placed in the Talairach stereotactic space. The initial built-in connections are thalamocortical ones. The structures and connections editors are provided to allow the user to add and modify cerebral structures and connections. Visualization and explorations tools are developed with four ways of exploring the brain connections model: composition, interrogation, navigation and diagnostic queries. The atlas is designed as an open system which can be extended independently in other centers according to their needs and discoveries.

Species-Specific Mechanisms of Neuron Subtype Specification Reveal Evolutionary Plasticity of Amniote Brain Development

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Tadashi Nomura

2018-03-01

Full Text Available Summary: Highly ordered brain architectures in vertebrates consist of multiple neuron subtypes with specific neuronal connections. However, the origin of and evolutionary changes in neuron specification mechanisms remain unclear. Here, we report that regulatory mechanisms of neuron subtype specification are divergent in developing amniote brains. In the mammalian neocortex, the transcription factors (TFs Ctip2 and Satb2 are differentially expressed in layer-specific neurons. In contrast, these TFs are co-localized in reptilian and avian dorsal pallial neurons. Multi-potential progenitors that produce distinct neuronal subtypes commonly exist in the reptilian and avian dorsal pallium, whereas a cis-regulatory element of avian Ctip2 exhibits attenuated transcription suppressive activity. Furthermore, the neuronal subtypes distinguished by these TFs are not tightly associated with conserved neuronal connections among amniotes. Our findings reveal the evolutionary plasticity of regulatory gene functions that contribute to species differences in neuronal heterogeneity and connectivity in developing amniote brains. : Neuronal heterogeneity is essential for assembling intricate neuronal circuits. Nomura et al. find that species-specific transcriptional mechanisms underlie diversities of excitatory neuron subtypes in mammalian and non-mammalian brains. Species differences in neuronal subtypes and connections suggest functional plasticity of regulatory genes for neuronal specification during amniote brain evolution. Keywords: Ctip2, Satb2, multi-potential progenitors, transcriptional regulation, neuronal connectivity

Alterations in Normal Aging Revealed by Cortical Brain Network Constructed Using IBASPM.

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Li, Wan; Yang, Chunlan; Shi, Feng; Wang, Qun; Wu, Shuicai; Lu, Wangsheng; Li, Shaowu; Nie, Yingnan; Zhang, Xin

2018-04-16

Normal aging has been linked with the decline of cognitive functions, such as memory and executive skills. One of the prominent approaches to investigate the age-related alterations in the brain is by examining the cortical brain connectome. IBASPM is a toolkit to realize individual atlas-based volume measurement. Hence, this study seeks to determine what further alterations can be revealed by cortical brain networks formed by IBASPM-extracted regional gray matter volumes. We found the reduced strength of connections between the superior temporal pole and middle temporal pole in the right hemisphere, global hubs as the left fusiform gyrus and right Rolandic operculum in the young and aging groups, respectively, and significantly reduced inter-module connection of one module in the aging group. These new findings are consistent with the phenomenon of normal aging mentioned in previous studies and suggest that brain network built with the IBASPM could provide supplementary information to some extent. The individualization of morphometric features extraction deserved to be given more attention in future cortical brain network research.

Exploring brain function from anatomical connectivity

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Gorka eZamora-López

2011-06-01

Full Text Available The intrinsic relationship between the architecture of the brain and the range of sensory and behavioral phenomena it produces is a relevant question in neuroscience. Here, we review recent knowledge gained on the architecture of the anatomical connectivity by means of complex network analysis. It has been found that corticocortical networks display a few prominent characteristics: (i modular organization, (ii abundant alternative processing paths and (iii the presence of highly connected hubs. Additionally, we present a novel classification of cortical areas of the cat according to the role they play in multisensory connectivity. All these properties represent an ideal anatomical substrate supporting rich dynamical behaviors, as-well-as facilitating the capacity of the brain to process sensory information of different modalities segregated and to integrate them towards a comprehensive perception of the real world. The result here exposed are mainly based in anatomical data of cats’ brain, but we show how further observations suggest that, from worms to humans, the nervous system of all animals might share fundamental principles of organization.

Dynamic functional brain connectivity for face perception

NARCIS (Netherlands)

Yang, Yuan; Qiu, Yihong; Schouten, Alfred C.

2015-01-01

Face perception is mediated by a distributed brain network comprised of the core system at occipito-temporal areas and the extended system at other relevant brain areas involving bilateral hemispheres. In this study we explored how the brain connectivity changes over the time for face-sensitive

The brain network reflecting bodily self-consciousness: a functional connectivity study

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Ionta, Silvio; Martuzzi, Roberto; Salomon, Roy

2014-01-01

Several brain regions are important for processing self-location and first-person perspective, two important aspects of bodily self-consciousness. However, the interplay between these regions has not been clarified. In addition, while self-location and first-person perspective in healthy subjects are associated with bilateral activity in temporoparietal junction (TPJ), disturbed self-location and first-person perspective result from damage of only the right TPJ. Identifying the involved brain network and understanding the role of hemispheric specializations in encoding self-location and first-person perspective, will provide important information on system-level interactions neurally mediating bodily self-consciousness. Here, we used functional connectivity and showed that right and left TPJ are bilaterally connected to supplementary motor area, ventral premotor cortex, insula, intraparietal sulcus and occipitotemporal cortex. Furthermore, the functional connectivity between right TPJ and right insula had the highest selectivity for changes in self-location and first-person perspective. Finally, functional connectivity revealed hemispheric differences showing that self-location and first-person perspective modulated the connectivity between right TPJ, right posterior insula, and right supplementary motor area, and between left TPJ and right anterior insula. The present data extend previous evidence on healthy populations and clinical observations in neurological deficits, supporting a bilateral, but right-hemispheric dominant, network for bodily self-consciousness. PMID:24396007

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.

Different alterations in brain functional networks according to direct and indirect topological connections in patients with schizophrenia.

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Park, Chang-Hyun; Lee, Seungyup; Kim, Taewon; Won, Wang Yeon; Lee, Kyoung-Uk

2017-10-01

Schizophrenia displays connectivity deficits in the brain, but the literature has shown inconsistent findings about alterations in global efficiency of brain functional networks. We supposed that such inconsistency at the whole brain level may be due to a mixture of different portions of global efficiency at sub-brain levels. Accordingly, we considered measuring portions of global efficiency in two aspects: spatial portions by considering sub-brain networks and topological portions by considering contributions to global efficiency according to direct and indirect topological connections. We proposed adjacency and indirect adjacency as new network parameters attributable to direct and indirect topological connections, respectively, and applied them to graph-theoretical analysis of brain functional networks constructed from resting state fMRI data of 22 patients with schizophrenia and 22 healthy controls. Group differences in the network parameters were observed not for whole brain and hemispheric networks, but for regional networks. Alterations in adjacency and indirect adjacency were in opposite directions, such that adjacency increased, but indirect adjacency decreased in patients with schizophrenia. Furthermore, over connections in frontal and parietal regions, increased adjacency was associated with more severe negative symptoms, while decreased adjacency was associated with more severe positive symptoms of schizophrenia. This finding indicates that connectivity deficits associated with positive and negative symptoms of schizophrenia may involve topologically different paths in the brain. In patients with schizophrenia, although changes in global efficiency may not be clearly shown, different alterations in brain functional networks according to direct and indirect topological connections could be revealed at the regional level. Copyright © 2017 Elsevier B.V. All rights reserved.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

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Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Differential structural and resting state connectivity between insular subdivisions and other pain-related brain regions.

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Wiech, K; Jbabdi, S; Lin, C S; Andersson, J; Tracey, I

2014-10-01

Functional neuroimaging studies suggest that the anterior, mid, and posterior division of the insula subserve different functions in the perception of pain. The anterior insula (AI) has predominantly been associated with cognitive-affective aspects of pain, while the mid and posterior divisions have been implicated in sensory-discriminative processing. We examined whether this functional segregation is paralleled by differences in (1) structural and (2) resting state connectivity and (3) in correlations with pain-relevant psychological traits. Analyses were restricted to the 3 insular subdivisions and other pain-related brain regions. Both type of analyses revealed largely overlapping results. The AI division was predominantly connected to the ventrolateral prefrontal cortex (structural and resting state connectivity) and orbitofrontal cortex (structural connectivity). In contrast, the posterior insula showed strong connections to the primary somatosensory cortex (SI; structural connectivity) and secondary somatosensory cortex (SII; structural and resting state connectivity). The mid insula displayed a hybrid connectivity pattern with strong connections with the ventrolateral prefrontal cortex, SII (structural and resting state connectivity) and SI (structural connectivity). Moreover, resting state connectivity revealed strong connectivity of all 3 subdivisions with the thalamus. On the behavioural level, AI structural connectivity was related to the individual degree of pain vigilance and awareness that showed a positive correlation with AI-amygdala connectivity and a negative correlation with AI-rostral anterior cingulate cortex connectivity. In sum, our findings show a differential structural and resting state connectivity for the anterior, mid, and posterior insula with other pain-relevant brain regions, which might at least partly explain their different functional profiles in pain processing. Copyright © 2014 The Authors. Published by Elsevier B.V. All

No abnormalities of intrinsic brain connectivity in the interictal phase of migraine with aura

DEFF Research Database (Denmark)

Hougaard, Anders; Amin, F M; Magon, S

2015-01-01

if cortical dysfunction is present at rest, i.e. in the absence of any external stimuli. Functional magnetic resonance imaging is a powerful technique for evaluating resting state functional connectivity, i.e. coherence of brain activity across cerebral areas. The objective of this study was to investigate...... resting-state functional brain connectivity in migraineurs with aura outside of attacks using functional magnetic resonance imaging. METHODS: Forty patients suffering from migraine with visual aura and 40 individually age and gender matched healthy controls with no history or family history of migraine......, and in a data-driven exploratory fashion (dual regression) in order to reveal any possible between-group differences of resting state networks. Age, gender, attack frequency and disease duration were included as nuisance variables. RESULTS: No differences of functional connectivity were found between patients...

Lasting modulation effects of rTMS on neural activity and connectivity as revealed by resting-state EEG.

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Ding, Lei; Shou, Guofa; Yuan, Han; Urbano, Diamond; Cha, Yoon-Hee

2014-07-01

The long-lasting neuromodulatory effects of repetitive transcranial magnetic stimulation (rTMS) are of great interest for therapeutic applications in various neurological and psychiatric disorders, due to which functional connectivity among brain regions is profoundly disturbed. Classic TMS studies selectively alter neural activity in specific brain regions and observe neural activity changes on nonperturbed areas to infer underlying connectivity and its changes. Less has been indicated in direct measures of functional connectivity and/or neural network and on how connectivity/network alterations occur. Here, we developed a novel analysis framework to directly investigate both neural activity and connectivity changes induced by rTMS from resting-state EEG (rsEEG) acquired in a group of subjects with a chronic disorder of imbalance, known as the mal de debarquement syndrome (MdDS). Resting-state activity in multiple functional brain areas was identified through a data-driven blind source separation analysis on rsEEG data, and the connectivity among them was characterized using a phase synchronization measure. Our study revealed that there were significant long-lasting changes in resting-state neural activity, in theta, low alpha, and high alpha bands and neural networks in theta, low alpha, high alpha and beta bands, over broad cortical areas 4 to 5 h after the last application of rTMS in a consecutive five-day protocol. Our results of rsEEG connectivity further indicated that the changes, mainly in the alpha band, over the parietal and occipital cortices from pre- to post-TMS sessions were significantly correlated, in both magnitude and direction, to symptom changes in this group of subjects with MdDS. This connectivity measure not only suggested that rTMS can generate positive treatment effects in MdDS patients, but also revealed new potential targets for future therapeutic trials to improve treatment effects. It is promising that the new connectivity measure

Comparing Structural Brain Connectivity by the Infinite Relational Model

DEFF Research Database (Denmark)

Ambrosen, Karen Marie Sandø; Herlau, Tue; Dyrby, Tim

2013-01-01

The growing focus in neuroimaging on analyzing brain connectivity calls for powerful and reliable statistical modeling tools. We examine the Infinite Relational Model (IRM) as a tool to identify and compare structure in brain connectivity graphs by contrasting its performance on graphs from...

Digital tissue and what it may reveal about the brain.

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Morgan, Josh L; Lichtman, Jeff W

2017-10-30

Imaging as a means of scientific data storage has evolved rapidly over the past century from hand drawings, to photography, to digital images. Only recently can sufficiently large datasets be acquired, stored, and processed such that tissue digitization can actually reveal more than direct observation of tissue. One field where this transformation is occurring is connectomics: the mapping of neural connections in large volumes of digitized brain tissue.

Brain connectivity study of brain tumor patients using MR-PET data: preliminary results

International Nuclear Information System (INIS)

Mendes, Ana Carina; Ribeiro, Andre Santos; Oros-Peusquens, Ana Maria; Langen, Karl Josef; Shah, Jon; Ferreira, Hugo Alexandre

2015-01-01

Brain activity results from anatomical and functional connections that can be disrupted or altered due to trauma or lesion. This work presents a first approach on the study of whole-brain connectivity of brain tumor patients using the Multimodal Imaging Brain Connectivity (MIBCA) toolbox. Two patients with glioblastoma lesions located in the left hemisphere (one in the motor cortex and the other in the temporal lobe) underwent simultaneous MRI and dynamic PET scans using a 3T MRI scanner with a BrainPET insert. The following data was acquired: T1-w MPRAGE (1x1x1mm 3 ), DTI (dir=30, b=0,800s/mm2, 2x2x2mm 3 ), and dynamic 18F-FET PET. The MIBCA toolbox was used to automatically pre-process MRI-PET data and to derive imaging and connectivity metrics from the multimodal data. Computed metrics included: cortical thickness from T1-w data; mean diffusivity (MD), fractional anisotropy (FA), node degree, clustering coefficient and pairwise ROI fibre tracking (structural connectivity) from DTI data; and standardized uptake value (SUV) from PET data. For all the metrics, the differences between left and right hemispherical structures were obtained, followed by a 25% threshold (except for SUV thresholded at 15%). Data was visualized in a connectogram, and both structural connectivity and metrics were studied in regions surrounding lesions. Preliminary results showed increased SUV values in regions surrounding the tumor for both patients. Patients also showed changes in structural connectivity involving these regions and also other more spatially distant regions such as the putamen and the pallidum, including decreased number of fibers between the subcortical structures themselves and with frontal regions. These findings suggest that the presence of a tumor may alter both local and more distant structural connections. Presently, a larger patient sample is being studied along with the inclusion of a control group to test the consistency of the findings.

Brain connectivity study of brain tumor patients using MR-PET data: preliminary results

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Mendes, Ana Carina [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon (Portugal); Ribeiro, Andre Santos [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon (Portugal); Centre for Neuropsychopharmacology, Division of Brain Sciences, Department of Medicine, Imperial College London, London (United Kingdom); Oros-Peusquens, Ana Maria; Langen, Karl Josef; Shah, Jon [Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich (Germany); Ferreira, Hugo Alexandre [Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon (Portugal)

2015-05-18

Brain activity results from anatomical and functional connections that can be disrupted or altered due to trauma or lesion. This work presents a first approach on the study of whole-brain connectivity of brain tumor patients using the Multimodal Imaging Brain Connectivity (MIBCA) toolbox. Two patients with glioblastoma lesions located in the left hemisphere (one in the motor cortex and the other in the temporal lobe) underwent simultaneous MRI and dynamic PET scans using a 3T MRI scanner with a BrainPET insert. The following data was acquired: T1-w MPRAGE (1x1x1mm{sup 3}), DTI (dir=30, b=0,800s/mm2, 2x2x2mm{sup 3}), and dynamic 18F-FET PET. The MIBCA toolbox was used to automatically pre-process MRI-PET data and to derive imaging and connectivity metrics from the multimodal data. Computed metrics included: cortical thickness from T1-w data; mean diffusivity (MD), fractional anisotropy (FA), node degree, clustering coefficient and pairwise ROI fibre tracking (structural connectivity) from DTI data; and standardized uptake value (SUV) from PET data. For all the metrics, the differences between left and right hemispherical structures were obtained, followed by a 25% threshold (except for SUV thresholded at 15%). Data was visualized in a connectogram, and both structural connectivity and metrics were studied in regions surrounding lesions. Preliminary results showed increased SUV values in regions surrounding the tumor for both patients. Patients also showed changes in structural connectivity involving these regions and also other more spatially distant regions such as the putamen and the pallidum, including decreased number of fibers between the subcortical structures themselves and with frontal regions. These findings suggest that the presence of a tumor may alter both local and more distant structural connections. Presently, a larger patient sample is being studied along with the inclusion of a control group to test the consistency of the findings.

Brain connectivity in pathological and pharmacological coma

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Quentin Noirhomme

2010-12-01

Full Text Available Recent studies in patients with disorders of consciousness (DOC tend to support the view that awareness is not related to activity in a single brain region but to thalamo-cortical connectivity in the frontoparietal network. Functional neuroimaging studies have shown preserved albeit disconnected low level cortical activation in response to external stimulation in patients in a vegetative state or unresponsive wakefulness syndrome. While activation of these primary sensory cortices does not necessarily reflect conscious awareness, activation in higher order associative cortices in minimally conscious state patients seems to herald some residual perceptual awareness. PET studies have identified a metabolic dysfunction in a widespread fronto-parietal global neuronal workspace in DOC patients including the midline default mode network, ‘intrinsic’ system, and the lateral frontoparietal cortices or ‘extrinsic system’. Recent studies have investigated the relation of awareness to the functional connectivity within intrinsic and extrinsic networks, and with the thalami in both pathological and pharmacological coma. In brain damaged patients, connectivity in all default network areas was found to be non-linearly correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative, coma and brain dead patients. Anesthesia-induced loss of consciousness was also shown to correlate with a global decrease in cortico-cortical and thalamo-cortical connectivity in both intrinsic and extrinsic networks, but not in auditory or visual networks. In anesthesia, unconsciousness was also associated with a loss of cross-modal interactions between networks. These results suggest that conscious awareness critically depends on the functional integrity of thalamo-cortical and cortico-cortical frontoparietal connectivity within and between intrinsic and extrinsic brain networks.

Brain functional connectivity in stimulant drug dependence and obsessive-compulsive disorder.

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Meunier, David; Ersche, Karen D; Craig, Kevin J; Fornito, Alex; Merlo-Pich, Emilio; Fineberg, Naomi A; Shabbir, Shaila S; Robbins, Trevor W; Bullmore, Edward T

2012-01-16

There are reasons for thinking that obsessive-compulsive disorder (OCD) and drug dependence, although conventionally distinct diagnostic categories, might share important cognitive and neurobiological substrates. We tested this hypothesis directly by comparing brain functional connectivity measures between patients with OCD, stimulant dependent individuals (SDIs; many of whom were non-dependent users of other recreational drugs) and healthy volunteers. We measured functional connectivity between each possible pair of 506 brain regional functional MRI time series representing low frequency (0.03-0.06 Hz) spontaneous brain hemodynamics in healthy volunteers (N=18), patients with OCD (N=18) and SDIs (N=18). We used permutation tests to identify i) brain regions where strength of connectivity was significantly different in both patient groups compared to healthy volunteers; and ii) brain regions and connections which had significantly different functional connectivity between patient groups. We found that functional connectivity of right inferior and superior orbitofrontal cortex (OFC) was abnormally reduced in both disorders. Whether diagnosed as OCD or SDI, patients with higher scores on measures of compulsive symptom severity showed greater reductions of right orbitofrontal connectivity. Functional connections specifically between OFC and dorsal medial pre-motor and cingulate cortex were attenuated in both patient groups. However, patients with OCD demonstrated more severe and extensive reductions of functional connectivity compared to SDIs. OCD and stimulant dependence are not identical at the level of brain functional systems but they have some important abnormalities in common compared with healthy volunteers. Orbitofrontal connectivity may serve as a human brain systems biomarker for compulsivity across diagnostic categories. Copyright © 2011 Elsevier Inc. All rights reserved.

Diffusion Tensor Imaging Tractography Reveals Disrupted White Matter Structural Connectivity Network in Healthy Adults with Insomnia Symptoms

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Feng-Mei Lu

2017-11-01

Full Text Available Neuroimaging studies have revealed that insomnia is characterized by aberrant neuronal connectivity in specific brain regions, but the topological disruptions in the white matter (WM structural connectivity networks remain largely unknown in insomnia. The current study uses diffusion tensor imaging (DTI tractography to construct the WM structural networks and graph theory analysis to detect alterations of the brain structural networks. The study participants comprised 30 healthy subjects with insomnia symptoms (IS and 62 healthy subjects without IS. Both the two groups showed small-world properties regarding their WM structural connectivity networks. By contrast, increased local efficiency and decreased global efficiency were identified in the IS group, indicating an insomnia-related shift in topology away from regular networks. In addition, the IS group exhibited disrupted nodal topological characteristics in regions involving the fronto-limbic and the default-mode systems. To our knowledge, this is the first study to explore the topological organization of WM structural network connectivity in insomnia. More importantly, the dysfunctions of large-scale brain systems including the fronto-limbic pathways, salience network and default-mode network in insomnia were identified, which provides new insights into the insomnia connectome. Topology-based brain network analysis thus could be a potential biomarker for IS.

The brain matures with stronger functional connectivity and decreased randomness of its network.

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Dirk J A Smit

Full Text Available We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998 graph parameters C (local clustering and L (global path length for alpha (~10 Hz, beta (~20 Hz, and theta (~4 Hz oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ~50 yrs. Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ~18 yrs. Older age (55+ was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05, while path length was related to both white matter (alpha: max. r = 38, p<001 and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001 volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain.

Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

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Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

2017-08-01

Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

Dynamic effective connectivity of inter-areal brain circuits.

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Demian Battaglia

Full Text Available Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity, related to the elusive question "Which areas cause the present activity of which others?". Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early

Direct Modulation Of Aberrant Brain Network Connectivity Through Real-Time NeuroFeedback

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White, Emily; Popal, Haroon; Roopchansingh, Vinai; Gonzalez-Castillo, Javier; Kimmich, Sara; Ramot, Michal; Martin Ph.D., Alex; Gotts, Stephen

2017-01-01

eLife digest Even when we are at rest, our brains are always active. For example, areas of the brain involved in vision remain active in complete darkness. Different brain regions that connect together to perform a given task often show coordinated activity at rest. Past studies have shown that these resting connections are different in people with conditions such as autism. Some brain regions are more weakly connected while others are more strongly connected in people with autism spectrum di...

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...

Connectivity and functional profiling of abnormal brain structures in pedophilia.

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Poeppl, Timm B; Eickhoff, Simon B; Fox, Peter T; Laird, Angela R; Rupprecht, Rainer; Langguth, Berthold; Bzdok, Danilo

2015-06-01

Despite its 0.5-1% lifetime prevalence in men and its general societal relevance, neuroimaging investigations in pedophilia are scarce. Preliminary findings indicate abnormal brain structure and function. However, no study has yet linked structural alterations in pedophiles to both connectional and functional properties of the aberrant hotspots. The relationship between morphological alterations and brain function in pedophilia as well as their contribution to its psychopathology thus remain unclear. First, we assessed bimodal connectivity of structurally altered candidate regions using meta-analytic connectivity modeling (MACM) and resting-state correlations employing openly accessible data. We compared the ensuing connectivity maps to the activation likelihood estimation (ALE) maps of a recent quantitative meta-analysis of brain activity during processing of sexual stimuli. Second, we functionally characterized the structurally altered regions employing meta-data of a large-scale neuroimaging database. Candidate regions were functionally connected to key areas for processing of sexual stimuli. Moreover, we found that the functional role of structurally altered brain regions in pedophilia relates to nonsexual emotional as well as neurocognitive and executive functions, previously reported to be impaired in pedophiles. Our results suggest that structural brain alterations affect neural networks for sexual processing by way of disrupted functional connectivity, which may entail abnormal sexual arousal patterns. The findings moreover indicate that structural alterations account for common affective and neurocognitive impairments in pedophilia. The present multimodal integration of brain structure and function analyses links sexual and nonsexual psychopathology in pedophilia. © 2015 Wiley Periodicals, Inc.

Joint brain connectivity estimation from diffusion and functional MRI data

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Chu, Shu-Hsien; Lenglet, Christophe; Parhi, Keshab K.

2015-03-01

Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information

Computational brain connectivity mapping: A core health and scientific challenge.

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Deriche, Rachid

2016-10-01

One third of the burden of all the diseases in Europe is due to problems caused by diseases affecting brain. Although exceptional progress have been obtained for exploring the brain during the past decades, it is still terra-incognita and calls for specific efforts in research to better understand its architecture and functioning. To take up this great challenge of modern science and to solve the limited view of the brain provided just by one imaging modality, this article advocates the idea developed in my research group of a global approach involving new generation of models for brain connectivity mapping and strong interactions between structural and functional connectivities. Capitalizing on the strengths of integrated and complementary non invasive imaging modalities such as diffusion Magnetic Resonance Imaging (dMRI) and Electro & Magneto-Encephalography (EEG & MEG) will contribute to achieve new frontiers for identifying and characterizing structural and functional brain connectivities and to provide a detailed mapping of the brain connectivity, both in space and time. Thus leading to an added clinical value for high impact diseases with new perspectives in computational neuro-imaging and cognitive neuroscience. Copyright © 2016 Elsevier B.V. All rights reserved.

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...

The Hungry Brain: The Nutrition/Cognition Connection

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Marcus, Susan Archibald

2007-01-01

The brain gets fed first! That is an important idea that directly relates to the nutrition/cognition connection in schools. As the education community faces the challenges of childhood obesity, malnutrition of the brain, food allergies, disorders of metal metabolism and biochemical imbalances, educators are eager to learn about how to guide…

Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

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Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

2018-02-01

The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

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

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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

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

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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

Cortical brain connectivity evaluated by graph theory in dementia: a correlation study between functional and structural data.

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Vecchio, Fabrizio; Miraglia, Francesca; Curcio, Giuseppe; Altavilla, Riccardo; Scrascia, Federica; Giambattistelli, Federica; Quattrocchi, Carlo Cosimo; Bramanti, Placido; Vernieri, Fabrizio; Rossini, Paolo Maria

2015-01-01

A relatively new approach to brain function in neuroscience is the "functional connectivity", namely the synchrony in time of activity in anatomically-distinct but functionally-collaborating brain regions. On the other hand, diffusion tensor imaging (DTI) is a recently developed magnetic resonance imaging (MRI)-based technique with the capability to detect brain structural connection with fractional anisotropy (FA) identification. FA decrease has been observed in the corpus callosum of subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI, an AD prodromal stage). Corpus callosum splenium DTI abnormalities are thought to be associated with functional disconnections among cortical areas. This study aimed to investigate possible correlations between structural damage, measured by MRI-DTI, and functional abnormalities of brain integration, measured by characteristic path length detected in resting state EEG source activity (40 participants: 9 healthy controls, 10 MCI, 10 mild AD, 11 moderate AD). For each subject, undirected and weighted brain network was built to evaluate graph core measures. eLORETA lagged linear connectivity values were used as weight of the edges of the network. Results showed that callosal FA reduction is associated to a loss of brain interhemispheric functional connectivity characterized by increased delta and decreased alpha path length. These findings suggest that "global" (average network shortest path length representing an index of how efficient is the information transfer between two parts of the network) functional measure can reflect the reduction of fiber connecting the two hemispheres as revealed by DTI analysis and also anticipate in time this structural loss.

Brain Connectivity Networks and the Aesthetic Experience of Music.

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Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

2018-06-12

Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.

Altered Brain Functional Connectivity in Betel Quid-Dependent Chewers.

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Huang, Xiaojun; Pu, Weidan; Liu, Haihong; Li, Xinmin; Greenshaw, Andrew J; Dursun, Serdar M; Xue, Zhimin; Liu, Zhening

2017-01-01

Betel quid (BQ) is a common psychoactive substance worldwide with particularly high usage in many Asian countries. This study aimed to explore the effect of BQ use on functional connectivity by comparing global functional brain networks and their subset between BQ chewers and healthy controls (HCs). Resting-state functional magnetic resonance imaging (fMRI) was obtained from 24 betel quid-dependent (BQD) male chewers and 27 healthy male individuals on a 3.0T scanner. We used independent component analysis (ICA) to determine components that represent the brain's functional networks and their spatial aspects of functional connectivity. Two sample t -tests were used to identify the functional connectivity differences in each network between these two groups. Seventeen networks were identified by ICA. Nine of them showed connectivity differences between BQD and HCs (two sample t -tests, p  betel quid dependence scale scores were positively related to the increased functional connectivity in the orbitofrontal ( r  = 0.39, p  = 0.03) while negatively related to the decreased functional connectivity in medial frontal/anterior cingulate networks ( r  = -0.35, p  = 0.02). Our findings provide further evidence that BQ chewing may lead to brain functional connectivity changes, which may play a key role in the psychological and physiological effects of BQ.

A review on functional and structural brain connectivity in numerical cognition

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Korbinian eMoeller

2015-05-01

Full Text Available Only recently has the complex anatomo-functional system underlying numerical cognition become accessible to evaluation in the living brain. We identified 26 studies investigating brain connectivity in numerical cognition. Despite considerable heterogeneity regarding methodological approaches, populations investigated, and assessment procedures implemented, the results provided largely converging evidence regarding the underlying brain connectivity involved in numerical cognition. Analyses of both functional/effective as well as structural connectivity have consistently corroborated the assumption that numerical cognition is subserved by a fronto-parietal network including (intraparietal as well as (prefrontal cortex sites. Evaluation of structural connectivity has indicated the involvement of fronto-parietal association fibers encompassing the superior longitudinal fasciculus dorsally and the external capsule/extreme capsule system ventrally. Additionally, commissural fibers seem to connect the bilateral intraparietal sulci when number magnitude information is processed. Finally, the identification of projection fibers such as the superior corona radiata indicates connections between cortex and basal ganglia as well as the thalamus in numerical cognition. Studies on functional/effective connectivity further indicated a specific role of the hippocampus. These specifications of brain connectivity augment the triple-code model of number processing and calculation with respect to how grey matter areas associated with specific number-related representations may work together.

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity.

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Finn, Emily S; Shen, Xilin; Scheinost, Dustin; Rosenberg, Monica D; Huang, Jessica; Chun, Marvin M; Papademetris, Xenophon; Constable, R Todd

2015-11-01

Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.

Measures for brain connectivity analysis: nodes centrality and their invariant patterns

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da Silva, Laysa Mayra Uchôa; Baltazar, Carlos Arruda; Silva, Camila Aquemi; Ribeiro, Mauricio Watanabe; de Aratanha, Maria Adelia Albano; Deolindo, Camila Sardeto; Rodrigues, Abner Cardoso; Machado, Birajara Soares

2017-07-01

The high dynamical complexity of the brain is related to its small-world topology, which enable both segregated and integrated information processing capabilities. Several measures of connectivity estimation have already been employed to characterize functional brain networks from multivariate electrophysiological data. However, understanding the properties of each measure that lead to a better description of the real topology and capture the complex phenomena present in the brain remains challenging. In this work we compared four nonlinear connectivity measures and show that each method characterizes distinct features of brain interactions. The results suggest an invariance of global network parameters from different behavioral states and that more complete description may be reached considering local features, independently of the connectivity measure employed. Our findings also point to future perspectives in connectivity studies that combine distinct and complementary dependence measures in assembling higher dimensions manifolds.

Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

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Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Leonardo, Cassandra D.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew A.; Thompson, Paul M.

2015-01-01

Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

Brain connectivity aberrations in anabolic-androgenic steroid users

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Lars T. Westlye

2017-01-01

Full Text Available Sustained anabolic-androgenic steroid (AAS use has adverse behavioral consequences, including aggression, violence and impulsivity. Candidate mechanisms include disruptions of brain networks with high concentrations of androgen receptors and critically involved in emotional and cognitive regulation. Here, we tested the effects of AAS on resting-state functional brain connectivity in the largest sample of AAS-users to date. We collected resting-state functional magnetic resonance imaging (fMRI data from 151 males engaged in heavy resistance strength training. 50 users tested positive for AAS based on the testosterone to epitestosterone (T/E ratio and doping substances in urine. 16 previous users and 59 controls tested negative. We estimated brain network nodes and their time-series using ICA and dual regression and defined connectivity matrices as the between-node partial correlations. In line with the emotional and behavioral consequences of AAS, current users exhibited reduced functional connectivity between key nodes involved in emotional and cognitive regulation, in particular reduced connectivity between the amygdala and default-mode network (DMN and between the dorsal attention network (DAN and a frontal node encompassing the superior and inferior frontal gyri (SFG/IFG and the anterior cingulate cortex (ACC, with further reductions as a function of dependency, lifetime exposure, and cycle state (on/off.

Cross-hemispheric functional connectivity in the human fetal brain.

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Thomason, Moriah E; Dassanayake, Maya T; Shen, Stephen; Katkuri, Yashwanth; Alexis, Mitchell; Anderson, Amy L; Yeo, Lami; Mody, Swati; Hernandez-Andrade, Edgar; Hassan, Sonia S; Studholme, Colin; Jeong, Jeong-Won; Romero, Roberto

2013-02-20

Compelling evidence indicates that psychiatric and developmental disorders are generally caused by disruptions in the functional connectivity (FC) of brain networks. Events occurring during development, and in particular during fetal life, have been implicated in the genesis of such disorders. However, the developmental timetable for the emergence of neural FC during human fetal life is unknown. We present the results of resting-state functional magnetic resonance imaging performed in 25 healthy human fetuses in the second and third trimesters of pregnancy (24 to 38 weeks of gestation). We report the presence of bilateral fetal brain FC and regional and age-related variation in FC. Significant bilateral connectivity was evident in half of the 42 areas tested, and the strength of FC between homologous cortical brain regions increased with advancing gestational age. We also observed medial to lateral gradients in fetal functional brain connectivity. These findings improve understanding of human fetal central nervous system development and provide a basis for examining the role of insults during fetal life in the subsequent development of disorders in neural FC.

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa

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Geisler, Daniel; Borchardt, Viola; Lord, Anton R.; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A.; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Background Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. Methods To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Results Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. Limitations The present results may be limited to the methods applied during preprocessing and network construction. Conclusion We demonstrated anorexia nervosa–related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger. PMID:26252451

Brain disease, connectivity, plasticity and cognitive therapy: A neurological view of mental disorders.

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Lubrini, G; Martín-Montes, A; Díez-Ascaso, O; Díez-Tejedor, E

2018-04-01

Our conception of the mind-brain relationship has evolved from the traditional idea of dualism to current evidence that mental functions result from brain activity. This paradigm shift, combined with recent advances in neuroimaging, has led to a novel definition of brain functioning in terms of structural and functional connectivity. The purpose of this literature review is to describe the relationship between connectivity, brain lesions, cerebral plasticity, and functional recovery. Assuming that brain function results from the organisation of the entire brain in networks, brain dysfunction would be a consequence of altered brain network connectivity. According to this approach, cognitive and behavioural impairment following brain damage result from disrupted functional organisation of brain networks. However, the dynamic and versatile nature of these circuits makes recovering brain function possible. Cerebral plasticity allows for functional reorganisation leading to recovery, whether spontaneous or resulting from cognitive therapy, after brain disease. Current knowledge of brain connectivity and cerebral plasticity provides new insights into normal brain functioning, the mechanisms of brain damage, and functional recovery, which in turn serve as the foundations of cognitive therapy. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Association Between Brain Activation and Functional Connectivity.

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Tomasi, Dardo; Volkow, Nora D

2018-04-13

The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

The functional connectivity landscape of the human brain.

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Bratislav Mišić

Full Text Available Functional brain networks emerge and dissipate over a primarily static anatomical foundation. The dynamic basis of these networks is inter-regional communication involving local and distal regions. It is assumed that inter-regional distances play a pivotal role in modulating network dynamics. Using three different neuroimaging modalities, 6 datasets were evaluated to determine whether experimental manipulations asymmetrically affect functional relationships based on the distance between brain regions in human participants. Contrary to previous assumptions, here we show that short- and long-range connections are equally likely to strengthen or weaken in response to task demands. Additionally, connections between homotopic areas are the most stable and less likely to change compared to any other type of connection. Our results point to a functional connectivity landscape characterized by fluid transitions between local specialization and global integration. This ability to mediate functional properties irrespective of spatial distance may engender a diverse repertoire of cognitive processes when faced with a dynamic environment.

Developmental Changes in Brain Network Hub Connectivity in Late Adolescence.

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Baker, Simon T E; Lubman, Dan I; Yücel, Murat; Allen, Nicholas B; Whittle, Sarah; Fulcher, Ben D; Zalesky, Andrew; Fornito, Alex

2015-06-17

The human brain undergoes substantial development throughout adolescence and into early adulthood. This maturational process is thought to include the refinement of connectivity between putative connectivity hub regions of the brain, which collectively form a dense core that enhances the functional integration of anatomically distributed, and functionally specialized, neural systems. Here, we used longitudinal diffusion magnetic resonance imaging to characterize changes in connectivity between 80 cortical and subcortical anatomical regions over a 2 year period in 31 adolescents between the ages of 15 and 19 years. Connectome-wide analysis indicated that only a small subset of connections showed evidence of statistically significant developmental change over the study period, with 8% and 6% of connections demonstrating decreased and increased structural connectivity, respectively. Nonetheless, these connections linked 93% and 90% of the 80 regions, respectively, pointing to a selective, yet anatomically distributed pattern of developmental changes that involves most of the brain. Hub regions showed a distinct tendency to be highly connected to each other, indicating robust "rich-club" organization. Moreover, connectivity between hubs was disproportionately influenced by development, such that connectivity between subcortical hubs decreased over time, whereas frontal-subcortical and frontal-parietal hub-hub connectivity increased over time. These findings suggest that late adolescence is characterized by selective, yet significant remodeling of hub-hub connectivity, with the topological organization of hubs shifting emphasis from subcortical hubs in favor of an increasingly prominent role for frontal hub regions. Copyright © 2015 the authors 0270-6474/15/359078-10$15.00/0.

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

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Stavros I. Dimitriadis

2015-01-01

Full Text Available Mild traumatic brain injury (mTBI may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI.

Age-Related Difference in Functional Brain Connectivity of Mastication

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Lin, Chia-shu; Wu, Ching-yi; Wu, Shih-yun; Lin, Hsiao-Han; Cheng, Dong-hui; Lo, Wen-liang

2017-01-01

The age-related decline in motor function is associated with changes in intrinsic brain signatures. Here, we investigated the functional connectivity (FC) associated with masticatory performance, a clinical index evaluating general masticatory function. Twenty-six older adults (OA) and 26 younger (YA) healthy adults were recruited and assessed using the masticatory performance index (MPI) and resting-state functional magnetic resonance imaging (rs-fMRI). We analyzed the rs-fMRI FC network related to mastication, which was constructed based on 12 bilateral mastication-related brain regions according to the literature. For the OA and the YA group, we identified the mastication-related hubs, i.e., the nodes for which the degree centrality (DC) was positively correlated with the MPI. For each pair of nodes, we identified the inter-nodal link for which the FC was positively correlated with the MPI. The network analysis revealed that, in the YA group, the FC between the sensorimotor cortex, the thalamus (THA) and the cerebellum was positively correlated with the MPI. Consistently, the cerebellum nodes were defined as the mastication-related hubs. In contrast, in the OA group, we found a sparser connection within the sensorimotor regions and cerebellum and a denser connection across distributed regions, including the FC between the superior parietal lobe (SPL), the anterior insula (aINS) and the dorsal anterior cingulate cortex (dACC). Compared to the YA group, the network of the OA group also comprised more mastication-related hubs, which were spatially distributed outside the sensorimotor regions, including the right SPL, the right aINS, and the bilateral dACC. In general, the findings supported the hypothesis that in OA, higher masticatory performance is associated with a widespread pattern of mastication-related hubs. Such a widespread engagement of multiple brain regions associated with the MPI may reflect an increased demand in sensorimotor integration, attentional

Flexible Connectivity in the Aging Brain Revealed by Task Modulations

NARCIS (Netherlands)

Geerligs, Linda; Saliasi, Emi; Renken, Remco J.; Maurits, Natasha M.; Lorist, Monicque M.

Recent studies have shown that aging has a large impact on connectivity within and between functional networks. An open question is whether elderly still have the flexibility to adapt functional network connectivity (FNC) to the demands of the task at hand. To study this, we collected fMRI data in

Mapping effective connectivity in the human brain with concurrent intracranial electrical stimulation and BOLD-fMRI.

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Oya, Hiroyuki; Howard, Matthew A; Magnotta, Vincent A; Kruger, Anton; Griffiths, Timothy D; Lemieux, Louis; Carmichael, David W; Petkov, Christopher I; Kawasaki, Hiroto; Kovach, Christopher K; Sutterer, Matthew J; Adolphs, Ralph

2017-02-01

Understanding brain function requires knowledge of how one brain region causally influences another. This information is difficult to obtain directly in the human brain, and is instead typically inferred from resting-state fMRI. Here, we demonstrate the safety and scientific promise of a novel and complementary approach: concurrent electrical stimulation and fMRI (es-fMRI) at 3T in awake neurosurgical patients with implanted depth electrodes. We document the results of safety testing, actual experimental setup, and stimulation parameters, that safely and reliably evoke activation in distal structures through stimulation of amygdala, cingulate, or prefrontal cortex. We compare connectivity inferred from the evoked patterns of activation with that estimated from standard resting-state fMRI in the same patients: while connectivity patterns obtained with each approach are correlated, each method produces unique results. Response patterns were stable over the course of 11min of es-fMRI runs. COMPARISON WITH EXISTING METHOD: es-fMRI in awake humans yields unique information about effective connectivity, complementing resting-state fMRI. Although our stimulations were below the level of inducing any apparent behavioral or perceptual effects, a next step would be to use es-fMRI to modulate task performances. This would reveal the acute network-level changes induced by the stimulation that mediate the behavioral and cognitive effects seen with brain stimulation. es-fMRI provides a novel and safe approach for mapping effective connectivity in the human brain in a clinical setting, and will inform treatments for psychiatric and neurodegenerative disorders that use deep brain stimulation. Copyright © 2016 Elsevier B.V. All rights reserved.

Adolescent Condom Use and Connectivity in the Social-Planful Brain.

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Caouette, Justin D; Hudson, Karen A; Bryan, Angela D; Feldstein Ewing, Sarah W

2018-05-14

To reduce rates of sexually transmitted infections (STIs) and unwanted pregnancy among adolescents, it is critical to investigate brain connectivity that may underlie adolescents' sexual health decision-making in the context of intercourse. This study explored relationships between adolescent condom use frequency and the brain's resting-state functional connectivity, to identify differential patterns of social-affective processing among sexually active youth. In this study, N = 143 sexually active adolescents (68.5% male, Mage = 16.2 years, SD = 1.06) completed magnetic resonance imaging and reported past 3-month frequency of condom use. Resting-state connectivity, seeded on a social region of the brain, the temporoparietal junction (TPJ), was assessed to determine its correspondence with protected sex (condom use). Condom use was associated with positive connectivity between the left TPJ and bilateral inferior frontal gyrus (IFG). This relationship was observed in adolescent males only; no connectivity differences were observed with adolescent females. This study reflects functional synchrony between nodes of the "social brain," including the TPJ, and a region of planfulness and control, the IFG. The relationship between these regions suggests that adolescents who have more coordinated systems of communication between these critical components of the brain are more likely to be successful in planning and engaging in safer sexual decision-making; for young males, this differentiated more frequent from less frequent condom use. In turn, interventions designed to reduce STIs/human immunodeficiency virus may benefit from targeting social-planfulness dimensions to help youth implement safer sex behaviors.

Network-based analysis reveals functional connectivity related to internet addiction tendency

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Tanya eWen

2016-02-01

Full Text Available IntroductionPreoccupation and compulsive use of the internet can have negative psychological effects, such that it is increasingly being recognized as a mental disorder. The present study employed network-based statistics to explore how whole-brain functional connections at rest is related to the extent of individual’s level of internet addiction, indexed by a self-rated questionnaire. We identified two topologically significant networks, one with connections that are positively correlated with internet addiction tendency, and one with connections negatively correlated with internet addiction tendency. The two networks are interconnected mostly at frontal regions, which might reflect alterations in the frontal region for different aspects of cognitive control (i.e., for control of internet usage and gaming skills. Next, we categorized the brain into several large regional subgroupings, and found that the majority of proportions of connections in the two networks correspond to the cerebellar model of addiction which encompasses the four-circuit model. Lastly, we observed that the brain regions with the most inter-regional connections associated with internet addiction tendency replicate those often seen in addiction literature, and is corroborated by our meta-analysis of internet addiction studies. This research provides a better understanding of large-scale networks involved in internet addiction tendency and shows that pre-clinical levels of internet addiction are associated with similar regions and connections as clinical cases of addiction.

Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.

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Dørum, Erlend S; Kaufmann, Tobias; Alnæs, Dag; Andreassen, Ole A; Richard, Geneviève; Kolskår, Knut K; Nordvik, Jan Egil; Westlye, Lars T

2017-03-01

Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task

Scholastic performance and functional connectivity of brain networks in children.

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Laura Chaddock-Heyman

Full Text Available One of the keys to understanding scholastic success is to determine the neural processes involved in school performance. The present study is the first to use a whole-brain connectivity approach to explore whether functional connectivity of resting state brain networks is associated with scholastic performance in seventy-four 7- to 9-year-old children. We demonstrate that children with higher scholastic performance across reading, math and language have more integrated and interconnected resting state networks, specifically the default mode network, salience network, and frontoparietal network. To add specificity, core regions of the dorsal attention and visual networks did not relate to scholastic performance. The results extend the cognitive role of brain networks in children as well as suggest the importance of network connectivity in scholastic success.

The Effects of Taekwondo Training on Brain Connectivity and Body Intelligence.

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Kim, Young Jae; Cha, Eun Joo; Kim, Sun Mi; Kang, Kyung Doo; Han, Doug Hyun

2015-07-01

Many studies have reported that Taekwondo training could improve body perception, control and brain activity, as assessed with an electroencephalogram. This study aimed to assess body intelligence and brain connectivity in children with Taekwondo training as compared to children without Taekwondo training. Fifteen children with Taekwondo training (TKD) and 13 age- and sex-matched children who had no previous experience of Taekwondo training (controls) were recruited. Body intelligence, clinical characteristics and brain connectivity in all children were assessed with the Body Intelligence Scale (BIS), self-report, and resting state functional magnetic resonance imaging. The mean BIS score in the TKD group was higher than that in the control group. The TKD group showed increased low-frequency fluctuations in the right frontal precentral gyrus and the right parietal precuneus, compared to the control group. The TKD group showed positive cerebellum vermis (lobe VII) seed to the right frontal, left frontal, and left parietal lobe. The control group showed positive cerebellum seed to the left frontal, parietal, and occipital cortex. Relative to the control group, the TKD group showed increased functional connectivity from cerebellum seed to the right inferior frontal gyrus. To the best of our knowledge, this is the first study to assess the effect of Taekwondo training on brain connectivity in children. Taekwondo training improved body intelligence and brain connectivity from the cerebellum to the parietal and frontal cortex.

Structural Graphical Lasso for Learning Mouse Brain Connectivity

KAUST Repository

Yang, Sen

2015-08-07

Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability of high-resolution brain imaging data. Sparse inverse covariance estimation with lasso and group lasso penalty has been demonstrated to be a powerful approach to discover brain networks. Motivated by the hierarchical structure of the brain networks, we consider the problem of estimating a graphical model with tree-structural regularization in this paper. The regularization encourages the graphical model to exhibit a brain-like structure. Specifically, in this hierarchical structure, hundreds of thousands of voxels serve as the leaf nodes of the tree. A node in the intermediate layer represents a region formed by voxels in the subtree rooted at that node. The whole brain is considered as the root of the tree. We propose to apply the tree-structural regularized graphical model to estimate the mouse brain network. However, the dimensionality of whole-brain data, usually on the order of hundreds of thousands, poses significant computational challenges. Efficient algorithms that are capable of estimating networks from high-dimensional data are highly desired. To address the computational challenge, we develop a screening rule which can quickly identify many zero blocks in the estimated graphical model, thereby dramatically reducing the computational cost of solving the proposed model. It is based on a novel insight on the relationship between screening and the so-called proximal operator that we first establish in this paper. We perform experiments on both synthetic data and real data from the Allen Developing Mouse Brain Atlas; results demonstrate the effectiveness and efficiency of the proposed approach.

The UCLA Multimodal Connectivity Database: A web-based platform for brain connectivity matrix sharing and analysis

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Jesse A. Brown

2012-11-01

Full Text Available Brain connectomics research has rapidly expanded using functional MRI (fMRI and diffusion-weighted MRI (dwMRI. A common product of these varied analyses is a connectivity matrix (CM. A CM stores the connection strength between any two regions (nodes in a brain network. This format is useful for several reasons: 1 it is highly distilled, with minimal data size and complexity, 2 graph theory can be applied to characterize the network’s topology, and 3 it retains sufficient information to capture individual differences such as age, gender, intelligence quotient, or disease state. Here we introduce the UCLA Multimodal Connectivity Database (http://umcd.humanconnectomeproject.org, an openly available website for brain network analysis and data sharing. The site is a repository for researchers to publicly share CMs derived from their data. The site also allows users to select any CM shared by another user, compute graph theoretical metrics on the site, visualize a report of results, or download the raw CM. To date, users have contributed over 2000 individual CMs, spanning different imaging modalities (fMRI, dwMRI and disorders (Alzheimer’s, autism, Attention Deficit Hyperactive Disorder. To demonstrate the site’s functionality, whole brain functional and structural connectivity matrices are derived from 60 subjects’ (ages 26-45 resting state fMRI (rs-fMRI and dwMRI data and uploaded to the site. The site is utilized to derive graph theory global and regional measures for the rs-fMRI and dwMRI networks. Global and nodal graph theoretical measures between functional and structural networks exhibit low correspondence. This example demonstrates how this tool can enhance the comparability of brain networks from different imaging modalities and studies. The existence of this connectivity-based repository should foster broader data sharing and enable larger-scale meta analyses comparing networks across imaging modality, age group, and disease state.

[Glucose homeostasis and gut-brain connection].

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De Vadder, Filipe; Mithieux, Gilles

2015-02-01

Since the XIX(th) century, the brain has been known for its role in regulating food intake (via the control of hunger sensation) and glucose homeostasis. Further interest has come from the discovery of gut hormones, which established a clear link between the gut and the brain in regulating glucose and energy homeostasis. The brain has two particular structures, the hypothalamus and the brainstem, which are sensitive to information coming either from peripheral organs or from the gut (via circulating hormones or nutrients) about the nutritional status of the organism. However, the efforts for a better understanding of these mechanisms have allowed to unveil a new gut-brain neural axis as a key regulator of the metabolic status of the organism. Certain nutrients control the hypothalamic homeostatic function via this axis. In this review, we describe how the gut is connected to the brain via different neural pathways, and how the interplay between these two organs drives the energy balance. © 2015 médecine/sciences – Inserm.

Brain Connectivity Studies in Schizophrenia: Unravelling the Effects of Antipsychotics

DEFF Research Database (Denmark)

Nejad, A.B.; Ebdrup, Bjørn Hylsebeck; Glenthøj, Birte Yding

2012-01-01

Impaired brain connectivity is a hallmark of schizophrenia brain dysfunction. However, the effect of drug treatment and challenges on the dysconnectivity of functional networks in schizophrenia is an understudied area. In this review, we provide an overview of functional magnetic resonance imaging...... studies examining dysconnectivity in schizophrenia and discuss the few studies which have also attempted to probe connectivity changes with antipsychotic drug treatment. We conclude with a discussion of possible avenues for further investigation....

Whole-brain structural connectivity in dyskinetic cerebral palsy and its association with motor and cognitive function.

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Ballester-Plané, Júlia; Schmidt, Ruben; Laporta-Hoyos, Olga; Junqué, Carme; Vázquez, Élida; Delgado, Ignacio; Zubiaurre-Elorza, Leire; Macaya, Alfons; Póo, Pilar; Toro, Esther; de Reus, Marcel A; van den Heuvel, Martijn P; Pueyo, Roser

2017-09-01

Dyskinetic cerebral palsy (CP) has long been associated with basal ganglia and thalamus lesions. Recent evidence further points at white matter (WM) damage. This study aims to identify altered WM pathways in dyskinetic CP from a standardized, connectome-based approach, and to assess structure-function relationship in WM pathways for clinical outcomes. Individual connectome maps of 25 subjects with dyskinetic CP and 24 healthy controls were obtained combining a structural parcellation scheme with whole-brain deterministic tractography. Graph theoretical metrics and the network-based statistic were applied to compare groups and to correlate WM state with motor and cognitive performance. Results showed a widespread reduction of WM volume in CP subjects compared to controls and a more localized decrease in degree (number of links per node) and fractional anisotropy (FA), comprising parieto-occipital regions and the hippocampus. However, supramarginal gyrus showed a significantly higher degree. At the network level, CP subjects showed a bilateral pathway with reduced FA, comprising sensorimotor, intraparietal and fronto-parietal connections. Gross and fine motor functions correlated with FA in a pathway comprising the sensorimotor system, but gross motor also correlated with prefrontal, temporal and occipital connections. Intelligence correlated with FA in a network with fronto-striatal and parieto-frontal connections, and visuoperception was related to right occipital connections. These findings demonstrate a disruption in structural brain connectivity in dyskinetic CP, revealing general involvement of posterior brain regions with relative preservation of prefrontal areas. We identified pathways in which WM integrity is related to clinical features, including but not limited to the sensorimotor system. Hum Brain Mapp 38:4594-4612, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Task-dependent activity and connectivity predict episodic memory network-based responses to brain stimulation in healthy aging.

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Vidal-Piñeiro, Dídac; Martin-Trias, Pablo; Arenaza-Urquijo, Eider M; Sala-Llonch, Roser; Clemente, Imma C; Mena-Sánchez, Isaias; Bargalló, Núria; Falcón, Carles; Pascual-Leone, Álvaro; Bartrés-Faz, David

2014-01-01

Transcranial magnetic stimulation (TMS) can affect episodic memory, one of the main cognitive hallmarks of aging, but the mechanisms of action remain unclear. To evaluate the behavioral and functional impact of excitatory TMS in a group of healthy elders. We applied a paradigm of repetitive TMS - intermittent theta-burst stimulation - over left inferior frontal gyrus in healthy elders (n = 24) and evaluated its impact on the performance of an episodic memory task with two levels of processing and the associated brain activity as captured by a pre and post fMRI scans. In the post-TMS fMRI we found TMS-related activity increases in left prefrontal and cerebellum-occipital areas specifically during deep encoding but not during shallow encoding or at rest. Furthermore, we found a task-dependent change in connectivity during the encoding task between cerebellum-occipital areas and the TMS-targeted left inferior frontal region. This connectivity change correlated with the TMS effects over brain networks. The results suggest that the aged brain responds to brain stimulation in a state-dependent manner as engaged by different tasks components and that TMS effect is related to inter-individual connectivity changes measures. These findings reveal fundamental insights into brain network dynamics in aging and the capacity to probe them with combined behavioral and stimulation approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Anomalous brain functional connectivity contributing to poor adaptive behavior in Down syndrome.

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Pujol, Jesus; del Hoyo, Laura; Blanco-Hinojo, Laura; de Sola, Susana; Macià, Dídac; Martínez-Vilavella, Gerard; Amor, Marta; Deus, Joan; Rodríguez, Joan; Farré, Magí; Dierssen, Mara; de la Torre, Rafael

2015-03-01

Research in Down syndrome has substantially progressed in the understanding of the effect of gene overexpression at the molecular level, but there is a paucity of information on the ultimate consequences on overall brain functional organization. We have assessed the brain functional status in Down syndrome using functional connectivity MRI. Resting-state whole-brain connectivity degree maps were generated in 20 Down syndrome individuals and 20 control subjects to identify sites showing anomalous synchrony with other areas. A subsequent region-of-interest mapping served to detail the anomalies and to assess their potential contribution to poor adaptive behavior. Down syndrome individuals showed higher regional connectivity in a ventral brain system involving the amygdala/anterior temporal region and the ventral aspect of both the anterior cingulate and frontal cortices. By contrast, lower functional connectivity was identified in dorsal executive networks involving dorsal prefrontal and anterior cingulate cortices and posterior insula. Both functional connectivity increases and decreases contributed to account for patient scoring on adaptive behavior related to communication skills. The data overall suggest a distinctive functional organization with system-specific anomalies associated with reduced adaptive efficiency. Opposite effects were identified on distinct frontal and anterior temporal structures and relative sparing of posterior brain areas, which is generally consistent with Down syndrome cognitive profile. Relevantly, measurable connectivity changes, as a marker of the brain functional anomaly, could have a role in the development of therapeutic strategies addressed to improve the quality of life in Down syndrome individuals. Copyright © 2014 Elsevier Ltd. All rights reserved.

Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury.

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De Simoni, Sara; Jenkins, Peter O; Bourke, Niall J; Fleminger, Jessica J; Hellyer, Peter J; Jolly, Amy E; Patel, Maneesh C; Cole, James H; Leech, Robert; Sharp, David J

2018-01-01

Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with measures of

The interface between neuroscience and neuro-psychoanalysis: focus on brain connectivity

Directory of Open Access Journals (Sweden)

Anatolia eSalone

2016-02-01

Full Text Available Over the past 20 years, the advent of advanced techniques has significantly enhanced our knowledge on the brain. Yet, our understanding of the physiological and pathological functioning of the mind is still far from being exhaustive. Both the localizationist and the reductionist neuroscientific approaches to psychiatric disorders have proven to be largely unsatisfactory and are outdated. Accruing evidence suggests that psychoanalysis can engage the neurosciences in a productive and mutually enriching dialogue that may further our understanding of psychiatric disorders. In particular, advances in brain connectivity research have provided evidence supporting the convergence of neuroscientific findings and psychoanalysis and helped characterize the circuitry and mechanisms that underlie higher brain functions. In the present paper we discuss how knowledge on brain connectivity can impact neuropsychoanalysis, with a particular focus on schizophrenia. Brain connectivity studies in schizophrenic patients indicate complex alterations in brain functioning and circuitry, with particular emphasis on the role of cortical midline structures and the default mode network. These networks seem to represent neural correlates of psychodynamic concepts central to the understanding of schizophrenia and of core psychopathological alterations of this disorder (i.e. ego disturbances and impaired primary process thinking.

The Interface between Neuroscience and Neuro-Psychoanalysis: Focus on Brain Connectivity

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Salone, Anatolia; Di Giacinto, Alessandra; Lai, Carlo; De Berardis, Domenico; Iasevoli, Felice; Fornaro, Michele; De Risio, Luisa; Santacroce, Rita; Martinotti, Giovanni; Giannantonio, Massimo Di

2016-01-01

Over the past 20 years, the advent of advanced techniques has significantly enhanced our knowledge on the brain. Yet, our understanding of the physiological and pathological functioning of the mind is still far from being exhaustive. Both the localizationist and the reductionist neuroscientific approaches to psychiatric disorders have proven to be largely unsatisfactory and are outdated. Accruing evidence suggests that psychoanalysis can engage the neurosciences in a productive and mutually enriching dialogue that may further our understanding of psychiatric disorders. In particular, advances in brain connectivity research have provided evidence supporting the convergence of neuroscientific findings and psychoanalysis and helped characterize the circuitry and mechanisms that underlie higher brain functions. In the present paper we discuss how knowledge on brain connectivity can impact neuropsychoanalysis, with a particular focus on schizophrenia. Brain connectivity studies in schizophrenic patients indicate complex alterations in brain functioning and circuitry, with particular emphasis on the role of cortical midline structures (CMS) and the default mode network (DMN). These networks seem to represent neural correlates of psychodynamic concepts central to the understanding of schizophrenia and of core psychopathological alterations of this disorder (i.e., ego disturbances and impaired primary process thinking). PMID:26869904

High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain

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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

Altered caudate connectivity is associated with executive dysfunction after traumatic brain injury

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De Simoni, Sara; Jenkins, Peter O; Bourke, Niall J; Fleminger, Jessica J; Jolly, Amy E; Patel, Maneesh C; Leech, Robert; Sharp, David J

2018-01-01

Abstract Traumatic brain injury often produces executive dysfunction. This characteristic cognitive impairment often causes long-term problems with behaviour and personality. Frontal lobe injuries are associated with executive dysfunction, but it is unclear how these injuries relate to corticostriatal interactions that are known to play an important role in behavioural control. We hypothesized that executive dysfunction after traumatic brain injury would be associated with abnormal corticostriatal interactions, a question that has not previously been investigated. We used structural and functional MRI measures of connectivity to investigate this. Corticostriatal functional connectivity in healthy individuals was initially defined using a data-driven approach. A constrained independent component analysis approach was applied in 100 healthy adult dataset from the Human Connectome Project. Diffusion tractography was also performed to generate white matter tracts. The output of this analysis was used to compare corticostriatal functional connectivity and structural integrity between groups of 42 patients with traumatic brain injury and 21 age-matched controls. Subdivisions of the caudate and putamen had distinct patterns of functional connectivity. Traumatic brain injury patients showed disruption to functional connectivity between the caudate and a distributed set of cortical regions, including the anterior cingulate cortex. Cognitive impairments in the patients were mainly seen in processing speed and executive function, as well as increased levels of apathy and fatigue. Abnormalities of caudate functional connectivity correlated with these cognitive impairments, with reductions in right caudate connectivity associated with increased executive dysfunction, information processing speed and memory impairment. Structural connectivity, measured using diffusion tensor imaging between the caudate and anterior cingulate cortex was impaired and this also correlated with

Enhanced functional connectivity properties of human brains during in-situ nature experience.

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Chen, Zheng; He, Yujia; Yu, Yuguo

2016-01-01

In this study, we investigated the impacts of in-situ nature and urban exposure on human brain activities and their dynamics. We randomly assigned 32 healthy right-handed college students (mean age = 20.6 years, SD = 1.6; 16 males) to a 20 min in-situ sitting exposure in either a nature (n = 16) or urban environment (n = 16) and measured their Electroencephalography (EEG) signals. Analyses revealed that a brief in-situ restorative nature experience may induce more efficient and stronger brain connectivity with enhanced small-world properties compared with a stressful urban experience. The enhanced small-world properties were found to be correlated with "coherent" experience measured by Perceived Restorativeness Scale (PRS). Exposure to nature also induces stronger long-term correlated activity across different brain regions with a right lateralization. These findings may advance our understanding of the functional activities during in-situ environmental exposures and imply that a nature or nature-like environment may potentially benefit cognitive processes and mental well-being.

An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging.

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Nielsen, Jared A; Zielinski, Brandon A; Ferguson, Michael A; Lainhart, Janet E; Anderson, Jeffrey S

2013-01-01

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "right-brained" network strength

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

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Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population

Effects of gender, digit ratio, and menstrual cycle on intrinsic brain functional connectivity: A whole-brain, voxel-wise exploratory study using simultaneous local and global functional connectivity mapping.

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Donishi, Tomohiro; Terada, Masaki; Kaneoke, Yoshiki

2018-01-01

Gender and sex hormones influence brain function, but their effects on functional network organization within the brain are not yet understood. We investigated the influence of gender, prenatal sex hormones (estimated by the 2D:4D digit ratio), and the menstrual cycle on the intrinsic functional network organization of the brain (as measured by 3T resting-state functional MRI (rs-fMRI)) using right-handed, age-matched university students (100 males and 100 females). The mean (± SD ) age was 20.9 ± 1.5 (range: 18-24) years and 20.8 ± 1.3 (range: 18-24) years for males and females, respectively. Using two parameters derived from the normalized alpha centrality analysis (one for local and another for global connectivity strength), we created mean functional connectivity strength maps. There was a significant difference between the male mean map and female mean map in the distributions of network properties in almost all cortical regions and the basal ganglia but not in the medial parietal, limbic, and temporal regions and the thalamus. A comparison between the mean map for the low 2D:4D digit ratio group (indicative of high exposure to testosterone during the prenatal period) and that for the high 2D:4D digit ratio group revealed a significant difference in the network properties of the medial parietal region for males and in the temporal region for females. The menstrual cycle affected network organization in the brain, which varied with the 2D:4D digit ratio. Most of these findings were reproduced with our other datasets created with different preprocessing steps. The results suggest that differences in gender, prenatal sex hormone exposure, and the menstrual cycle are useful for understanding the normal brain and investigating the mechanisms underlying the variable prevalence and symptoms of neurological and psychiatric diseases.

Brain activity and cognition: a connection from thermodynamics and information theory.

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Collell, Guillem; Fauquet, Jordi

2015-01-01

The connection between brain and mind is an important scientific and philosophical question that we are still far from completely understanding. A crucial point to our work is noticing that thermodynamics provides a convenient framework to model brain activity, whereas cognition can be modeled in information-theoretical terms. In fact, several models have been proposed so far from both approaches. A second critical remark is the existence of deep theoretical connections between thermodynamics and information theory. In fact, some well-known authors claim that the laws of thermodynamics are nothing but principles in information theory. Unlike in physics or chemistry, a formalization of the relationship between information and energy is currently lacking in neuroscience. In this paper we propose a framework to connect physical brain and cognitive models by means of the theoretical connections between information theory and thermodynamics. Ultimately, this article aims at providing further insight on the formal relationship between cognition and neural activity.

Brain activity and cognition: a connection from thermodynamics and information theory

Science.gov (United States)

Collell, Guillem; Fauquet, Jordi

2015-01-01

The connection between brain and mind is an important scientific and philosophical question that we are still far from completely understanding. A crucial point to our work is noticing that thermodynamics provides a convenient framework to model brain activity, whereas cognition can be modeled in information-theoretical terms. In fact, several models have been proposed so far from both approaches. A second critical remark is the existence of deep theoretical connections between thermodynamics and information theory. In fact, some well-known authors claim that the laws of thermodynamics are nothing but principles in information theory. Unlike in physics or chemistry, a formalization of the relationship between information and energy is currently lacking in neuroscience. In this paper we propose a framework to connect physical brain and cognitive models by means of the theoretical connections between information theory and thermodynamics. Ultimately, this article aims at providing further insight on the formal relationship between cognition and neural activity. PMID:26136709

Revealing the cerebello-ponto-hypothalamic pathway in the human brain.

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Kamali, Arash; Karbasian, Niloofar; Rabiei, Pejman; Cano, Andres; Riascos, Roy F; Tandon, Nitin; Arevalo, Octavio; Ocasio, Laura; Younes, Kyan; Khayat-Khoei, Mahsa; Mirbagheri, Saeedeh; Hasan, Khader M

2018-04-16

The cerebellum is shown to be involved in some limbic functions of the human brain such as emotion and affect. The major connection of the cerebellum with the limbic system is known to be through the cerebello-hypothalamic pathways. The consensus is that the projections from the cerebellar nuclei to the limbic system, and particularly the hypothalamus, or from the hypothalamus to the cerebellar nuclei, are through multisynaptic pathways in the bulbar reticular formation. The detailed anatomy of the pathways responsible for mediating these responses, however, is yet to be determined. Diffusion tensor imaging may be helpful in better visualizing the surgical anatomy of the cerebello-ponto-hypothalamic (CPH) pathway. This study aimed to investigate the utility of high-spatial-resolution diffusion tensor tractography for mapping the trajectory of the CPH tract in the human brain. Fifteen healthy adults were studied. We delineated, for the first time, the detailed trajectory of the CPH tract of the human brain in fifteen normal adult subjects using high-spatial-resolution diffusion tensor tractography. We further revealed the close relationship of the CPH tract with the optic tract, temporo-pontine tract, amygdalofugal tract and the fornix in the human brain. Copyright © 2018. Published by Elsevier B.V.

Meta-connectomics: human brain network and connectivity meta-analyses.

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Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Brain intrinsic network connectivity in individuals with frequent tanning behavior.

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Ketcherside, Ariel; Filbey, Francesca M; Aubert, Pamela M; Seibyl, John P; Price, Julianne L; Adinoff, Bryon

2018-05-01

Emergent studies suggest a bidirectional relationship between brain functioning and the skin. This neurocutaneous connection may be responsible for the reward response to tanning and, thus, may contribute to excessive tanning behavior. To date, however, this association has not yet been examined. To explore whether intrinsic brain functional connectivity within the default mode network (DMN) is related to indoor tanning behavior. Resting state functional connectivity (rsFC) was obtained in twenty adults (16 females) with a history of indoor tanning. Using a seed-based [(posterior cingulate cortex (PCC)] approach, the relationship between tanning severity and FC strength was assessed. Tanning severity was measured with symptom count from the Structured Clinical Interview for Tanning Abuse and Dependence (SITAD) and tanning intensity (lifetime indoor tanning episodes/years tanning). rsFC strength between the PCC and other DMN regions (left globus pallidus, left medial frontal gyrus, left superior frontal gyrus) is positively correlated with tanning symptom count. rsFC strength between the PCC and salience network regions (right anterior cingulate cortex, left inferior parietal lobe, left inferior temporal gyrus) is correlated with tanning intensity. Greater connectivity between tanning severity and DMN and salience network connectivity suggests that heightened self-awareness of salient stimuli may be a mechanism that underlies frequent tanning behavior. These findings add to the growing evidence of brain-skin connection and reflect dysregulation in the reward processing networks in those with frequent tanning.

Intrinsic brain connectivity related to age in young and middle aged adults.

Directory of Open Access Journals (Sweden)

Michelle Hampson

Full Text Available Age-related variations in resting state connectivity of the human brain were examined from young adulthood through middle age. A voxel-based network measure, degree, was used to assess age-related differences in tissue connectivity throughout the brain. Increases in connectivity with age were found in paralimbic cortical and subcortical regions. Decreases in connectivity were found in cortical regions, including visual areas and the default mode network. These findings differ from those of recent developmental studies examining earlier growth trajectories, and are consistent with known changes in cognitive function and emotional processing during mature aging. The results support and extend previous findings that relied on a priori definitions of regions of interest for their analyses. This approach of applying a voxel-based measure to examine the functional connectivity of individual tissue elements over time, without the need for a priori region of interest definitions, provides an important new tool in brain science.

Analyzing the association between functional connectivity of the brain and intellectual performance

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Pamplona, Gustavo S. P.; Santos Neto, Gérson S.; Rosset, Sara R. E.; Rogers, Baxter P.; Salmon, Carlos E. G.

2015-01-01

Measurements of functional connectivity support the hypothesis that the brain is composed of distinct networks with anatomically separated nodes but common functionality. A few studies have suggested that intellectual performance may be associated with greater functional connectivity in the fronto-parietal network and enhanced global efficiency. In this fMRI study, we performed an exploratory analysis of the relationship between the brain's functional connectivity and intelligence scores derived from the Portuguese language version of the Wechsler Adult Intelligence Scale (WAIS-III) in a sample of 29 people, born and raised in Brazil. We examined functional connectivity between 82 regions, including graph theoretic properties of the overall network. Some previous findings were extended to the Portuguese-speaking population, specifically the presence of small-world organization of the brain and relationships of intelligence with connectivity of frontal, pre-central, parietal, occipital, fusiform and supramarginal gyrus, and caudate nucleus. Verbal comprehension was associated with global network efficiency, a new finding. PMID:25713528

Analyzing the association between functional connectivity of the brain and intellectual performance

Directory of Open Access Journals (Sweden)

Gustavo Santo Pedro Pamplona

2015-02-01

Full Text Available Measurements of functional connectivity support the hypothesis that the brain is composed of distinct networks with anatomically separated nodes but common functionality. A few studies have suggested that intellectual performance may be associated with greater functional connectivity in the fronto-parietal network and enhanced global efficiency. In this fMRI study, we performed an exploratory analysis of the relationship between the brain's functional connectivity and intelligence scores derived from the Portuguese language version of the Wechsler Adult Intelligence Scale (WAIS-III in a sample of 29 people, born and raised in Brazil. We examined functional connectivity between 82 regions, including graph theoretic properties of the overall network. Some previous findings were extended to the Portuguese-speaking population, specifically the presence of small-world organization of the brain and relationships of intelligence with connectivity of frontal, pre-central, parietal, occipital, fusiform and supramarginal gyrus and caudate nucleus. Verbal comprehension was associated with global network efficiency, a new finding.

Directed connectivity of brain default networks in resting state using GCA and motif.

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Jiao, Zhuqing; Wang, Huan; Ma, Kai; Zou, Ling; Xiang, Jianbo

2017-06-01

Nowadays, there is a lot of interest in assessing functional interactions between key brain regions. In this paper, Granger causality analysis (GCA) and motif structure are adopted to study directed connectivity of brain default mode networks (DMNs) in resting state. Firstly, the time series of functional magnetic resonance imaging (fMRI) data in resting state were extracted, and the causal relationship values of the nodes representing related brain regions are analyzed in time domain to construct a default network. Then, the network structures were searched from the default networks of controls and patients to determine the fixed connection mode in the networks. The important degree of motif structures in directed connectivity of default networks was judged according to p-value and Z-score. Both node degree and average distance were used to analyze the effect degree an information transfer rate of brain regions in motifs and default networks, and efficiency of the network. Finally, activity and functional connectivity strength of the default brain regions are researched according to the change of energy distributions between the normals and the patients' brain regions. Experimental results demonstrate that, both normal subjects and stroke patients have some corresponding fixed connection mode of three nodes, and the efficiency and power spectrum of the patient's default network is somewhat lower than that of the normal person. In particular, the Right Posterior Cingulate Gyrus (PCG.R) has a larger change in functional connectivity and its activity. The research results verify the feasibility of the application of GCA and motif structure to study the functional connectivity of default networks in resting state.

Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder.

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Ecker, Christine; Ronan, Lisa; Feng, Yue; Daly, Eileen; Murphy, Clodagh; Ginestet, Cedric E; Brammer, Michael; Fletcher, Paul C; Bullmore, Edward T; Suckling, John; Baron-Cohen, Simon; Williams, Steve; Loth, Eva; Murphy, Declan G M

2013-08-06

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions that are accompanied by atypical brain connectivity. So far, in vivo evidence for atypical structural brain connectivity in ASD has mainly been based on neuroimaging studies of cortical white matter. However, genetic studies suggest that abnormal connectivity in ASD may also affect neural connections within the cortical gray matter. Such intrinsic gray-matter connections are inherently more difficult to describe in vivo but may be inferred from a variety of surface-based geometric features that can be measured using magnetic resonance imaging. Here, we present a neuroimaging study that examines the intrinsic cortico-cortical connectivity of the brain in ASD using measures of "cortical separation distances" to assess the global and local intrinsic "wiring costs" of the cortex (i.e., estimated length of horizontal connections required to wire the cortex within the cortical sheet). In a sample of 68 adults with ASD and matched controls, we observed significantly reduced intrinsic wiring costs of cortex in ASD, both globally and locally. Differences in global and local wiring cost were predominantly observed in fronto-temporal regions and also significantly predicted the severity of social and repetitive symptoms (respectively). Our study confirms that atypical cortico-cortical "connectivity" in ASD is not restricted to the development of white-matter connections but may also affect the intrinsic gray-matter architecture (and connectivity) within the cortical sheet. Thus, the atypical connectivity of the brain in ASD is complex, affecting both gray and white matter, and forms part of the core neural substrates underlying autistic symptoms.

Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity

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Finn, Emily S.; Shen, Xilin; Holahan, John M.; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E.; Shaywitz, Bennett A.; Constable, R. Todd

2013-01-01

Background Functional connectivity analyses of fMRI data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which may result in mixing distinct activation timecourses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Methods Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Results Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Conclusions Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words based on their visual properties, while DYS readers recruit altered reading circuits and rely on laborious phonology-based “sounding out” strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. PMID:24124929

The Effects of Long Duration Bed Rest on Brain Functional Connectivity and Sensorimotor Functioning

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Cassady, K.; Koppelmans, V.; De Dios, Y.; Stepanyan, V.; Szecsy, D.; Gadd, N.; Wood, S.; Reuter-Lorenz, P.; Castenada, R. Riascos; Kofman, I.;

An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging.

Directory of Open Access Journals (Sweden)

Jared A Nielsen

Full Text Available Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction and language regions (e.g., Broca Area and Wernicke Area, whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields. Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "right-brained

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

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Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

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Yiming Fan

2017-09-01

Full Text Available Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying functional connectivity patterns of the developing and aging brain. Normal brain development is characterized by continuous and significant network evolution through infancy, childhood, and adolescence, following specific maturational patterns. Normal aging is related to some resting state brain networks disruption, which are associated with certain cognitive decline. It is a big challenge to design an integral metric to track connectome evolution patterns across the lifespan, which is to understand the principles of network organization in the human brain. In this study, we first defined a brain network eigen-entropy (NEE based on the energy probability (EP of each brain node. Next, we used the NEE to characterize the lifespan orderness trajectory of the whole-brain functional connectivity of 173 healthy individuals ranging in age from 7 to 85 years. The results revealed that during the lifespan, the whole-brain NEE exhibited a significant non-linear decrease and that the EP distribution shifted from concentration to wide dispersion, implying orderness enhancement of functional connectome over age. Furthermore, brain regions with significant EP changes from the flourishing (7–20 years to the youth period (23–38 years were mainly located in the right prefrontal cortex and basal ganglia, and were involved in emotion regulation and executive function in coordination with the action of the sensory system, implying that self-awareness and voluntary control performance significantly changed during neurodevelopment. However, the changes from the youth period to middle age (40–59 years were located in the mesial temporal lobe and caudate, which are associated with long-term memory, implying that the memory of the human brain begins to decline with age during this period. Overall, the findings suggested that the human connectome

Morphological brain plasticity induced by musical expertise is accompanied by modulation of functional connectivity at rest.

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Fauvel, Baptiste; Groussard, Mathilde; Chételat, Gaël; Fouquet, Marine; Landeau, Brigitte; Eustache, Francis; Desgranges, Béatrice; Platel, Hervé

2014-04-15

The aim of this study was to explore whether musical practice-related gray matter increases in brain regions are accompanied by modifications in their resting-state functional connectivity. 16 young musically experienced adults and 17 matched nonmusicians underwent an anatomical magnetic resonance imaging (MRI) and a resting-state functional MRI (rsfMRI). A whole-brain two-sample t test run on the T1-weighted structural images revealed four clusters exhibiting significant increases in gray matter (GM) volume in the musician group, located within the right posterior and middle cingulate gyrus, left superior temporal gyrus and right inferior orbitofrontal gyrus. Each cluster was used as a seed region to generate and compare whole-brain resting-state functional connectivity maps. The two clusters within the cingulate gyrus exhibited greater connectivity for musicians with the right prefrontal cortex and left temporal pole, which play a role in autobiographical and semantic memory, respectively. The cluster in the left superior temporal gyrus displayed enhanced connectivity with several language-related areas (e.g., left premotor cortex, bilateral supramarginal gyri). Finally, the cluster in the right inferior frontal gyrus displayed more synchronous activity at rest with claustrum, areas thought to play a role in binding sensory and motor information. We interpreted these findings as the consequence of repeated collaborative use in general networks supporting some of the memory, perceptual-motor and emotional features of musical practice. Copyright © 2014 Elsevier Inc. All rights reserved.

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

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Bauer, Corinna M.; Hirsch, Gabriella V.; Zajac, Lauren; Koo, Bang-Bon; Collignon, Olivier

2017-01-01

In the setting of profound ocular blindness, numerous lines of evidence demonstrate the existence of dramatic anatomical and functional changes within the brain. However, previous studies based on a variety of distinct measures have often provided inconsistent findings. To help reconcile this issue, we used a multimodal magnetic resonance (MR)-based imaging approach to provide complementary structural and functional information regarding this neuroplastic reorganization. This included gray matter structural morphometry, high angular resolution diffusion imaging (HARDI) of white matter connectivity and integrity, and resting state functional connectivity MRI (rsfcMRI) analysis. When comparing the brains of early blind individuals to sighted controls, we found evidence of co-occurring decreases in cortical volume and cortical thickness within visual processing areas of the occipital and temporal cortices respectively. Increases in cortical volume in the early blind were evident within regions of parietal cortex. Investigating white matter connections using HARDI revealed patterns of increased and decreased connectivity when comparing both groups. In the blind, increased white matter connectivity (indexed by increased fiber number) was predominantly left-lateralized, including between frontal and temporal areas implicated with language processing. Decreases in structural connectivity were evident involving frontal and somatosensory regions as well as between occipital and cingulate cortices. Differences in white matter integrity (as indexed by quantitative anisotropy, or QA) were also in general agreement with observed pattern changes in the number of white matter fibers. Analysis of resting state sequences showed evidence of both increased and decreased functional connectivity in the blind compared to sighted controls. Specifically, increased connectivity was evident between temporal and inferior frontal areas. Decreases in functional connectivity were observed

Adapting Parcellation Schemes to Study Fetal Brain Connectivity in Serial Imaging Studies

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Cheng, Xi; Wilm, Jakob; Seshamani, Sharmishtaa

2013-01-01

A crucial step in studying brain connectivity is the definition of the Regions Of Interest (ROI's) which are considered as nodes of a network graph. These ROI's identified in structural imaging reflect consistent functional regions in the anatomies being compared. However in serial studies...... of the developing fetal brain such functional and associated structural markers are not consistently present over time. In this study we adapt two non-atlas based parcellation schemes to study the development of connectivity networks of a fetal monkey brain using Diffusion Weighted Imaging techniques. Results...... demonstrate that the fetal brain network exhibits small-world characteristics and a pattern of increased cluster coefficients and decreased global efficiency. These findings may provide a route to creating a new biomarker for healthy fetal brain development....

A Systematic Review of Investigations into Functional Brain Connectivity Following Spinal Cord Injury

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Alkinoos Athanasiou

2017-10-01

Full Text Available Background: Complete or incomplete spinal cord injury (SCI results in varying degree of motor, sensory and autonomic impairment. Long-lasting, often irreversible disability results from disconnection of efferent and afferent pathways. How does this disconnection affect brain function is not so clear. Changes in brain organization and structure have been associated with SCI and have been extensively studied and reviewed. Yet, our knowledge regarding brain connectivity changes following SCI is overall lacking.Methods: In this study we conduct a systematic review of articles regarding investigations of functional brain networks following SCI, searching on PubMed, Scopus and ScienceDirect according to PRISMA-P 2015 statement standards.Results: Changes in brain connectivity have been shown even during the early stages of the chronic condition and correlate with the degree of neurological impairment. Connectivity changes appear as dynamic post-injury procedures. Sensorimotor networks of patients and healthy individuals share similar patterns but new functional interactions have been identified as unique to SCI networks.Conclusions: Large-scale, multi-modal, longitudinal studies on SCI patients are needed to understand how brain network reorganization is established and progresses through the course of the condition. The expected insight holds clinical relevance in preventing maladaptive plasticity after SCI through individualized neurorehabilitation, as well as the design of connectivity-based brain-computer interfaces and assistive technologies for SCI patients.

Lagged and instantaneous dynamical influences related to brain structural connectivity

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Carmen eAlonso Montes

2015-07-01

Full Text Available Contemporary neuroimaging methods can shed light on the basis of human neural and cognitive specializations, with important implications for neuroscience and medicine. Indeed, different MRI acquisitions provide different brain networks at the macroscale; whilst diffusion-weighted MRI (dMRI provides a structural connectivity (SC coincident with the bundles of parallel fibers between brain areas, functional MRI (fMRI accounts for the variations in the blood-oxygenation-level-dependent T2* signal, providing functional connectivity (FC. Understanding the precise relation between FC and SC, that is, between brain dynamics and structure, is still a challenge for neuroscience.To investigate this problem, we acquired data at rest and built the corresponding SC (with matrix elements corresponding to the fiber number between brain areas to be compared with FC connectivity matrices obtained by three different methods: directed dependencies by an exploratory version of structural equation modeling (eSEM, linear correlations (C and partial correlations (PC. We also considered the possibility of using lagged correlations in time series; in particular, we compared a lagged version of eSEM and Granger causality (GC. Our results were two-fold: firstly, eSEM performance in correlating with SC was comparable to those obtained from C and PC, but eSEM (not C, nor PC provides information about directionality of the functional interactions. Second, interactions on a time scale much smaller than the sampling time, captured by instantaneous connectivity methods, are much more related to SC than slow directed influences captured by the lagged analysis. Indeed the performance in correlating with SC was much worse for GC and for the lagged version of eSEM. We expect these results to supply further insights to the interplay between SC and functional patterns, an important issue in the study of brain physiology and function.

Enhanced functional connectivity properties of human brains during in-situ nature experience

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Zheng Chen

2016-07-01

Full Text Available In this study, we investigated the impacts of in-situ nature and urban exposure on human brain activities and their dynamics. We randomly assigned 32 healthy right-handed college students (mean age = 20.6 years, SD = 1.6; 16 males to a 20 min in-situ sitting exposure in either a nature (n = 16 or urban environment (n = 16 and measured their Electroencephalography (EEG signals. Analyses revealed that a brief in-situ restorative nature experience may induce more efficient and stronger brain connectivity with enhanced small-world properties compared with a stressful urban experience. The enhanced small-world properties were found to be correlated with “coherent” experience measured by Perceived Restorativeness Scale (PRS. Exposure to nature also induces stronger long-term correlated activity across different brain regions with a right lateralization. These findings may advance our understanding of the functional activities during in-situ environmental exposures and imply that a nature or nature-like environment may potentially benefit cognitive processes and mental well-being.

Dynamic Changes in Amygdala Psychophysiological Connectivity Reveal Distinct Neural Networks for Facial Expressions of Basic Emotions.

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Diano, Matteo; Tamietto, Marco; Celeghin, Alessia; Weiskrantz, Lawrence; Tatu, Mona-Karina; Bagnis, Arianna; Duca, Sergio; Geminiani, Giuliano; Cauda, Franco; Costa, Tommaso

2017-03-27

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.

Altered Brain Functional Connectivity in Betel Quid-Dependent Chewers

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Xiaojun Huang

2017-11-01

Full Text Available BackgroundBetel quid (BQ is a common psychoactive substance worldwide with particularly high usage in many Asian countries. This study aimed to explore the effect of BQ use on functional connectivity by comparing global functional brain networks and their subset between BQ chewers and healthy controls (HCs.MethodsResting-state functional magnetic resonance imaging (fMRI was obtained from 24 betel quid-dependent (BQD male chewers and 27 healthy male individuals on a 3.0T scanner. We used independent component analysis (ICA to determine components that represent the brain’s functional networks and their spatial aspects of functional connectivity. Two sample t-tests were used to identify the functional connectivity differences in each network between these two groups.ResultsSeventeen networks were identified by ICA. Nine of them showed connectivity differences between BQD and HCs (two sample t-tests, p < 0.001 uncorrected. We found increased functional connectivity in the orbitofrontal, bilateral frontoparietal, frontotemporal, occipital/parietal, frontotemporal/cerebellum, and temporal/limbic networks, and decreased connectivity in the parietal and medial frontal/anterior cingulate networks in the BQD compared to the HCs. The betel quid dependence scale scores were positively related to the increased functional connectivity in the orbitofrontal (r = 0.39, p = 0.03 while negatively related to the decreased functional connectivity in medial frontal/anterior cingulate networks (r = −0.35, p = 0.02.DiscussionOur findings provide further evidence that BQ chewing may lead to brain functional connectivity changes, which may play a key role in the psychological and physiological effects of BQ.

Connections that Count: Brain-Computer Interface Enables the Profoundly Paralyzed to Communicate

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... Home Current Issue Past Issues Connections that Count: Brain-Computer Interface Enables the Profoundly Paralyzed to Communicate Past Issues / ... of this page please turn Javascript on. A brain-computer interface (BCI) system This brain-computer interface (BCI) system ...

Frequency of Maternal Touch Predicts Resting Activity and Connectivity of the Developing Social Brain.

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Brauer, Jens; Xiao, Yaqiong; Poulain, Tanja; Friederici, Angela D; Schirmer, Annett

2016-08-01

Previous behavioral research points to a positive relationship between maternal touch and early social development. Here, we explored the brain correlates of this relationship. The frequency of maternal touch was recorded for 43 five-year-old children during a 10 min standardized play session. Additionally, all children completed a resting-state functional magnetic resonance imaging session. Investigating the default mode network revealed a positive relation between the frequency of maternal touch and activity in the right posterior superior temporal sulcus (pSTS) extending into the temporo-parietal junction. Using this effect as a seed in a functional connectivity analysis identified a network including extended bilateral regions along the temporal lobe, bilateral frontal cortex, and left insula. Compared with children with low maternal touch, children with high maternal touch showed additional connectivity with the right dorso-medial prefrontal cortex. Together these results support the notion that childhood tactile experiences shape the developing "social brain" with a particular emphasis on a network involved in mentalizing. © The Author 2016. Published by Oxford University Press.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

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Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

2017-02-01

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Gender differences in functional connectivities between insular subdivisions and selective pain-related brain structures.

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Dai, Yu-Jie; Zhang, Xin; Yang, Yang; Nan, Hai-Yan; Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Bo; Zhang, Jin; Qiu, Zi-Yu; Gao, Yi; Cui, Guang-Bin; Chen, Bi-Liang; Wang, Wen

2018-03-14

The incidence of pain disorders in women is higher than in men, making gender differences in pain a research focus. The human insular cortex is an important brain hub structure for pain processing and is divided into several subdivisions, serving different functions in pain perception. Here we aimed to examine the gender differences of the functional connectivities (FCs) between the twelve insular subdivisions and selected pain-related brain structures in healthy adults. Twenty-six healthy males and 11 age-matched healthy females were recruited in this cross-sectional study. FCs between the 12 insular subdivisions (as 12 regions of interest (ROIs)) and the whole brain (ROI-whole brain level) or 64 selected pain-related brain regions (64 ROIs, ROI-ROI level) were measured between the males and females. Significant gender differences in the FCs of the insular subdivisions were revealed: (1) The FCs between the dorsal dysgranular insula (dId) and other brain regions were significantly increased in males using two different techniques (ROI-whole brain and ROI-ROI analyses); (2) Based on the ROI-whole brain analysis, the FC increases in 4 FC-pairs were observed in males, including the left dId - the right median cingulate and paracingulate/ right posterior cingulate gyrus/ right precuneus, the left dId - the right median cingulate and paracingulate, the left dId - the left angular as well as the left dId - the left middle frontal gyrus; (3) According to the ROI-ROI analysis, increased FC between the left dId and the right rostral anterior cingulate cortex was investigated in males. In summary, the gender differences in the FCs of the insular subdivisions with pain-related brain regions were revealed in the current study, offering neuroimaging evidence for gender differences in pain processing. ClinicalTrials.gov, NCT02820974 . Registered 28 June 2016.

Short parietal lobe connections of the human and monkey brain

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Catani, Marco; Robertsson, Naianna; Beyh, Ahmad

2017-01-01

projections were reconstructed for both species and results compared to identify similarities or differences in tract anatomy (i.e., trajectories and cortical projections). In addition, post-mortem dissections were performed in a human brain. The largest tract identified in both human and monkey brains...... and angular gyri of the inferior parietal lobule in humans but only to the supramarginal gyrus in the monkey brain. The third tract connects the postcentral gyrus to the anterior region of the superior parietal lobule and is more prominent in monkeys compared to humans. Finally, short U-shaped fibres...... and monkeys with some differences for those areas that have cytoarchitectonically distinct features in humans. The overall pattern of intraparietal connectivity supports the special role of the inferior parietal lobule in cognitive functions characteristic of humans....

Large Scale Computing for the Modelling of Whole Brain Connectivity

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Albers, Kristoffer Jon

organization of the brain in continuously increasing resolution. From these images, networks of structural and functional connectivity can be constructed. Bayesian stochastic block modelling provides a prominent data-driven approach for uncovering the latent organization, by clustering the networks into groups...... of neurons. Relying on Markov Chain Monte Carlo (MCMC) simulations as the workhorse in Bayesian inference however poses significant computational challenges, especially when modelling networks at the scale and complexity supported by high-resolution whole-brain MRI. In this thesis, we present how to overcome...... these computational limitations and apply Bayesian stochastic block models for un-supervised data-driven clustering of whole-brain connectivity in full image resolution. We implement high-performance software that allows us to efficiently apply stochastic blockmodelling with MCMC sampling on large complex networks...

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy.

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Wirsich, Jonathan; Perry, Alistair; Ridley, Ben; Proix, Timothée; Golos, Mathieu; Bénar, Christian; Ranjeva, Jean-Philippe; Bartolomei, Fabrice; Breakspear, Michael; Jirsa, Viktor; Guye, Maxime

2016-01-01

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain. We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome. In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

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

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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.

Exploring the Associations Between Intrinsic Brain Connectivity and Creative Ability Using Functional Connectivity Strength and Connectome Analysis.

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Gao, Zhenni; Zhang, Delong; Liang, Aiying; Liang, Bishan; Wang, Zengjian; Cai, Yuxuan; Li, Junchao; Gao, Mengxia; Liu, Xiaojin; Chang, Song; Jiao, Bingqing; Huang, Ruiwang; Liu, Ming

2017-11-01

The present study aimed to explore the association between resting-state functional connectivity and creativity ability. Toward this end, the figural Torrance Tests of Creative Thinking (TTCT) scores were collected from 180 participants. Based on the figural TTCT measures, we collected resting-state functional magnetic resonance imaging data for participants with two different levels of creativity ability (a high-creativity group [HG, n = 22] and a low-creativity group [LG, n = 20]). For the aspect of group difference, this study combined voxel-wise functional connectivity strength (FCS) and seed-based functional connectivity to identify brain regions with group-change functional connectivity. Furthermore, the connectome properties of the identified regions and their associations with creativity were investigated using the permutation test, discriminative analysis, and brain-behavior correlation analysis. The results indicated that there were 4 regions with group differences in FCS, and these regions were linked to 30 other regions, demonstrating different functional connectivity between the groups. Together, these regions form a creativity-related network, and we observed higher network efficiency in the HG compared with the LG. The regions involved in the creativity network were widely distributed across the modality-specific/supramodality cerebral cortex, subcortex, and cerebellum. Notably, properties of regions in the supramodality networks (i.e., the default mode network and attention network) carried creativity-level discriminative information and were significantly correlated with the creativity performance. Together, these findings demonstrate a link between intrinsic brain connectivity and creative ability, which should provide new insights into the neural basis of creativity.

Assessing Brain–Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions

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Federico Gennaro

2018-02-01

Full Text Available Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography (EEG is capable of non-invasively measuring cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity. This step marked a new opportunity for the investigation of the brains’ role while moving and was tagged mobile brain/body imaging (MoBI. This methodology involves simultaneous mobile recording of brain activity with several other body behavioral variables (e.g., muscle activity and kinematics, through wireless recording wearable devices/sensors. Notably, several MoBI studies using EEG–EMG approaches recently showed that the brain is functionally connected to the muscles and active throughout the whole gait cycle and, thus, rejecting the long-lasting idea of a solely spinal-driven bipedalism. However, MoBI and brain/muscle connectivity assessments during human locomotion are still in their fledgling state of investigation. Mobile brain/body imaging approaches hint toward promising opportunities; however, there are some remaining pitfalls that need to be resolved before considering their routine clinical use. This article discusses several of these pitfalls and proposes research to address them. Examples relate to the validity, reliability, and reproducibility of this method in ecologically valid scenarios and in different populations. Furthermore, whether brain/muscle connectivity within the MoBI framework represents a potential biomarker in neuromuscular syndromes where gait disturbances are evident (e.g., age-related sarcopenia remains to be determined.

Markov models for fMRI correlation structure: Is brain functional connectivity small world, or decomposable into networks?

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Varoquaux, G; Gramfort, A; Poline, J B; Thirion, B

2012-01-01

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Resting-state EEG oscillatory dynamics in fragile X syndrome: abnormal functional connectivity and brain network organization.

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Melle J W van der Molen

Full Text Available Disruptions in functional connectivity and dysfunctional brain networks are considered to be a neurological hallmark of neurodevelopmental disorders. Despite the vast literature on functional brain connectivity in typical brain development, surprisingly few attempts have been made to characterize brain network integrity in neurodevelopmental disorders. Here we used resting-state EEG to characterize functional brain connectivity and brain network organization in eight males with fragile X syndrome (FXS and 12 healthy male controls. Functional connectivity was calculated based on the phase lag index (PLI, a non-linear synchronization index that is less sensitive to the effects of volume conduction. Brain network organization was assessed with graph theoretical analysis. A decrease in global functional connectivity was observed in FXS males for upper alpha and beta frequency bands. For theta oscillations, we found increased connectivity in long-range (fronto-posterior and short-range (frontal-frontal and posterior-posterior clusters. Graph theoretical analysis yielded evidence of increased path length in the theta band, suggesting that information transfer between brain regions is particularly impaired for theta oscillations in FXS. These findings are discussed in terms of aberrant maturation of neuronal oscillatory dynamics, resulting in an imbalance in excitatory and inhibitory neuronal circuit activity.

Differences in interregional brain connectivity in children with unilateral hearing loss.

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Jung, Matthew E; Colletta, Miranda; Coalson, Rebecca; Schlaggar, Bradley L; Lieu, Judith E C

2017-11-01

To identify functional network architecture differences in the brains of children with unilateral hearing loss (UHL) using resting-state functional-connectivity magnetic resonance imaging (rs-fcMRI). Prospective observational study. Children (7 to 17 years of age) with severe to profound hearing loss in one ear, along with their normal hearing (NH) siblings, were recruited and imaged using rs-fcMRI. Eleven children had right UHL; nine had left UHL; and 13 had normal hearing. Forty-one brain regions of interest culled from established brain networks such as the default mode (DMN); cingulo-opercular (CON); and frontoparietal networks (FPN); as well as regions for language, phonological, and visual processing, were analyzed using regionwise correlations and conjunction analysis to determine differences in functional connectivity between the UHL and normal hearing children. When compared to the NH group, children with UHL showed increased connectivity patterns between multiple networks, such as between the CON and visual processing centers. However, there were decreased, as well as aberrant connectivity patterns with the coactivation of the DMN and FPN, a relationship that usually is negatively correlated. Children with UHL demonstrate multiple functional connectivity differences between brain networks involved with executive function, cognition, and language comprehension that may represent adaptive as well as maladaptive changes. These findings suggest that possible interventions or habilitation, beyond amplification, might be able to affect some children's requirement for additional help at school. 3b. Laryngoscope, 127:2636-2645, 2017. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Community structure in networks of functional connectivity: resolving functional organization in the rat brain with pharmacological MRI.

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Schwarz, Adam J; Gozzi, Alessandro; Bifone, Angelo

2009-08-01

In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline). This approach resulted in bilaterally symmetric sub-networks corresponding to meaningful anatomical and functional connectivity pathways consistent with the purported mechanism of action of each drug. Interestingly, common features across all three networks revealed two groups of tightly coupled brain structures that responded as functional units independent of the specific neurotransmitter systems stimulated by the drug challenge, including a network involving the prefrontal cortex and sub-cortical regions extending from the striatum to the amygdala. This finding suggests that each of these networks includes general underlying features of the functional organization of the rat brain.

Distinct phasic and sustained brain responses and connectivity of amygdala and bed nucleus of the stria terminalis during threat anticipation in panic disorder.

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Brinkmann, L; Buff, C; Feldker, K; Tupak, S V; Becker, M P I; Herrmann, M J; Straube, T

2017-11-01

Panic disorder (PD) patients are constantly concerned about future panic attacks and exhibit general hypersensitivity to unpredictable threat. We aimed to reveal phasic and sustained brain responses and functional connectivity of the amygdala and the bed nucleus of the stria terminalis (BNST) during threat anticipation in PD. Using functional magnetic resonance imaging (fMRI), we investigated 17 PD patients and 19 healthy controls (HC) during anticipation of temporally unpredictable aversive and neutral sounds. We used a phasic and sustained analysis model to disentangle temporally dissociable brain activations. PD patients compared with HC showed phasic amygdala and sustained BNST responses during anticipation of aversive v. neutral stimuli. Furthermore, increased phasic activation was observed in anterior cingulate cortex (ACC), insula and prefrontal cortex (PFC). Insula and PFC also showed sustained activation. Functional connectivity analyses revealed partly distinct phasic and sustained networks. We demonstrate a role for the BNST during unpredictable threat anticipation in PD and provide first evidence for dissociation between phasic amygdala and sustained BNST activation and their functional connectivity. In line with a hypersensitivity to uncertainty in PD, our results suggest time-dependent involvement of brain regions related to fear and anxiety.

Progressively Disrupted Brain Functional Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment Patients.

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Sang, Linqiong; Chen, Lin; Wang, Li; Zhang, Jingna; Zhang, Ye; Li, Pengyue; Li, Chuanming; Qiu, Mingguo

2018-01-01

Cognitive impairment caused by subcortical ischemic vascular disease (SIVD) has been elucidated by many neuroimaging studies. However, little is known regarding the changes in brain functional connectivity networks in relation to the severity of cognitive impairment in SIVD. In the present study, 20 subcortical ischemic vascular cognitive impairment no dementia patients (SIVCIND) and 20 dementia patients (SIVaD) were enrolled; additionally, 19 normal controls were recruited. Each participant underwent a resting-state functional MRI scan. Whole-brain functional networks were analyzed with graph theory and network-based statistics (NBS) to study the functional organization of networks and find alterations in functional connectivity among brain regions. After adjustments for age, gender, and duration of formal education, there were significant group differences for two network functional organization indices, global efficiency and local efficiency, which decreased (NC > SIVCIND > SIVaD) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, p  impairment worsened, with an increased number of decreased connections between brain regions. We also observed more reductions in nodal efficiency in the prefrontal and temporal cortices for SIVaD than for SIVCIND. These findings indicated a progressively disrupted pattern of the brain functional connectivity network with increased cognitive impairment and showed promise for the development of reliable biomarkers of network metric changes related to cognitive impairment caused by SIVD.

Brain network connectivity in individuals with schizophrenia and their siblings.

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Repovs, Grega; Csernansky, John G; Barch, Deanna M

2011-05-15

Research on brain activity in schizophrenia has shown that changes in the function of any single region cannot explain the range of cognitive and affective impairments in this illness. Rather, neural circuits that support sensory, cognitive, and emotional processes are now being investigated as substrates for cognitive and affective impairments in schizophrenia, a shift in focus consistent with long-standing hypotheses about schizophrenia as a disconnection syndrome. Our goal was to further examine alterations in functional connectivity within and between the default mode network and three cognitive control networks (frontal-parietal, cingulo-opercular, and cerebellar) as a basis for such impairments. Resting state functional magnetic resonance imaging was collected from 40 individuals with DSM-IV-TR schizophrenia, 31 siblings of individuals with schizophrenia, 15 healthy control subjects, and 18 siblings of healthy control subjects while they rested quietly with their eyes closed. Connectivity metrics were compared between patients and control subjects for both within- and between-network connections and were used to predict clinical symptoms and cognitive function. Individuals with schizophrenia showed reduced distal and somewhat enhanced local connectivity between the cognitive control networks compared with control subjects. Additionally, greater connectivity between the frontal-parietal and cerebellar regions was robustly predictive of better cognitive performance across groups and predictive of fewer disorganization symptoms among patients. These results are consistent with the hypothesis that impairments of executive function and cognitive control result from disruption in the coordination of activity across brain networks and additionally suggest that these might reflect impairments in normal pattern of brain connectivity development. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

From Brain-Environment Connections to Temporal Dynamics and Social Interaction: Principles of Human Brain Function.

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Hari, Riitta

2017-06-07

Experimental data about brain function accumulate faster than does our understanding of how the brain works. To tackle some general principles at the grain level of behavior, I start from the omnipresent brain-environment connection that forces regularities of the physical world to shape the brain. Based on top-down processing, added by sparse sensory information, people are able to form individual "caricature worlds," which are similar enough to be shared among other people and which allow quick and purposeful reactions to abrupt changes. Temporal dynamics and social interaction in natural environments serve as further essential organizing principles of human brain function. Copyright © 2017 Elsevier Inc. All rights reserved.

Developmental changes in brain connectivity assessed using the sleep EEG.

OpenAIRE

Tarokh L; Carskadon M A; Achermann P

2010-01-01

Adolescence represents a time of significant cortical restructuring. Current theories posit that during this period connections between frequently utilized neural networks are strengthened while underutilized synaptic connections are discarded. The aim of the present study was to examine the developmental evolution of connectivity between brain regions using the sleep EEG. All night sleep EEG recordings in two longitudinal cohorts (children and teens) followed at 1.5 3 year intervals and one ...

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

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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

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

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Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

Magnetic resonance imaging of functional connectivity in Parkinson disease in the resting brain

International Nuclear Information System (INIS)

Liu Xian; Liu Bo; Luo Xiaodong; Li Ningna; Chen Zhiguang; Chen Jun

2009-01-01

Objective: To investigate functional connectivity changes in Parkinson disease in the resting brain using functional magnetic resonance imaging. Methods: Nine patients with Parkinson disease and eight age-matched healthy volunteers were entered into the study. The bilateral globus pallidus were chosen as seed points, the functional MR data acquired in the resting state were processed to investigate functional connectivity in PD patients and the results were compared with those of the controls. Results: In age-matched healthy controls, there are regions which had functional connectivity with bilateral globus pallidus, including bilateral temporal poles, bilateral hippocampus, bilateral thalami, posterior cingulate cortex, right middle occipital gyms and right superior parietal gyms. In PD patients, brain regions including bilateral cerebellum, left hippocampus, bilateral superior temporal gyri, left inferior frontal gyrus, left middle frontal gyrus, left precentral gyrus, left inferior parietal gyrus and left superior parietal gyrus, had functional connectivity with bilateral globus pallidus. Compared to healthy controls, increased functional connectivity in bilateral cerebellum, bilateral temporal lobes, left frontal lobe and left parietal lobe, and decreased functional connectivity in bilateral thalami were observed in PD patients. Conclusion: Abnormal changes of brain functional connectivity exists in Parkinson's disease in the resting state. (authors)

Single-trial effective brain connectivity patterns enhance discriminability of mental imagery tasks

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Rathee, Dheeraj; Cecotti, Hubert; Prasad, Girijesh

2017-10-01

Objective. The majority of the current approaches of connectivity based brain-computer interface (BCI) systems focus on distinguishing between different motor imagery (MI) tasks. Brain regions associated with MI are anatomically close to each other, hence these BCI systems suffer from low performances. Our objective is to introduce single-trial connectivity feature based BCI system for cognition imagery (CI) based tasks wherein the associated brain regions are located relatively far away as compared to those for MI. Approach. We implemented time-domain partial Granger causality (PGC) for the estimation of the connectivity features in a BCI setting. The proposed hypothesis has been verified with two publically available datasets involving MI and CI tasks. Main results. The results support the conclusion that connectivity based features can provide a better performance than a classical signal processing framework based on bandpass features coupled with spatial filtering for CI tasks, including word generation, subtraction, and spatial navigation. These results show for the first time that connectivity features can provide a reliable performance for imagery-based BCI system. Significance. We show that single-trial connectivity features for mixed imagery tasks (i.e. combination of CI and MI) can outperform the features obtained by current state-of-the-art method and hence can be successfully applied for BCI applications.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

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Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

2016-01-01

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

Science.gov (United States)

Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

2016-04-13

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear

Brain structural connectivity and context-dependent extinction memory.

Science.gov (United States)

Hermann, Andrea; Stark, Rudolf; Blecker, Carlo R; Milad, Mohammed R; Merz, Christian J

2017-08-01

Extinction of conditioned fear represents an important mechanism in the treatment of anxiety disorders. Return of fear after successful extinction or exposure therapy in patients with anxiety disorders might be linked to poor temporal or contextual generalization of extinction due to individual differences in brain structural connectivity. The goal of this magnetic resonance imaging study was therefore to investigate the association of context-dependent extinction recall with brain structural connectivity. Diffusion-tensor imaging was used to determine the fractional anisotropy as a measure of white matter structural integrity of fiber tracts connecting central brain regions of the fear and extinction circuit (uncinate fasciculus, cingulum). Forty-five healthy men participated in a two-day fear conditioning experiment with fear acquisition in context A and extinction learning in context B on the first day. Extinction recall in the extinction context as well as renewal in the acquisition context and a novel context C took place one day later. Renewal of conditioned fear (skin conductance responses) in the acquisition context was associated with higher structural integrity of the hippocampal part of the cingulum. Enhanced structural integrity of the cingulum might be related to stronger hippocampal modulation of the dorsal anterior cingulate cortex, a region important for modulating conditioned fear output by excitatory projections to the amygdala. This finding underpins the crucial role of individual differences in the structural integrity of relevant fiber tracts for context-dependent extinction recall and return of fear after exposure therapy in anxiety disorders. © 2017 Wiley Periodicals, Inc.

Sparse coding reveals greater functional connectivity in female brains during naturalistic emotional experience.

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Yudan Ren

Full Text Available Functional neuroimaging is widely used to examine changes in brain function associated with age, gender or neuropsychiatric conditions. FMRI (functional magnetic resonance imaging studies employ either laboratory-designed tasks that engage the brain with abstracted and repeated stimuli, or resting state paradigms with little behavioral constraint. Recently, novel neuroimaging paradigms using naturalistic stimuli are gaining increasing attraction, as they offer an ecologically-valid condition to approximate brain function in real life. Wider application of naturalistic paradigms in exploring individual differences in brain function, however, awaits further advances in statistical methods for modeling dynamic and complex dataset. Here, we developed a novel data-driven strategy that employs group sparse representation to assess gender differences in brain responses during naturalistic emotional experience. Comparing to independent component analysis (ICA, sparse coding algorithm considers the intrinsic sparsity of neural coding and thus could be more suitable in modeling dynamic whole-brain fMRI signals. An online dictionary learning and sparse coding algorithm was applied to the aggregated fMRI signals from both groups, which was subsequently factorized into a common time series signal dictionary matrix and the associated weight coefficient matrix. Our results demonstrate that group sparse representation can effectively identify gender differences in functional brain network during natural viewing, with improved sensitivity and reliability over ICA-based method. Group sparse representation hence offers a superior data-driven strategy for examining brain function during naturalistic conditions, with great potential for clinical application in neuropsychiatric disorders.

Development of Brain EEG Connectivity across Early Childhood: Does Sleep Play a Role?

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Monique K. LeBourgeois

2013-11-01

Full Text Available Sleep has beneficial effects on brain function and learning, which are reflected in plastic changes in the cortex. Early childhood is a time of rapid maturation in fundamental skills—e.g., language, cognitive control, working memory—that are predictive of future functioning. Little is currently known about the interactions between sleep and brain maturation during this developmental period. We propose coherent electroencephalogram (EEG activity during sleep may provide unique insight into maturational processes of functional brain connectivity. Longitudinal sleep EEG assessments were performed in eight healthy subjects at ages 2, 3 and 5 years. Sleep EEG coherence increased across development in a region- and frequency-specific manner. Moreover, although connectivity primarily decreased intra-hemispherically across a night of sleep, an inter-hemispheric overnight increase occurred in the frequency range of slow waves (0.8–2 Hz, theta (4.8–7.8 Hz and sleep spindles (10–14 Hz, with connectivity changes of up to 20% across a night of sleep. These findings indicate sleep EEG coherence reflects processes of brain maturation—i.e., programmed unfolding of neuronal networks—and moreover, sleep-related alterations of brain connectivity during the sensitive maturational window of early childhood.

A Brain-Wide Study of Age-Related Changes in Functional Connectivity

NARCIS (Netherlands)

Geerligs, Linda; Renken, Remco J.; Saliasi, Emi; Maurits, Natasha M.; Lorist, Monicque M.

Aging affects functional connectivity between brain areas, however, a complete picture of how aging affects integration of information within and between functional networks is missing. We used complex network measures, derived from a brain-wide graph, to provide a comprehensive overview of

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.

Science.gov (United States)

Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P

2018-05-18

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the

Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

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Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

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

Decreased Cerebellar-Orbitofrontal Connectivity Correlates with Stuttering Severity: Whole-Brain Functional and Structural Connectivity Associations with Persistent Developmental Stuttering.

Science.gov (United States)

Sitek, Kevin R; Cai, Shanqing; Beal, Deryk S; Perkell, Joseph S; Guenther, Frank H; Ghosh, Satrajit S

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex (OFC). Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and OFC may underlie successful compensatory mechanisms by more fluent stutterers.

Decreased Cerebellar-Orbitofrontal Connectivity Correlates with Stuttering Severity: Whole-Brain Functional and Structural Connectivity Associations with Persistent Developmental Stuttering

Science.gov (United States)

Sitek, Kevin R.; Cai, Shanqing; Beal, Deryk S.; Perkell, Joseph S.; Guenther, Frank H.; Ghosh, Satrajit S.

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex (OFC). Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and OFC may underlie successful compensatory mechanisms by more fluent stutterers. PMID:27199712

Decreased cerebellar-orbitofrontal connectivity correlates with stuttering severity: Whole-brain functional and structural connectivity associations with persistent developmental stuttering

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Kevin Richard Sitek

2016-05-01

Full Text Available Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here, we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex. Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and orbitofrontal cortex may underlie successful compensatory mechanisms by more fluent stutterers.

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

International Nuclear Information System (INIS)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul; Kang, Hyejin; Kim, Heejung; Park, Hyojin

2008-01-01

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults

Energy Technology Data Exchange (ETDEWEB)

Lee, Dong Soo; Oh, Jungsu S.; Lee, Jae Sung; Lee, Myung Chul [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Kang, Hyejin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Programs in Brain and Neuroscience, Seoul (Korea); Kim, Heejung; Park, Hyojin [Seoul National University, College of Medicine, Department of Nuclear Medicine, Jongno-gu, Seoul (Korea); Seoul National University, Interdisciplinary Program in Cognitive Science, Seoul (Korea)

2008-09-15

Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as population-based cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain. (orig.)

Structural and Functional Brain Connectivity of People with Obesity and Prediction of Body Mass Index Using Connectivity.

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Bo-yong Park

Full Text Available Obesity is a medical condition affecting billions of people. Various neuroimaging methods including magnetic resonance imaging (MRI have been used to obtain information about obesity. We adopted a multi-modal approach combining diffusion tensor imaging (DTI and resting state functional MRI (rs-fMRI to incorporate complementary information and thus better investigate the brains of non-healthy weight subjects. The objective of this study was to explore multi-modal neuroimaging and use it to predict a practical clinical score, body mass index (BMI. Connectivity analysis was applied to DTI and rs-fMRI. Significant regions and associated imaging features were identified based on group-wise differences between healthy weight and non-healthy weight subjects. Six DTI-driven connections and 10 rs-fMRI-driven connectivities were identified. DTI-driven connections better reflected group-wise differences than did rs-fMRI-driven connectivity. We predicted BMI values using multi-modal imaging features in a partial least-square regression framework (percent error 15.0%. Our study identified brain regions and imaging features that can adequately explain BMI. We identified potentially good imaging biomarker candidates for obesity-related diseases.

ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation.

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Adeshina, A M; Hashim, R

2016-03-01

Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the

Multimodal brain connectivity analysis in unmedicated late-life depression.

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Reza Tadayonnejad

Full Text Available Late-life depression (LLD is a common disorder associated with emotional distress, cognitive impairment and somatic complains. Structural abnormalities have been suggested as one of the main neurobiological correlates in LLD. However the relationship between these structural abnormalities and altered functional brain networks in LLD remains poorly understood. 15 healthy elderly comparison subjects from the community and 10 unmedicated and symptomatic subjects with geriatric depression were selected for this study. For each subject, 87 regions of interest (ROI were generated from whole brain anatomical parcellation of resting state fMRI data. Whole-brain ROI-wise correlations were calculated and compared between groups. Group differences were assessed using an analysis of covariance after controlling for age, sex and education with multiple comparison correction using the false discovery rate. Structural connectivity was assessed by tract-based spatial statistics (TBSS. LLD subjects had significantly decreased connectivity between the right accumbens area (rA and the right medial orbitofrontal cortex (rmOFC as well as between the right rostral anterior cingulate cortex (rrACC and bilateral superior frontal gyrus (bsSFG. Altered connectivity of rrACC with the bsSFG was significantly correlated with depression severity in depressed subjects. TBSS analysis showed a 20% reduction in fractional anisotropy (FA in the right Forceps Minor (rFM in depressed subjects. rFM FA values were positively correlated with rA-rmOFC and rrACC-bsFG functional connectivity values in our total study sample. Coordinated structural and functional impairment in circuits involved in emotion regulation and reward pathways play an important role in the pathophysiology of LLD.

Human Thalamic-Prefrontal Peduncle Connectivity Revealed by Diffusion Spectrum Imaging Fiber Tracking

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Chuanqi Sun

2018-04-01

Full Text Available The thalamic-prefrontal peduncle (TPP is a large bundle connecting the thalamus and prefrontal cortex. The definitive structure and function of the TPP are still controversial. To investigate the connectivity and segmentation patterns of the TPP, we employed diffusion spectrum imaging with generalized q-sampling reconstruction to perform both subject-specific and template-based analyses. Our results confirmed the trajectory and spatial relationship of the TPP in the human brain and identified the connection areas in the prefrontal cortex. The TPP-connecting areas identified based on Brodmann areas (BAs were BAs 8–11 and 45–47. Based on the automated anatomical atlas, these areas were the medial superior frontal gyrus, superior frontal gyrus, middle frontal gyrus, pars triangularis, pars orbitalis, anterior orbital gyrus, and lateral orbital gyrus. In addition, we identified the TPP connection areas in the thalamus, including the anterior and medial nuclei, and the lateral dorsal/lateral posterior nuclei. TPP fibers connected the thalamus with the ipsilateral prefrontal BAs 11, 47, 10, 46, 45, 9, and 8 seriatim from medial to lateral, layer by layer. Our results provide further details of the thalamic-prefrontal peduncle structure, and may aid future studies and a better understanding of the functional roles of the TPP in the human brain.

Coherence-based Time Series Clustering for Brain Connectivity Visualization

KAUST Repository

Euan, Carolina

2017-11-19

We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by

Coherence-based Time Series Clustering for Brain Connectivity Visualization

KAUST Repository

Euan, Carolina; Sun, Ying; Ombao, Hernando

2017-01-01

We develop the hierarchical cluster coherence (HCC) method for brain signals, a procedure for characterizing connectivity in a network by clustering nodes or groups of channels that display high level of coordination as measured by

Using computational models to relate structural and functional brain connectivity

Czech Academy of Sciences Publication Activity Database

Hlinka, Jaroslav; Coombes, S.

2012-01-01

Roč. 36, č. 2 (2012), s. 2137-2145 ISSN 0953-816X R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : brain disease * computational modelling * functional connectivity * graph theory * structural connectivity Subject RIV: FH - Neurology Impact factor: 3.753, year: 2012

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy.

Science.gov (United States)

Fang, Peng; An, Jie; Zeng, Ling-Li; Shen, Hui; Chen, Fanglin; Wang, Wensheng; Qiu, Shijun; Hu, Dewen

2015-01-01

Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE), but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right) mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

ELUCIDATING BRAIN CONNECTIVITY NETWORKS IN MAJOR DEPRESSIVE DISORDER USING CLASSIFICATION-BASED SCORING.

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Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

2014-04-01

Graph theory is increasingly used in the field of neuroscience to understand the large-scale network structure of the human brain. There is also considerable interest in applying machine learning techniques in clinical settings, for example, to make diagnoses or predict treatment outcomes. Here we used support-vector machines (SVMs), in conjunction with whole-brain tractography, to identify graph metrics that best differentiate individuals with Major Depressive Disorder (MDD) from nondepressed controls. To do this, we applied a novel feature-scoring procedure that incorporates iterative classifier performance to assess feature robustness. We found that small-worldness , a measure of the balance between global integration and local specialization, most reliably differentiated MDD from nondepressed individuals. Post-hoc regional analyses suggested that heightened connectivity of the subcallosal cingulate gyrus (SCG) in MDDs contributes to these differences. The current study provides a novel way to assess the robustness of classification features and reveals anomalies in large-scale neural networks in MDD.

Graph Analysis and Modularity of Brain Functional Connectivity Networks: Searching for the Optimal Threshold

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Cécile Bordier

2017-08-01

Full Text Available Neuroimaging data can be represented as networks of nodes and edges that capture the topological organization of the brain connectivity. Graph theory provides a general and powerful framework to study these networks and their structure at various scales. By way of example, community detection methods have been widely applied to investigate the modular structure of many natural networks, including brain functional connectivity networks. Sparsification procedures are often applied to remove the weakest edges, which are the most affected by experimental noise, and to reduce the density of the graph, thus making it theoretically and computationally more tractable. However, weak links may also contain significant structural information, and procedures to identify the optimal tradeoff are the subject of active research. Here, we explore the use of percolation analysis, a method grounded in statistical physics, to identify the optimal sparsification threshold for community detection in brain connectivity networks. By using synthetic networks endowed with a ground-truth modular structure and realistic topological features typical of human brain functional connectivity networks, we show that percolation analysis can be applied to identify the optimal sparsification threshold that maximizes information on the networks' community structure. We validate this approach using three different community detection methods widely applied to the analysis of brain connectivity networks: Newman's modularity, InfoMap and Asymptotical Surprise. Importantly, we test the effects of noise and data variability, which are critical factors to determine the optimal threshold. This data-driven method should prove particularly useful in the analysis of the community structure of brain networks in populations characterized by different connectivity strengths, such as patients and controls.

The effect of criticism on functional brain connectivity and associations with neuroticism.

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Michelle Nadine Servaas

Full Text Available Neuroticism is a robust personality trait that constitutes a risk factor for psychopathology, especially anxiety disorders and depression. High neurotic individuals tend to be more self-critical and are overly sensitive to criticism by others. Hence, we used a novel resting-state paradigm to investigate the effect of criticism on functional brain connectivity and associations with neuroticism. Forty-eight participants completed the NEO Personality Inventory Revised (NEO-PI-R to assess neuroticism. Next, we recorded resting state functional magnetic resonance imaging (rsfMRI during two sessions. We manipulated the second session before scanning by presenting three standardized critical remarks through headphones, in which the subject was urged to please lie still in the scanner. A seed-based functional connectivity method and subsequent clustering were used to analyse the resting state data. Based on the reviewed literature related to criticism, we selected brain regions associated with self-reflective processing and stress-regulation as regions of interest. The findings showed enhanced functional connectivity between the clustered seed regions and brain areas involved in emotion processing and social cognition during the processing of criticism. Concurrently, functional connectivity was reduced between these clusters and brain structures related to the default mode network and higher-order cognitive control. Furthermore, individuals scoring higher on neuroticism showed altered functional connectivity between the clustered seed regions and brain areas involved in the appraisal, expression and regulation of negative emotions. These results may suggest that the criticized person is attempting to understand the beliefs, perceptions and feelings of the critic in order to facilitate flexible and adaptive social behavior. Furthermore, multiple aspects of emotion processing were found to be affected in individuals scoring higher on neuroticism during

Brain connectivity measures: computation and comparison

Directory of Open Access Journals (Sweden)

Jovanović Aleksandar

2013-12-01

Full Text Available In this article computation and comparison of causality measures which are used in determination of brain connectivity patterns is investigated. Main analyzed examples included published computation and comparisons of Directed Transfer Function ‐ DTF and Partial Directed Coherence ‐ PDC. It proved that serious methodology mistakes were involved in measure computations and comparisons. It is shown that the neighborhood of zero is of accented importance in such evaluations and that the issues of semantic stability have to be treated with more attention. Published results on the relationship of these two important measures are partly unstable with small changes of zero threshold and pictures of involved brain structures deduced from the cited articles have to be corrected. Analysis of the operators involved in evaluation and comparisons is given with suggestions for their improvement and complementary additional actions.

Estimation of Time-Varying Coherence and Its Application in Understanding Brain Functional Connectivity

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Cheng Liu

2010-01-01

Full Text Available Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.

Development of large-scale functional brain networks in children.

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Kaustubh Supekar

2009-07-01

Full Text Available The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y and 22 young-adults (ages 19-22 y. Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Development of large-scale functional brain networks in children.

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Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach.

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Manelis, Anna; Almeida, Jorge R C; Stiffler, Richelle; Lockovich, Jeanette C; Aslam, Haris A; Phillips, Mary L

2016-09-01

Bipolar disorder is often misdiagnosed as major depressive disorder, which leads to inadequate treatment. Depressed individuals versus healthy control subjects, show increased expectation of negative outcomes. Due to increased impulsivity and risk for mania, however, depressed individuals with bipolar disorder may differ from those with major depressive disorder in neural mechanisms underlying anticipation processes. Graph theory methods for neuroimaging data analysis allow the identification of connectivity between multiple brain regions without prior model specification, and may help to identify neurobiological markers differentiating these disorders, thereby facilitating development of better therapeutic interventions. This study aimed to compare brain connectivity among regions involved in win/loss anticipation in depressed individuals with bipolar disorder (BDD) versus depressed individuals with major depressive disorder (MDD) versus healthy control subjects using graph theory methods. The study was conducted at the University of Pittsburgh Medical Center and included 31 BDD, 39 MDD, and 36 healthy control subjects. Participants were scanned while performing a number guessing reward task that included the periods of win and loss anticipation. We first identified the anticipatory network across all 106 participants by contrasting brain activation during all anticipation periods (win anticipation + loss anticipation) versus baseline, and win anticipation versus loss anticipation. Brain connectivity within the identified network was determined using the Independent Multiple sample Greedy Equivalence Search (IMaGES) and Linear non-Gaussian Orientation, Fixed Structure (LOFS) algorithms. Density of connections (the number of connections in the network), path length, and the global connectivity direction ('top-down' versus 'bottom-up') were compared across groups (BDD/MDD/healthy control subjects) and conditions (win/loss anticipation). These analyses showed that

Towards mapping the brain connectome in depression: functional connectivity by perfusion SPECT.

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Gardner, Ann; Åstrand, Disa; Öberg, Johanna; Jacobsson, Hans; Jonsson, Cathrine; Larsson, Stig; Pagani, Marco

2014-08-30

Several studies have demonstrated altered brain functional connectivity in the resting state in depression. However, no study has investigated interregional networking in patients with persistent depressive disorder (PDD). The aim of this study was to assess differences in brain perfusion distribution and connectivity between large groups of patients and healthy controls. Participants comprised 91 patients with PDD and 65 age- and sex-matched healthy controls. Resting state perfusion was investigated by single photon emission computed tomography, and group differences were assessed by Statistical Parametric Mapping. Brain connectivity was explored through a voxel-wise interregional correlation analysis using as covariate of interest the normalized values of clusters of voxels in which perfusion differences were found in group analysis. Significantly increased regional brain perfusion distribution covering a large part of the cerebellum was observed in patients as compared with controls. Patients showed a significant negative functional connectivity between the cerebellar cluster and caudate, bilaterally. This study demonstrated inverse relative perfusion between the cerebellum and the caudate in PDD. Functional uncoupling may be associated with a dysregulation between the role of the cerebellum in action control and of the caudate in action selection, initiation and decision making in the patients. The potential impact of the resting state condition and the possibility of mitochondrial impairment are discussed. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Motor sequence learning-induced neural efficiency in functional brain connectivity.

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Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

2017-02-15

Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigating changes in brain network properties in HIV-associated neurocognitive disease (HAND) using mutual connectivity analysis (MCA)

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Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

About 50% of subjects infected with HIV present deficits in cognitive domains, which are known collectively as HIV associated neurocognitive disorder (HAND). The underlying synaptodendritic damage can be captured using resting state functional MRI, as has been demonstrated by a few earlier studies. Such damage may induce topological changes of brain connectivity networks. We test this hypothesis by capturing the functional interdependence of 90 brain network nodes using a Mutual Connectivity Analysis (MCA) framework with non-linear time series modeling based on Generalized Radial Basis function (GRBF) neural networks. The network nodes are selected based on the regions defined in the Automated Anatomic Labeling (AAL) atlas. Each node is represented by the average time series of the voxels of that region. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We tested for differences in these properties in network graphs obtained for 10 subjects (6 male and 4 female, 5 HIV+ and 5 HIV-). Global network properties captured some differences between these subject cohorts, though significant differences were seen only with the clustering coefficient measure. Local network properties, such as local efficiency and the degree of connections, captured significant differences in regions of the frontal lobe, precentral and cingulate cortex amongst a few others. These results suggest that our method can be used to effectively capture differences occurring in brain network connectivity properties revealed by resting-state functional MRI in neurological disease states, such as HAND.

Brain Functional Connectivity in MS: An EEG-NIRS Study

Science.gov (United States)

2015-10-01

1 AWARD NUMBER: W81XWH-14-1-0582 TITLE: Brain Functional Connectivity in MS: An EEG -NIRS Study PRINCIPAL INVESTIGATOR: Heather Wishart...Functional Connectivity in MS: An EEG -NIRS Study 5b. GRANT NUMBER W81XWH-14-1-0582 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Heather...electrical ( EEG ) and blood volume and blood oxygen-based (NIRS and fMRI) signals, and to use the results to help optimize blood oxygen level

Connecting the Retina to the Brain

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Lynda Erskine

2014-12-01

Full Text Available The visual system is beautifully crafted to transmit information of the external world to visual processing and cognitive centers in the brain. For visual information to be relayed to the brain, a series of axon pathfinding events must take place to ensure that the axons of retinal ganglion cells, the only neuronal cell type in the retina that sends axons out of the retina, find their way out of the eye to connect with targets in the brain. In the past few decades, the power of molecular and genetic tools, including the generation of genetically manipulated mouse lines, have multiplied our knowledge about the molecular mechanisms involved in the sculpting of the visual system. Here, we review major advances in our understanding of the mechanisms controlling the differentiation of RGCs, guidance of their axons from the retina to the primary visual centers, and the refinement processes essential for the establishment of topographic maps and eye-specific axon segregation. Human disorders, such as albinism and achiasmia, that impair RGC axon growth and guidance and, thus, the establishment of a fully functioning visual system will also be discussed.

FLOW-BASED NETWORK MEASURES OF BRAIN CONNECTIVITY IN ALZHEIMER'S DISEASE.

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Prasad, Gautam; Joshi, Shantanu H; Nir, Talia M; Toga, Arthur W; Thompson, Paul M

2013-01-01

We present a new flow-based method for modeling brain structural connectivity. The method uses a modified maximum-flow algorithm that is robust to noise in the diffusion data and guided by biologically viable pathways and structure of the brain. A flow network is first created using a lattice graph by connecting all lattice points (voxel centers) to all their neighbors by edges. Edge weights are based on the orientation distribution function (ODF) value in the direction of the edge. The maximum-flow is computed based on this flow graph using the flow or the capacity between each region of interest (ROI) pair by following the connected tractography fibers projected onto the flow graph edges. Network measures such as global efficiency, transitivity, path length, mean degree, density, modularity, small world, and assortativity are computed from the flow connectivity matrix. We applied our method to diffusion-weighted images (DWIs) from 110 subjects (28 normal elderly, 56 with early and 11 with late mild cognitive impairment, and 15 with AD) and segmented co-registered anatomical MRIs into cortical regions. Experimental results showed better performance compared to the standard fiber-counting methods when distinguishing Alzheimer's disease from normal aging.

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...

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.

Low-frequency connectivity is associated with mild traumatic brain injury

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B.T. Dunkley

2015-01-01

Full Text Available Mild traumatic brain injury (mTBI occurs from a closed-head impact. Often referred to as concussion, about 20% of cases complain of secondary psychological sequelae, such as disorders of attention and memory. Known as post-concussive symptoms (PCS, these problems can severely disrupt the patient's quality of life. Changes in local spectral power, particularly low-frequency amplitude increases and/or peak alpha slowing have been reported in mTBI, but large-scale connectivity metrics based on inter-regional amplitude correlations relevant for integration and segregation in functional brain networks, and their association with disorders in cognition and behaviour, remain relatively unexplored. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in a group with mTBI (n = 20, and a control group (n = 21. We observed a trend for atypical slow-wave power changes in subcortical, temporal and parietal regions in mTBI, as well as significant long-range increases in amplitude envelope correlations among deep-source, temporal, and frontal regions in the delta, theta, and alpha bands. Subsequently, we conducted an exploratory analysis of patterns of connectivity most associated with variability in secondary symptoms of mTBI, including inattention, anxiety, and depression. Differential patterns of altered resting state neurophysiological network connectivity were found across frequency bands. This indicated that multiple network and frequency specific alterations in large scale brain connectivity may contribute to overlapping cognitive sequelae in mTBI. In conclusion, we show that local spectral power content can be supplemented with measures of correlations in amplitude to define general networks that are atypical in mTBI, and suggest that certain cognitive difficulties are mediated by disturbances in a variety of alterations in network interactions which are differentially

Hyperthermia-induced disruption of functional connectivity in the human brain network.

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Gang Sun

Full Text Available BACKGROUND: Passive hyperthermia is a potential risk factor to human cognitive performance and work behavior in many extreme work environments. Previous studies have demonstrated significant effects of passive hyperthermia on human cognitive performance and work behavior. However, there is a lack of a clear understanding of the exact affected brain regions and inter-regional connectivities. METHODOLOGY AND PRINCIPAL FINDINGS: We simulated 1 hour environmental heat exposure to thirty-six participants under two environmental temperature conditions (25 °C and 50 °C, and collected resting-state functional brain activity. The functional connectivities with a preselected region of interest (ROI in the posterior cingulate cortex and precuneus (PCC/PCu, furthermore, inter-regional connectivities throughout the entire brain using a prior Anatomical Automatic Labeling (AAL atlas were calculated. We identified decreased correlations of a set of regions with the PCC/PCu, including the medial orbitofrontal cortex (mOFC and bilateral medial temporal cortex, as well as increased correlations with the partial orbitofrontal cortex particularly in the bilateral orbital superior frontal gyrus. Compared with the normal control (NC group, the hyperthermia (HT group showed 65 disturbed functional connectivities with 50 of them being decreased and 15 of them being increased. While the decreased correlations mainly involved with the mOFC, temporal lobe and occipital lobe, increased correlations were mainly located within the limbic system. In consideration of physiological system changes, we explored the correlations of the number of significantly altered inter-regional connectivities with differential rectal temperatures and weight loss, but failed to obtain significant correlations. More importantly, during the attention network test (ANT we found that the number of significantly altered functional connectivities was positively correlated with an increase in

Novel MRI methodology to detect human whole-brain connectivity changes after ingestion of fructose or glucose

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Tsao, Sinchai; Wilkins, Bryce; Page, Kathleen A.; Singh, Manbir

2012-03-01

A novel MRI protocol has been developed to investigate the differential effects of glucose or fructose consumption on whole-brain functional brain connectivity. A previous study has reported a decrease in the fMRI blood oxygen level dependent (BOLD) signal of the hypothalamus following glucose ingestion, but due to technical limitations, was restricted to a single slice covering the hypothalamus, and thus unable to detect whole-brain connectivity. In another previous study, a protocol was devised to acquire whole-brain fMRI data following food intake, but only after restricting image acquisition to an MR sampling or repetition time (TR) of 20s, making the protocol unsuitable to detect functional connectivity above 0.025Hz. We have successfully implemented a continuous 36-min, 40 contiguous slices, whole-brain BOLD acquisition protocol on a 3T scanner with TR=4.5s to ensure detection of up to 0.1Hz frequencies for whole-brain functional connectivity analysis. Human data were acquired first with ingestion of water only, followed by a glucose or fructose drink within the scanner, without interrupting the scanning. Whole-brain connectivity was analyzed using standard correlation methodology in the 0.01-0.1 Hz range. The correlation coefficient differences between fructose and glucose ingestion among targeted regions were converted to t-scores using the water-only correlation coefficients as a null condition. Results show a dramatic increase in the hypothalamic connectivity to the hippocampus, amygdala, insula, caudate and the nucleus accumben for fructose over glucose. As these regions are known to be key components of the feeding and reward brain circuits, these results suggest a preference for fructose ingestion.

Multivariate pattern analysis reveals anatomical connectivity differences between the left and right mesial temporal lobe epilepsy

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Peng Fang

2015-01-01

Full Text Available Previous studies have demonstrated differences of clinical signs and functional brain network organizations between the left and right mesial temporal lobe epilepsy (mTLE, but the anatomical connectivity differences underlying functional variance between the left and right mTLE remain uncharacterized. We examined 43 (22 left, 21 right mTLE patients with hippocampal sclerosis and 39 healthy controls using diffusion tensor imaging. After the whole-brain anatomical networks were constructed for each subject, multivariate pattern analysis was applied to classify the left mTLE from the right mTLE and extract the anatomical connectivity differences between the left and right mTLE patients. The classification results reveal 93.0% accuracy for the left mTLE versus the right mTLE, 93.4% accuracy for the left mTLE versus controls and 90.0% accuracy for the right mTLE versus controls. Compared with the right mTLE, the left mTLE exhibited a different connectivity pattern in the cortical-limbic network and cerebellum. The majority of the most discriminating anatomical connections were located within or across the cortical-limbic network and cerebellum, thereby indicating that these disease-related anatomical network alterations may give rise to a portion of the complex of emotional and memory deficit between the left and right mTLE. Moreover, the orbitofrontal gyrus, cingulate cortex, hippocampus and parahippocampal gyrus, which exhibit high discriminative power in classification, may play critical roles in the pathophysiology of mTLE. The current study demonstrated that anatomical connectivity differences between the left mTLE and the right mTLE may have the potential to serve as a neuroimaging biomarker to guide personalized diagnosis of the left and right mTLE.

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

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Kaushal, Mayank; Oni-Orisan, Akinwunmi; Chen, Gang; Li, Wenjun; Leschke, Jack; Ward, Doug; Kalinosky, Benjamin; Budde, Matthew; Schmit, Brian; Li, Shi-Jiang; Muqeet, Vaishnavi; Kurpad, Shekar

2017-09-01

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

The CLAIR model: Extension of Brodmann areas based on brain oscillations and connectivity.

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Başar, Erol; Düzgün, Aysel

2016-05-01

Since the beginning of the last century, the localization of brain function has been represented by Brodmann areas, maps of the anatomic organization of the brain. They are used to broadly represent cortical structures with their given sensory-cognitive functions. In recent decades, the analysis of brain oscillations has become important in the correlation of brain functions. Moreover, spectral connectivity can provide further information on the dynamic connectivity between various structures. In addition, brain responses are dynamic in nature and structural localization is almost impossible, according to Luria (1966). Therefore, brain functions are very difficult to localize; hence, a combined analysis of oscillation and event-related coherences is required. In this study, a model termed as "CLAIR" is described to enrich and possibly replace the concept of the Brodmann areas. A CLAIR model with optimum function may take several years to develop, but this study sets out to lay its foundation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

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Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Strong Functional Connectivity among Homotopic Brain Areas Is Vital for Motor Control in Unilateral Limb Movement.

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Wei, Pengxu; Zhang, Zuting; Lv, Zeping; Jing, Bin

2017-01-01

The mechanism underlying brain region organization for motor control in humans remains poorly understood. In this functional magnetic resonance imaging (fMRI) study, right-handed volunteers were tasked to maintain unilateral foot movements on the right and left sides as consistently as possible. We aimed to identify the similarities and differences between brain motor networks of the two conditions. We recruited 18 right-handed healthy volunteers aged 25 ± 2.3 years and used a whole-body 3T system for magnetic resonance (MR) scanning. Image analysis was performed using SPM8, Conn toolbox and Brain Connectivity Toolbox. We determined a craniocaudally distributed, mirror-symmetrical modular structure. The functional connectivity between homotopic brain areas was generally stronger than the intrahemispheric connections, and such strong connectivity led to the abovementioned modular structure. Our findings indicated that the interhemispheric functional interaction between homotopic brain areas is more intensive than the interaction along the conventional top-down and bottom-up pathways within the brain during unilateral limb movement. The detected strong interhemispheric horizontal functional interaction is an important aspect of motor control but often neglected or underestimated. The strong interhemispheric connectivity may explain the physiological phenomena and effects of promising therapeutic approaches. Further accurate and effective therapeutic methods may be developed on the basis of our findings.

Exercise training reinstates cortico-cortical sensorimotor functional connectivity following striatal lesioning: Development and application of a subregional-level analytic toolbox for perfusion autoradiographs of the rat brain

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Peng, Yu-Hao; Heintz, Ryan; Wang, Zhuo; Guo, Yumei; Myers, Kalisa; Scremin, Oscar; Maarek, Jean-Michel; Holschneider, Daniel

2014-12-01

Current rodent connectome projects are revealing brain structural connectivity with unprecedented resolution and completeness. How subregional structural connectivity relates to subregional functional interactions is an emerging research topic. We describe a method for standardized, mesoscopic-level data sampling from autoradiographic coronal sections of the rat brain, and for correlation-based analysis and intuitive display of cortico-cortical functional connectivity (FC) on a flattened cortical map. A graphic user interface “Cx-2D” allows for the display of significant correlations of individual regions-of-interest, as well as graph theoretical metrics across the cortex. Cx-2D was tested on an autoradiographic data set of cerebral blood flow (CBF) of rats that had undergone bilateral striatal lesions, followed by 4 weeks of aerobic exercise training or no exercise. Effects of lesioning and exercise on cortico-cortical FC were examined during a locomotor challenge in this rat model of Parkinsonism. Subregional FC analysis revealed a rich functional reorganization of the brain in response to lesioning and exercise that was not apparent in a standard analysis focused on CBF of isolated brain regions. Lesioned rats showed diminished degree centrality of lateral primary motor cortex, as well as neighboring somatosensory cortex--changes that were substantially reversed in lesioned rats following exercise training. Seed analysis revealed that exercise increased positive correlations in motor and somatosensory cortex, with little effect in non-sensorimotor regions such as visual, auditory, and piriform cortex. The current analysis revealed that exercise partially reinstated sensorimotor FC lost following dopaminergic deafferentation. Cx-2D allows for standardized data sampling from images of brain slices, as well as analysis and display of cortico-cortical FC in the rat cerebral cortex with potential applications in a variety of autoradiographic and histologic

State-Dependent Changes of Connectivity Patterns and Functional Brain Network Topology in Autism Spectrum Disorder

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Barttfeld, Pablo; Wicker, Bruno; Cukier, Sebastian; Navarta, Silvana; Lew, Sergio; Leiguarda, Ramon; Sigman, Mariano

2012-01-01

Anatomical and functional brain studies have converged to the hypothesis that autism spectrum disorders (ASD) are associated with atypical connectivity. Using a modified resting-state paradigm to drive subjects' attention, we provide evidence of a very marked interaction between ASD brain functional connectivity and cognitive state. We show that…

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

Science.gov (United States)

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-09-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory.

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Tanimizu, Toshiyuki; Kenney, Justin W; Okano, Emiko; Kadoma, Kazune; Frankland, Paul W; Kida, Satoshi

2017-04-12

Social recognition memory is an essential and basic component of social behavior that is used to discriminate familiar and novel animals/humans. Previous studies have shown the importance of several brain regions for social recognition memories; however, the mechanisms underlying the consolidation of social recognition memory at the molecular and anatomic levels remain unknown. Here, we show a brain network necessary for the generation of social recognition memory in mice. A mouse genetic study showed that cAMP-responsive element-binding protein (CREB)-mediated transcription is required for the formation of social recognition memory. Importantly, significant inductions of the CREB target immediate-early genes c-fos and Arc were observed in the hippocampus (CA1 and CA3 regions), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and amygdala (basolateral region) when social recognition memory was generated. Pharmacological experiments using a microinfusion of the protein synthesis inhibitor anisomycin showed that protein synthesis in these brain regions is required for the consolidation of social recognition memory. These findings suggested that social recognition memory is consolidated through the activation of CREB-mediated gene expression in the hippocampus/mPFC/ACC/amygdala. Network analyses suggested that these four brain regions show functional connectivity with other brain regions and, more importantly, that the hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas the ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. We have found that a brain network composed of the hippocampus/mPFC/ACC/amygdala is required for the consolidation of social recognition memory. SIGNIFICANCE STATEMENT Here, we identify brain networks composed of multiple brain regions for the consolidation of social recognition memory. We

Increased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imaging.

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Peng Fang

Full Text Available Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients=86.4%, controls=96.2%; permutation test, p<0.0001 of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.

Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

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Vecchio, Fabrizio; Miraglia, Francesca; Rossini, Paolo Maria

2018-05-01

The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human "Connectome." Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task's performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

Short circuit : how brain connectivity and disconnectivity relate to brain function

OpenAIRE

Langen, Carolyn

2018-01-01

markdownabstractThe brain is like a super computer: it is a collection of interconnected computational units which work together to enable both basic functions, such as regulation of breathing, as well as higher functions, such as cognition, thought and emotion. The computational units, or regions, are located in the grey matter (i.e. the cortical surface and in the subcortex), whereas the connections between them, or tracts, are found in the white matter. The development and maintenance of b...

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks

OpenAIRE

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-01-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control...

Functional connectivity analysis of brain hemodynamics during rubber hand illusion.

Science.gov (United States)

Arizono, Naoki; Kondo, Toshiyuki

2015-08-01

Embodied cognition has been eagerly studied in the recent neuroscience research field. In particular, hand ownership has been investigated through the rubber hand illusion (RHI). Most of the research measured the brain activities during the RHI by using EEG, fMRI, etc., however, near-infrared spectroscopy (NIRS) has not yet been utilized. Here we attempt to measure the brain activities during the RHI task with NIRS, and analyze the functional connectivity so as to understand the relationship between NIRS features and the state of embodied cognition. For the purpose, we developed a visuo-tactile stimulator in the study. As a result, we found that the subjects felt illusory experience showed significant peaks of oxy-Hb in both prefrontal and premotor cortices during RHI. Furthermore, we confirmed a reliable causality connection from right prefrontal to right premotor cortex. This result suggests that the RHI is associated with the neural circuits underlying motor control. Therefore, we considered that the RHI with the functional connectivity analysis will become an appropriate model investigating a biomarker for neurorehabilitation, and the diagnosis of the mental disorders.

An Evaluation of the Left-Brain vs. Right-Brain Hypothesis with Resting State Functional Connectivity Magnetic Resonance Imaging

OpenAIRE

Nielsen, Jared A.; Zielinski, Brandon A.; Ferguson, Michael A.; Lainhart, Janet E.; Anderson, Jeffrey S.

2013-01-01

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from...

Altered resting brain connectivity in persistent cancer related fatigue

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Johnson P. Hampson

2015-01-01

Full Text Available There is an estimated 3 million women in the US living as breast cancer survivors and persistent cancer related fatigue (PCRF disrupts the lives of an estimated 30% of these women. PCRF is associated with decreased quality of life, decreased sleep quality, impaired cognition and depression. The mechanisms of cancer related fatigue are not well understood; however, preliminary findings indicate dysfunctional activity in the brain as a potential factor. Here we investigate the relationship between PCRF on intrinsic resting state connectivity in this population. Twenty-three age matched breast cancer survivors (15 fatigued and 8 non-fatigued who completed all cancer-related treatments at least 12 weeks prior to the study, were recruited to undergo functional connectivity magnetic resonance imaging (fcMRI. Intrinsic resting state networks were examined with both seed based and independent component analysis methods. Comparisons of brain connectivity patterns between groups as well as correlations with self-reported fatigue symptoms were performed. Fatigued patients displayed greater left inferior parietal lobule to superior frontal gyrus connectivity as compared to non-fatigued patients (P < 0.05 FDR corrected. This enhanced connectivity was associated with increased physical fatigue (P = 0.04, r = 0.52 and poor sleep quality (P = 0.04, r = 0.52 in the fatigued group. In contrast greater connectivity in the non-fatigued group was found between the right precuneus to the periaqueductal gray as well as the left IPL to subgenual cortex (P < 0.05 FDR corrected. Mental fatigue scores were associated with greater default mode network (DMN connectivity to the superior frontal gyrus (P = 0.05 FDR corrected among fatigued subjects (r = 0.82 and less connectivity in the non-fatigued group (r = −0.88. These findings indicate that there is enhanced intrinsic DMN connectivity to the frontal gyrus in breast cancer survivors with persistent

Strong Functional Connectivity among Homotopic Brain Areas Is Vital for Motor Control in Unilateral Limb Movement

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Pengxu Wei

2017-07-01

Full Text Available The mechanism underlying brain region organization for motor control in humans remains poorly understood. In this functional magnetic resonance imaging (fMRI study, right-handed volunteers were tasked to maintain unilateral foot movements on the right and left sides as consistently as possible. We aimed to identify the similarities and differences between brain motor networks of the two conditions. We recruited 18 right-handed healthy volunteers aged 25 ± 2.3 years and used a whole-body 3T system for magnetic resonance (MR scanning. Image analysis was performed using SPM8, Conn toolbox and Brain Connectivity Toolbox. We determined a craniocaudally distributed, mirror-symmetrical modular structure. The functional connectivity between homotopic brain areas was generally stronger than the intrahemispheric connections, and such strong connectivity led to the abovementioned modular structure. Our findings indicated that the interhemispheric functional interaction between homotopic brain areas is more intensive than the interaction along the conventional top–down and bottom–up pathways within the brain during unilateral limb movement. The detected strong interhemispheric horizontal functional interaction is an important aspect of motor control but often neglected or underestimated. The strong interhemispheric connectivity may explain the physiological phenomena and effects of promising therapeutic approaches. Further accurate and effective therapeutic methods may be developed on the basis of our findings.

Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states

NARCIS (Netherlands)

Deco, Gustavo; Cabral, Joana; Saenger, Victor M; Boly, Melanie; Tagliazucchi, Enzo; Laufs, Helmut; Van Someren, Eus; Jobst, Beatrice; Stevner, Angus; Kringelbach, Morten L

2017-01-01

Human neuroimaging research has revealed that wakefulness and sleep involve very different activity patterns. Yet, it is not clear why brain states differ in their dynamical complexity, e.g. in the level of integration and segregation across brain networks over time. Here, we investigate the

Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states

NARCIS (Netherlands)

Deco, Gustavo; Cabral, Joana; Saenger, Victor M; Boly, Melanie; Tagliazucchi, Enzo; Laufs, Helmut; Van Someren, Eus; Jobst, Beatrice M; Stevner, Angus B A; Kringelbach, Morten L

2018-01-01

Human neuroimaging research has revealed that wakefulness and sleep involve very different activity patterns. Yet, it is not clear why brain states differ in their dynamical complexity, e.g. in the level of integration and segregation across brain networks over time. Here, we investigate the

A functional genomics screen in planarians reveals regulators of whole-brain regeneration

Science.gov (United States)

Roberts-Galbraith, Rachel H; Brubacher, John L; Newmark, Phillip A

2016-01-01

Planarians regenerate all body parts after injury, including the central nervous system (CNS). We capitalized on this distinctive trait and completed a gene expression-guided functional screen to identify factors that regulate diverse aspects of neural regeneration in Schmidtea mediterranea. Our screen revealed molecules that influence neural cell fates, support the formation of a major connective hub, and promote reestablishment of chemosensory behavior. We also identified genes that encode signaling molecules with roles in head regeneration, including some that are produced in a previously uncharacterized parenchymal population of cells. Finally, we explored genes downregulated during planarian regeneration and characterized, for the first time, glial cells in the planarian CNS that respond to injury by repressing several transcripts. Collectively, our studies revealed diverse molecules and cell types that underlie an animal’s ability to regenerate its brain. DOI: http://dx.doi.org/10.7554/eLife.17002.001 PMID:27612384

Abnormal functional brain connectivity and personality traits in myotonic dystrophy type 1.

Science.gov (United States)

Serra, Laura; Silvestri, Gabriella; Petrucci, Antonio; Basile, Barbara; Masciullo, Marcella; Makovac, Elena; Torso, Mario; Spanò, Barbara; Mastropasqua, Chiara; Harrison, Neil A; Bianchi, Maria L E; Giacanelli, Manlio; Caltagirone, Carlo; Cercignani, Mara; Bozzali, Marco

2014-05-01

Myotonic dystrophy type 1 (DM1), the most common muscular dystrophy observed in adults, is a genetic multisystem disorder affecting several other organs besides skeletal muscle, including the brain. Cognitive and personality abnormalities have been reported; however, no studies have investigated brain functional networks and their relationship with personality traits/disorders in patients with DM1. To use resting-state functional magnetic resonance imaging to assess the potential relationship between personality traits/disorders and changes to functional connectivity within the default mode network (DMN) in patients with DM1. We enrolled 27 patients with genetically confirmed DM1 and 16 matched healthy control individuals. Patients underwent personality assessment using clinical interview and Minnesota Multiphasic Personality Inventory-2 administration; all participants underwent resting-state functional magnetic resonance imaging. Investigations were conducted at the Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Catholic University of Sacred Heart, and Azienda Ospedaliera San Camillo Forlanini. Resting-state functional magnetic resonance imaging. Measures of personality traits in patients and changes in functional connectivity within the DMN in patients and controls. Changes in functional connectivity and atypical personality traits in patients were correlated. We combined results obtained from the Minnesota Multiphasic Personality Inventory-2 and clinical interview to identify a continuum of atypical personality profiles ranging from schizotypal personality traits to paranoid personality disorder within our DM1 patients. We also demonstrated an increase in functional connectivity in the bilateral posterior cingulate and left parietal DMN nodes in DM1 patients compared with controls. Moreover, patients with DM1 showed strong associations between DMN functional connectivity and schizotypal-paranoid traits. Our findings provide novel

Bayesian network analysis revealed the connectivity difference of the default mode network from the resting-state to task-state

Science.gov (United States)

Wu, Xia; Yu, Xinyu; Yao, Li; Li, Rui

2014-01-01

Functional magnetic resonance imaging (fMRI) studies have converged to reveal the default mode network (DMN), a constellation of regions that display co-activation during resting-state but co-deactivation during attention-demanding tasks in the brain. Here, we employed a Bayesian network (BN) analysis method to construct a directed effective connectivity model of the DMN and compared the organizational architecture and interregional directed connections under both resting-state and task-state. The analysis results indicated that the DMN was consistently organized into two closely interacting subsystems in both resting-state and task-state. The directed connections between DMN regions, however, changed significantly from the resting-state to task-state condition. The results suggest that the DMN intrinsically maintains a relatively stable structure whether at rest or performing tasks but has different information processing mechanisms under varied states. PMID:25309414

Correlation Networks for Identifying Changes in Brain Connectivity during Epileptiform Discharges and Transcranial Magnetic Stimulation

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Elsa Siggiridou

2014-07-01

Full Text Available The occurrence of epileptiform discharges (ED in electroencephalographic (EEG recordings of patients with epilepsy signifies a change in brain dynamics and particularly brain connectivity. Transcranial magnetic stimulation (TMS has been recently acknowledged as a non-invasive brain stimulation technique that can be used in focal epilepsy for therapeutic purposes. In this case study, it is investigated whether simple time-domain connectivity measures, namely cross-correlation and partial cross-correlation, can detect alterations in the connectivity structure estimated from selected EEG channels before and during ED, as well as how this changes with the application of TMS. The correlation for each channel pair is computed on non-overlapping windows of 1 s duration forming weighted networks. Further, binary networks are derived by thresholding or statistical significance tests (parametric and randomization tests. The information for the binary networks is summarized by statistical network measures, such as the average degree and the average path length. Alterations of brain connectivity before, during and after ED with or without TMS are identified by statistical analysis of the network measures at each state.

Group-ICA model order highlights patterns of functional brain connectivity

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Ahmed eAbou Elseoud

2011-06-01

Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.

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.

Vigilance task-related change in brain functional connectivity as revealed by wavelet phase coherence analysis of near-infrared spectroscopy signals

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Wang Wei

2016-08-01

Full Text Available This study aims to assess the vigilance task-related change in connectivity in healthy adults using wavelet phase coherence (WPCO analysis of near-infrared spectroscopy signals (NIRS. NIRS is a non-invasive neuroimaging technique for assessing brain activity. Continuous recordings of the NIRS signals were obtained from the prefrontal cortex (PFC and sensorimotor cortical areas of 20 young healthy adults (24.9±3.3 years during a 10-min resting state and a 20-min vigilance task state. The vigilance task was used to simulate driving mental load by judging three random numbers (i.e., whether odd numbers. The task was divided into two sessions: the first 10 minutes (Task t1 and the second 10 minutes (Task t2. The WPCO of six channel pairs were calculated in five frequency intervals: 0.6–2 Hz (I, 0.145–0.6 Hz (II, 0.052–0.145 Hz (III, 0.021–0.052 Hz (IV, and 0.0095–0.021 Hz (V. The significant WPCO formed global connectivity (GC maps in intervals I and II and functional connectivity (FC maps in intervals III to V. Results show that the GC levels in interval I and FC levels in interval III were significantly lower in the Task t2 than in the resting state (p < 0.05, particularly between the left PFC and bilateral sensorimotor regions. Also, the reaction time shows an increase in Task t2 compared with that in Task t1. However, no significant difference in WPCO was found between Task t1 and resting state. The results showed that the change in FC at the range of 0.6-2 Hz was not attributed to the vigilance task pe se, but the interaction effect of vigilance task and time factors. The findings suggest that the decreased attention level might be partly attributed to the reduced GC levels between the left prefrontal region and sensorimotor area. The present results provide a new insight into the vigilance task-related brain activity.

Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

Science.gov (United States)

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

2014-01-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging.

Science.gov (United States)

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S; Huang, Hao

2015-02-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Electroconvulsive therapy-induced brain functional connectivity predicts therapeutic efficacy in patients with schizophrenia: a multivariate pattern recognition study.

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Li, Peng; Jing, Ri-Xing; Zhao, Rong-Jiang; Ding, Zeng-Bo; Shi, Le; Sun, Hong-Qiang; Lin, Xiao; Fan, Teng-Teng; Dong, Wen-Tian; Fan, Yong; Lu, Lin

2017-05-11

REVEAL GOOD CANDIDATES FOR BRAIN STIMULATION: Connectivity patterns in the brain may help identify patients with schizophrenia most likely to benefit from electroconvulsive therapy. A team led by Lin Lu from Peking University, China, and Yong Fan from the University of Pennsylvania, USA, took functional magnetic resonance imaging (MRI) scans of 34 people with schizophrenia and 34 control individuals without mental illness. Those with schizophrenia were scanned before and after treatment; some received antipsychotics alone, others received medication plus electroconvulsive therapy. The researchers created organizational brain maps known as "intrinsic connectivity networks" for each individual, and showed that the neuroimaging pattern could discriminate between people with and without schizophrenia. For the schizophrenia patients, the connectivity networks taken prior to treatment also helped predict who would benefit from the brain-stimulation procedure. Such a biomarker could prove a useful diagnostic tool for clinicians.

Effects of Cognitive-Behavioral Therapy (CBT) on Brain Connectivity Supporting Catastrophizing in Fibromyalgia.

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Lazaridou, Asimina; Kim, Jieun; Cahalan, Christine M; Loggia, Marco L; Franceschelli, Olivia; Berna, Chantal; Schur, Peter; Napadow, Vitaly; Edwards, Robert R

2017-03-01

Fibromyalgia (FM) is a chronic, common pain disorder characterized by hyperalgesia. A key mechanism by which cognitive-behavioral therapy (CBT) fosters improvement in pain outcomes is via reductions in hyperalgesia and pain-related catastrophizing, a dysfunctional set of cognitive-emotional processes. However, the neural underpinnings of these CBT effects are unclear. Our aim was to assess CBT's effects on the brain circuitry underlying hyperalgesia in FM patients, and to explore the role of treatment-associated reduction in catastrophizing as a contributor to normalization of pain-relevant brain circuitry and clinical improvement. In total, 16 high-catastrophizing FM patients were enrolled in the study and randomized to 4 weeks of individual treatment with either CBT or a Fibromyalgia Education (control) condition. Resting state functional magnetic resonance imaging scans evaluated functional connectivity between key pain-processing brain regions at baseline and posttreatment. Clinical outcomes were assessed at baseline, posttreatment, and 6-month follow-up. Catastrophizing correlated with increased resting state functional connectivity between S1 and anterior insula. The CBT group showed larger reductions (compared with the education group) in catastrophizing at posttreatment (PCBT produced significant reductions in both pain and catastrophizing at the 6-month follow-up (PCBT group also showed reduced resting state connectivity between S1 and anterior/medial insula at posttreatment; these reductions in resting state connectivity were associated with concurrent treatment-related reductions in catastrophizing. The results add to the growing support for the clinically important associations between S1-insula connectivity, clinical pain, and catastrophizing, and suggest that CBT may, in part via reductions in catastrophizing, help to normalize pain-related brain responses in FM.

Connectivity dynamics in typical development and its relationship to autistic traits and autism spectrum disorder.

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Rashid, Barnaly; Blanken, Laura M E; Muetzel, Ryan L; Miller, Robyn; Damaraju, Eswar; Arbabshirani, Mohammad R; Erhardt, Erik B; Verhulst, Frank C; van der Lugt, Aad; Jaddoe, Vincent W V; Tiemeier, Henning; White, Tonya; Calhoun, Vince

2018-03-30

Recent advances in neuroimaging techniques have provided significant insights into developmental trajectories of human brain function. Characterizations of typical neurodevelopment provide a framework for understanding altered neurodevelopment, including differences in brain function related to developmental disorders and psychopathology. Historically, most functional connectivity studies of typical and atypical development operate under the assumption that connectivity remains static over time. We hypothesized that relaxing stationarity assumptions would reveal novel features of both typical brain development related to children on the autism spectrum. We employed a "chronnectomic" (recurring, time-varying patterns of connectivity) approach to evaluate transient states of connectivity using resting-state functional MRI in a population-based sample of 774 6- to 10-year-old children. Dynamic connectivity was evaluated using a sliding-window approach, and revealed four transient states. Internetwork connectivity increased with age in modularized dynamic states, illustrating an important pattern of connectivity in the developing brain. Furthermore, we demonstrated that higher levels of autistic traits and ASD diagnosis were associated with longer dwell times in a globally disconnected state. These results provide a roadmap to the chronnectomic organization of the developing brain and suggest that characteristics of functional brain connectivity are related to children on the autism spectrum. © 2018 Wiley Periodicals, Inc.

On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

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Thompson, William Hedley; Fransson, Peter

2016-12-01

Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

Change in brain network connectivity during PACAP38-induced migraine attacks

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Amin, Faisal Mohammad; Hougaard, Anders; Magon, Stefano

2016-01-01

OBJECTIVE: To investigate resting-state functional connectivity in the salience network (SN), the sensorimotor network (SMN), and the default mode network (DMN) during migraine attacks induced by pituitary adenylate cyclase-activating polypeptide-38 (PACAP38). METHODS: In a double-blind, randomized...... connectivity with the bilateral opercular part of the inferior frontal gyrus in the SN. In SMN, there was increased connectivity with the right premotor cortex and decreased connectivity with the left visual cortex. Several areas showed increased (left primary auditory, secondary somatosensory, premotor......, and visual cortices) and decreased (right cerebellum and left frontal lobe) connectivity with DMN. We found no resting-state network changes after VIP (n = 15). CONCLUSIONS: PACAP38-induced migraine attack is associated with altered connectivity of several large-scale functional networks of the brain....

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

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Hampson, M; Hoffman, R E

2010-01-01

There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

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Michelle Hampson

2010-08-01

Full Text Available There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Changes in brain connectivity related to the treatment of depression measured through fMRI: a systematic review

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Gudayol-Ferré, Esteve; Peró-Cebollero, Maribel; González-Garrido, Andrés A.; Guàrdia-Olmos, Joan

2015-01-01

Depression is a mental illness that presents alterations in brain connectivity in the Default Mode Network (DMN), the Affective Network (AN) and other cortical-limbic networks, and the Cognitive Control Network (CCN), among others. In recent years the interest in the possible effect of the different antidepressant treatments on functional connectivity has increased substantially. The goal of this paper is to conduct a systematic review of the studies on the relationship between the treatment of depression and brain connectivity. Nineteen studies were found in a systematic review on this topic. In all of them, there was improvement of the clinical symptoms after antidepressant treatment. In 18 out of the 19 studies, clinical improvement was associated to changes in brain connectivity. It seems that both DMN and the connectivity between cortical and limbic structures consistently changes after antidepressant treatment. However, the current evidence does not allow us to assure that the treatment of depression leads to changes in the CCN. In this regard, some papers report a positive correlation between changes in brain connectivity and improvement of depressive symptomatology, particularly when they measure cortical-limbic connectivity, whereas the changes in DMN do not significantly correlate with clinical improvement. Finally, some papers suggest that changes in connectivity after antidepressant treatment might be partly related to the mechanisms of action of the treatment administered. This effect has been observed in two studies with stimulation treatment (one with rTMS and one with ECT), and in two papers that administered three different pharmacological treatments. Our review allows us to make a series of recommendations that might guide future researchers exploring the effect of anti-depression treatments on brain connectivity. PMID:26578927

Repeated verum but not placebo acupuncture normalizes connectivity in brain regions dysregulated in chronic pain

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Natalia Egorova

2015-01-01

Full Text Available Acupuncture, an ancient East Asian therapy, is aimed at rectifying the imbalance within the body caused by disease. Studies evaluating the efficacy of acupuncture with neuroimaging tend to concentrate on brain regions within the pain matrix, associated with acute pain. We, however, focused on the effect of repeated acupuncture treatment specifically on brain regions known to support functions dysregulated in chronic pain disorders. Transition to chronic pain is associated with increased attention to pain, emotional rumination, nociceptive memory and avoidance learning, resulting in brain connectivity changes, specifically affecting the periaqueductal gray (PAG, medial frontal cortex (MFC and bilateral hippocampus (Hpc. We demonstrate that the PAG–MFC and PAG–Hpc connectivity in patients with chronic pain due to knee osteoarthritis indeed correlates with clinical severity scores and further show that verum acupuncture-induced improvement in pain scores (compared to sham is related to the modulation of PAG–MFC and PAG–Hpc connectivity in the predicted direction. This study shows that repeated verum acupuncture might act by restoring the balance in the connectivity of the key pain brain regions, altering pain-related attention and memory.

Connecting Learning: Brain-Based Strategies for Linking Prior Knowledge in the Library Media Center

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Vanderbilt, Kathi L.

2005-01-01

The brain is a complex organ and learning is a complex process. While there is not complete agreement among researchers about brain-based learning and its direct connection to neuroscience, knowledge about the brain as well as the examination of cognitive psychology, anthropology, professional experience, and educational research can provide…

Integrated analysis and visualization of group differences in structural and functional brain connectivity: Applications in typical ageing and schizophrenia

NARCIS (Netherlands)

C.D. Langen (Carolyn); T.J.H. White (Tonya); M.A. Ikram (Arfan); M.W. Vernooij (Meike); W.J. Niessen (Wiro)

2015-01-01

textabstractStructural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uniand bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity : Applications in Typical Ageing and Schizophrenia

NARCIS (Netherlands)

Langen, C.D.; White, T.; Ikram, M.A.; Vernooij, M.W.; Niessen, W.J.

2015-01-01

Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

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Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant

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

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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

Natural Learning for a Connected World: Education, Technology, and the Human Brain

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Caine, Renate N.; Caine, Geoffrey

2011-01-01

Why do video games fascinate kids so much that they will spend hours pursuing a difficult skill? Why don't they apply this kind of intensity to their schoolwork? These questions are answered by the authors who pioneered brain/mind learning with the publication of "Making Connections: Teaching and the Human Brain". In their new book, "Natural…

Cross-sensory gating in schizophrenia and autism spectrum disorder: EEG evidence for impaired brain connectivity?

DEFF Research Database (Denmark)

Magnée, Maurice J C M; Oranje, Bob; van Engeland, Herman

2009-01-01

activation, which provides crucial information about functional integrity of connections between brain areas involved in cross-sensory processing in both disorders. Thirteen high functioning adult males with ASD, 13 high functioning adult males with schizophrenia, and 16 healthy adult males participated...... with the notion that filtering deficits may be secondary to earlier sensory dysfunction. Also, atypical cross-sensory suppression was found, which implies that the cognitive impairments seen in schizophrenia may be due to deficits in the integrity of connections between brain areas involved in low-level cross-sensory......Autism spectrum disorders (ASD) and schizophrenia are both neurodevelopmental disorders that have extensively been associated with impairments in functional brain connectivity. Using a cross-sensory P50 suppression paradigm, this study investigated low-level audiovisual interactions on cortical EEG...

Serum BDNF correlates with connectivity in the (pre)motor hub in the aging human brain--a resting-state fMRI pilot study.

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Mueller, Karsten; Arelin, Katrin; Möller, Harald E; Sacher, Julia; Kratzsch, Jürgen; Luck, Tobias; Riedel-Heller, Steffi; Villringer, Arno; Schroeter, Matthias L

2016-02-01

Brain-derived neurotrophic factor (BDNF) has been discussed to be involved in plasticity processes in the human brain, in particular during aging. Recently, aging and its (neurodegenerative) diseases have increasingly been conceptualized as disconnection syndromes. Here, connectivity changes in neural networks (the connectome) are suggested to be the most relevant and characteristic features for such processes or diseases. To further elucidate the impact of aging on neural networks, we investigated the interaction between plasticity processes, brain connectivity, and healthy aging by measuring levels of serum BDNF and resting-state fMRI data in 25 young (mean age 24.8 ± 2.7 (SD) years) and 23 old healthy participants (mean age, 68.6 ± 4.1 years). To identify neural hubs most essentially related to serum BDNF, we applied graph theory approaches, namely the new data-driven and parameter-free approach eigenvector centrality (EC) mapping. The analysis revealed a positive correlation between serum BDNF and EC in the premotor and motor cortex in older participants in contrast to young volunteers, where we did not detect any association. This positive relationship between serum BDNF and EC appears to be specific for older adults. Our results might indicate that the amount of physical activity and learning capacities, leading to higher BDNF levels, increases brain connectivity in (pre)motor areas in healthy aging in agreement with rodent animal studies. Pilot results have to be replicated in a larger sample including behavioral data to disentangle the cause for the relationship between BDNF levels and connectivity. Copyright © 2016 Elsevier Inc. All rights reserved.

Language learning and brain reorganization in a 3.5-year-old child with left perinatal stroke revealed using structural and functional connectivity.

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François, Clément; Ripollés, Pablo; Bosch, Laura; Garcia-Alix, Alfredo; Muchart, Jordi; Sierpowska, Joanna; Fons, Carme; Solé, Jorgina; Rebollo, Monica; Gaitán, Helena; Rodriguez-Fornells, Antoni

2016-04-01

Brain imaging methods have contributed to shed light on the possible mechanisms of recovery and cortical reorganization after early brain insult. The idea that a functional left hemisphere is crucial for achieving a normalized pattern of language development after left perinatal stroke is still under debate. We report the case of a 3.5-year-old boy born at term with a perinatal ischemic stroke of the left middle cerebral artery, affecting mainly the supramarginal gyrus, superior parietal and insular cortex extending to the precentral and postcentral gyri. Neurocognitive development was assessed at 25 and 42 months of age. Language outcomes were more extensively evaluated at the latter age with measures on receptive vocabulary, phonological whole-word production and linguistic complexity in spontaneous speech. Word learning abilities were assessed using a fast-mapping task to assess immediate and delayed recall of newly mapped words. Functional and structural imaging data as well as a measure of intrinsic connectivity were also acquired. While cognitive, motor and language levels from the Bayley Scales fell within the average range at 25 months, language scores were below at 42 months. Receptive vocabulary fell within normal limits but whole word production was delayed and the child had limited spontaneous speech. Critically, the child showed clear difficulties in both the immediate and delayed recall of the novel words, significantly differing from an age-matched control group. Neuroimaging data revealed spared classical cortical language areas but an affected left dorsal white-matter pathway together with right lateralized functional activations. In the framework of the model for Social Communication and Language Development, these data confirm the important role of the left arcuate fasciculus in understanding and producing morpho-syntactic elements in sentences beyond two word combinations and, most importantly, in learning novel word-referent associations, a

Moral competence and brain connectivity: a resting-state fMRI study

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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

Network connectivity and individual responses to brain stimulation in the human motor system.

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Cárdenas-Morales, Lizbeth; Volz, Lukas J; Michely, Jochen; Rehme, Anne K; Pool, Eva-Maria; Nettekoven, Charlotte; Eickhoff, Simon B; Fink, Gereon R; Grefkes, Christian

2014-07-01

The mechanisms driving cortical plasticity in response to brain stimulation are still incompletely understood. We here explored whether neural activity and connectivity in the motor system relate to the magnitude of cortical plasticity induced by repetitive transcranial magnetic stimulation (rTMS). Twelve right-handed volunteers underwent functional magnetic resonance imaging during rest and while performing a simple hand motor task. Resting-state functional connectivity, task-induced activation, and task-related effective connectivity were assessed for a network of key motor areas. We then investigated the effects of intermittent theta-burst stimulation (iTBS) on motor-evoked potentials (MEP) for up to 25 min after stimulation over left primary motor cortex (M1) or parieto-occipital vertex (for control). ITBS-induced increases in MEP amplitudes correlated negatively with movement-related fMRI activity in left M1. Control iTBS had no effect on M1 excitability. Subjects with better response to M1-iTBS featured stronger preinterventional effective connectivity between left premotor areas and left M1. In contrast, resting-state connectivity did not predict iTBS aftereffects. Plasticity-related changes in M1 following brain stimulation seem to depend not only on local factors but also on interconnected brain regions. Predominantly activity-dependent properties of the cortical motor system are indicative of excitability changes following induction of cortical plasticity with rTMS. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

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Zhao Baixiao

2008-11-01

Full Text Available Abstract Background Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear. Results In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network. Conclusion Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation.

Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity.

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Yongbin Chen

Full Text Available Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD, which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.

Increased Brain Connectivity In Early Postmenopausal Women with Subjective Cognitive Impairment

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Jennifer N Vega

2016-09-01

Full Text Available Cognitive changes after menopause are a common complaint, especially as the loss of estradiol at menopause has been hypothesized to contribute to the higher rates of dementia in women. To explore the neural processes related to subjective cognitive complaints, this study examined resting state functional connectivity in 31 postmenopausal women (aged 50-60 in relationship to cognitive complaints following menopause. A cognitive complaint index was calculated using responses to a 120-item questionnaire. Seed regions were identified for resting state brain networks important for higher-order cognitive processes and for areas that have shown differences in volume and functional activity associated with cognitive complaints in prior studies. Results indicated a positive correlation between the executive control network and cognitive complaint score, weaker negative functional connectivity within the frontal cortex, and stronger positive connectivity within the right middle temporal gyrus in postmenopausal women who report more cognitive complaints. While longitudinal studies are needed to confirm this hypothesis, these data are consistent with previous findings suggesting that high levels of cognitive complaints may reflect changes in brain connectivity and may be a potential marker for the risk of late-life cognitive dysfunction in postmenopausal women with otherwise normal cognitive performance.

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

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Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

Exploring the brains of Baduk (Go experts: gray matter morphometry, resting-state functional connectivity, and graph theoretical analysis

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Wi Hoon eJung

2013-10-01

Full Text Available One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the brains of Baduk experts compared with those of experts in other strategy games. Therefore, we performed voxel-based morphometry and FC analyses in Baduk experts to investigate structural brain differences and to clarify the influence of these differences on functional interactions. We also conducted graph theoretical analysis to explore the topological organization of whole-brain functional networks. Compared to novices, Baduk experts exhibited decreased and increased gray matter volume in the amygdala and nucleus accumbens, respectively. We also found increased FC between the amygdala and medial orbitofrontal cortex and decreased FC between the nucleus accumbens and medial prefrontal cortex. Further graph theoretical analysis revealed differences in measures of the integration of the network and in the regional nodal characteristics of various brain regions activated during Baduk. This study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in Baduk experts. Our findings also offer novel suggestions about the cognitive mechanisms behind Baduk expertise, which involves intuitive decision-making mediated by somatic marker circuitry and visuospatial processing.

Increased intrinsic brain connectivity between pons and somatosensory cortex during attacks of migraine with aura

DEFF Research Database (Denmark)

Hougaard, Anders; Amin, Faisal Mohammad; Larsson, Henrik B W

2017-01-01

The neurological disturbances of migraine aura are caused by transient cortical dysfunction due to waves of spreading depolarization that disrupt neuronal signaling. The effects of these cortical events on intrinsic brain connectivity during attacks of migraine aura have not previously been......-based approach focusing on cortical visual areas and areas involved in migraine pain, and a data-driven independent component analysis approach to detect changes in intrinsic brain signaling during attacks. In addition, we performed the analyses after mirroring the MRI data according to the side of perceived......-sided pain. For aura-side normalized data, we found increased connectivity during attacks between visual area V5 and the lower middle frontal gyrus in the symptomatic hemisphere (peak voxel: P = 0.0194, (x, y, z) = (40, 40, 12). The present study provides evidence of altered intrinsic brain connectivity...

Flexible modulation of network connectivity related to cognition in Alzheimer’s disease

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McLaren, Donald G.; Sperling, Reisa A.; Atria, Alireza

2014-01-01

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer’s disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54–82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive

Analyses of functional brain connectivity; Untersuchungen zur funktionellen Konnektivitaet des Gehirns

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Stephan, K.E.

2003-03-01

This dissertation includes two independent studies that investigate two complementary aspects of functional connectivity in the Macaque and the human brain. In the first study, a computational meta-analysis of published electrophysiological data on context-independent functional brain connectivity was conducted by means of three independent methods. The second study investigated the effects of the atypical antipsychotic substance olanzapine on the functional connectivity of the cerebellum during a simple motor task (self-paced finger tapping). Six schizophrenic patients and six control subjects matched for age and sex were investigated by functional magnetic resonance imaging (fMRI) twice. This study provided the first experimental data on the effects of atypical antipsychotic agents on functional brain connectivity and demonstrated pronounced olanzapine-dependent changes of functional couplings between cerebellum, thalamus, and prefrontal cortex. (orig.) [German] In der hier vorgelegten Arbeit werden zwei komplementaere Aspekte der funktionellen Konnektivitaet - im Gehirn des Makaken und Menschen anhand zweier separater Studien untersucht. In der ersten Studie wurde mittels dreier unabhaengiger Methoden eine Metaanalyse publizierter elektrophysiologischer Daten zur kontextunabhaengigen funktionellen Konnektivitaet des Makakenkortex durchgefuehrt. Diese Studie erbrachte damit zum ersten Mal den Nachweis einer funktionellen Small World-Netzwerkstruktur des Primatenkortex. In der zweiten Studie wurde der Effekt des atypischen Neuroleptikums Olanzapin auf die funktionelle Konnektivitaet des Zerebellums im Kontext einer einfachen motorischen Aufgabe (selbstgesteuertes Fingertrapping) untersucht. Sechs schizophrene Patienten, die Neuroleptika-naiv bzw. -entwoehnt waren, sowie sechs alters- und geschlechtsentprechende Kontrollprobanden wurden im Abstand von jeweils drei Wochen mit funktioneller Magnetresonanztomografie (fMRT) untersucht. Diese Studie lieferte die ersten

Brain-Wide Analysis of Functional Connectivity in First-Episode and Chronic Stages of Schizophrenia.

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Li, Tao; Wang, Qiang; Zhang, Jie; Rolls, Edmund T; Yang, Wei; Palaniyappan, Lena; Zhang, Lu; Cheng, Wei; Yao, Ye; Liu, Zhaowen; Gong, Xiaohong; Luo, Qiang; Tang, Yanqing; Crow, Timothy J; Broome, Matthew R; Xu, Ke; Li, Chunbo; Wang, Jijun; Liu, Zhening; Lu, Guangming; Wang, Fei; Feng, Jianfeng

2017-03-01

Published reports of functional abnormalities in schizophrenia remain divergent due to lack of staging point-of-view and whole-brain analysis. To identify key functional-connectivity differences of first-episode (FE) and chronic patients from controls using resting-state functional MRI, and determine changes that are specifically associated with disease onset, a clinical staging model is adopted. We analyze functional-connectivity differences in prodromal, FE (mostly drug naïve), and chronic patients from their matched controls from 6 independent datasets involving a total of 789 participants (343 patients). Brain-wide functional-connectivity analysis was performed in different datasets and the results from the datasets of the same stage were then integrated by meta-analysis, with Bonferroni correction for multiple comparisons. Prodromal patients differed from controls in their pattern of functional-connectivity involving the inferior frontal gyri (Broca's area). In FE patients, 90% of the functional-connectivity changes involved the frontal lobes, mostly the inferior frontal gyrus including Broca's area, and these changes were correlated with delusions/blunted affect. For chronic patients, functional-connectivity differences extended to wider areas of the brain, including reduced thalamo-frontal connectivity, and increased thalamo-temporal and thalamo-sensorimoter connectivity that were correlated with the positive, negative, and general symptoms, respectively. Thalamic changes became prominent at the chronic stage. These results provide evidence for distinct patterns of functional-dysconnectivity across FE and chronic stages of schizophrenia. Importantly, abnormalities in the frontal language networks appear early, at the time of disease onset. The identification of stage-specific pathological processes may help to understand the disease course of schizophrenia and identify neurobiological markers crucial for early diagnosis. © The Author 2016. Published by

Brain connectivity study of joint attention using frequency-domain optical imaging technique

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Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.

Early Environmental Enrichment Enhances Abnormal Brain Connectivity in a Rabbit Model of Intrauterine Growth Restriction.

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Illa, Miriam; Brito, Verónica; Pla, Laura; Eixarch, Elisenda; Arbat-Plana, Ariadna; Batallé, Dafnis; Muñoz-Moreno, Emma; Crispi, Fatima; Udina, Esther; Figueras, Francesc; Ginés, Silvia; Gratacós, Eduard

2017-10-12

The structural correspondence of neurodevelopmental impairments related to intrauterine growth restriction (IUGR) that persists later in life remains elusive. Moreover, early postnatal stimulation strategies have been proposed to mitigate these effects. Long-term brain connectivity abnormalities in an IUGR rabbit model and the effects of early postnatal environmental enrichment (EE) were explored. IUGR was surgically induced in one horn, whereas the contralateral one produced the controls. Postnatally, a subgroup of IUGR animals was housed in an enriched environment. Functional assessment was performed at the neonatal and long-term periods. At the long-term period, structural brain connectivity was evaluated by means of diffusion-weighted brain magnetic resonance imaging and by histological assessment focused on the hippocampus. IUGR animals displayed poorer functional results and presented altered whole-brain networks and decreased median fractional anisotropy in the hippocampus. Reduced density of dendritic spines and perineuronal nets from hippocampal neurons were also observed. Of note, IUGR animals exposed to enriched environment presented an improvement in terms of both function and structure. IUGR is associated with altered brain connectivity at the global and cellular level. A strategy based on early EE has the potential to restore the neurodevelopmental consequences of IUGR. © 2017 S. Karger AG, Basel.

Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity.

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Fjell, Anders M; Sneve, Markus H; Storsve, Andreas B; Grydeland, Håkon; Yendiki, Anastasia; Walhovd, Kristine B

2016-03-01

Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Moral competence and brain connectivity: A resting-state fMRI study.

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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.

Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivity

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Giancardo, Luca; Ellmore, Timothy M.; Suescun, Jessika; Ocasio, Laura; Kamali, Arash; Riascos-Castaneda, Roy; Schiess, Mya C.

2018-02-01

Methods to identify neuroplasticity patterns in human brains are of the utmost importance in understanding and potentially treating neurodegenerative diseases. Parkinson disease (PD) research will greatly benefit and advance from the discovery of biomarkers to quantify brain changes in the early stages of the disease, a prodromal period when subjects show no obvious clinical symptoms. Diffusion tensor imaging (DTI) allows for an in-vivo estimation of the structural connectome inside the brain and may serve to quantify the degenerative process before the appearance of clinical symptoms. In this work, we introduce a novel strategy to compute longitudinal structural connectomes in the context of a whole-brain data-driven pipeline. In these initial tests, we show that our predictive models are able to distinguish controls from asymptomatic subjects at high risk of developing PD (REM sleep behavior disorder, RBD) with an area under the receiving operating characteristic curve of 0.90 (pParkinson's Progression Markers Initiative. By analyzing the brain connections most relevant for the predictive ability of the best performing model, we find connections that are biologically relevant to the disease.

Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art

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Farràs-Permanyer, Laia; Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel

2015-01-01

In the last 15 years, many articles have studied brain connectivity in Mild Cognitive Impairment patients with fMRI techniques, seemingly using different connectivity statistical models in each investigation to identify complex connectivity structures so as to recognize typical behavior in this type of patient. This diversity in statistical approaches may cause problems in results comparison. This paper seeks to describe how researchers approached the study of brain connectivity in MCI patients using fMRI techniques from 2002 to 2014. The focus is on the statistical analysis proposed by each research group in reference to the limitations and possibilities of those techniques to identify some recommendations to improve the study of functional connectivity. The included articles came from a search of Web of Science and PsycINFO using the following keywords: f MRI, MCI, and functional connectivity. Eighty-one papers were found, but two of them were discarded because of the lack of statistical analysis. Accordingly, 79 articles were included in this review. We summarized some parts of the articles, including the goal of every investigation, the cognitive paradigm and methods used, brain regions involved, use of ROI analysis and statistical analysis, emphasizing on the connectivity estimation model used in each investigation. The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found. Additionally, the study of brain connectivity in this type of population is not providing, at the moment, any significant information or results related to clinical aspects relevant for prediction and treatment. We propose to follow guidelines for publishing fMRI data that would be a good solution to the problem of study replication. The latter aspect could be important for future publications because a higher homogeneity would benefit the comparison between publications and the generalization of results. PMID:26300802

Chimera states in brain networks: Empirical neural vs. modular fractal connectivity

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Chouzouris, Teresa; Omelchenko, Iryna; Zakharova, Anna; Hlinka, Jaroslav; Jiruska, Premysl; Schöll, Eckehard

2018-04-01

Complex spatiotemporal patterns, called chimera states, consist of coexisting coherent and incoherent domains and can be observed in networks of coupled oscillators. The interplay of synchrony and asynchrony in complex brain networks is an important aspect in studies of both the brain function and disease. We analyse the collective dynamics of FitzHugh-Nagumo neurons in complex networks motivated by its potential application to epileptology and epilepsy surgery. We compare two topologies: an empirical structural neural connectivity derived from diffusion-weighted magnetic resonance imaging and a mathematically constructed network with modular fractal connectivity. We analyse the properties of chimeras and partially synchronized states and obtain regions of their stability in the parameter planes. Furthermore, we qualitatively simulate the dynamics of epileptic seizures and study the influence of the removal of nodes on the network synchronizability, which can be useful for applications to epileptic surgery.

Brain Connectivity Alterations Are Associated with the Development of Dementia in Parkinson's Disease.

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Bertrand, Josie-Anne; McIntosh, Anthony R; Postuma, Ronald B; Kovacevic, Natasha; Latreille, Véronique; Panisset, Michel; Chouinard, Sylvain; Gagnon, Jean-François

2016-04-01

Dementia affects a high proportion of Parkinson's disease (PD) patients and poses a burden on caregivers and healthcare services. Electroencephalography (EEG) is a common nonevasive and nonexpensive technique that can easily be used in clinical settings to identify brain functional abnormalities. Only few studies had identified EEG abnormalities that can predict PD patients at higher risk for dementia. Brain connectivity EEG measures, such as multiscale entropy (MSE) and phase-locking value (PLV) analyses, may be more informative and sensitive to brain alterations leading to dementia than previously used methods. This study followed 62 dementia-free PD patients for a mean of 3.4 years to identify cerebral alterations that are associated with dementia. Baseline resting state EEG of patients who developed dementia (N = 18) was compared to those of patients who remained dementia-free (N = 44) and of 37 healthy subjects. MSE and PLV analyses were performed. Partial least squares statistical analysis revealed group differences associated with the development of dementia. Patients who developed dementia showed higher signal complexity and lower PLVs in low frequencies (mainly in delta frequency) than patients who remained dementia-free and controls. Conversely, both patient groups showed lower signal variability and higher PLVs in high frequencies (mainly in gamma frequency) compared to controls, with the strongest effect in patients who developed dementia. These findings suggest that specific disruptions of brain communication can be measured before PD patients develop dementia, providing a new potential marker to identify patients at highest risk of developing dementia and who are the best candidates for neuroprotective trials.

Temporal slice registration and robust diffusion-tensor reconstruction for improved fetal brain structural connectivity analysis.

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Marami, Bahram; Mohseni Salehi, Seyed Sadegh; Afacan, Onur; Scherrer, Benoit; Rollins, Caitlin K; Yang, Edward; Estroff, Judy A; Warfield, Simon K; Gholipour, Ali

2017-08-01

Diffusion weighted magnetic resonance imaging, or DWI, is one of the most promising tools for the analysis of neural microstructure and the structural connectome of the human brain. The application of DWI to map early development of the human connectome in-utero, however, is challenged by intermittent fetal and maternal motion that disrupts the spatial correspondence of data acquired in the relatively long DWI acquisitions. Fetuses move continuously during DWI scans. Reliable and accurate analysis of the fetal brain structural connectome requires careful compensation of motion effects and robust reconstruction to avoid introducing bias based on the degree of fetal motion. In this paper we introduce a novel robust algorithm to reconstruct in-vivo diffusion-tensor MRI (DTI) of the moving fetal brain and show its effect on structural connectivity analysis. The proposed algorithm involves multiple steps of image registration incorporating a dynamic registration-based motion tracking algorithm to restore the spatial correspondence of DWI data at the slice level and reconstruct DTI of the fetal brain in the standard (atlas) coordinate space. A weighted linear least squares approach is adapted to remove the effect of intra-slice motion and reconstruct DTI from motion-corrected data. The proposed algorithm was tested on data obtained from 21 healthy fetuses scanned in-utero at 22-38 weeks gestation. Significantly higher fractional anisotropy values in fiber-rich regions, and the analysis of whole-brain tractography and group structural connectivity, showed the efficacy of the proposed method compared to the analyses based on original data and previously proposed methods. The results of this study show that slice-level motion correction and robust reconstruction is necessary for reliable in-vivo structural connectivity analysis of the fetal brain. Connectivity analysis based on graph theoretic measures show high degree of modularity and clustering, and short average

Connectivity-based parcellation reveals distinct cortico-striatal connectivity fingerprints in Autism Spectrum Disorder.

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Balsters, Joshua H; Mantini, Dante; Wenderoth, Nicole

2018-04-15

Autism Spectrum Disorder (ASD) has been associated with abnormal synaptic development causing a breakdown in functional connectivity. However, when measured at the macro scale using resting state fMRI, these alterations are subtle and often difficult to detect due to the large heterogeneity of the pathology. Recently, we outlined a novel approach for generating robust biomarkers of resting state functional magnetic resonance imaging (RS-fMRI) using connectivity based parcellation of gross morphological structures to improve single-subject reproducibility and generate more robust connectivity fingerprints. Here we apply this novel approach to investigating the organization and connectivity strength of the cortico-striatal system in a large sample of ASD individuals and typically developed (TD) controls (N=130 per group). Our results showed differences in the parcellation of the striatum in ASD. Specifically, the putamen was found to be one single structure in ASD, whereas this was split into anterior and posterior segments in an age, IQ, and head movement matched TD group. An analysis of the connectivity fingerprints revealed that the group differences in clustering were driven by differential connectivity between striatum and the supplementary motor area, posterior cingulate cortex, and posterior insula. Our approach for analysing RS-fMRI in clinical populations has provided clear evidence that cortico-striatal circuits are organized differently in ASD. Based on previous task-based segmentations of the striatum, we believe that the anterior putamen cluster present in TD, but not in ASD, likely contributes to social and language processes. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS.

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Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

2016-01-01

This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, after true (sham) acupuncture in each group. Analysis of changes in connectivity among the brain areas was performed using the brain functional connectivity method. The right cerebrum temporal lobe was selected as the seed point to analyze the functional connectivity. It had a functional connectivity with right cerebrum superior frontal gyrus, limbic lobe cingulate gyrus and left cerebrum inferior temporal gyrus (BA 37), inferior parietal lobule compared by before vs. after acupuncture at LR3, and right cerebrum sub-lobar insula and left cerebrum middle frontal gyrus, medial frontal gyrus compared by true vs. sham acupuncture at LR3, and right cerebrum occipital lobe cuneus, occipital lobe sub-gyral, parietal lobe precuneus and left cerebellum anterior lobe culmen by acupuncture at LR3 vs. sham acupoint. Acupuncture at LR3 mainly specifically activated the brain functional network that participates in visual function, associative function, and emotion cognition, which are similar to the features on LR3 in tradition Chinese medicine. These brain areas constituted a neural network structure with specific functions that had specific reference values for the interpretation of the acupoint specificity of the Taichong acupoint.

Integrated Analysis and Visualization of Group Differences in Structural and Functional Brain Connectivity: Applications in Typical Ageing and Schizophrenia.

Directory of Open Access Journals (Sweden)

Carolyn D Langen

Full Text Available Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1 middle-aged versus elderly subjects; and (2 patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only

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

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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.

The Impact of Age and Cognitive Reserve on Resting-State Brain Connectivity

Directory of Open Access Journals (Sweden)

Jessica I. Fleck

2017-12-01

Full Text Available Cognitive reserve (CR is a protective mechanism that supports sustained cognitive function following damage to the physical brain associated with age, injury, or disease. The goal of the research was to identify relationships between age, CR, and brain connectivity. A sample of 90 cognitively normal adults, ages 45–64 years, had their resting-state brain activity recorded with electroencephalography (EEG and completed a series of memory and executive function assessments. CR was estimated using years of education and verbal IQ scores. Participants were divided into younger and older age groups and low- and high-CR groups. We observed greater left- than right-hemisphere coherence in younger participants, and greater right- than left-hemisphere coherence in older participants. In addition, greater coherence was observed under eyes-closed than eyes-open recording conditions for both low-CR and high-CR participants, with a more substantial difference between recording conditions in individuals high in CR regardless of age. Finally, younger participants low in CR exhibited greater mean coherence than younger participants high in CR, whereas the opposite pattern was observed in older participants, with greater coherence in older participants high in CR. Together, these findings suggest the possibility of a shift in the relationship between CR and brain connectivity during aging.

Developmental Reorganization of the Core and Extended Face Networks Revealed by Global Functional Connectivity.

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Wang, Xu; Zhu, Qi; Song, Yiying; Liu, Jia

2017-08-28

Prior studies on development of functional specialization in human brain mainly focus on age-related increases in regional activation and connectivity among regions. However, a few recent studies on the face network demonstrate age-related decrease in face-specialized activation in the extended face network (EFN), in addition to increase in activation in the core face network (CFN). Here we used a voxel-based global brain connectivity approach to investigate whether development of the face network exhibited both increase and decrease in network connectivity. We found the voxel-wise resting-state functional connectivity (FC) within the CFN increased with age in bilateral posterior superior temporal sulcus, suggesting the integration of the CFN during development. Interestingly, the FC of the voxels in the EFN to the right fusiform face area and occipital face area decreased with age, suggesting that the CFN segregated from the EFN during development. Moreover, the age-related connectivity in the CFN was related to behavioral performance in face processing. Overall, our study demonstrated developmental reorganization of the face network achieved by both integration within the CFN and segregation of the CFN from the EFN, which may account for the simultaneous increases and decreases in neural activation during the development of the face network. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Brain Functional Connectivity in Small Cell Lung Cancer Population after Chemotherapy Treatment: an ICA fMRI Study

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Bromis, K.; Kakkos, I.; Gkiatis, K.; Karanasiou, I. S.; Matsopoulos, G. K.

2017-11-01

Previous neurocognitive assessments in Small Cell Lung Cancer (SCLC) population, highlight the presence of neurocognitive impairments (mainly in attention processing and executive functioning) in this type of cancer. The majority of these studies, associate these deficits with the Prophylactic Cranial Irradiation (PCI) that patients undergo in order to avoid brain metastasis. However, there is not much evidence exploring cognitive impairments induced by chemotherapy in SCLC patients. For this reason, we aimed to investigate the underlying processes that may potentially affect cognition by examining brain functional connectivity in nineteen SCLC patients after chemotherapy treatment, while additionally including fourteen healthy participants as control group. Independent Component Analysis (ICA) is a functional connectivity measure aiming to unravel the temporal correlation between brain regions, which are called brain networks. We focused on two brain networks related to the aforementioned cognitive functions, the Default Mode Network (DMN) and the Task-Positive Network (TPN). Permutation tests were performed between the two groups to assess the differences and control for familywise errors in the statistical parametric maps. ICA analysis showed functional connectivity disruptions within both of the investigated networks. These results, propose a detrimental effect of chemotherapy on brain functioning in the SCLC population.

Degree-based statistic and center persistency for brain connectivity analysis.

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Yoo, Kwangsun; Lee, Peter; Chung, Moo K; Sohn, William S; Chung, Sun Ju; Na, Duk L; Ju, Daheen; Jeong, Yong

2017-01-01

Brain connectivity analyses have been widely performed to investigate the organization and functioning of the brain, or to observe changes in neurological or psychiatric conditions. However, connectivity analysis inevitably introduces the problem of mass-univariate hypothesis testing. Although, several cluster-wise correction methods have been suggested to address this problem and shown to provide high sensitivity, these approaches fundamentally have two drawbacks: the lack of spatial specificity (localization power) and the arbitrariness of an initial cluster-forming threshold. In this study, we propose a novel method, degree-based statistic (DBS), performing cluster-wise inference. DBS is designed to overcome the above-mentioned two shortcomings. From a network perspective, a few brain regions are of critical importance and considered to play pivotal roles in network integration. Regarding this notion, DBS defines a cluster as a set of edges of which one ending node is shared. This definition enables the efficient detection of clusters and their center nodes. Furthermore, a new measure of a cluster, center persistency (CP) was introduced. The efficiency of DBS with a known "ground truth" simulation was demonstrated. Then they applied DBS to two experimental datasets and showed that DBS successfully detects the persistent clusters. In conclusion, by adopting a graph theoretical concept of degrees and borrowing the concept of persistence from algebraic topology, DBS could sensitively identify clusters with centric nodes that would play pivotal roles in an effect of interest. DBS is potentially widely applicable to variable cognitive or clinical situations and allows us to obtain statistically reliable and easily interpretable results. Hum Brain Mapp 38:165-181, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Brain Activity and Functional Connectivity Associated with Hypnosis.

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Jiang, Heidi; White, Matthew P; Greicius, Michael D; Waelde, Lynn C; Spiegel, David

2017-08-01

Hypnosis has proven clinical utility, yet changes in brain activity underlying the hypnotic state have not yet been fully identified. Previous research suggests that hypnosis is associated with decreased default mode network (DMN) activity and that high hypnotizability is associated with greater functional connectivity between the executive control network (ECN) and the salience network (SN). We used functional magnetic resonance imaging to investigate activity and functional connectivity among these three networks in hypnosis. We selected 57 of 545 healthy subjects with very high or low hypnotizability using two hypnotizability scales. All subjects underwent four conditions in the scanner: rest, memory retrieval, and two different hypnosis experiences guided by standard pre-recorded instructions in counterbalanced order. Seeds for the ECN, SN, and DMN were left and right dorsolateral prefrontal cortex, dorsal anterior cingulate cortex (dACC), and posterior cingulate cortex (PCC), respectively. During hypnosis there was reduced activity in the dACC, increased functional connectivity between the dorsolateral prefrontal cortex (DLPFC;ECN) and the insula in the SN, and reduced connectivity between the ECN (DLPFC) and the DMN (PCC). These changes in neural activity underlie the focused attention, enhanced somatic and emotional control, and lack of self-consciousness that characterizes hypnosis. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Complex brain networks: From topological communities to clustered

Indian Academy of Sciences (India)

Complex brain networks: From topological communities to clustered dynamics ... Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. ... Pramana – Journal of Physics | News.

Can musical training influence brain connectivity? Evidence from diffusion tensor MRI.

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Moore, Emma; Schaefer, Rebecca S; Bastin, Mark E; Roberts, Neil; Overy, Katie

2014-06-10

In recent years, musicians have been increasingly recruited to investigate grey and white matter neuroplasticity induced by skill acquisition. The development of Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) has allowed more detailed investigation of white matter connections within the brain, addressing questions about the effect of musical training on connectivity between specific brain regions. Here, current DT-MRI analysis techniques are discussed and the available evidence from DT-MRI studies into differences in white matter architecture between musicians and non-musicians is reviewed. Collectively, the existing literature tends to support the hypothesis that musical training can induce changes in cross-hemispheric connections, with significant differences frequently reported in various regions of the corpus callosum of musicians compared with non-musicians. However, differences found in intra-hemispheric fibres have not always been replicated, while findings regarding the internal capsule and corticospinal tracts appear to be contradictory. There is also recent evidence to suggest that variances in white matter structure in non-musicians may correlate with their ability to learn musical skills, offering an alternative explanation for the structural differences observed between musicians and non-musicians. Considering the inconsistencies in the current literature, possible reasons for conflicting results are offered, along with suggestions for future research in this area.

Alpha band functional connectivity correlates with the performance of brain-machine interfaces to decode real and imagined movements

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Hisato eSugata

2014-08-01

Full Text Available Brain signals recorded from the primary motor cortex (M1 are known to serve a significant role in coding the information brain-machine interfaces (BMIs need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beamforming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.

New insights in the homotopic and heterotopic connectivity of the frontal portion of the human corpus callosum revealed by microdissection and diffusion tractography.

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De Benedictis, Alessandro; Petit, Laurent; Descoteaux, Maxime; Marras, Carlo Efisio; Barbareschi, Mattia; Corsini, Francesco; Dallabona, Monica; Chioffi, Franco; Sarubbo, Silvio

2016-12-01

Extensive studies revealed that the human corpus callosum (CC) plays a crucial role in providing large-scale bi-hemispheric integration of sensory, motor and cognitive processing, especially within the frontal lobe. However, the literature lacks of conclusive data regarding the structural macroscopic connectivity of the frontal CC. In this study, a novel microdissection approach was adopted, to expose the frontal fibers of CC from the dorsum to the lateral cortex in eight hemispheres and in one entire brain. Post-mortem results were then combined with data from advanced constrained spherical deconvolution in 130 healthy subjects. We demonstrated as the frontal CC provides dense inter-hemispheric connections. In particular, we found three types of fronto-callosal fibers, having a dorso-ventral organization. First, the dorso-medial CC fibers subserve homotopic connections between the homologous medial cortices of the superior frontal gyrus. Second, the ventro-lateral CC fibers subserve homotopic connections between lateral frontal cortices, including both the middle frontal gyrus and the inferior frontal gyrus, as well as heterotopic connections between the medial and lateral frontal cortices. Third, the ventro-striatal CC fibers connect the medial and lateral frontal cortices with the contralateral putamen and caudate nucleus. We also highlighted an intricate crossing of CC fibers with the main association pathways terminating in the lateral regions of the frontal lobes. This combined approach of ex vivo microdissection and in vivo diffusion tractography allowed demonstrating a previously unappreciated three-dimensional architecture of the anterior frontal CC, thus clarifying the functional role of the CC in mediating the inter-hemispheric connectivity. Hum Brain Mapp 37:4718-4735, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A signaling network for patterning of neuronal connectivity in the Drosophila brain.

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Mohammed Srahna

2006-10-01

Full Text Available The precise number and pattern of axonal connections generated during brain development regulates animal behavior. Therefore, understanding how developmental signals interact to regulate axonal extension and retraction to achieve precise neuronal connectivity is a fundamental goal of neurobiology. We investigated this question in the developing adult brain of Drosophila and find that it is regulated by crosstalk between Wnt, fibroblast growth factor (FGF receptor, and Jun N-terminal kinase (JNK signaling, but independent of neuronal activity. The Rac1 GTPase integrates a Wnt-Frizzled-Disheveled axon-stabilizing signal and a Branchless (FGF-Breathless (FGF receptor axon-retracting signal to modulate JNK activity. JNK activity is necessary and sufficient for axon extension, whereas the antagonistic Wnt and FGF signals act to balance the extension and retraction required for the generation of the precise wiring pattern.

Gender differences of brain glucose metabolic networks revealed by FDG-PET: evidence from a large cohort of 400 young adults.

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Hu, Yuxiao; Xu, Qiang; Li, Kai; Zhu, Hong; Qi, Rongfeng; Zhang, Zhiqiang; Lu, Guangming

2013-01-01

Gender differences of the human brain are an important issue in neuroscience research. In recent years, an increasing amount of evidence has been gathered from noninvasive neuroimaging studies supporting a sexual dimorphism of the human brain. However, there is a lack of imaging studies on gender differences of brain metabolic networks based on a large population sample. FDG PET data of 400 right-handed, healthy subjects, including 200 females (age: 25:45 years, mean age ± SD: 40.9 ± 3.9 years) and 200 age-matched males were obtained and analyzed in the present study. We first investigated the regional differences of brain glucose metabolism between genders using a voxel-based two-sample t-test analysis. Subsequently, we investigated the gender differences of the metabolic networks. Sixteen metabolic covariance networks using seed-based correlation were analyzed. Seven regions showing significant regional metabolic differences between genders, and nine regions conventionally used in the resting-state network studies were selected as regions-of-interest. Permutation tests were used for comparing within- and between-network connectivity between genders. Compared with the males, females showed higher metabolism in the posterior part and lower metabolism in the anterior part of the brain. Moreover, there were widely distributed patterns of the metabolic networks in the human brain. In addition, significant gender differences within and between brain glucose metabolic networks were revealed in the present study. This study provides solid data that reveal gender differences in regional brain glucose metabolism and brain glucose metabolic networks. These observations might contribute to the better understanding of the gender differences in human brain functions, and suggest that gender should be included as a covariate when designing experiments and explaining results of brain glucose metabolic networks in the control and experimental individuals or patients.

Effect of dietary docosahexaenoic acid connecting phospholipids on the lipid peroxidation of the brain in mice.

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Hiratsuka, Seiichi; Ishihara, Kenji; Kitagawa, Tomoko; Wada, Shun; Yokogoshi, Hidehiko

2008-12-01

The effect of dietary docosahexaenoic acid (DHA, C22:6n-3) with two lipid types on lipid peroxidation of the brain was investigated in streptozotocin (STZ)-induced diabetic mice. Each group of female Balb/c mice was fed a diet containing DHA-connecting phospholipids (DHA-PL) or DHA-connecting triacylglycerols (DHA-TG) for 5 wk. Safflower oil was fed as the control. The lipid peroxide level of the brain was significantly lower in the mice fed the DHA-PL diet when compared to those fed the DHA-TG and safflower oil diets, while the alpha-tocopherol level was significantly higher in the mice fed the DHA-PL diet than in those fed the DHA-TG and safflower oil diets. The DHA level of phosphatidylethanolamine in the brain was significantly higher in the mice fed the DHA-PL diet than in those fed the safflower oil diet. The dimethylacetal levels were significantly higher in the mice fed the DHA-PL diet than in those fed the safflower oil and DHA-TG diets. These results suggest that the dietary DHA-connecting phospholipids have an antioxidant activity on the brain lipids in mice, and the effect may be related to the brain plasmalogen.

Stereoscopic Three-Dimensional Visualization Applied to Multimodal Brain Images: Clinical Applications and a Functional Connectivity Atlas.

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Gonzalo M Rojas

2014-11-01

Full Text Available Effective visualization is central to the exploration and comprehension of brain imaging data. While MRI data are acquired in three-dimensional space, the methods for visualizing such data have rarely taken advantage of three-dimensional stereoscopic technologies. We present here results of stereoscopic visualization of clinical data, as well as an atlas of whole-brain functional connectivity. In comparison with traditional 3D rendering techniques, we demonstrate the utility of stereoscopic visualizations to provide an intuitive description of the exact location and the relative sizes of various brain landmarks, structures and lesions. In the case of resting state fMRI, stereoscopic 3D visualization facilitated comprehension of the anatomical position of complex large-scale functional connectivity patterns. Overall, stereoscopic visualization improves the intuitive visual comprehension of image contents, and brings increased dimensionality to visualization of traditional MRI data, as well as patterns of functional connectivity.

Brain functional connectivity and the pathophysiology of schizophrenia.

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Angelopoulos, E

2014-01-01

In the last decade there is extensive evidence to suggest that cognitive functions depending on coordination of distributed neuronal responses are associated with synchronized oscillatory activity in various frequency ranges suggesting a functional mechanism of neural oscillations in cortical networks. In addition to their role in normal brain functioning, there is increasing evidence that altered oscillatory activity may be associated with certain neuropsychiatric disorders, such as schizophrenia. Consequently, disturbances in neural synchronization may represent the functional relationship of disordered connectivity of cortical networks underlying the characteristic fragmentation of mind and behavior in schizophrenia. In recent studies the synchronization of oscillatory activity in the experience of characteristic symptoms such as auditory verbal hallucinations and thought blocks have been studied in patients with schizophrenia. Studies involving analysis of EEG activity obtained from individuals in resting state (in cage Faraday, isolated from external influences and with eyes closed). In patients with schizophrenia and persistent auditory verbal hallucinations (AVHs) observed a temporary increase in the synchronization phase of α and high θ oscillations of the electroencephalogram (EEG) compared with those of healthy controls and patients without AVHs . This functional hyper-connection manifested in time windows corresponding to experience AVHs, as noted by the patients during the recording of EEG and observed in speech related cortical areas. In another study an interaction of theta and gamma oscillations engages in the production and experience of AVHs. The results showed increased phase coupling between theta and gamma EEG rhythms in the left temporal cortex during AVHs experiences. A more recent study, approaches the thought blocking experience in terms of functional brain connectivity. Thought blocks (TBs) are characterized by regular interruptions of

Mapping cell-specific functional connections in the mouse brain using ChR2-evoked hemodynamics (Conference Presentation)

Science.gov (United States)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.

Altered Insula Connectivity under MDMA.

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Walpola, Ishan C; Nest, Timothy; Roseman, Leor; Erritzoe, David; Feilding, Amanda; Nutt, David J; Carhart-Harris, Robin L

2017-10-01

Recent work with noninvasive human brain imaging has started to investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA) on large-scale patterns of brain activity. MDMA, a potent monoamine-releaser with particularly pronounced serotonin- releasing properties, has unique subjective effects that include: marked positive mood, pleasant/unusual bodily sensations and pro-social, empathic feelings. However, the neurobiological basis for these effects is not properly understood, and the present analysis sought to address this knowledge gap. To do this, we administered MDMA-HCl (100 mg p.o.) and, separately, placebo (ascorbic acid) in a randomized, double-blind, repeated-measures design with twenty-five healthy volunteers undergoing fMRI scanning. We then employed a measure of global resting-state functional brain connectivity and follow-up seed-to-voxel analysis to the fMRI data we acquired. Results revealed decreased right insula/salience network functional connectivity under MDMA. Furthermore, these decreases in right insula/salience network connectivity correlated with baseline trait anxiety and acute experiences of altered bodily sensations under MDMA. The present findings highlight insular disintegration (ie, compromised salience network membership) as a neurobiological signature of the MDMA experience, and relate this brain effect to trait anxiety and acutely altered bodily sensations-both of which are known to be associated with insular functioning.

Three Types of Cortical L5 Neurons that Differ in Brain-Wide Connectivity and Function

Science.gov (United States)

Kim, Euiseok J.; Juavinett, Ashley L.; Kyubwa, Espoir M.; Jacobs, Matthew W.; Callaway, Edward M.

2015-01-01

SUMMARY Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception. PMID:26671462

Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease.

Science.gov (United States)

Jie, Biao; Liu, Mingxia; Shen, Dinggang

2018-07-01

Functional connectivity networks (FCNs) using resting-state functional magnetic resonance imaging (rs-fMRI) have been applied to the analysis and diagnosis of brain disease, such as Alzheimer's disease (AD) and its prodrome, i.e., mild cognitive impairment (MCI). Different from conventional studies focusing on static descriptions on functional connectivity (FC) between brain regions in rs-fMRI, recent studies have resorted to dynamic connectivity networks (DCNs) to characterize the dynamic changes of FC, since dynamic changes of FC may indicate changes in macroscopic neural activity patterns in cognitive and behavioral aspects. However, most of the existing studies only investigate the temporal properties of DCNs (e.g., temporal variability of FC between specific brain regions), ignoring the important spatial properties of the network (e.g., spatial variability of FC associated with a specific brain region). Also, emerging evidence on FCNs has suggested that, besides temporal variability, there is significant spatial variability of activity foci over time. Hence, integrating both temporal and spatial properties of DCNs can intuitively promote the performance of connectivity-network-based learning methods. In this paper, we first define a new measure to characterize the spatial variability of DCNs, and then propose a novel learning framework to integrate both temporal and spatial variabilities of DCNs for automatic brain disease diagnosis. Specifically, we first construct DCNs from the rs-fMRI time series at successive non-overlapping time windows. Then, we characterize the spatial variability of a specific brain region by computing the correlation of functional sequences (i.e., the changing profile of FC between a pair of brain regions within all time windows) associated with this region. Furthermore, we extract both temporal variabilities and spatial variabilities from DCNs as features, and integrate them for classification by using manifold regularized multi

Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease.

Science.gov (United States)

Muñoz-Moreno, Emma; Tudela, Raúl; López-Gil, Xavier; Soria, Guadalupe

2018-02-07

Animal models of Alzheimer's disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain connectivity at an early stage (5 months of age) before a significant concentration of β-amyloid plaques is present. Cognitive abilities were assessed by a delayed nonmatch-to-sample (DNMS) task preceded by a training phase where the animals learned the task. The number of training sessions required to achieve a learning criterion was recorded and evaluated. After DNMS, MRI acquisition was performed, including diffusion-weighted MRI and resting-state functional MRI, which were processed to obtain the structural and functional connectomes, respectively. Global and regional graph metrics were computed to evaluate network organization in both transgenic and control rats. The results pointed to a delay in learning the working memory-related task in the AD rats, which also completed a lower number of trials in the DNMS task. Regarding connectivity properties, less efficient organization of the structural brain networks of the transgenic rats with respect to controls was observed. Specific regional differences in connectivity were identified in both structural and functional networks. In addition, a strong correlation was observed between cognitive performance and brain networks, including whole-brain structural connectivity as well as functional and structural network metrics of regions related to memory and reward processes. In this study, connectivity and neurocognitive impairments were identified in TgF344-AD rats at a very early stage of the disease when most of the pathological hallmarks

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

Brain activation and connectivity of social cognition using diffuse optical imaging

Science.gov (United States)

Zhu, Banghe; Godavarty, Anuradha

2009-02-01

In the current research, diffuse optical imaging (DOI) is used for the first time towards studies related to sociocommunication impairments, which is a characteristic feature of autism. DOI studies were performed on normal adult volunteers to determine the differences in the brain activation (cognitive regions) in terms of the changes in the cerebral blood oxygenation levels in response to joint and non-joint attention based stimulus (i.e. socio-communicative paradigms shown as video clips). Functional connectivity models are employed to assess the extent of synchronization between the left and right pre-frontal regions of the brain in response to the above stimuli.

Unraveling the multiscale structural organization and connectivity of the human brain: the role of diffusion MRI

Directory of Open Access Journals (Sweden)

Matteo eBastiani

2015-06-01

Full Text Available The structural architecture and the anatomical connectivity of the human brain show different organizational principles at distinct spatial scales. Histological staining and light microscopy techniques have been widely used in classical neuroanatomical studies to unravel brain organization. Using such techniques is a laborious task performed on 2-dimensional histological sections by skilled anatomists possibly aided by semi-automated algorithms. With the recent advent of modern magnetic resonance imaging (MRI contrast mechanisms, cortical layers and columns can now be reliably identified and their structural properties quantified post mortem. These developments are allowing the investigation of neuroanatomical features of the brain at a spatial resolution that could be interfaced with that of histology. Diffusion MRI and tractography techniques, in particular, have been used to probe the architecture of both white and gray matter in three dimensions. Combined with mathematical network analysis, these techniques are increasingly influential in the investigation of the macro-, meso- and microscopic organization of brain connectivity and anatomy, both in vivo and ex vivo. Diffusion MRI-based techniques in combination with histology approaches can therefore support the endeavor of creating multimodal atlases that take into account the different spatial scales or levels on which the brain is organized. The aim of this review is to illustrate and discuss the structural architecture and the anatomical connectivity of the human brain at different spatial scales and how recently developed diffusion MRI techniques can help investigate these.

A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease

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Murat Demirtaş

2017-01-01

Full Text Available Alzheimer's disease (AD is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC of the subjects with preclinical Alzheimer's disease (PAD, mild cognitive impairment due to AD (MCI and mild dementia due to Alzheimer's disease (AD, the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1−42 total tau (t-tau and phosphorylated tau (p-tau. CSF Aβ1−42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1−42. APOE4 carriership showed no significant correlations with the connectivity measures.

Subcomponents and connectivity of the superior longitudinal fasciculus in the human brain.

Science.gov (United States)

Wang, Xuhui; Pathak, Sudhir; Stefaneanu, Lucia; Yeh, Fang-Cheng; Li, Shiting; Fernandez-Miranda, Juan C

2016-05-01

The subcomponents of the human superior longitudinal fasciculus (SLF) are disputed. The objective of this study was to investigate the segments, connectivity and asymmetry of the SLF. We performed high angular diffusion spectrum imaging (DSI) analysis on ten healthy adults. We also conducted fiber tracking on a 30-subject DSI template (CMU-30) and 488-subject template from the Human Connectome Project (HCP-488). In addition, five normal brains obtained at autopsy were microdissected. Based on tractography and microdissection results, we show that the human SLF differs significantly from that of monkey. The fibers corresponding to SLF-I found in 6 out of 20 hemispheres proved to be part of the cingulum fiber system in all cases and confirmed on both DSI and HCP-488 template. The most common patterns of connectivity bilaterally were as follows: from angular gyrus to caudal middle frontal gyrus and dorsal precentral gyrus representing SLF-II (or dorsal SLF), and from supramarginal gyrus to ventral precentral gyrus and pars opercularis to form SLF-III (or ventral SLF). Some connectivity features were, however, clearly asymmetric. Thus, we identified a strong asymmetry of the dorsal SLF (SLF-II), where the connectivity between the supramarginal gyrus with the dorsal precentral gyrus and the caudal middle frontal gyrus was only present in the left hemisphere. Contrarily, the ventral SLF (SLF-III) showed fairly constant connectivity with pars triangularis only in the right hemisphere. The results provide a novel neuroanatomy of the SLF that may help to better understand its functional role in the human brain.

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy

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Jonathan Wirsich

2016-01-01

In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.

Brain Functional Connectivity Is Modified by a Hypocaloric Mediterranean Diet and Physical Activity in Obese Women

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Natalia García-Casares

2017-07-01

Full Text Available Functional magnetic resonance imaging (fMRI in the resting state has shown altered brain connectivity networks in obese individuals. However, the impact of a Mediterranean diet on cerebral connectivity in obese patients when losing weight has not been previously explored. The aim of this study was to examine the connectivity between brain structures before and six months after following a hypocaloric Mediterranean diet and physical activity program in a group of sixteen obese women aged 46.31 ± 4.07 years. Before and after the intervention program, the body mass index (BMI (kg/m2 was 38.15 ± 4.7 vs. 34.18 ± 4.5 (p < 0.02, and body weight (kg was 98.5 ± 13.1 vs. 88.28 ± 12.2 (p < 0.03. All subjects underwent a pre- and post-intervention fMRI under fasting conditions. Functional connectivity was assessed using seed-based correlations. After the intervention, we found decreased connectivity between the left inferior parietal cortex and the right temporal cortex (p < 0.001, left posterior cingulate (p < 0.001, and right posterior cingulate (p < 0.03; decreased connectivity between the left superior frontal gyrus and the right temporal cortex (p < 0.01; decreased connectivity between the prefrontal cortex and the somatosensory cortex (p < 0.025; and decreased connectivity between the left and right posterior cingulate (p < 0.04. Results were considered significant at a voxel-wise threshold of p ≤ 0.05, and a cluster-level family-wise error correction for multiple comparisons of p ≤ 0.05. In conclusion, functional connectivity between brain structures involved in the pathophysiology of obesity (the inferior parietal lobe, posterior cingulate, temporo-insular cortex, prefrontal cortex may be modified by a weight loss program including a Mediterranean diet and physical exercise.

Brain Functional Connectivity Is Modified by a Hypocaloric Mediterranean Diet and Physical Activity in Obese Women.

Science.gov (United States)

García-Casares, Natalia; Bernal-López, María R; Roé-Vellvé, Nuria; Gutiérrez-Bedmar, Mario; Fernández-García, Jose C; García-Arnés, Juan A; Ramos-Rodriguez, José R; Alfaro, Francisco; Santamaria-Fernández, Sonia; Steward, Trevor; Jiménez-Murcia, Susana; Garcia-Garcia, Isabel; Valdivielso, Pedro; Fernández-Aranda, Fernando; Tinahones, Francisco J; Gómez-Huelgas, Ricardo

2017-07-01

Functional magnetic resonance imaging (fMRI) in the resting state has shown altered brain connectivity networks in obese individuals. However, the impact of a Mediterranean diet on cerebral connectivity in obese patients when losing weight has not been previously explored. The aim of this study was to examine the connectivity between brain structures before and six months after following a hypocaloric Mediterranean diet and physical activity program in a group of sixteen obese women aged 46.31 ± 4.07 years. Before and after the intervention program, the body mass index (BMI) (kg/m²) was 38.15 ± 4.7 vs. 34.18 ± 4.5 ( p diet and physical exercise.

Quetiapine modulates functional connectivity in brain aggression networks.

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Klasen, Martin; Zvyagintsev, Mikhail; Schwenzer, Michael; Mathiak, Krystyna A; Sarkheil, Pegah; Weber, René; Mathiak, Klaus

2013-07-15

Aggressive behavior is associated with dysfunctions in an affective regulation network encompassing amygdala and prefrontal areas such as orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC). In particular, prefrontal regions have been postulated to control amygdala activity by inhibitory projections, and this process may be disrupted in aggressive individuals. The atypical antipsychotic quetiapine successfully attenuates aggressive behavior in various disorders; the underlying neural processes, however, are unknown. A strengthened functional coupling in the prefrontal-amygdala system may account for these anti-aggressive effects. An inhibition of this network has been reported for virtual aggression in violent video games as well. However, there have been so far no in-vivo observations of pharmacological influences on corticolimbic projections during human aggressive behavior. In a double-blind, placebo-controlled study, quetiapine and placebo were administered for three successive days prior to an fMRI experiment. In this experiment, functional brain connectivity was assessed during virtual aggressive behavior in a violent video game and an aggression-free control task in a non-violent modification. Quetiapine increased the functional connectivity of ACC and DLPFC with the amygdala during virtual aggression, whereas OFC-amygdala coupling was attenuated. These effects were observed neither for placebo nor for the non-violent control. These results demonstrate for the first time a pharmacological modification of aggression-related human brain networks in a naturalistic setting. The violence-specific modulation of prefrontal-amygdala networks appears to control aggressive behavior and provides a neurobiological model for the anti-aggressive effects of quetiapine. Copyright © 2013 Elsevier Inc. All rights reserved.

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

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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.

Structural and effective connectivity reveals potential network-based influences on category-sensitive visual areas

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Nicholas eFurl

2015-05-01

Full Text Available Visual category perception is thought to depend on brain areas that respond specifically when certain categories are viewed. These category-sensitive areas are often assumed to be modules (with some degree of processing autonomy and to act predominantly on feedforward visual input. This modular view can be complemented by a view that treats brain areas as elements within more complex networks and as influenced by network properties. This network-oriented viewpoint is emerging from studies using either diffusion tensor imaging to map structural connections or effective connectivity analyses to measure how their functional responses influence each other. This literature motivates several hypotheses that predict category-sensitive activity based on network properties. Large, long-range fiber bundles such as inferior fronto-occipital, arcuate and inferior longitudinal fasciculi are associated with behavioural recognition and could play crucial roles in conveying backward influences on visual cortex from anterior temporal and frontal areas. Such backward influences could support top-down functions such as visual search and emotion-based visual modulation. Within visual cortex itself, areas sensitive to different categories appear well-connected (e.g., face areas connect to object- and motion sensitive areas and their responses can be predicted by backward modulation. Evidence supporting these propositions remains incomplete and underscores the need for better integration of DTI and functional imaging.

Concurrent tACS-fMRI Reveals Causal Influence of Power Synchronized Neural Activity on Resting State fMRI Connectivity.

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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

Sex Commonalities and Differences in Obesity-Related Alterations in Intrinsic Brain Activity and Connectivity.

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Gupta, Arpana; Mayer, Emeran A; Labus, Jennifer S; Bhatt, Ravi R; Ju, Tiffany; Love, Aubrey; Bal, Amanat; Tillisch, Kirsten; Naliboff, Bruce; Sanmiguel, Claudia P; Kilpatrick, Lisa A

2018-02-01

This study aimed to characterize obesity-related sex differences in the intrinsic activity and connectivity of the brain's reward networks. Eighty-six women (n = 43) and men (n = 43) completed a 10-minute resting functional magnetic resonance imaging scan. Sex differences and commonalities in BMI-related frequency power distribution and reward seed-based connectivity were investigated by using partial least squares analysis. For whole-brain activity in both men and women, increased BMI was associated with increased slow-5 activity in the left globus pallidus (GP) and substantia nigra. In women only, increased BMI was associated with increased slow-4 activity in the right GP and bilateral putamen. For seed-based connectivity in women, increased BMI was associated with reduced slow-5 connectivity between the left GP and putamen and the emotion and cortical regulation regions, but in men, increased BMI was associated with increased connectivity with the medial frontal cortex. In both men and women, increased BMI was associated with increased slow-4 connectivity between the right GP and bilateral putamen and the emotion regulation and sensorimotor-related regions. The stronger relationship between increased BMI and decreased connectivity of core reward network components with cortical and emotion regulation regions in women may be related to the greater prevalence of emotional eating. The present findings suggest the importance of personalized treatments for obesity that consider the sex of the affected individual. © 2017 The Obesity Society.

Patterns of brain structural connectivity differentiate normal weight from overweight subjects.

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Gupta, Arpana; Mayer, Emeran A; Sanmiguel, Claudia P; Van Horn, John D; Woodworth, Davis; Ellingson, Benjamin M; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S

2015-01-01

Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

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Gupta, Arpana; Mayer, Emeran A.; Sanmiguel, Claudia P.; Van Horn, John D.; Woodworth, Davis; Ellingson, Benjamin M.; Fling, Connor; Love, Aubrey; Tillisch, Kirsten; Labus, Jennifer S.

2015-01-01

Background Alterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks. Aim To apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements. Methods Structural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals. Results 1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42

Aging Effects on Whole-Brain Functional Connectivity in Adults Free of Cognitive and Psychiatric Disorders.

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Ferreira, Luiz Kobuti; Regina, Ana Carolina Brocanello; Kovacevic, Natasa; Martin, Maria da Graça Morais; Santos, Pedro Paim; Carneiro, Camila de Godoi; Kerr, Daniel Shikanai; Amaro, Edson; McIntosh, Anthony Randal; Busatto, Geraldo F

2016-09-01

Aging is associated with decreased resting-state functional connectivity (RSFC) within the default mode network (DMN), but most functional imaging studies have restricted the analysis to specific brain regions or networks, a strategy not appropriate to describe system-wide changes. Moreover, few investigations have employed operational psychiatric interviewing procedures to select participants; this is an important limitation since mental disorders are prevalent and underdiagnosed and can be associated with RSFC abnormalities. In this study, resting-state fMRI was acquired from 59 adults free of cognitive and psychiatric disorders according to standardized criteria and based on extensive neuropsychological and clinical assessments. We tested for associations between age and whole-brain RSFC using Partial Least Squares, a multivariate technique. We found that normal aging is not only characterized by decreased RSFC within the DMN but also by ubiquitous increases in internetwork positive correlations and focal internetwork losses of anticorrelations (involving mainly connections between the DMN and the attentional networks). Our results reinforce the notion that the aging brain undergoes a dedifferentiation processes with loss of functional diversity. These findings advance the characterization of healthy aging effects on RSFC and highlight the importance of adopting a broad, system-wide perspective to analyze brain connectivity. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity.

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De Pasquale, Francesco; Caravasso, Chiara Falletta; Péran, Patrice; Catani, Sheila; Tuovinen, Noora; Sabatini, Umberto; Formisano, Rita

2015-01-01

The aim of this preliminary study was to present a new approach for connectivity analysis in patients with severe acquired brain injury (ABI) that overcomes some of the difficulties created by anatomical abnormalities due to the brain injury. Using a data-driven approach, resting-state structural MRI (sMRI) and functional MRI (fMRI) data from three severe ABI patients - two with disorders of consciousness (DOC) and one who had recovered consciousness (non-DOC) - were integrated and analyzed. Parameters extracted from the distribution of the connectivity values, such as mean, standard deviation and skeweness, were considered. The distribution parameters estimated seem to provide an accurate multivariate classification of the considered cases that can be summarized as follows: connectivity in the severe ABI patients with DOC was on average lower than in the severe ABI non-DOC patient and healthy subjects. The dispersion of connectivity values of the severe ABI patients, non-DOC and DOC, was comparable, however the shape of the distribution was different in the non-DOC patient. Eventually, seed-based connectivity maps of the default mode Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity network show a pattern of increasing disruption of this network from the healthy subjects to non-DOC and DOC patients. Consistent results are obtained using an ICA-based approach..

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

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Arpana Gupta

2015-01-01

Conclusions: 1. An increased BMI (i.e., overweight subjects is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity.

From correlation to causation: Estimating effective connectivity from zero-lag covariances of brain signals.

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Schiefer, Jonathan; Niederbühl, Alexander; Pernice, Volker; Lennartz, Carolin; Hennig, Jürgen; LeVan, Pierre; Rotter, Stefan

2018-03-01

Knowing brain connectivity is of great importance both in basic research and for clinical applications. We are proposing a method to infer directed connectivity from zero-lag covariances of neuronal activity recorded at multiple sites. This allows us to identify causal relations that are reflected in neuronal population activity. To derive our strategy, we assume a generic linear model of interacting continuous variables, the components of which represent the activity of local neuronal populations. The suggested method for inferring connectivity from recorded signals exploits the fact that the covariance matrix derived from the observed activity contains information about the existence, the direction and the sign of connections. Assuming a sparsely coupled network, we disambiguate the underlying causal structure via L1-minimization, which is known to prefer sparse solutions. In general, this method is suited to infer effective connectivity from resting state data of various types. We show that our method is applicable over a broad range of structural parameters regarding network size and connection probability of the network. We also explored parameters affecting its activity dynamics, like the eigenvalue spectrum. Also, based on the simulation of suitable Ornstein-Uhlenbeck processes to model BOLD dynamics, we show that with our method it is possible to estimate directed connectivity from zero-lag covariances derived from such signals. In this study, we consider measurement noise and unobserved nodes as additional confounding factors. Furthermore, we investigate the amount of data required for a reliable estimate. Additionally, we apply the proposed method on full-brain resting-state fast fMRI datasets. The resulting network exhibits a tendency for close-by areas being connected as well as inter-hemispheric connections between corresponding areas. In addition, we found that a surprisingly large fraction of more than one third of all identified connections were of

Brain networks engaged in audiovisual integration during speech perception revealed by persistent homology-based network filtration.

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Kim, Heejung; Hahm, Jarang; Lee, Hyekyoung; Kang, Eunjoo; Kang, Hyejin; Lee, Dong Soo

2015-05-01

The human brain naturally integrates audiovisual information to improve speech perception. However, in noisy environments, understanding speech is difficult and may require much effort. Although the brain network is supposed to be engaged in speech perception, it is unclear how speech-related brain regions are connected during natural bimodal audiovisual or unimodal speech perception with counterpart irrelevant noise. To investigate the topological changes of speech-related brain networks at all possible thresholds, we used a persistent homological framework through hierarchical clustering, such as single linkage distance, to analyze the connected component of the functional network during speech perception using functional magnetic resonance imaging. For speech perception, bimodal (audio-visual speech cue) or unimodal speech cues with counterpart irrelevant noise (auditory white-noise or visual gum-chewing) were delivered to 15 subjects. In terms of positive relationship, similar connected components were observed in bimodal and unimodal speech conditions during filtration. However, during speech perception by congruent audiovisual stimuli, the tighter couplings of left anterior temporal gyrus-anterior insula component and right premotor-visual components were observed than auditory or visual speech cue conditions, respectively. Interestingly, visual speech is perceived under white noise by tight negative coupling in the left inferior frontal region-right anterior cingulate, left anterior insula, and bilateral visual regions, including right middle temporal gyrus, right fusiform components. In conclusion, the speech brain network is tightly positively or negatively connected, and can reflect efficient or effortful processes during natural audiovisual integration or lip-reading, respectively, in speech perception.

Traveling Slow Oscillations During Sleep: A Marker of Brain Connectivity in Childhood.

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Kurth, Salome; Riedner, Brady A; Dean, Douglas C; O'Muircheartaigh, Jonathan; Huber, Reto; Jenni, Oskar G; Deoni, Sean C L; LeBourgeois, Monique K

2017-09-01

Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the role of sleep in brain maturation trajectories. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Connectivity and tissue microstructural alterations in right and left temporal lobe epilepsy revealed by diffusion spectrum imaging.

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Lemkaddem, Alia; Daducci, Alessandro; Kunz, Nicolas; Lazeyras, François; Seeck, Margitta; Thiran, Jean-Philippe; Vulliémoz, Serge

2014-01-01

Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.

Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity.

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Vasily A Vakorin

2016-12-01

Full Text Available Accurate means to detect mild traumatic brain injury (mTBI using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz, together with increased connectivity in the slower alpha band (8-12 Hz. A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI.

Charting Monosynaptic Connectivity Maps by Two-Color Light-Sheet Fluorescence Microscopy

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Christian J. Niedworok

2012-11-01

Full Text Available Cellular resolution three-dimensional (3D visualization of defined, fluorescently labeled long-range neuronal networks in the uncut adult mouse brain has been elusive. Here, a virus-based strategy is described that allowed fluorescent labeling of centrifugally projecting neuronal populations in the ventral forebrain and their directly, monosynaptically connected bulbar interneurons upon a single stereotaxic injection into select neuronal populations. Implementation of improved tissue clearing combined with light-sheet fluorescence microscopy permitted imaging of the resulting connectivity maps in a single whole-brain scan. Subsequent 3D reconstructions revealed the exact distribution of the diverse neuronal ensembles monosynaptically connected with distinct bulbar interneuron populations. Moreover, rehydratation of brains after light-sheet fluorescence imaging enabled the immunohistochemical identification of synaptically connected neurons. Thus, this study describes a method for identifying monosynaptic connectivity maps from distinct, virally labeled neuronal populations that helps in better understanding of information flow in neural systems.

Network science and the effects of music preference on functional brain connectivity: from Beethoven to Eminem.

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Wilkins, R W; Hodges, D A; Laurienti, P J; Steen, M; Burdette, J H

2014-08-28

Most people choose to listen to music that they prefer or 'like' such as classical, country or rock. Previous research has focused on how different characteristics of music (i.e., classical versus country) affect the brain. Yet, when listening to preferred music--regardless of the type--people report they often experience personal thoughts and memories. To date, understanding how this occurs in the brain has remained elusive. Using network science methods, we evaluated differences in functional brain connectivity when individuals listened to complete songs. We show that a circuit important for internally-focused thoughts, known as the default mode network, was most connected when listening to preferred music. We also show that listening to a favorite song alters the connectivity between auditory brain areas and the hippocampus, a region responsible for memory and social emotion consolidation. Given that musical preferences are uniquely individualized phenomena and that music can vary in acoustic complexity and the presence or absence of lyrics, the consistency of our results was unexpected. These findings may explain why comparable emotional and mental states can be experienced by people listening to music that differs as widely as Beethoven and Eminem. The neurobiological and neurorehabilitation implications of these results are discussed.

Changes in Structural Connectivity Following a Cognitive Intervention in Children With Traumatic Brain Injury.

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Yuan, Weihong; Treble-Barna, Amery; Sohlberg, McKay M; Harn, Beth; Wade, Shari L

2017-02-01

Structural connectivity analysis based on graph theory and diffusion tensor imaging tractography is a novel method that quantifies the topological characteristics in the brain network. This study aimed to examine structural connectivity changes following the Attention Intervention and Management (AIM) program designed to improve attention and executive function (EF) in children with traumatic brain injury (TBI). Seventeen children with complicated mild to severe TBI (13.66 ± 2.68 years; >12 months postinjury) completed magnetic resonance imaging (MRI) and neurobehavioral measures at time 1, 10 of whom completed AIM and assessment at time 2. Eleven matched healthy comparison (HC) children (13.37 ± 2.08 years) completed MRI and neurobehavioral assessment at both time points, but did not complete AIM. Network characteristics were analyzed to quantify the structural connectivity before and after the intervention. Mixed model analyses showed that small-worldness was significantly higher in the TBI group than the HC group at time 1, and both small-worldness and normalized clustering coefficient decreased significantly at time 2 in the TBI group whereas the HC group remained relatively unchanged. Reductions in mean local efficiency were significantly correlated with improvements in verbal inhibition and both parent- and child-reported EF. Increased normalized characteristic path length was significantly correlated with improved sustained attention. The results provide preliminary evidence suggesting that graph theoretical analysis may be a sensitive tool in pediatric TBI for detecting ( a) abnormalities of structural connectivity in brain network and ( b) structural neuroplasticity associated with neurobehavioral improvement following a short-term intervention for attention and EF.

Altered intrinsic and extrinsic connectivity in schizophrenia.

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Zhou, Yuan; Zeidman, Peter; Wu, Shihao; Razi, Adeel; Chen, Cheng; Yang, Liuqing; Zou, Jilin; Wang, Gaohua; Wang, Huiling; Friston, Karl J

2018-01-01

Schizophrenia is a disorder characterized by functional dysconnectivity among distributed brain regions. However, it is unclear how causal influences among large-scale brain networks are disrupted in schizophrenia. In this study, we used dynamic causal modeling (DCM) to assess the hypothesis that there is aberrant directed (effective) connectivity within and between three key large-scale brain networks (the dorsal attention network, the salience network and the default mode network) in schizophrenia during a working memory task. Functional MRI data during an n-back task from 40 patients with schizophrenia and 62 healthy controls were analyzed. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes, we found that intrinsic (within-region) and extrinsic (between-region) effective connectivity involving prefrontal regions were abnormal in schizophrenia. Specifically, in patients (i) inhibitory self-connections in prefrontal regions of the dorsal attention network were decreased across task conditions; (ii) extrinsic connectivity between regions of the default mode network was increased; specifically, from posterior cingulate cortex to the medial prefrontal cortex; (iii) between-network extrinsic connections involving the prefrontal cortex were altered; (iv) connections within networks and between networks were correlated with the severity of clinical symptoms and impaired cognition beyond working memory. In short, this study revealed the predominance of reduced synaptic efficacy of prefrontal efferents and afferents in the pathophysiology of schizophrenia.

Towards a comprehensive atlas of cortical connections in a primate brain: Mapping tracer injection studies of the common marmoset into a reference digital template.

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Majka, Piotr; Chaplin, Tristan A; Yu, Hsin-Hao; Tolpygo, Alexander; Mitra, Partha P; Wójcik, Daniel K; Rosa, Marcello G P

2016-08-01

The marmoset is an emerging animal model for large-scale attempts to understand primate brain connectivity, but achieving this aim requires the development and validation of procedures for normalization and integration of results from many neuroanatomical experiments. Here we describe a computational pipeline for coregistration of retrograde tracing data on connections of cortical areas into a 3D marmoset brain template, generated from Nissl-stained sections. The procedure results in a series of spatial transformations that are applied to the coordinates of labeled neurons in the different cases, bringing them into common stereotaxic space. We applied this procedure to 17 injections, placed in the frontal lobe of nine marmosets as part of earlier studies. Visualizations of cortical patterns of connections revealed by these injections are supplied as Supplementary Materials. Comparison between the results of the automated and human-based processing of these cases reveals that the centers of injection sites can be reconstructed, on average, to within 0.6 mm of coordinates estimated by an experienced neuroanatomist. Moreover, cell counts obtained in different areas by the automated approach are highly correlated (r = 0.83) with those obtained by an expert, who examined in detail histological sections for each individual. The present procedure enables comparison and visualization of large datasets, which in turn opens the way for integration and analysis of results from many animals. Its versatility, including applicability to archival materials, may reduce the number of additional experiments required to produce the first detailed cortical connectome of a primate brain. J. Comp. Neurol. 524:2161-2181, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Brain Connectivity and Neuropsychological Functioning in Recently Treated Testicular Cancer Patients

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Amidi, Ali; Agerbæk, Mads; Leemans, Alexander

neuropsychological functioning. Cisplatin-based chemotherapy has well-known neurotoxic side effects and neural populations such as progenitor cells, oligodendrocytes, and hippocampal neurons are exceptionally vulnerable to even small concentrations of cisplatin. The aim of the present study was to investigate...... the possible adverse effects of BEP on brain white matter connectivity and neuropsychological functioning in recently treated men with TC....

Alterations in Brain Structure and Functional Connectivity in Alcohol Dependent Patients and Possible Association with Impulsivity.

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Wang, Junkai; Fan, Yunli; Dong, Yue; Ma, Mengying; Ma, Yi; Dong, Yuru; Niu, Yajuan; Jiang, Yin; Wang, Hong; Wang, Zhiyan; Wu, Liuzhen; Sun, Hongqiang; Cui, Cailian

2016-01-01

Previous studies have documented that heightened impulsivity likely contributes to the development and maintenance of alcohol use disorders. However, there is still a lack of studies that comprehensively detected the brain changes associated with abnormal impulsivity in alcohol addicts. This study was designed to investigate the alterations in brain structure and functional connectivity associated with abnormal impulsivity in alcohol dependent patients. Brain structural and functional magnetic resonance imaging data as well as impulsive behavior data were collected from 20 alcohol dependent patients and 20 age- and sex-matched healthy controls respectively. Voxel-based morphometry was used to investigate the differences of grey matter volume, and tract-based spatial statistics was used to detect abnormal white matter regions between alcohol dependent patients and healthy controls. The alterations in resting-state functional connectivity in alcohol dependent patients were examined using selected brain areas with gray matter deficits as seed regions. Compared with healthy controls, alcohol dependent patients had significantly reduced gray matter volume in the mesocorticolimbic system including the dorsal posterior cingulate cortex, the dorsal anterior cingulate cortex, the medial prefrontal cortex, the orbitofrontal cortex and the putamen, decreased fractional anisotropy in the regions connecting the damaged grey matter areas driven by higher radial diffusivity value in the same areas and decreased resting-state functional connectivity within the reward network. Moreover, the gray matter volume of the left medial prefrontal cortex exhibited negative correlations with various impulse indices. These findings suggest that chronic alcohol dependence could cause a complex neural changes linked to abnormal impulsivity.

Enhanced temporal variability of amygdala-frontal functional connectivity in patients with schizophrenia.

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Yue, Jing-Li; Li, Peng; Shi, Le; Lin, Xiao; Sun, Hong-Qiang; Lu, Lin

2018-01-01

The "dysconnectivity hypothesis" was proposed 20 years ago. It characterized schizophrenia as a disorder with dysfunctional connectivity across a large range of distributed brain areas. Resting-state functional magnetic resonance imaging (rsfMRI) data have supported this theory. Previous studies revealed that the amygdala might be responsible for the emotion regulation-related symptoms of schizophrenia. However, conventional methods oversimplified brain activities by assuming that it remained static throughout the entire scan duration, which may explain why inconsistent results have been reported for the same brain region. An emerging technique is sliding time window analysis, which is used to describe functional connectivity based on the temporal variability of regions of interest (e.g., amygdala) in patients with schizophrenia. Conventional analysis of the static functional connectivity between the amygdala and whole brain was also conducted. Static functional connectivity between the amygdala and orbitofrontal region was impaired in patients with schizophrenia. The variability of connectivity between the amygdala and medial prefrontal cortex was enhanced (i.e., greater dynamics) in patients with schizophrenia. A negative relationship was found between the variability of connectivity and information processing efficiency. A positive correlation was found between the variability of connectivity and symptom severity. The findings suggest that schizophrenia was related to abnormal patterns of fluctuating communication among brain areas that are involved in emotion regulations. Unveiling the temporal properties of functional connectivity could disentangle the inconsistent results of previous functional connectivity studies.

Identifying the Alteration Patterns of Brain Functional Connectivity in Progressive Mild Cognitive Impairment Patients: A Longitudinal Whole-Brain Voxel-Wise Degree Analysis.

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Deng, Yanjia; Liu, Kai; Shi, Lin; Lei, Yi; Liang, Peipeng; Li, Kuncheng; Chu, Winnie C W; Wang, Defeng

2016-01-01

Patients with mild cognitive impairment (MCI) are at high risk for developing Alzheimer's disease (AD), while some of them may remain stable over decades. The underlying mechanism is still not fully understood. In this study, we aimed to explore the connectivity differences between progressive MCI (PMCI) and stable MCI (SMCI) individuals on a whole-brain scale and on a voxel-wise basis, and we also aimed to reveal the differential dynamic alteration patterns between these two disease subtypes. The resting-state functional magnetic resonance images of PMCI and SMCI patients at baseline and year-one were obtained from the Alzheimer's Disease Neuroimaging Initiative dataset, and the progression was determined based on a 3-year follow-up. A whole-brain voxel-wise degree map that was calculated based on graph-theory was constructed for each subject, and then the cross-sectional and longitudinal analyses on the degree maps were performed between PMCI and SMCI patients. In longitudinal analyses, compared with SMCI group, PMCI group showed decreased long-range degree in the left middle occipital/supramarginal gyrus, while the short-range degree was increased in the left supplementary motor area and middle frontal gyrus and decreased in the right middle temporal pole. A significant longitudinal alteration of decreased short-range degree in the right middle occipital was found in PMCI group. Taken together with previous evidence, our current findings may suggest that PMCI, compared with SMCI, might be a "severe" presentation of disease along the AD continuum, and the rapidly reduced degree in the right middle occipital gyrus may have indicative value for the disease progression. Moreover, the cross-sectional comparison results and corresponding receiver-operator characteristic-curves analyses may indicate that the baseline degree difference is not a good predictor of disease progression in MCI patients. Overall, these findings may provide objective evidence and an indicator

Identifying the Alternation Patterns of Brain Functional Connectivity in Progressive Mild Cognitive Impairment Patients: A Longitudinal Whole-brain Voxel-wise Degree Analysis

Directory of Open Access Journals (Sweden)

Yanjia Deng

2016-08-01

Full Text Available Patients with mild cognitive impairment (MCI are at high risk for developing Alzheimer’s disease (AD, while some of them may remain stable over decades. The underlying mechanism is still not fully understood. In this study, we aimed to explore the connectivity differences between progressive MCI (PMCI and stable MCI (SMCI individuals on a whole-brain scale and on a voxel-wise basis, and we also aimed to reveal the differential dynamic alternation patterns between these two disease subtypes. The resting-state functional magnetic resonance images of PMCI and SMCI patients at baseline and year-one were obtained from the Alzheimer’s Disease Neuroimaging Initiative dataset, and the progression was determined based on a three-year follow-up. A whole-brain voxel-wise degree map that was calculated based on graph-theory was constructed for each subject, and then the cross-sectional and longitudinal analyses on the degree maps were performed between PMCI and SMCI patients. In longitudinal analyses, compared with SMCI group, PMCI group showed decreased long-range degree in the left middle occipital/supramarginal gyrus, while the short-range degree was increased in the left supplementary motor area and middle frontal gyrus and decreased in the right middle temporal pole. A significant longitudinal alteration of decreased short-range degree in the right middle occipital was found in PMCI group. Taken together with previous evidence, our current findings may suggest that PMCI, compared with SMCI, might be a severe presentation of disease along the AD continuum, and the rapidly reduced degree in the right middle occipital gyrus may have indicative value for the disease progression. Moreover, the cross-sectional comparison results and corresponding receiver-operator characteristic-curves analyses may indicate that the baseline degree difference is not a good predictor of disease progression in MCI patients. Overall, these findings may provide objective

Contribution of transcranial magnetic stimulation to assessment of brain connectivity and networks.

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Hallett, Mark; Di Iorio, Riccardo; Rossini, Paolo Maria; Park, Jung E; Chen, Robert; Celnik, Pablo; Strafella, Antonio P; Matsumoto, Hideyuki; Ugawa, Yoshikazu

2017-11-01

The goal of this review is to show how transcranial magnetic stimulation (TMS) techniques can make a contribution to the study of brain networks. Brain networks are fundamental in understanding how the brain operates. Effects on remote areas can be directly observed or identified after a period of stimulation, and each section of this review will discuss one method. EEG analyzed following TMS is called TMS-evoked potentials (TEPs). A conditioning TMS can influence the effect of a test TMS given over the motor cortex. A disynaptic connection can be tested also by assessing the effect of a pre-conditioning stimulus on the conditioning-test pair. Basal ganglia-cortical relationships can be assessed using electrodes placed in the process of deep brain stimulation therapy. Cerebellar-cortical relationships can be determined using TMS over the cerebellum. Remote effects of TMS on the brain can be found as well using neuroimaging, including both positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). The methods complement each other since they give different views of brain networks, and it is often valuable to use more than one technique to achieve converging evidence. The final product of this type of work is to show how information is processed and transmitted in the brain. Published by Elsevier B.V.

Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.

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Kim, Euiseok J; Juavinett, Ashley L; Kyubwa, Espoir M; Jacobs, Matthew W; Callaway, Edward M

2015-12-16

Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology, and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception. Copyright © 2015 Elsevier Inc. All rights reserved.

Correspondence Between Aberrant Intrinsic Network Connectivity and Gray-Matter Volume in the Ventral Brain of Preterm Born Adults.

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Bäuml, Josef G; Daamen, Marcel; Meng, Chun; Neitzel, Julia; Scheef, Lukas; Jaekel, Julia; Busch, Barbara; Baumann, Nicole; Bartmann, Peter; Wolke, Dieter; Boecker, Henning; Wohlschläger, Afra M; Sorg, Christian

2015-11-01

Widespread brain changes are present in preterm born infants, adolescents, and even adults. While neurobiological models of prematurity facilitate powerful explanations for the adverse effects of preterm birth on the developing brain at microscale, convincing linking principles at large-scale level to explain the widespread nature of brain changes are still missing. We investigated effects of preterm birth on the brain's large-scale intrinsic networks and their relation to brain structure in preterm born adults. In 95 preterm and 83 full-term born adults, structural and functional magnetic resonance imaging at-rest was used to analyze both voxel-based morphometry and spatial patterns of functional connectivity in ongoing blood oxygenation level-dependent activity. Differences in intrinsic functional connectivity (iFC) were found in cortical and subcortical networks. Structural differences were located in subcortical, temporal, and cingulate areas. Critically, for preterm born adults, iFC-network differences were overlapping and correlating with aberrant regional gray-matter (GM) volume specifically in subcortical and temporal areas. Overlapping changes were predicted by prematurity and in particular by neonatal medical complications. These results provide evidence that preterm birth has long-lasting effects on functional connectivity of intrinsic networks, and these changes are specifically related to structural alterations in ventral brain GM. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Intrinsic Functional Connectivity in the Adult Brain and Success in Second-Language Learning.

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Chai, Xiaoqian J; Berken, Jonathan A; Barbeau, Elise B; Soles, Jennika; Callahan, Megan; Chen, Jen-Kai; Klein, Denise

2016-01-20

There is considerable variability in an individual's ability to acquire a second language (L2) during adulthood. Using resting-state fMRI data acquired before training in English speakers who underwent a 12 week intensive French immersion training course, we investigated whether individual differences in intrinsic resting-state functional connectivity relate to a person's ability to acquire an L2. We focused on two key aspects of language processing--lexical retrieval in spontaneous speech and reading speed--and computed whole-brain functional connectivity from two regions of interest in the language network, namely the left anterior insula/frontal operculum (AI/FO) and the visual word form area (VWFA). Connectivity between the left AI/FO and left posterior superior temporal gyrus (STG) and between the left AI/FO and dorsal anterior cingulate cortex correlated positively with improvement in L2 lexical retrieval in spontaneous speech. Connectivity between the VWFA and left mid-STG correlated positively with improvement in L2 reading speed. These findings are consistent with the different language functions subserved by subcomponents of the language network and suggest that the human capacity to learn an L2 can be predicted by an individual's intrinsic functional connectivity within the language network. Significance statement: There is considerable variability in second-language learning abilities during adulthood. We investigated whether individual differences in intrinsic functional connectivity in the adult brain relate to success in second-language learning, using resting-state functional magnetic resonance imaging in English speakers who underwent a 12 week intensive French immersion training course. We found that pretraining functional connectivity within two different language subnetworks correlated strongly with learning outcome in two different language skills: lexical retrieval in spontaneous speech and reading speed. Our results suggest that the human

Organization of intrinsic functional brain connectivity predicts decisions to reciprocate social behavior.

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Cáceda, Ricardo; James, G Andrew; Gutman, David A; Kilts, Clinton D

2015-10-01

Reciprocation of trust exchanges is central to the development of interpersonal relationships and societal well-being. Understanding how humans make pro-social and self-centered decisions in dyadic interactions and how to predict these choices has been an area of great interest in social neuroscience. A functional magnetic resonance imaging (fMRI) based technology with potential clinical application is the study of resting state brain connectivity. We tested if resting state connectivity may predict choice behavior in a social context. Twenty-nine healthy adults underwent resting state fMRI before performing the Trust Game, a two person monetary exchange game. We assessed the ability of patterns of resting-state functional brain organization, demographic characteristics and a measure of moral development, the Defining Issues Test (DIT-2), to predict individuals' decisions to reciprocate money during the Trust Game. Subjects reciprocated in 74.9% of the trials. Independent component analysis identified canonical resting-state networks. Increased functional connectivity between the salience (bilateral insula/anterior cingulate) and central executive (dorsolateral prefrontal cortex/ posterior parietal cortex) networks significantly predicted the choice to reciprocate pro-social behavior (R(2) = 0.20, p = 0.015). Stepwise linear regression analysis showed that functional connectivity between these two networks (p = 0.002), age (p = 0.007) and DIT-2 personal interest schema score (p = 0.032) significantly predicted reciprocity behavior (R(2) = 0.498, p = 0.001). Intrinsic functional connectivity between neural networks in conjunction with other individual characteristics may be a valuable tool for predicting performance during social interactions. Future replication and temporal extension of these findings may bolster the understanding of decision making in clinical, financial and marketing settings. Copyright © 2015 Elsevier B.V. All rights reserved.

Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

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Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

2014-01-01

Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

Altered functional brain connectivity in patients with visually induced dizziness

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Angelique Van Ombergen

2017-01-01

Conclusions: We found alterations in the visual and vestibular cortical network in VID patients that could underlie the typical VID symptoms such as a worsening of their vestibular symptoms when being exposed to challenging visual stimuli. These preliminary findings provide the first insights into the underlying functional brain connectivity in VID patients. Future studies should extend these findings by employing larger sample sizes, by investigating specific task-based paradigms in these patients and by exploring the implications for treatment.

Imbalance in subregional connectivity of the right temporoparietal junction in major depression.

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Poeppl, Timm B; Müller, Veronika I; Hoffstaedter, Felix; Bzdok, Danilo; Laird, Angela R; Fox, Peter T; Langguth, Berthold; Rupprecht, Rainer; Sorg, Christian; Riedl, Valentin; Goya-Maldonado, Roberto; Gruber, Oliver; Eickhoff, Simon B

2016-08-01

Major depressive disorder (MDD) involves impairment in cognitive and interpersonal functioning. The right temporoparietal junction (RTPJ) is a key brain region subserving cognitive-attentional and social processes. Yet, findings on the involvement of the RTPJ in the pathophysiology of MDD have so far been controversial. Recent connectivity-based parcellation data revealed a topofunctional dualism within the RTPJ, linking its anterior and posterior part (aRTPJ/pRTPJ) to antagonistic brain networks for attentional and social processing, respectively. Comparing functional resting-state connectivity of the aRTPJ and pRTPJ in 72 MDD patients and 76 well-matched healthy controls, we found a seed (aRTPJ/pRTPJ) × diagnosis (MDD/controls) interaction in functional connectivity for eight regions. Employing meta-data from a large-scale neuroimaging database, functional characterization of these regions exhibiting differentially altered connectivity with the aRTPJ/pRTPJ revealed associations with cognitive (dorsolateral prefrontal cortex, parahippocampus) and behavioral (posterior medial frontal cortex) control, visuospatial processing (dorsal visual cortex), reward (subgenual anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex), as well as memory retrieval and social cognition (precuneus). These findings suggest that an imbalance in connectivity of subregions, rather than disturbed connectivity of the RTPJ as a whole, characterizes the connectional disruption of the RTPJ in MDD. This imbalance may account for key symptoms of MDD in cognitive, emotional, and social domains. Hum Brain Mapp 37:2931-2942, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Novel fingerprinting method characterises the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome

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Fernandes, Henrique M.; Van Hartevelt, Tim J.; Boccard, Sandra G. J.; Owen, Sarah L. F.; Cabral, Joana; Deco, Gustavo; Green, Alex L.; Fitzgerald, James J.; Aziz, Tipu Z.; Kringelbach, Morten L.

2015-01-01

Deep brain stimulation (DBS) is a remarkably effective clinical tool, used primarily for movement disorders. DBS relies on precise targeting of specific brain regions to rebalance the oscillatory behaviour of whole-brain neural networks. Traditionally, DBS targeting has been based upon animal models (such as MPTP for Parkinson’s disease) but has also been the result of serendipity during human lesional neurosurgery. There are, however, no good animal models of psychiatric disorders such as depression and schizophrenia, and progress in this area has been slow. In this paper, we use advanced tractography combined with whole-brain anatomical parcellation to provide a rational foundation for identifying the connectivity ‘fingerprint’ of existing, successful DBS targets. This knowledge can then be used pre-surgically and even potentially for the discovery of novel targets. First, using data from our recent case series of cingulate DBS for patients with treatment-resistant chronic pain, we demonstrate how to identify the structural ‘fingerprints’ of existing successful and unsuccessful DBS targets in terms of their connectivity to other brain regions, as defined by the whole-brain anatomical parcellation. Second, we use a number of different strategies to identify the successful fingerprints of structural connectivity across four patients with successful outcomes compared with two patients with unsuccessful outcomes. This fingerprinting method can potentially be used pre-surgically to account for a patient’s individual connectivity and identify the best DBS target. Ultimately, our novel fingerprinting method could be combined with advanced whole-brain computational modelling of the spontaneous dynamics arising from the structural changes in disease, to provide new insights and potentially new targets for hitherto impenetrable neuropsychiatric disorders.

Research review: Functional brain connectivity and child psychopathology--overview and methodological considerations for investigators new to the field.

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Matthews, Marguerite; Fair, Damien A

2015-04-01

Functional connectivity MRI is an emerging technique that can be used to investigate typical and atypical brain function in developing and aging populations. Despite some of the current confounds in the field of functional connectivity MRI, the translational potential of the technique available to investigators may eventually be used to improve diagnosis, early disease detection, and therapy monitoring. Based on a comprehensive survey of the literature, this review offers an introduction of resting-state functional connectivity for new investigators to the field of resting-state functional connectivity. We discuss a brief history of the technique, various methods of analysis, the relationship of functional networks to behavior, as well as the translational potential of functional connectivity MRI to investigate neuropsychiatric disorders. We also address some considerations and limitations with data analysis and interpretation. The information provided in this review should serve as a foundation for investigators new to the field of resting-state functional connectivity. The discussion provides a means to better understand functional connectivity and its application to typical and atypical brain function. © 2014 Association for Child and Adolescent Mental Health.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs.

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Nastase, Samuel A; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

Transcranial Magnetic Stimulation and Connectivity Mapping: Tools for Studying the Neural Bases of Brain Disorders

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Hampson, M.; Hoffman, R. E.

2010-01-01

There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through...

Brain structure and functional connectivity associated with pornography consumption: the brain on porn.

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Kühn, Simone; Gallinat, Jürgen

2014-07-01

Since pornography appeared on the Internet, the accessibility, affordability, and anonymity of consuming visual sexual stimuli have increased and attracted millions of users. Based on the assumption that pornography consumption bears resemblance with reward-seeking behavior, novelty-seeking behavior, and addictive behavior, we hypothesized alterations of the frontostriatal network in frequent users. To determine whether frequent pornography consumption is associated with the frontostriatal network. In a study conducted at the Max Planck Institute for Human Development in Berlin, Germany, 64 healthy male adults covering a wide range of pornography consumption reported hours of pornography consumption per week. Pornography consumption was associated with neural structure, task-related activation, and functional resting-state connectivity. Gray matter volume of the brain was measured by voxel-based morphometry and resting state functional connectivity was measured on 3-T magnetic resonance imaging scans. We found a significant negative association between reported pornography hours per week and gray matter volume in the right caudate (P < .001, corrected for multiple comparisons) as well as with functional activity during a sexual cue-reactivity paradigm in the left putamen (P < .001). Functional connectivity of the right caudate to the left dorsolateral prefrontal cortex was negatively associated with hours of pornography consumption. The negative association of self-reported pornography consumption with the right striatum (caudate) volume, left striatum (putamen) activation during cue reactivity, and lower functional connectivity of the right caudate to the left dorsolateral prefrontal cortex could reflect change in neural plasticity as a consequence of an intense stimulation of the reward system, together with a lower top-down modulation of prefrontal cortical areas. Alternatively, it could be a precondition that makes pornography consumption more rewarding.

Role of sound stimulation in reprogramming brain connectivity.

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Chaudhury, Sraboni; Nag, Tapas C; Jain, Suman; Wadhwa, Shashi

2013-09-01

Sensory stimulation has a critical role to play in the development of an individual. Environmental factors tend to modify the inputs received by the sensory pathway. The developing brain is most vulnerable to these alterations and interacts with the environment to modify its neural circuitry. In addition to other sensory stimuli, auditory stimulation can also act as external stimuli to provide enrichment during the perinatal period. There is evidence that suggests that enriched environment in the form of auditory stimulation can play a substantial role in modulating plasticity during the prenatal period. This review focuses on the emerging role of prenatal auditory stimulation in the development of higher brain functions such as learning and memory in birds and mammals. The molecular mechanisms of various changes in the hippocampus following sound stimulation to effect neurogenesis, learning and memory are described. Sound stimulation can also modify neural connectivity in the early postnatal life to enhance higher cognitive function or even repair the secondary damages in various neurological and psychiatric disorders. Thus, it becomes imperative to examine in detail the possible ameliorating effects of prenatal sound stimulation in existing animal models of various psychiatric disorders, such as autism.

Impaired functional connectivity of brain reward circuitry in patients with schizophrenia and cannabis use disorder: Effects of cannabis and THC.

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Fischer, Adina S; Whitfield-Gabrieli, Susan; Roth, Robert M; Brunette, Mary F; Green, Alan I

2014-09-01

Cannabis use disorder (CUD) occurs in up to 42% of patients with schizophrenia and substantially worsens disease progression. The basis of CUD in schizophrenia is unclear and available treatments are rarely successful at limiting cannabis use. We have proposed that a dysregulated brain reward circuit (BRC) may underpin cannabis use in these patients. In the present pilot study, we used whole-brain seed-to-voxel resting state functional connectivity (rs-fc) to examine the BRC of patients with schizophrenia and CUD, and to explore the effects of smoked cannabis and orally administered delta-9-tetrahydrocannabinol (THC) on the BRC. 12 patients with schizophrenia and CUD and 12 control subjects each completed two fMRI resting scans, with patients administered either a 3.6% THC cannabis cigarette (n=6) or a 15 mg THC capsule (n=6) prior to their second scan. Results revealed significantly reduced connectivity at baseline in patients relative to controls, with most pronounced hypoconnectivity found between the nucleus accumbens and prefrontal cortical BRC regions (i.e., anterior prefrontal cortex, orbitofrontal cortex, and anterior cingulate cortex). Both cannabis and THC administration increased connectivity between these regions, in direct correlation with increases in plasma THC levels. This study is the first to investigate interregional connectivity of the BRC and the effects of cannabis and THC on this circuit in patients with schizophrenia and CUD. The findings from this pilot study support the use of rs-fc as a means of measuring the integrity of the BRC and the effects of pharmacologic agents acting on this circuit in patients with schizophrenia and CUD. Copyright © 2014. Published by Elsevier B.V.

Connectivity derived thalamic segmentation in deep brain stimulation for tremor

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Harith Akram

Full Text Available The ventral intermediate nucleus (VIM of the thalamus is an established surgical target for stereotactic ablation and deep brain stimulation (DBS in the treatment of tremor in Parkinson's disease (PD and essential tremor (ET. It is centrally placed on a cerebello-thalamo-cortical network connecting the primary motor cortex, to the dentate nucleus of the contralateral cerebellum through the dentato-rubro-thalamic tract (DRT. The VIM is not readily visible on conventional MR imaging, so identifying the surgical target traditionally involved indirect targeting that relies on atlas-defined coordinates. Unfortunately, this approach does not fully account for individual variability and requires surgery to be performed with the patient awake to allow for intraoperative targeting confirmation. The aim of this study is to identify the VIM and the DRT using probabilistic tractography in patients that will undergo thalamic DBS for tremor. Four male patients with tremor dominant PD and five patients (three female with ET underwent high angular resolution diffusion imaging (HARDI (128 diffusion directions, 1.5 mm isotropic voxels and b value = 1500 preoperatively. Patients received VIM-DBS using an MR image guided and MR image verified approach with indirect targeting. Postoperatively, using parallel Graphical Processing Unit (GPU processing, thalamic areas with the highest diffusion connectivity to the primary motor area (M1, supplementary motor area (SMA, primary sensory area (S1 and contralateral dentate nucleus were identified. Additionally, volume of tissue activation (VTA corresponding to active DBS contacts were modelled. Response to treatment was defined as 40% reduction in the total Fahn-Tolosa-Martin Tremor Rating Score (FTMTRS with DBS-ON, one year from surgery. Three out of nine patients had a suboptimal, long-term response to treatment. The segmented thalamic areas corresponded well to anatomically known counterparts in the ventrolateral

Structural connections in the brain in relation to gender identity and sexual orientation.

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Burke, Sarah M; Manzouri, Amir H; Savic, Ivanka

2017-12-20

Both transgenderism and homosexuality are facets of human biology, believed to derive from different sexual differentiation of the brain. The two phenomena are, however, fundamentally unalike, despite an increased prevalence of homosexuality among transgender populations. Transgenderism is associated with strong feelings of incongruence between one's physical sex and experienced gender, not reported in homosexual persons. The present study searches to find neural correlates for the respective conditions, using fractional anisotropy (FA) as a measure of white matter connections that has consistently shown sex differences. We compared FA in 40 transgender men (female birth-assigned sex) and 27 transgender women (male birth-assigned sex), with both homosexual (29 male, 30 female) and heterosexual (40 male, 40 female) cisgender controls. Previously reported sex differences in FA were reproduced in cis-heterosexual groups, but were not found among the cis-homosexual groups. After controlling for sexual orientation, the transgender groups showed sex-typical FA-values. The only exception was the right inferior fronto-occipital tract, connecting parietal and frontal brain areas that mediate own body perception. Our findings suggest that the neuroanatomical signature of transgenderism is related to brain areas processing the perception of self and body ownership, whereas homosexuality seems to be associated with less cerebral sexual differentiation.

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity

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Zhang, Lei; Sun, Jinyan; Sun, Bailei; Luo, Qingming; Gong, Hui

2014-05-01

Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology. In this study, we measured hemodynamic activity of the prefrontal cortex (PFC) during a color-word matching Stroop task using NIRS. Hemispheric lateralization was examined by employing traditional activation and novel NIRS-based connectivity analyses simultaneously. Wavelet transform coherence was used to assess intrahemispheric functional connectivity. Spearman correlation analysis was used to examine the relationship between behavioral performance and activation/functional connectivity, respectively. In agreement with activation analysis, functional connectivity analysis revealed leftward lateralization for the Stroop effect and correlation with behavioral performance. However, functional connectivity was more sensitive than activation for identifying hemispheric lateralization. Granger causality was used to evaluate the effective connectivity between hemispheres. The results showed increased information flow from the left to the right hemispheres for the incongruent versus the neutral task, indicating a leading role of the left PFC. This study demonstrates that the NIRS-based connectivity can reveal the functional architecture of the brain more comprehensively than traditional activation, helping to better utilize the advantages of NIRS.

Altered intrinsic connectivity of the auditory cortex in congenital amusia.

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Leveque, Yohana; Fauvel, Baptiste; Groussard, Mathilde; Caclin, Anne; Albouy, Philippe; Platel, Hervé; Tillmann, Barbara

2016-07-01

Congenital amusia, a neurodevelopmental disorder of music perception and production, has been associated with abnormal anatomical and functional connectivity in a right frontotemporal pathway. To investigate whether spontaneous connectivity in brain networks involving the auditory cortex is altered in the amusic brain, we ran a seed-based connectivity analysis, contrasting at-rest functional MRI data of amusic and matched control participants. Our results reveal reduced frontotemporal connectivity in amusia during resting state, as well as an overconnectivity between the auditory cortex and the default mode network (DMN). The findings suggest that the auditory cortex is intrinsically more engaged toward internal processes and less available to external stimuli in amusics compared with controls. Beyond amusia, our findings provide new evidence for the link between cognitive deficits in pathology and abnormalities in the connectivity between sensory areas and the DMN at rest. Copyright © 2016 the American Physiological Society.

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.

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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.

Traffic pollution exposure is associated with altered brain connectivity in school children.

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Pujol, Jesus; Martínez-Vilavella, Gerard; Macià, Dídac; Fenoll, Raquel; Alvarez-Pedrerol, Mar; Rivas, Ioar; Forns, Joan; Blanco-Hinojo, Laura; Capellades, Jaume; Querol, Xavier; Deus, Joan; Sunyer, Jordi

2016-04-01

Children are more vulnerable to the effects of environmental elements due to their active developmental processes. Exposure to urban air pollution has been associated with poorer cognitive performance, which is thought to be a result of direct interference with brain maturation. We aimed to assess the extent of such potential effects of urban pollution on child brain maturation using general indicators of vehicle exhaust measured in the school environment and a comprehensive imaging evaluation. A group of 263 children, aged 8 to 12 years, underwent MRI to quantify regional brain volumes, tissue composition, myelination, cortical thickness, neural tract architecture, membrane metabolites, functional connectivity in major neural networks and activation/deactivation dynamics during a sensory task. A combined measurement of elemental carbon and NO2 was used as a putative marker of vehicle exhaust. Air pollution exposure was associated with brain changes of a functional nature, with no evident effect on brain anatomy, structure or membrane metabolites. Specifically, a higher content of pollutants was associated with lower functional integration and segregation in key brain networks relevant to both inner mental processes (the default mode network) and stimulus-driven mental operations. Age and performance (motor response speed) both showed the opposite effect to that of pollution, thus indicating that higher exposure is associated with slower brain maturation. In conclusion, urban air pollution appears to adversely affect brain maturation in a critical age with changes specifically concerning the functional domain. Copyright © 2016 Elsevier Inc. All rights reserved.

Functional Connectivity Bias in the Prefrontal Cortex of Psychopaths.

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Contreras-Rodríguez, Oren; Pujol, Jesus; Batalla, Iolanda; Harrison, Ben J; Soriano-Mas, Carles; Deus, Joan; López-Solà, Marina; Macià, Dídac; Pera, Vanessa; Hernández-Ribas, Rosa; Pifarré, Josep; Menchón, José M; Cardoner, Narcís

2015-11-01

Psychopathy is characterized by a distinctive interpersonal style that combines callous-unemotional traits with inflexible and antisocial behavior. Traditional emotion-based perspectives link emotional impairment mostly to alterations in amygdala-ventromedial frontal circuits. However, these models alone cannot explain why individuals with psychopathy can regularly benefit from emotional information when placed on their focus of attention and why they are more resistant to interference from nonaffective contextual cues. The present study aimed to identify abnormal or distinctive functional links between and within emotional and cognitive brain systems in the psychopathic brain to characterize further the neural bases of psychopathy. High-resolution anatomic magnetic resonance imaging with a functional sequence acquired in the resting state was used to assess 22 subjects with psychopathy and 22 control subjects. Anatomic and functional connectivity alterations were investigated first using a whole-brain analysis. Brain regions showing overlapping anatomic and functional changes were examined further using seed-based functional connectivity mapping. Subjects with psychopathy showed gray matter reduction involving prefrontal cortex, paralimbic, and limbic structures. Anatomic changes overlapped with areas showing increased degree of functional connectivity at the medial-dorsal frontal cortex. Subsequent functional seed-based connectivity mapping revealed a pattern of reduced functional connectivity of prefrontal areas with limbic-paralimbic structures and enhanced connectivity within the dorsal frontal lobe in subjects with psychopathy. Our results suggest that a weakened link between emotional and cognitive domains in the psychopathic brain may combine with enhanced functional connections within frontal executive areas. The identified functional alterations are discussed in the context of potential contributors to the inflexible behavior displayed by individuals with

An algebraic topological method for multimodal brain networks comparison

Directory of Open Access Journals (Sweden)

Tiago eSimas

2015-07-01

Full Text Available Understanding brain connectivity is one of the most important issues in neuroscience. Nonetheless, connectivity data can reflect either functional relationships of brain activities or anatomical connections between brain areas. Although both representations should be related, this relationship is not straightforward. We have devised a powerful method that allows different operations between networks that share the same set of nodes, by embedding them in a common metric space, enforcing transitivity to the graph topology. Here, we apply this method to construct an aggregated network from a set of functional graphs, each one from a different subject. Once this aggregated functional network is constructed, we use again our method to compare it with the structural connectivity to identify particular brain regions that differ in both modalities (anatomical and functional. Remarkably, these brain regions include functional areas that form part of the classical resting state networks. We conclude that our method -based on the comparison of the aggregated functional network- reveals some emerging features that could not be observed when the comparison is performed with the classical averaged functional network.

The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

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Yi, Guo-Sheng; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Li, Nuo

2013-02-01

Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world" network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels.

The modulation of brain functional connectivity with manual acupuncture in healthy subjects: An electroencephalograph case study

International Nuclear Information System (INIS)

Yi Guo-Sheng; Wang Jiang; Deng Bin; Wei Xi-Le; Li Nuo; Han Chun-Xiao

2013-01-01

Manual acupuncture is widely used for pain relief and stress control. Previous studies on acupuncture have shown its modulatory effects on the functional connectivity associated with one or a few preselected brain regions. To investigate how manual acupuncture modulates the organization of functional networks at a whole-brain level, we acupuncture at ST36 of a right leg to obtain electroencephalograph (EEG) signals. By coherence estimation, we determine the synchronizations between all pairwise combinations of EEG channels in three acupuncture states. The resulting synchronization matrices are converted into functional networks by applying a threshold, and the clustering coefficients and path lengths are computed as a function of threshold. The results show that acupuncture can increase functional connections and synchronizations between different brain areas. For a wide range of thresholds, the clustering coefficient during acupuncture and post-acupuncture period is higher than that during the pre-acupuncture control period, whereas the characteristic path length is shorter. We provide further support for the presence of “small-world” network characteristics in functional networks by using acupuncture. These preliminary results highlight the beneficial modulations of functional connectivity by manual acupuncture, which could contribute to the understanding of the effects of acupuncture on the entire brain, as well as the neurophysiological mechanisms underlying acupuncture. Moreover, the proposed method may be a useful approach to the further investigation of the complexity of patterns of interrelations between EEG channels. (interdisciplinary physics and related areas of science and technology)

Optical mapping of prefrontal brain connectivity and activation during emotion anticipation.

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Wang, Meng-Yun; Lu, Feng-Mei; Hu, Zhishan; Zhang, Juan; Yuan, Zhen

2018-09-17

Accumulated neuroimaging evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is activated during emotion anticipation. The aim of this work is to examine the brain connectivity and activation differences in dlPFC between the positive, neutral and negative emotion anticipation by using functional near-infrared spectroscopy (fNIRS). The hemodynamic responses were first assessed for all subjects during the performance of various emotion anticipation tasks. And then small-world analysis was performed, in which the small-world network indicators including the clustering coefficient, average path length, average node degree, and measure of small-world index were calculated for the functional brain networks associated with the positive, neutral and negative emotion anticipation, respectively. We discovered that compared to negative and neutral emotion anticipation, the positive one exhibited enhanced brain activation in the left dlPFC. Although the functional brain networks for the three emotion anticipation cases manifested the small-world properties regarding the clustering coefficient, average path length, average node degree, and measure of small-world index, the positive one showed significantly higher clustering coefficient and shorter average path length than those from the neutral and negative cases. Consequently, the small-world network indicators and brain activation in dlPPC were able to distinguish well between the positive, neutral and negative emotion anticipation. Copyright © 2018 Elsevier B.V. All rights reserved.

Decreased Cerebellar-Orbitofrontal Connectivity Correlates with Stuttering Severity: Whole-Brain Functional and Structural Connectivity Associations with Persistent Developmental Stuttering

OpenAIRE

Sitek, Kevin R.; Cai, Shanqing; Beal, Deryk S.; Perkell, Joseph S.; Guenther, Frank H.; Ghosh, Satrajit S.

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had st...

Decreased cerebellar-orbitofrontal connectivity correlates with stuttering severity: Whole-brain functional and structural connectivity associations with persistent developmental stuttering

OpenAIRE

Kevin Richard Sitek; Kevin Richard Sitek; Shanqing eCai; Shanqing eCai; Deryk Scott Beal; Deryk Scott Beal; Deryk Scott Beal; Deryk Scott Beal; Deryk Scott Beal; Joseph S Perkell; Joseph S Perkell; Frank eGuenther; Satrajit S Ghosh; Satrajit S Ghosh

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here, we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had ...

Correlating subcortical interhemispheric connectivity and cortical hemispheric dominance in brain tumor patients: A repetitive navigated transcranial magnetic stimulation study.

Science.gov (United States)

Sollmann, Nico; Ille, Sebastian; Tussis, Lorena; Maurer, Stefanie; Hauck, Theresa; Negwer, Chiara; Bauer, Jan S; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-02-01

The present study aims to investigate the relationship between transcallosal interhemispheric connectivity (IC) and hemispheric language lateralization by using a novel approach including repetitive navigated transcranial magnetic stimulation (rTMS), hemispheric dominance ratio (HDR) calculation, and rTMS-based diffusion tensor imaging fiber tracking (DTI FT). 31 patients with left-sided perisylvian brain lesions underwent diffusion tensor imaging (DTI) and rTMS language mapping. Cortical language-positive rTMS spots were used to calculate HDRs (HDR: quotient of the left-sided divided by right-sided naming error rates for corresponding left- and right-sided cortical regions) and to create regions of interest (ROIs) for DTI FT. Then, fibers connecting the rTMS-based ROIs of both hemispheres were tracked, and the correlation of IC to HDRs was calculated via Spearman's rank correlation coefficient (rs). Fibers connecting rTMS-based ROIs of both hemispheres were detected in 12 patients (38.7%). Within the patients in which IC was detected, the mean number of subcortical IC fibers ± standard deviation (SD) was 138.0 ± 346.5 (median: 7.5; range: 1-1,217 fibers). Regarding rs for the correlation of HDRs and fiber numbers of patients that showed IC, only moderate correlation was revealed. Our approach might be beneficial and technically feasible for further investigation of the relationship between IC and language lateralization. However, only moderate correlation was revealed in the present study. Copyright © 2015 Elsevier B.V. All rights reserved.