Evaluation of MLACF based calculated attenuation brain PET imaging for FDG patient studies

Science.gov (United States)

Bal, Harshali; Panin, Vladimir Y.; Platsch, Guenther; Defrise, Michel; Hayden, Charles; Hutton, Chloe; Serrano, Benjamin; Paulmier, Benoit; Casey, Michael E.

2017-04-01

Calculating attenuation correction for brain PET imaging rather than using CT presents opportunities for low radiation dose applications such as pediatric imaging and serial scans to monitor disease progression. Our goal is to evaluate the iterative time-of-flight based maximum-likelihood activity and attenuation correction factors estimation (MLACF) method for clinical FDG brain PET imaging. FDG PET/CT brain studies were performed in 57 patients using the Biograph mCT (Siemens) four-ring scanner. The time-of-flight PET sinograms were acquired using the standard clinical protocol consisting of a CT scan followed by 10 min of single-bed PET acquisition. Images were reconstructed using CT-based attenuation correction (CTAC) and used as a gold standard for comparison. Two methods were compared with respect to CTAC: a calculated brain attenuation correction (CBAC) and MLACF based PET reconstruction. Plane-by-plane scaling was performed for MLACF images in order to fix the variable axial scaling observed. The noise structure of the MLACF images was different compared to those obtained using CTAC and the reconstruction required a higher number of iterations to obtain comparable image quality. To analyze the pooled data, each dataset was registered to a standard template and standard regions of interest were extracted. An SUVr analysis of the brain regions of interest showed that CBAC and MLACF were each well correlated with CTAC SUVrs. A plane-by-plane error analysis indicated that there were local differences for both CBAC and MLACF images with respect to CTAC. Mean relative error in the standard regions of interest was less than 5% for both methods and the mean absolute relative errors for both methods were similar (3.4%  ±  3.1% for CBAC and 3.5%  ±  3.1% for MLACF). However, the MLACF method recovered activity adjoining the frontal sinus regions more accurately than CBAC method. The use of plane-by-plane scaling of MLACF images was found to be a

Improving the accuracy of brain tumor surgery via Raman-based technology.

Science.gov (United States)

Hollon, Todd; Lewis, Spencer; Freudiger, Christian W; Sunney Xie, X; Orringer, Daniel A

2016-03-01

Despite advances in the surgical management of brain tumors, achieving optimal surgical results and identification of tumor remains a challenge. Raman spectroscopy, a laser-based technique that can be used to nondestructively differentiate molecules based on the inelastic scattering of light, is being applied toward improving the accuracy of brain tumor surgery. Here, the authors systematically review the application of Raman spectroscopy for guidance during brain tumor surgery. Raman spectroscopy can differentiate normal brain from necrotic and vital glioma tissue in human specimens based on chemical differences, and has recently been shown to differentiate tumor-infiltrated tissues from noninfiltrated tissues during surgery. Raman spectroscopy also forms the basis for coherent Raman scattering (CRS) microscopy, a technique that amplifies spontaneous Raman signals by 10,000-fold, enabling real-time histological imaging without the need for tissue processing, sectioning, or staining. The authors review the relevant basic and translational studies on CRS microscopy as a means of providing real-time intraoperative guidance. Recent studies have demonstrated how CRS can be used to differentiate tumor-infiltrated tissues from noninfiltrated tissues and that it has excellent agreement with traditional histology. Under simulated operative conditions, CRS has been shown to identify tumor margins that would be undetectable using standard bright-field microscopy. In addition, CRS microscopy has been shown to detect tumor in human surgical specimens with near-perfect agreement to standard H & E microscopy. The authors suggest that as the intraoperative application and instrumentation for Raman spectroscopy and imaging matures, it will become an essential component in the neurosurgical armamentarium for identifying residual tumor and improving the surgical management of brain tumors.

Anatomically standardized statistical mapping of 123I-IMP SPECT in brain tumors

International Nuclear Information System (INIS)

Shibata, Yasushi; Akimoto, Manabu; Matsushita, Akira; Yamamoto, Tetsuya; Takano, Shingo; Matsumura, Akira

2010-01-01

123 I-iodoamphetamine Single Photon Emission Computed Tomography (IMP SPECT) is used to evaluate cerebral blood flow. However, application of IMP SPECT to patients with brain tumors has been rarely reported. Primary central nervous system lymphoma (PCNSL) is a rare tumor that shows delayed IMP uptake. The relatively low spatial resolution of SPECT is a clinical problem in diagnosing brain tumors. We examined anatomically standardized statistical mapping of IMP SPECT in patients with brain lesions. This study included 49 IMP SPECT images for 49 patients with brain lesions: 20 PCNSL, 1 Burkitt's lymphoma, 14 glioma, 4 other tumor, 7 inflammatory disease and 3 without any pathological diagnosis but a clinical diagnosis of PCNSL. After intravenous injection of 222 MBq of 123 I-IMP, early (15 minutes) and delayed (4 hours) images were acquired using a multi-detector SPECT machine. All SPECT data were transferred to a newly developed software program iNeurostat+ (Nihon Medi-physics). SPECT data were anatomically standardized on normal brain images. Regions of increased uptake of IMP were statistically mapped on the tomographic images of normal brain. Eighteen patients showed high uptake in the delayed IMP SPECT images (16 PCNSL, 2 unknown). Other tumor or diseases did not show high uptake of delayed IMP SPECT, so there were no false positives. Four patients with pathologically proven PCNSL showed no uptake in original IMP SPECT. These tumors were too small to detect in IMP SPECT. However, statistical mapping revealed IMP uptake in 18 of 20 pathologically verified PCNSL patients. A heterogeneous IMP uptake was seen in homogenous tumors in MRI. For patients with a hot IMP uptake, statistical mapping showed clearer uptake. IMP SPECT is a sensitive test to diagnose of PCNSL, although it produced false negative results for small posterior fossa tumor. Anatomically standardized statistical mapping is therefore considered to be a useful method for improving the diagnostic

Standardized Uptake Value Ratio-Independent Evaluation of Brain Amyloidosis.

Science.gov (United States)

Chincarini, Andrea; Sensi, Francesco; Rei, Luca; Bossert, Irene; Morbelli, Silvia; Guerra, Ugo Paolo; Frisoni, Giovanni; Padovani, Alessandro; Nobili, Flavio

2016-10-18

The assessment of in vivo18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based on standardized uptake value ratio (SUVr) measurements. We target the difficulties of image reading and possible shortcomings of the SUVr methods by validating a new semi-quantitative approach named ELBA. ELBA involves a minimal image preprocessing and does not rely on small, specific regions of interest (ROIs). It evaluates the whole brain and delivers a geometrical/intensity score to be used for ranking and dichotomic assessment. The method was applied to adniimages 18F-florbetapir images from the ADNI database. Five expert readers provided visual assessment in blind and open sessions. The longitudinal trend and the comparison to SUVr measurements were also evaluated. ELBA performed with area under the roc curve (AUC) = 0.997 versus the visual assessment. The score was significantly correlated to the SUVr values (r = 0.86, p analysis estimated a test/retest error of ≃2.3%. Cohort and longitudinal analysis suggests that the ELBA method accurately ranks the brain amyloid burden. The expert readers confirmed its relevance in aiding the visual assessment in a significant number (85) of difficult cases. Despite the good performance, poor and uneven image quality constitutes the major limitation.

Pig brain stereotaxic standard space: Mapping of cerebral blood flow normative values and effect of MPTP-lesioning

DEFF Research Database (Denmark)

Andersen, F.; Watanabe, H.; Bjarkam, C.R.

2005-01-01

The analysis of physiological processes in brain by position emission tomography (PET) is facilitated when images are spatially normalized to a standard coordinate system. Thus, PET activation studies of human brain frequently employ the common stereotaxic coordinates of Talairach. We have...... developed an analogous stereotaxic coordinate system for the brain of the Gottingen miniature pig, based on automatic co-registration of magnetic resonance (MR) images obtained in 22 male pigs. The origin of the pig brain stereotaxic space (0, 0, 0) was arbitrarily placed in the centroid of the pineal gland...... as identified on the average MRI template. The orthogonal planes were imposed using the line between stereotaxic zero and the optic chiasm. A series of mean MR images in the coronal, sagittal and horizontal planes were generated. To test the utility of the common coordinate system for functional imaging studies...

Brain-Based Learning. Research Brief

Science.gov (United States)

Walker, Karen

2005-01-01

What does brain-based research say about how adolescents learn? The 1990s was declared as the Decade of the Brain by President Bush and Congress. With the advancement of MRIs (Magnetic Resonance Imagining) and PET (positron emission tomography) scans, it has become much easier to study live healthy brains. As a result, the concept of…

Template based rodent brain extraction and atlas mapping.

Science.gov (United States)

Weimin Huang; Jiaqi Zhang; Zhiping Lin; Su Huang; Yuping Duan; Zhongkang Lu

2016-08-01

Accurate rodent brain extraction is the basic step for many translational studies using MR imaging. This paper presents a template based approach with multi-expert refinement to automatic rodent brain extraction. We first build the brain appearance model based on the learning exemplars. Together with the template matching, we encode the rodent brain position into the search space to reliably locate the rodent brain and estimate the rough segmentation. With the initial mask, a level-set segmentation and a mask-based template learning are implemented further to the brain region. The multi-expert fusion is used to generate a new mask. We finally combine the region growing based on the histogram distribution learning to delineate the final brain mask. A high-resolution rodent atlas is used to illustrate that the segmented low resolution anatomic image can be well mapped to the atlas. Tested on a public data set, all brains are located reliably and we achieve the mean Jaccard similarity score at 94.99% for brain segmentation, which is a statistically significant improvement compared to two other rodent brain extraction methods.

Comparative study of standard space and real space analysis of quantitative MR brain data.

Science.gov (United States)

Aribisala, Benjamin S; He, Jiabao; Blamire, Andrew M

2011-06-01

To compare the robustness of region of interest (ROI) analysis of magnetic resonance imaging (MRI) brain data in real space with analysis in standard space and to test the hypothesis that standard space image analysis introduces more partial volume effect errors compared to analysis of the same dataset in real space. Twenty healthy adults with no history or evidence of neurological diseases were recruited; high-resolution T(1)-weighted, quantitative T(1), and B(0) field-map measurements were collected. Algorithms were implemented to perform analysis in real and standard space and used to apply a simple standard ROI template to quantitative T(1) datasets. Regional relaxation values and histograms for both gray and white matter tissues classes were then extracted and compared. Regional mean T(1) values for both gray and white matter were significantly lower using real space compared to standard space analysis. Additionally, regional T(1) histograms were more compact in real space, with smaller right-sided tails indicating lower partial volume errors compared to standard space analysis. Standard space analysis of quantitative MRI brain data introduces more partial volume effect errors biasing the analysis of quantitative data compared to analysis of the same dataset in real space. Copyright © 2011 Wiley-Liss, Inc.

A clearer view of the insect brain – combining bleaching with standard whole-mount immunocytochemistry allows confocal imaging of pigment-covered brain areas for 3D reconstruction.

Directory of Open Access Journals (Sweden)

Anna Lisa Stöckl

2015-09-01

Full Text Available In the study of insect neuroanatomy, three-dimensional reconstructions of neurons and neuropils have become a standard technique. As images have to be obtained from whole-mount brain preparations, pigmentation on the brain surface poses a serious challenge to imaging. In insects, this is a major problematic in the first visual neuropil of the optic lobe, the lamina, which is obstructed by the pigment of the retina as well as by the pigmented fenestration layer. This has prevented inclusion of this major processing center of the insect visual system into most neuroanatomical brain atlases and hinders imaging of neurons within the lamina by confocal microscopy. It has recently been shown that hydrogen peroxide bleaching is compatible with immunohistochemical labeling in insect brains, and we therefore developed a simple technique for removal of pigments on the surface of insect brains by chemical bleaching. We show that our technique enables imaging of the pigment-obstructed regions of insect brains when combined with standard protocols for both anti-synapsin-labeled as well as neurobiotin-injected samples. This method can be combined with different fixation procedures, as well as different fluorophore excitation wavelengths without negative effects on staining quality. It can therefore serve as an effective addition to most standard histology protocols used in insect neuroanatomy.

Developing a Korean standard brain atlas on the basis of statistical and probabilistic approach and visualization tool for functional image analysis

Energy Technology Data Exchange (ETDEWEB)

Koo, B. B.; Lee, J. M.; Kim, J. S.; Kim, I. Y.; Kim, S. I. [Hanyang University, Seoul (Korea, Republic of); Lee, J. S.; Lee, D. S.; Kwon, J. S. [Seoul National University College of Medicine, Seoul (Korea, Republic of); Kim, J. J. [Yonsei University College of Medicine, Seoul (Korea, Republic of)

2003-06-01

The probabilistic anatomical maps are used to localize the functional neuro-images and morphological variability. The quantitative indicator is very important to inquire the anatomical position of an activated region because functional image data has the low-resolution nature and no inherent anatomical information. Although previously developed MNI probabilistic anatomical map was enough to localize the data, it was not suitable for the Korean brains because of the morphological difference between Occidental and Oriental. In this study, we develop a probabilistic anatomical map for Korean normal brain. Normal 75 brains of T1-weighted spoiled gradient echo magnetic resonance images were acquired on a 1.5-T GESIGNA scanner. Then, a standard brain is selected in the group through a clinician searches a brain of the average property in the Talairach coordinate system. With the standard brain, an anatomist delineates 89 regions of interest (ROI) parcellating cortical and subcortical areas. The parcellated ROIs of the standard are warped and overlapped into each brain by maximizing intensity similarity. And every brain is automatically labeled with the registered ROIs. Each of the same-labeled region is linearly normalize to the standard brain, and the occurrence of each region is counted. Finally, 89 probabilistic ROI volumes are generated. This paper presents a probabilistic anatomical map for localizing the functional and structural analysis of Korean normal brain. In the future, we'll develop the group specific probabilistic anatomical maps of OCD and schizophrenia disease.

Developing a Korean standard brain atlas on the basis of statistical and probabilistic approach and visualization tool for functional image analysis

International Nuclear Information System (INIS)

Koo, B. B.; Lee, J. M.; Kim, J. S.; Kim, I. Y.; Kim, S. I.; Lee, J. S.; Lee, D. S.; Kwon, J. S.; Kim, J. J.

2003-01-01

The probabilistic anatomical maps are used to localize the functional neuro-images and morphological variability. The quantitative indicator is very important to inquire the anatomical position of an activated region because functional image data has the low-resolution nature and no inherent anatomical information. Although previously developed MNI probabilistic anatomical map was enough to localize the data, it was not suitable for the Korean brains because of the morphological difference between Occidental and Oriental. In this study, we develop a probabilistic anatomical map for Korean normal brain. Normal 75 brains of T1-weighted spoiled gradient echo magnetic resonance images were acquired on a 1.5-T GESIGNA scanner. Then, a standard brain is selected in the group through a clinician searches a brain of the average property in the Talairach coordinate system. With the standard brain, an anatomist delineates 89 regions of interest (ROI) parcellating cortical and subcortical areas. The parcellated ROIs of the standard are warped and overlapped into each brain by maximizing intensity similarity. And every brain is automatically labeled with the registered ROIs. Each of the same-labeled region is linearly normalize to the standard brain, and the occurrence of each region is counted. Finally, 89 probabilistic ROI volumes are generated. This paper presents a probabilistic anatomical map for localizing the functional and structural analysis of Korean normal brain. In the future, we'll develop the group specific probabilistic anatomical maps of OCD and schizophrenia disease

Zebrafish brain mapping--standardized spaces, length scales, and the power of N and n.

Science.gov (United States)

Hunter, Paul R; Hendry, Aenea C; Lowe, Andrew S

2015-06-01

Mapping anatomical and functional parameters of the zebrafish brain is moving apace. Research communities undertaking such studies are becoming ever larger and more diverse. The unique features, tools, and technologies associated with zebrafish are propelling them as the 21st century model organism for brain mapping. Uniquely positioned as a vertebrate model system, the zebrafish enables imaging of anatomy and function at different length scales from intraneuronal compartments to sparsely distributed whole brain patterns. With a variety of diverse and established statistical modeling and analytic methods available from the wider brain mapping communities, the richness of zebrafish neuroimaging data is being realized. The statistical power of population observations (N) within and across many samples (n) projected onto a standardized space will provide vast databases for data-driven biological approaches. This article reviews key brain mapping initiatives at different levels of scale that highlight the potential of zebrafish brain mapping. By way of introduction to the next wave of brain mappers, an accessible introduction to the key concepts and caveats associated with neuroimaging are outlined and discussed. © 2014 Wiley Periodicals, Inc.

The Credentials of Brain-Based Learning

Science.gov (United States)

Davis, Andrew

2004-01-01

This paper discusses the current fashion for brain-based learning, in which value-laden claims about learning are grounded in neurophysiology. It argues that brain science cannot have the authority about learning that some seek to give it. It goes on to discuss whether the claim that brain science is relevant to learning involves a category…

Brain-Based Teaching/Learning and Implications for Religious Education.

Science.gov (United States)

Weber, Jean Marie

2002-01-01

Argues that physical activity and water can increase brain activity, and hence, learning. Findings of neuroscientists regarding the brain can inform educators. Brain-based teaching emphasizes teamwork, cooperative learning, and global responsibility. Argues against gathering information without relevance. Connects brain-based learning concepts to…

The national DBS brain tissue network pilot study: need for more tissue and more standardization.

Science.gov (United States)

Vedam-Mai, V; Krock, N; Ullman, M; Foote, K D; Shain, W; Smith, K; Yachnis, A T; Steindler, D; Reynolds, B; Merritt, S; Pagan, F; Marjama-Lyons, J; Hogarth, P; Resnick, A S; Zeilman, P; Okun, M S

2011-08-01

Over 70,000 DBS devices have been implanted worldwide; however, there remains a paucity of well-characterized post-mortem DBS brains available to researchers. We propose that the overall understanding of DBS can be improved through the establishment of a Deep Brain Stimulation-Brain Tissue Network (DBS-BTN), which will further our understanding of DBS and brain function. The objectives of the tissue bank are twofold: (a) to provide a complete (clinical, imaging and pathological) database for DBS brain tissue samples, and (b) to make available DBS tissue samples to researchers, which will help our understanding of disease and underlying brain circuitry. Standard operating procedures for processing DBS brains were developed as part of the pilot project. Complete data files were created for individual patients and included demographic information, clinical information, imaging data, pathology, and DBS lead locations/settings. 19 DBS brains were collected from 11 geographically dispersed centers from across the U.S. The average age at the time of death was 69.3 years (51-92, with a standard deviation or SD of 10.13). The male:female ratio was almost 3:1. Average post-mortem interval from death to brain collection was 10.6 h (SD of 7.17). The DBS targets included: subthalamic nucleus, globus pallidus interna, and ventralis intermedius nucleus of the thalamus. In 16.7% of cases the clinical diagnosis failed to match the pathological diagnosis. We provide neuropathological findings from the cohort, and perilead responses to DBS. One of the most important observations made in this pilot study was the missing data, which was approximately 25% of all available data fields. Preliminary results demonstrated the feasibility and utility of creating a National DBS-BTN resource for the scientific community. We plan to improve our techniques to remedy omitted clinical/research data, and expand the Network to include a larger donor pool. We will enhance sample preparation to

Development of representative magnetic resonance imaging-based atlases of the canine brain and evaluation of three methods for atlas-based segmentation.

Science.gov (United States)

Milne, Marjorie E; Steward, Christopher; Firestone, Simon M; Long, Sam N; O'Brien, Terrence J; Moffat, Bradford A

2016-04-01

To develop representative MRI atlases of the canine brain and to evaluate 3 methods of atlas-based segmentation (ABS). 62 dogs without clinical signs of epilepsy and without MRI evidence of structural brain disease. The MRI scans from 44 dogs were used to develop 4 templates on the basis of brain shape (brachycephalic, mesaticephalic, dolichocephalic, and combined mesaticephalic and dolichocephalic). Atlas labels were generated by segmenting the brain, ventricular system, hippocampal formation, and caudate nuclei. The MRI scans from the remaining 18 dogs were used to evaluate 3 methods of ABS (manual brain extraction and application of a brain shape-specific template [A], automatic brain extraction and application of a brain shape-specific template [B], and manual brain extraction and application of a combined template [C]). The performance of each ABS method was compared by calculation of the Dice and Jaccard coefficients, with manual segmentation used as the gold standard. Method A had the highest mean Jaccard coefficient and was the most accurate ABS method assessed. Measures of overlap for ABS methods that used manual brain extraction (A and C) ranged from 0.75 to 0.95 and compared favorably with repeated measures of overlap for manual extraction, which ranged from 0.88 to 0.97. Atlas-based segmentation was an accurate and repeatable method for segmentation of canine brain structures. It could be performed more rapidly than manual segmentation, which should allow the application of computer-assisted volumetry to large data sets and clinical cases and facilitate neuroimaging research and disease diagnosis.

A survey of MRI-based medical image analysis for brain tumor studies

Science.gov (United States)

Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

2013-07-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

A survey of MRI-based medical image analysis for brain tumor studies

International Nuclear Information System (INIS)

Bauer, Stefan; Nolte, Lutz-P; Reyes, Mauricio; Wiest, Roland

2013-01-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines. (topical review)

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

Science.gov (United States)

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.

Brain structural changes following adaptive cognitive training assessed by Tensor-Based Morphometry (TBM).

Science.gov (United States)

Colom, Roberto; Hua, Xue; Martínez, Kenia; Burgaleta, Miguel; Román, Francisco J; Gunter, Jeffrey L; Carmona, Susanna; Jaeggi, Susanne M; Thompson, Paul M

2016-10-01

Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. Copyright © 2016 Elsevier Ltd. All rights reserved.

Signifikansi Brain Based Learning Pendidikan Anak Usia Dini

OpenAIRE

Jazariyah

2017-01-01

This study based on the reality of learning in the early childhood level and the system has not noticed the potential of the brain learners. The potential and the working system of the brain is very important in early childhood. This paper aims to reveal the importance of brain-based learning in Early Childhood Education (ECD). The problem in this study is what the nature of early childhood education and how to use the potential and work system of the brain in early childhood learning. This s...

A capillary-based perfusion phantom for simulation of brain perfusion for MRI

International Nuclear Information System (INIS)

Maciak, A.; Kronfeld, A.; Mueller-Forell, W.; Wille, C.; Kempski, O.; Stoeter, P.

2010-01-01

Purpose: The measurement of the CBF is a non-standardized procedure and there are no reliable gold standards. This abstract shows a capillary-based perfusion-phantom for CE-DSC-MRI. It has equivalent flow properties to those within the tissue capillary system of the human brain and allows the validation of the Siemens Perfusion (MR) software. Materials and Methods: The perfusion phantom consists of a dialyzer for the simulation of the capillary system, a feeding tube for simulation of the AIF and a pulsatile pump for simulation of the heart. Using this perfusion phantom, the exact determination of the gold standard CBF due to the well-known geometry of the phantom is easy. It was validated based on different perfusion measurements. These measurements were investigated with standard software (Siemens Perfusion MR). The software determined the CBF within the capillary system. Based on this CBF, a comparison to the gold standard was made with several different flow speeds. After AIF selection, a total of 726 CBF data points were automatically extracted by the software. Results: This results in a comparison of the gold standard CBF to these 726 CBF values. Therefore, a reproducible and reliable deviation estimation between gold standard CBF and measured CBF using the software was computed. It can be shown that the deviation between gold standard and software-based evaluation ranges between 1 and 31 %. Conclusion: There is no significance for any correlation between flow speed and amount of deviation. The mean measured CBF is 11.4 % higher than the gold standard CBF (p-value < 0.001). Using this kind of perfusion-phantom, the validation of different software systems allows reliable conclusions about their quality. (orig.)

Validation of model-based brain shift correction in neurosurgery via intraoperative magnetic resonance imaging: preliminary results

Science.gov (United States)

Luo, Ma; Frisken, Sarah F.; Weis, Jared A.; Clements, Logan W.; Unadkat, Prashin; Thompson, Reid C.; Golby, Alexandra J.; Miga, Michael I.

2017-03-01

The quality of brain tumor resection surgery is dependent on the spatial agreement between preoperative image and intraoperative anatomy. However, brain shift compromises the aforementioned alignment. Currently, the clinical standard to monitor brain shift is intraoperative magnetic resonance (iMR). While iMR provides better understanding of brain shift, its cost and encumbrance is a consideration for medical centers. Hence, we are developing a model-based method that can be a complementary technology to address brain shift in standard resections, with resource-intensive cases as referrals for iMR facilities. Our strategy constructs a deformation `atlas' containing potential deformation solutions derived from a biomechanical model that account for variables such as cerebrospinal fluid drainage and mannitol effects. Volumetric deformation is estimated with an inverse approach that determines the optimal combinatory `atlas' solution fit to best match measured surface deformation. Accordingly, preoperative image is updated based on the computed deformation field. This study is the latest development to validate our methodology with iMR. Briefly, preoperative and intraoperative MR images of 2 patients were acquired. Homologous surface points were selected on preoperative and intraoperative scans as measurement of surface deformation and used to drive the inverse problem. To assess the model accuracy, subsurface shift of targets between preoperative and intraoperative states was measured and compared to model prediction. Considering subsurface shift above 3 mm, the proposed strategy provides an average shift correction of 59% across 2 cases. While further improvements in both the model and ability to validate with iMR are desired, the results reported are encouraging.

The scientifically substantiated art of teaching: A study in the development of standards in the new academic field of neuroeducation (mind, brain, and education science)

Science.gov (United States)

Tokuhama-Espinosa, Tracey Noel

Concepts from neuroeducation, commonly referred in the popular press as "brain-based learning," have been applied indiscreetly and inconsistently to classroom teaching practices for many years. While standards exist in neurology, psychology and pedagogy, there are no agreed upon standards in their intersection, neuroeducation, and a formal bridge linking the fields is missing. This study used grounded theory development to determine the parameters of the emerging neuroeducational field based on a meta-analysis of the literature over the past 30 years, which included over 2,200 documents. This research results in a new model for neuroeducation. The design of the new model was followed by a Delphi survey of 20 international experts from six different countries that further refined the model contents over several months of reflection. Finally, the revised model was compared to existing information sources, including popular press, peer review journals, academic publications, teacher training textbooks and the Internet, to determine to what extent standards in neuroeducation are met in the current literature. This study determined that standards in the emerging field, now labeled Mind, Brain, and Education: The Science of Teaching and Learning after the Delphi rounds, are the union of standards in the parent fields of neuroscience, psychology, and education. Additionally, the Delphi expert panel agreed upon the goals of the new discipline, its history, the thought leaders, and a model for judging quality information. The study culminated in a new model of the academic discipline of Mind, Brain, and Education science, which explains the tenets, principles and instructional guidelines supported by the meta-analysis of the literature and the Delphi response.

Navigation with a passive brain based interface

NARCIS (Netherlands)

Erp, J.B.F. van; Werkhoven, P.J.; Thurlings, M.E.; Brouwer, A.-M.

2009-01-01

In this paper, we describe a Brain Computer Interface (BCI) for navigation. The system is based on detecting brain signals that are elicited by tactile stimulation on the torso indicating the desired direction.

Applying Brain-Based Learning Principles to Athletic Training Education

Science.gov (United States)

Craig, Debbie I.

2007-01-01

Objective: To present different concepts and techniques related to the application of brain-based learning principles to Athletic Training clinical education. Background: The body of knowledge concerning how our brains physically learn continues to grow. Brain-based learning principles, developed by numerous authors, offer advice on how to…

Errors in MR-based attenuation correction for brain imaging with PET/MR scanners

International Nuclear Information System (INIS)

Rota Kops, Elena; Herzog, Hans

2013-01-01

Aim: Attenuation correction of PET data acquired by hybrid MR/PET scanners remains a challenge, even if several methods for brain and whole-body measurements have been developed recently. A template-based attenuation correction for brain imaging proposed by our group is easy to handle and delivers reliable attenuation maps in a short time. However, some potential error sources are analyzed in this study. We investigated the choice of template reference head among all the available data (error A), and possible skull anomalies of the specific patient, such as discontinuities due to surgery (error B). Materials and methods: An anatomical MR measurement and a 2-bed-position transmission scan covering the whole head and neck region were performed in eight normal subjects (4 females, 4 males). Error A: Taking alternatively one of the eight heads as reference, eight different templates were created by nonlinearly registering the images to the reference and calculating the average. Eight patients (4 females, 4 males; 4 with brain lesions, 4 w/o brain lesions) were measured in the Siemens BrainPET/MR scanner. The eight templates were used to generate the patients' attenuation maps required for reconstruction. ROI and VOI atlas-based comparisons were performed employing all the reconstructed images. Error B: CT-based attenuation maps of two volunteers were manipulated by manually inserting several skull lesions and filling a nasal cavity. The corresponding attenuation coefficients were substituted with the water's coefficient (0.096/cm). Results: Error A: The mean SUVs over the eight templates pairs for all eight patients and all VOIs did not differ significantly one from each other. Standard deviations up to 1.24% were found. Error B: After reconstruction of the volunteers' BrainPET data with the CT-based attenuation maps without and with skull anomalies, a VOI-atlas analysis was performed revealing very little influence of the skull lesions (less than 3%), while the filled

Errors in MR-based attenuation correction for brain imaging with PET/MR scanners

Science.gov (United States)

Rota Kops, Elena; Herzog, Hans

2013-02-01

AimAttenuation correction of PET data acquired by hybrid MR/PET scanners remains a challenge, even if several methods for brain and whole-body measurements have been developed recently. A template-based attenuation correction for brain imaging proposed by our group is easy to handle and delivers reliable attenuation maps in a short time. However, some potential error sources are analyzed in this study. We investigated the choice of template reference head among all the available data (error A), and possible skull anomalies of the specific patient, such as discontinuities due to surgery (error B). Materials and methodsAn anatomical MR measurement and a 2-bed-position transmission scan covering the whole head and neck region were performed in eight normal subjects (4 females, 4 males). Error A: Taking alternatively one of the eight heads as reference, eight different templates were created by nonlinearly registering the images to the reference and calculating the average. Eight patients (4 females, 4 males; 4 with brain lesions, 4 w/o brain lesions) were measured in the Siemens BrainPET/MR scanner. The eight templates were used to generate the patients' attenuation maps required for reconstruction. ROI and VOI atlas-based comparisons were performed employing all the reconstructed images. Error B: CT-based attenuation maps of two volunteers were manipulated by manually inserting several skull lesions and filling a nasal cavity. The corresponding attenuation coefficients were substituted with the water's coefficient (0.096/cm). ResultsError A: The mean SUVs over the eight templates pairs for all eight patients and all VOIs did not differ significantly one from each other. Standard deviations up to 1.24% were found. Error B: After reconstruction of the volunteers' BrainPET data with the CT-based attenuation maps without and with skull anomalies, a VOI-atlas analysis was performed revealing very little influence of the skull lesions (less than 3%), while the filled nasal

Hemispheric asymmetry of electroencephalography-based functional brain networks.

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Jalili, Mahdi

2014-11-12

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Why standard brain-computer interface (BCI) training protocols should be changed: an experimental study

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Jeunet, Camille; Jahanpour, Emilie; Lotte, Fabien

2016-06-01

Objective. While promising, electroencephaloraphy based brain-computer interfaces (BCIs) are barely used due to their lack of reliability: 15% to 30% of users are unable to control a BCI. Standard training protocols may be partly responsible as they do not satisfy recommendations from psychology. Our main objective was to determine in practice to what extent standard training protocols impact users’ motor imagery based BCI (MI-BCI) control performance. Approach. We performed two experiments. The first consisted in evaluating the efficiency of a standard BCI training protocol for the acquisition of non-BCI related skills in a BCI-free context, which enabled us to rule out the possible impact of BCIs on the training outcome. Thus, participants (N = 54) were asked to perform simple motor tasks. The second experiment was aimed at measuring the correlations between motor tasks and MI-BCI performance. The ten best and ten worst performers of the first study were recruited for an MI-BCI experiment during which they had to learn to perform two MI tasks. We also assessed users’ spatial ability and pre-training μ rhythm amplitude, as both have been related to MI-BCI performance in the literature. Main results. Around 17% of the participants were unable to learn to perform the motor tasks, which is close to the BCI illiteracy rate. This suggests that standard training protocols are suboptimal for skill teaching. No correlation was found between motor tasks and MI-BCI performance. However, spatial ability played an important role in MI-BCI performance. In addition, once the spatial ability covariable had been controlled for, using an ANCOVA, it appeared that participants who faced difficulty during the first experiment improved during the second while the others did not. Significance. These studies suggest that (1) standard MI-BCI training protocols are suboptimal for skill teaching, (2) spatial ability is confirmed as impacting on MI-BCI performance, and (3) when faced

Functional community analysis of brain: a new approach for EEG-based investigation of the brain pathology.

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Ahmadlou, Mehran; Adeli, Hojjat

2011-09-15

Analysis of structure of the brain functional connectivity (SBFC) is a fundamental issue for understanding of the brain cognition as well as the pathology of brain disorders. Analysis of communities among sub-parts of a system is increasingly used for social, ecological, and other networks. This paper presents a new methodology for investigation of the SBFC and understanding of the brain based on graph theory and community pattern analysis of functional connectivity graph of the brain obtained from encephalograms (EEGs). The methodology consists of three main parts: fuzzy synchronization likelihood (FSL), community partitioning, and decisions based on partitions. As an example application, the methodology is applied to analysis of brain of patients with attention deficit/hyperactivity disorder (ADHD) and the problem of discrimination of ADHD EEGs from healthy (non-ADHD) EEGs. Copyright © 2011. Published by Elsevier Inc.

Brain medical image diagnosis based on corners with importance-values.

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Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection

Enhancing Student Learning with Brain-Based Research

Science.gov (United States)

Bonnema, Ted R.

2009-01-01

This paper discusses brain-based learning and its relation to classroom instruction. A rapidly growing quantity of research currently exists regarding how the brain perceives, processes, and ultimately learns new information. In order to maximize their teaching efficacy, educators should have a basic understanding of key memory functions in the…

The Brains behind Brain-Based Research: The Tale of Two Postsecondary Online Learners

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McGuckin, Dawn; Ladhani, Mubeen

2010-01-01

This paper is written from the perspective of two postsecondary students who realized the implications for brain-based learning in the online environment. This paper explores the relationship between online learning in regards to how the brain generates meaning and understanding, the role of emotions, the collaborative construction of knowledge,…

Simulation-based training in brain death determination.

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MacDougall, Benjamin J; Robinson, Jennifer D; Kappus, Liana; Sudikoff, Stephanie N; Greer, David M

2014-12-01

Despite straightforward guidelines on brain death determination by the American Academy of Neurology (AAN), substantial practice variability exists internationally, between states, and among institutions. We created a simulation-based training course on proper determination based on the AAN practice parameters to address and assess knowledge and practice gaps at our institution. Our intervention consisted of a didactic course and a simulation exercise, and was bookended by before and after multiple-choice tests. The 40-min didactic course, including a video demonstration, covered all aspects of the brain death examination. Simulation sessions utilized a SimMan 3G manikin and involved a complete examination, including an apnea test. Possible confounders and signs incompatible with brain death were embedded throughout. Facilitators evaluated performance with a 26-point checklist based on the most recent AAN guidelines. A senior neurologist conducted all aspects of the course, including the didactic session, simulation, and debriefing session. Ninety physicians from multiple specialties have participated in the didactic session, 38 of whom have completed the simulation. Pre-test scores were poor (41.4 %), with attendings scoring higher than residents (46.6 vs. 40.4 %, p = 0.07), and neurologists and neurosurgeons significantly outperforming other specialists (53.9 vs. 38.9 %, p = 0.003). Post-test scores (73.3 %) were notably higher than pre-test scores (45.4 %). Participant feedback has been uniformly positive. Baseline knowledge of brain death determination among providers was low but improved greatly after the course. Our intervention represents an effective model that can be replicated at other institutions to train clinicians in the determination of brain death according to evidence-based guidelines.

Model brain based learning (BBL and whole brain teaching (WBT in learning

Directory of Open Access Journals (Sweden)

Baiq Sri Handayani

2017-08-01

Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical

Partial volume correction and image segmentation for accurate measurement of standardized uptake value of grey matter in the brain.

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Bural, Gonca; Torigian, Drew; Basu, Sandip; Houseni, Mohamed; Zhuge, Ying; Rubello, Domenico; Udupa, Jayaram; Alavi, Abass

2015-12-01

Our aim was to explore a novel quantitative method [based upon an MRI-based image segmentation that allows actual calculation of grey matter, white matter and cerebrospinal fluid (CSF) volumes] for overcoming the difficulties associated with conventional techniques for measuring actual metabolic activity of the grey matter. We included four patients with normal brain MRI and fluorine-18 fluorodeoxyglucose (F-FDG)-PET scans (two women and two men; mean age 46±14 years) in this analysis. The time interval between the two scans was 0-180 days. We calculated the volumes of grey matter, white matter and CSF by using a novel segmentation technique applied to the MRI images. We measured the mean standardized uptake value (SUV) representing the whole metabolic activity of the brain from the F-FDG-PET images. We also calculated the white matter SUV from the upper transaxial slices (centrum semiovale) of the F-FDG-PET images. The whole brain volume was calculated by summing up the volumes of the white matter, grey matter and CSF. The global cerebral metabolic activity was calculated by multiplying the mean SUV with total brain volume. The whole brain white matter metabolic activity was calculated by multiplying the mean SUV for the white matter by the white matter volume. The global cerebral metabolic activity only reflects those of the grey matter and the white matter, whereas that of the CSF is zero. We subtracted the global white matter metabolic activity from that of the whole brain, resulting in the global grey matter metabolism alone. We then divided the grey matter global metabolic activity by grey matter volume to accurately calculate the SUV for the grey matter alone. The brain volumes ranged between 1546 and 1924 ml. The mean SUV for total brain was 4.8-7. Total metabolic burden of the brain ranged from 5565 to 9617. The mean SUV for white matter was 2.8-4.1. On the basis of these measurements we generated the grey matter SUV, which ranged from 8.1 to 11.3. The

[Acid-base equilibrium and the brain].

Science.gov (United States)

Rabary, O; Boussofara, M; Grimaud, D

1994-01-01

In physiological conditions, the regulation of acid-base balance in brain maintains a noteworthy stability of cerebral pH. During systemic metabolic acid-base imbalances cerebral pH is well controlled as the blood/brain barrier is slowly and poorly permeable to electrolytes (HCO3- and H+). Cerebral pH is regulated by a modulation of the respiratory drive, triggered by the early alterations of interstitial fluid pH, close to medullary chemoreceptors. As blood/brain barrier is highly permeable to Co2, CSF pH is corrected in a few hours, even in case of severe metabolic acidosis and alkalosis. Conversely, during ventilatory acidosis and alkalosis the cerebral pH varies in the same direction and in the same range than blood pH. Therefore, the brain is better protected against metabolic than ventilatory acid-base imbalances. Ventilatory acidosis and alkalosis are able to impair cerebral blood flow and brain activity through interstitial pH alterations. During respiratory acidosis, [HCO3-] increases in extracellular fluids to control cerebral pH by two main ways: a carbonic anhydrase activation at the blood/brain and blood/CSF barriers level and an increase in chloride shift in glial cells (HCO3- exchanged for Cl-). During respiratory alkalosis, [HCO3-] decreases in extracellular fluids by the opposite changes in HCO3- transport and by an increase in lactic acid synthesis by cerebral cells. The treatment of metabolic acidosis with bicarbonates may induce a cerebral acidosis and worsen a cerebral oedema during ketoacidosis. Moderate hypocapnia carried out to treat intracranial hypertension is mainly effective when cerebral blood flow is high and vascular CO2 reactivity maintained. Hypocapnia may restore an altered cerebral blood flow autoregulation. Instrumental hypocapnia requires a control of cerebral perfusion pressure and cerebral arteriovenous difference for oxygen, to select patients for whom this kind of treatment may be of benefit, to choose the optimal level of

Legal Standards for Brain Death and Undue Influence in Euthanasia Laws.

Science.gov (United States)

Pope, Thaddeus Mason; Okninski, Michaela E

2016-06-01

A major appellate court decision from the United States seriously questions the legal sufficiency of prevailing medical criteria for the determination of death by neurological criteria. There may be a mismatch between legal and medical standards for brain death, requiring the amendment of either or both. In South Australia, a Bill seeks to establish a legal right for a defined category of persons suffering unbearably to request voluntary euthanasia. However, an essential criterion of a voluntary decision is that it is not tainted by undue influence, and this Bill falls short of providing adequate guidance to assess for undue influence.

PET/MRI for Oncologic Brain Imaging

DEFF Research Database (Denmark)

Rausch, Ivo; Rischka, Lucas; Ladefoged, Claes N

2017-01-01

The aim of this study was to compare attenuation-correction (AC) approaches for PET/MRI in clinical neurooncology.Methods:Forty-nine PET/MRI brain scans were included: brain tumor studies using18F-fluoro-ethyl-tyrosine (18F-FET) (n= 31) and68Ga-DOTANOC (n= 7) and studies of healthy subjects using18...... by Siemens Healthcare). As a reference, AC maps were derived from patient-specific CT images (CTref). PET data were reconstructed using standard settings after AC with all 4 AC methods. We report changes in diagnosis for all brain tumor patients and the following relative differences values (RDs...... of the whole brain and 10 anatomic regions segmented on MR images.Results:For brain tumor imaging (A and B), the standard PET-based diagnosis was not affected by any of the 3 MR-AC methods. For A, the average RDs of SUVmeanwere -10%, -4%, and -3% and of the VOIs 1%, 2%, and 7% for DIXON, UTE, and BD...

Mapping the regional influence of genetics on brain structure variability--a tensor-based morphometry study.

Science.gov (United States)

Brun, Caroline C; Leporé, Natasha; Pennec, Xavier; Lee, Agatha D; Barysheva, Marina; Madsen, Sarah K; Avedissian, Christina; Chou, Yi-Yu; de Zubicaray, Greig I; McMahon, Katie L; Wright, Margaret J; Toga, Arthur W; Thompson, Paul M

2009-10-15

Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8+/-1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

Touch-based Brain Computer Interfaces: State of the art

NARCIS (Netherlands)

Erp, J.B.F. van; Brouwer, A.M.

2014-01-01

Brain Computer Interfaces (BCIs) rely on the user's brain activity to control equipment or computer devices. Many BCIs are based on imagined movement (called active BCIs) or the fact that brain patterns differ in reaction to relevant or attended stimuli in comparison to irrelevant or unattended

Optimized temporal pattern of brain stimulation designed by computational evolution.

Science.gov (United States)

Brocker, David T; Swan, Brandon D; So, Rosa Q; Turner, Dennis A; Gross, Robert E; Grill, Warren M

2017-01-04

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson's disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We varied the temporal pattern of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson's disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in a parkinsonian rat model and in patients. Both optimized and standard high-frequency stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution of temporal patterns to increase the efficiency of brain stimulation in treating Parkinson's disease and thereby reduce the energy required for successful treatment below that of current brain stimulation paradigms. Copyright © 2017, American Association for the Advancement of Science.

Brain-Based Education: Its Pedagogical Implications and Research Relevance

Science.gov (United States)

Laxman, Kumar; Chin, Yap Kueh

2010-01-01

The brain, being the organ of learning, must be understood if classrooms are to be places of meaningful learning. Understanding the brain has the potential to alter the foundation of education, transform traditional classrooms to interactive learning environments and promote better instructional approaches amongst teachers. Brain-based education…

Technology-Based Rehabilitation to Improve Communication after Acquired Brain Injury

Directory of Open Access Journals (Sweden)

Carrie A. Des Roches

2017-07-01

Full Text Available The utilization of technology has allowed for several advances in aphasia rehabilitation for individuals with acquired brain injury. Thirty-one previous studies that provide technology-based language or language and cognitive rehabilitation are examined in terms of the domains addressed, the types of treatments that were provided, details about the methods and the results, including which types of outcomes are reported. From this, we address questions about how different aspects of the delivery of treatment can influence rehabilitation outcomes, such as whether the treatment was standardized or tailored, whether the participants were prescribed homework or not, and whether intensity was varied. Results differed by these aspects of treatment delivery but ultimately the studies demonstrated consistent improvement on various outcome measures. With these aspects of technology-based treatment in mind, the ultimate goal of personalized rehabilitation is discussed.

Technology-Based Rehabilitation to Improve Communication after Acquired Brain Injury.

Science.gov (United States)

Des Roches, Carrie A; Kiran, Swathi

2017-01-01

The utilization of technology has allowed for several advances in aphasia rehabilitation for individuals with acquired brain injury. Thirty-one previous studies that provide technology-based language or language and cognitive rehabilitation are examined in terms of the domains addressed, the types of treatments that were provided, details about the methods and the results, including which types of outcomes are reported. From this, we address questions about how different aspects of the delivery of treatment can influence rehabilitation outcomes, such as whether the treatment was standardized or tailored, whether the participants were prescribed homework or not, and whether intensity was varied. Results differed by these aspects of treatment delivery but ultimately the studies demonstrated consistent improvement on various outcome measures. With these aspects of technology-based treatment in mind, the ultimate goal of personalized rehabilitation is discussed.

Multiple brain atlas database and atlas-based neuroimaging system.

Science.gov (United States)

Nowinski, W L; Fang, A; Nguyen, B T; Raphel, J K; Jagannathan, L; Raghavan, R; Bryan, R N; Miller, G A

1997-01-01

For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.

Progress and roadblocks in the search for brain-based biomarkers of autism and attention-deficit/hyperactivity disorder.

Science.gov (United States)

Uddin, L Q; Dajani, D R; Voorhies, W; Bednarz, H; Kana, R K

2017-08-22

Children with neurodevelopmental disorders benefit most from early interventions and treatments. The development and validation of brain-based biomarkers to aid in objective diagnosis can facilitate this important clinical aim. The objective of this review is to provide an overview of current progress in the use of neuroimaging to identify brain-based biomarkers for autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), two prevalent neurodevelopmental disorders. We summarize empirical work that has laid the foundation for using neuroimaging to objectively quantify brain structure and function in ways that are beginning to be used in biomarker development, noting limitations of the data currently available. The most successful machine learning methods that have been developed and applied to date are discussed. Overall, there is increasing evidence that specific features (for example, functional connectivity, gray matter volume) of brain regions comprising the salience and default mode networks can be used to discriminate ASD from typical development. Brain regions contributing to successful discrimination of ADHD from typical development appear to be more widespread, however there is initial evidence that features derived from frontal and cerebellar regions are most informative for classification. The identification of brain-based biomarkers for ASD and ADHD could potentially assist in objective diagnosis, monitoring of treatment response and prediction of outcomes for children with these neurodevelopmental disorders. At present, however, the field has yet to identify reliable and reproducible biomarkers for these disorders, and must address issues related to clinical heterogeneity, methodological standardization and cross-site validation before further progress can be achieved.

Reproducibility Between Brain Uptake Ratio Using Anatomic Standardization and Patlak-Plot Methods.

Science.gov (United States)

Shibutani, Takayuki; Onoguchi, Masahisa; Noguchi, Atsushi; Yamada, Tomoki; Tsuchihashi, Hiroko; Nakajima, Tadashi; Kinuya, Seigo

2015-12-01

The Patlak-plot and conventional methods of determining brain uptake ratio (BUR) have some problems with reproducibility. We formulated a method of determining BUR using anatomic standardization (BUR-AS) in a statistical parametric mapping algorithm to improve reproducibility. The objective of this study was to demonstrate the inter- and intraoperator reproducibility of mean cerebral blood flow as determined using BUR-AS in comparison to the conventional-BUR (BUR-C) and Patlak-plot methods. The images of 30 patients who underwent brain perfusion SPECT were retrospectively used in this study. The images were reconstructed using ordered-subset expectation maximization and processed using an automatic quantitative analysis for cerebral blood flow of ECD tool. The mean SPECT count was calculated from axial basal ganglia slices of the normal side (slices 31-40) drawn using a 3-dimensional stereotactic region-of-interest template after anatomic standardization. The mean cerebral blood flow was calculated from the mean SPECT count. Reproducibility was evaluated using coefficient of variation and Bland-Altman plotting. For both inter- and intraoperator reproducibility, the BUR-AS method had the lowest coefficient of variation and smallest error range about the Bland-Altman plot. Mean CBF obtained using the BUR-AS method had the highest reproducibility. Compared with the Patlak-plot and BUR-C methods, the BUR-AS method provides greater inter- and intraoperator reproducibility of cerebral blood flow measurement. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Brain Tumor Image Segmentation in MRI Image

Science.gov (United States)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Radiotherapy for pediatric brain tumors: Standard of care, current clinical trials, and new directions

International Nuclear Information System (INIS)

Kun, Larry E.

1996-01-01

Objectives: To review the clinical characteristics of childhood brain tumors, including neurologic signs, neuroimaging and neuropathology. To critically assess indications for therapy relevant to presenting characteristics, age, and disease status. To discuss current management strategies including neurosurgery, radiation therapy, and chemotherapy. To analyze current clinical trials and future directions of clinical research. Brain tumors account for 20% of neoplastic diseases in children. The most common tumors include astrocytoma and malignant gliomas, medulloblastoma and supratentorial PNET's, ependymoma, craniopharyngioma, and intracranial germ cell tumors. Tumor type and clinical course are often correlated with age at presentation and anatomic site. The clinical characteristics and disease extent largely determine the relative merits of available 'standard' and investigational therapeutic approaches. Treatment outcome, including disease control and functional integrity, is dependent upon age at presentation, tumor type, and disease extent. An understanding of the clinical, neuroimaging, and histologic characteristics as they relate to decisions regarding therapy is critical to the radiation oncologist. Appropriate radiation therapy is central to curative therapy for a majority of pediatric brain tumor presentations. Technical advances in neurosurgery provide greater safety for 'gross total resection' in a majority of hemispheric astrocytomas and medulloblastomas. The relative roles of 'standard' radiation therapy and evolving chemotherapy for centrally located astrocytomas (e.g., diencephalic, optic pathway) need to be analyzed in the context of initial and overall disease control, neurotoxicities, and potential modifications in the risk:benefit ratio apparent in the introduction of precision radiation techniques. Modifications in radiation delivery are fundamental to current investigations in medulloblastoma; the rationale for contemporary and projected

Magnetic resonance imaging and cell-based neurorestorative therapy after brain injury

Directory of Open Access Journals (Sweden)

Quan Jiang

2016-01-01

Full Text Available Restorative cell-based therapies for experimental brain injury, such as stroke and traumatic brain injury, substantially improve functional outcome. We discuss and review state of the art magnetic resonance imaging methodologies and their applications related to cell-based treatment after brain injury. We focus on the potential of magnetic resonance imaging technique and its associated challenges to obtain useful new information related to cell migration, distribution, and quantitation, as well as vascular and neuronal remodeling in response to cell-based therapy after brain injury. The noninvasive nature of imaging might more readily help with translation of cell-based therapy from the laboratory to the clinic.

Subcortical Brain Morphology in Schizophrenia : Descriptive analysis based on MRI findings of subcortical brain volumes

OpenAIRE

Gunleiksrud, Sindre

2009-01-01

The aim of this study was to investigate magnetic resonance images (MR) from patients with schizophrenia and healthy control subjects for difference in brain morphology with focus on subcortical brain volumes. Method: The study compared fourteen subcortical brain structure volumes of 96 patients diagnosed with schizophrenia (n=81) or schizoaffective disorder (n=15) with 106 healthy control subjects. Volume measures were obtained using voxel-based morphometry (FreeSurfer software suite) of ...

CHAOS-BASED ADVANCED ENCRYPTION STANDARD

KAUST Repository

Abdulwahed, Naif B.

2013-01-01

This thesis introduces a new chaos-based Advanced Encryption Standard (AES). The AES is a well-known encryption algorithm that was standardized by U.S National Institute of Standard and Technology (NIST) in 2001. The thesis investigates and explores

Tissue-Based MRI Intensity Standardization: Application to Multicentric Datasets

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Nicolas Robitaille

2012-01-01

Full Text Available Intensity standardization in MRI aims at correcting scanner-dependent intensity variations. Existing simple and robust techniques aim at matching the input image histogram onto a standard, while we think that standardization should aim at matching spatially corresponding tissue intensities. In this study, we present a novel automatic technique, called STI for STandardization of Intensities, which not only shares the simplicity and robustness of histogram-matching techniques, but also incorporates tissue spatial intensity information. STI uses joint intensity histograms to determine intensity correspondence in each tissue between the input and standard images. We compared STI to an existing histogram-matching technique on two multicentric datasets, Pilot E-ADNI and ADNI, by measuring the intensity error with respect to the standard image after performing nonlinear registration. The Pilot E-ADNI dataset consisted in 3 subjects each scanned in 7 different sites. The ADNI dataset consisted in 795 subjects scanned in more than 50 different sites. STI was superior to the histogram-matching technique, showing significantly better intensity matching for the brain white matter with respect to the standard image.

Gamma Knife irradiation method based on dosimetric controls to target small areas in rat brains

International Nuclear Information System (INIS)

Constanzo, Julie; Paquette, Benoit; Charest, Gabriel; Masson-Côté, Laurence; Guillot, Mathieu

2015-01-01

Purpose: Targeted and whole-brain irradiation in humans can result in significant side effects causing decreased patient quality of life. To adequately investigate structural and functional alterations after stereotactic radiosurgery, preclinical studies are needed. The purpose of this work is to establish a robust standardized method of targeted irradiation on small regions of the rat brain. Methods: Euthanized male Fischer rats were imaged in a stereotactic bed, by computed tomography (CT), to estimate positioning variations relative to the bregma skull reference point. Using a rat brain atlas and the stereotactic bregma coordinates obtained from CT images, different regions of the brain were delimited and a treatment plan was generated. A single isocenter treatment plan delivering ≥100 Gy in 100% of the target volume was produced by Leksell GammaPlan using the 4 mm diameter collimator of sectors 4, 5, 7, and 8 of the Gamma Knife unit. Impact of positioning deviations of the rat brain on dose deposition was simulated by GammaPlan and validated with dosimetric measurements. Results: The authors’ results showed that 90% of the target volume received 100 ± 8 Gy and the maximum of deposited dose was 125 ± 0.7 Gy, which corresponds to an excellent relative standard deviation of 0.6%. This dose deposition calculated with GammaPlan was validated with dosimetric films resulting in a dose-profile agreement within 5%, both in X- and Z-axes. Conclusions: The authors’ results demonstrate the feasibility of standardizing the irradiation procedure of a small volume in the rat brain using a Gamma Knife

Progress in EEG-Based Brain Robot Interaction Systems

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Xiaoqian Mao

2017-01-01

Full Text Available The most popular noninvasive Brain Robot Interaction (BRI technology uses the electroencephalogram- (EEG- based Brain Computer Interface (BCI, to serve as an additional communication channel, for robot control via brainwaves. This technology is promising for elderly or disabled patient assistance with daily life. The key issue of a BRI system is to identify human mental activities, by decoding brainwaves, acquired with an EEG device. Compared with other BCI applications, such as word speller, the development of these applications may be more challenging since control of robot systems via brainwaves must consider surrounding environment feedback in real-time, robot mechanical kinematics, and dynamics, as well as robot control architecture and behavior. This article reviews the major techniques needed for developing BRI systems. In this review article, we first briefly introduce the background and development of mind-controlled robot technologies. Second, we discuss the EEG-based brain signal models with respect to generating principles, evoking mechanisms, and experimental paradigms. Subsequently, we review in detail commonly used methods for decoding brain signals, namely, preprocessing, feature extraction, and feature classification, and summarize several typical application examples. Next, we describe a few BRI applications, including wheelchairs, manipulators, drones, and humanoid robots with respect to synchronous and asynchronous BCI-based techniques. Finally, we address some existing problems and challenges with future BRI techniques.

Rapid prototyping of an EEG-based brain-computer interface (BCI).

Science.gov (United States)

Guger, C; Schlögl, A; Neuper, C; Walterspacher, D; Strein, T; Pfurtscheller, G

2001-03-01

The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).

Standardized Environmental Enrichment Supports Enhanced Brain Plasticity in Healthy Rats and Prevents Cognitive Impairment in Epileptic Rats

Science.gov (United States)

Kouchi, Hayet Y.; Bodennec, Jacques; Morales, Anne; Georges, Béatrice; Bonnet, Chantal; Bouvard, Sandrine; Sloviter, Robert S.; Bezin, Laurent

2013-01-01

Environmental enrichment of laboratory animals influences brain plasticity, stimulates neurogenesis, increases neurotrophic factor expression, and protects against the effects of brain insult. However, these positive effects are not constantly observed, probably because standardized procedures of environmental enrichment are lacking. Therefore, we engineered an enriched cage (the Marlau™ cage), which offers: (1) minimally stressful social interactions; (2) increased voluntary exercise; (3) multiple entertaining activities; (4) cognitive stimulation (maze exploration), and (5) novelty (maze configuration changed three times a week). The maze, which separates food pellet and water bottle compartments, guarantees cognitive stimulation for all animals. Compared to rats raised in groups in conventional cages, rats housed in Marlau™ cages exhibited increased cortical thickness, hippocampal neurogenesis and hippocampal levels of transcripts encoding various genes involved in tissue plasticity and remodeling. In addition, rats housed in Marlau™ cages exhibited better performances in learning and memory, decreased anxiety-associated behaviors, and better recovery of basal plasma corticosterone level after acute restraint stress. Marlau™ cages also insure inter-experiment reproducibility in spatial learning and brain gene expression assays. Finally, housing rats in Marlau™ cages after severe status epilepticus at weaning prevents the cognitive impairment observed in rats subjected to the same insult and then housed in conventional cages. By providing a standardized enriched environment for rodents during housing, the Marlau™ cage should facilitate the uniformity of environmental enrichment across laboratories. PMID:23342033

Standardized environmental enrichment supports enhanced brain plasticity in healthy rats and prevents cognitive impairment in epileptic rats.

Directory of Open Access Journals (Sweden)

Raafat P Fares

Full Text Available Environmental enrichment of laboratory animals influences brain plasticity, stimulates neurogenesis, increases neurotrophic factor expression, and protects against the effects of brain insult. However, these positive effects are not constantly observed, probably because standardized procedures of environmental enrichment are lacking. Therefore, we engineered an enriched cage (the Marlau™ cage, which offers: (1 minimally stressful social interactions; (2 increased voluntary exercise; (3 multiple entertaining activities; (4 cognitive stimulation (maze exploration, and (5 novelty (maze configuration changed three times a week. The maze, which separates food pellet and water bottle compartments, guarantees cognitive stimulation for all animals. Compared to rats raised in groups in conventional cages, rats housed in Marlau™ cages exhibited increased cortical thickness, hippocampal neurogenesis and hippocampal levels of transcripts encoding various genes involved in tissue plasticity and remodeling. In addition, rats housed in Marlau™ cages exhibited better performances in learning and memory, decreased anxiety-associated behaviors, and better recovery of basal plasma corticosterone level after acute restraint stress. Marlau™ cages also insure inter-experiment reproducibility in spatial learning and brain gene expression assays. Finally, housing rats in Marlau™ cages after severe status epilepticus at weaning prevents the cognitive impairment observed in rats subjected to the same insult and then housed in conventional cages. By providing a standardized enriched environment for rodents during housing, the Marlau™ cage should facilitate the uniformity of environmental enrichment across laboratories.

Public School Teachers' Knowledge, Perception, and Implementation of Brain-Based Learning Practices

Science.gov (United States)

Wachob, David A.

2012-01-01

The purpose of this study was to determine K-12 teachers' knowledge, beliefs, and practices of brain-based learning strategies in western Pennsylvania schools. The following five research questions were explored: (a) What is the extent of knowledge K-12 public school teachers have about the indicators of brain-based learning and Brain Gym?; (b) To…

Near infrared spectroscopy based brain-computer interface

Science.gov (United States)

Ranganatha, Sitaram; Hoshi, Yoko; Guan, Cuntai

2005-04-01

A brain-computer interface (BCI) provides users with an alternative output channel other than the normal output path of the brain. BCI is being given much attention recently as an alternate mode of communication and control for the disabled, such as patients suffering from Amyotrophic Lateral Sclerosis (ALS) or "locked-in". BCI may also find applications in military, education and entertainment. Most of the existing BCI systems which rely on the brain's electrical activity use scalp EEG signals. The scalp EEG is an inherently noisy and non-linear signal. The signal is detrimentally affected by various artifacts such as the EOG, EMG, ECG and so forth. EEG is cumbersome to use in practice, because of the need for applying conductive gel, and the need for the subject to be immobile. There is an urgent need for a more accessible interface that uses a more direct measure of cognitive function to control an output device. The optical response of Near Infrared Spectroscopy (NIRS) denoting brain activation can be used as an alternative to electrical signals, with the intention of developing a more practical and user-friendly BCI. In this paper, a new method of brain-computer interface (BCI) based on NIRS is proposed. Preliminary results of our experiments towards developing this system are reported.

"Celebration of the Neurons": The Application of Brain Based Learning in Classroom Environment

Science.gov (United States)

Duman, Bilal

2007-01-01

The purpose of this study is to investigate approaches and techniques related to how brain based learning used in classroom atmosphere. This general purpose were answered following the questions: (1) What is the aim of brain based learning? (2) What are general approaches and techniques that brain based learning used? and (3) How should be used…

MRI-based Brain Healthcare Quotients: A bridge between neural and behavioral analyses for keeping the brain healthy.

Science.gov (United States)

Nemoto, Kiyotaka; Oka, Hiroki; Fukuda, Hiroki; Yamakawa, Yoshinori

2017-01-01

Neurological and psychiatric disorders are a burden on social and economic resources. Therefore, maintaining brain health and preventing these disorders are important. While the physiological functions of the brain are well studied, few studies have focused on keeping the brain healthy from a neuroscientific viewpoint. We propose a magnetic resonance imaging (MRI)-based quotient for monitoring brain health, the Brain Healthcare Quotient (BHQ), which is based on the volume of gray matter (GM) and the fractional anisotropy (FA) of white matter (WM). We recruited 144 healthy adults to acquire structural neuroimaging data, including T1-weighted images and diffusion tensor images, and data associated with both physical (BMI, blood pressure, and daily time use) and social (subjective socioeconomic status, subjective well-being, post-materialism and Epicureanism) factors. We confirmed that the BHQ was sensitive to an age-related decline in GM volume and WM integrity. Further analysis revealed that the BHQ was critically affected by both physical and social factors. We believe that our BHQ is a simple yet highly sensitive, valid measure for brain health research that will bridge the needs of the scientific community and society and help us lead better lives in which we stay healthy, active, and sharp.

MRI-based Brain Healthcare Quotients: A bridge between neural and behavioral analyses for keeping the brain healthy.

Directory of Open Access Journals (Sweden)

Kiyotaka Nemoto

Full Text Available Neurological and psychiatric disorders are a burden on social and economic resources. Therefore, maintaining brain health and preventing these disorders are important. While the physiological functions of the brain are well studied, few studies have focused on keeping the brain healthy from a neuroscientific viewpoint. We propose a magnetic resonance imaging (MRI-based quotient for monitoring brain health, the Brain Healthcare Quotient (BHQ, which is based on the volume of gray matter (GM and the fractional anisotropy (FA of white matter (WM. We recruited 144 healthy adults to acquire structural neuroimaging data, including T1-weighted images and diffusion tensor images, and data associated with both physical (BMI, blood pressure, and daily time use and social (subjective socioeconomic status, subjective well-being, post-materialism and Epicureanism factors. We confirmed that the BHQ was sensitive to an age-related decline in GM volume and WM integrity. Further analysis revealed that the BHQ was critically affected by both physical and social factors. We believe that our BHQ is a simple yet highly sensitive, valid measure for brain health research that will bridge the needs of the scientific community and society and help us lead better lives in which we stay healthy, active, and sharp.

Learning-based meta-algorithm for MRI brain extraction.

Science.gov (United States)

Shi, Feng; Wang, Li; Gilmore, John H; Lin, Weili; Shen, Dinggang

2011-01-01

Multiple-segmentation-and-fusion method has been widely used for brain extraction, tissue segmentation, and region of interest (ROI) localization. However, such studies are hindered in practice by their computational complexity, mainly coming from the steps of template selection and template-to-subject nonlinear registration. In this study, we address these two issues and propose a novel learning-based meta-algorithm for MRI brain extraction. Specifically, we first use exemplars to represent the entire template library, and assign the most similar exemplar to the test subject. Second, a meta-algorithm combining two existing brain extraction algorithms (BET and BSE) is proposed to conduct multiple extractions directly on test subject. Effective parameter settings for the meta-algorithm are learned from the training data and propagated to subject through exemplars. We further develop a level-set based fusion method to combine multiple candidate extractions together with a closed smooth surface, for obtaining the final result. Experimental results show that, with only a small portion of subjects for training, the proposed method is able to produce more accurate and robust brain extraction results, at Jaccard Index of 0.956 +/- 0.010 on total 340 subjects under 6-fold cross validation, compared to those by the BET and BSE even using their best parameter combinations.

Voxel-based analysis of whole-brain effects of age and gender on dopamine transporter SPECT imaging in healthy subjects

International Nuclear Information System (INIS)

Eusebio, Alexandre; Azulay, Jean-Philippe; Ceccaldi, Mathieu; Girard, Nadine; Mundler, Olivier; Guedj, Eric

2012-01-01

Several studies have shown age- and gender-related differences in striatal dopamine transporter (DaT) binding. These studies were based on a striatal region on interest approach that may have underestimated these effects and could not evaluate extrastriatal regions. Our aim was to determine the effects at the voxel level of age and gender on whole-brain DaT distribution using [ 123 I]FP-CIT SPECT in healthy subjects. We performed a whole-brain [ 123 I]FP-CIT SPECT voxel-based analysis using SPM8 and a standardized normalization template (p < 0.05, corrected using the false discovery rate method) in 51 healthy subjects aged from 21 to 79 years. We found an age-related DaT binding decrease in the striatum, anterior cingulate/medial frontal cortices and insulo-opercular cortices. Also DaT binding ratios were higher in women than men in the striatum and opercular cortices. This study showed both striatal and extrastriatal age-related and gender-related differences in DaT binding in healthy subjects using a whole-brain voxel-based non-a priori approach. These differences highlight the need for careful age and gender matching in DaT analyses of neuropsychiatric disorders. (orig.)

Voxel-based analysis of whole-brain effects of age and gender on dopamine transporter SPECT imaging in healthy subjects

Energy Technology Data Exchange (ETDEWEB)

Eusebio, Alexandre; Azulay, Jean-Philippe [APHM, Hopital de la Timone, Service de Neurologie et Pathologie du Mouvement, Marseille (France); CNRS, Aix-Marseille Univ, Institut de Neurosciences de la Timone, Marseille (France); Ceccaldi, Mathieu [APHM, Hopital de la Timone, Service de Neurologie et de Neuropsychologie, Marseille (France); Aix-Marseille Univ, UMR Inserm 1106, Institut de Neurosciences des Systemes, Marseille (France); Girard, Nadine [APHM, Hopital de la Timone, Service de Neuroradiologie diagnostique et interventionnelle, Marseille (France); Mundler, Olivier [APHM, Hopital de la Timone, Service Central de Biophysique et Medecine Nucleaire, Marseille (France); Aix-Marseille Univ, CERIMED, Marseille (France); Guedj, Eric [CNRS, Aix-Marseille Univ, Institut de Neurosciences de la Timone, Marseille (France); APHM, Hopital de la Timone, Service Central de Biophysique et Medecine Nucleaire, Marseille (France); Aix-Marseille Univ, CERIMED, Marseille (France)

2012-11-15

Several studies have shown age- and gender-related differences in striatal dopamine transporter (DaT) binding. These studies were based on a striatal region on interest approach that may have underestimated these effects and could not evaluate extrastriatal regions. Our aim was to determine the effects at the voxel level of age and gender on whole-brain DaT distribution using [{sup 123}I]FP-CIT SPECT in healthy subjects. We performed a whole-brain [{sup 123}I]FP-CIT SPECT voxel-based analysis using SPM8 and a standardized normalization template (p < 0.05, corrected using the false discovery rate method) in 51 healthy subjects aged from 21 to 79 years. We found an age-related DaT binding decrease in the striatum, anterior cingulate/medial frontal cortices and insulo-opercular cortices. Also DaT binding ratios were higher in women than men in the striatum and opercular cortices. This study showed both striatal and extrastriatal age-related and gender-related differences in DaT binding in healthy subjects using a whole-brain voxel-based non-a priori approach. These differences highlight the need for careful age and gender matching in DaT analyses of neuropsychiatric disorders. (orig.)

Novel modeling of task versus rest brain state predictability using a dynamic time warping spectrum: comparisons and contrasts with other standard measures of brain dynamics

Directory of Open Access Journals (Sweden)

Martin eDinov

2016-05-01

Full Text Available Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches and the sum squared error (SSE from a multilayer perceptron (MLP prediction of the EEG timeseries, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach.

Quality assessment of brain images by Hoffman phantom

International Nuclear Information System (INIS)

Karimian, A.R.; Saddad, F.; Mosalla, B.; Moradkhani, S.; Degbankhan, R.; Pouladi, M.

2002-01-01

The purpose of this investigation is using Hoffman brain phantom for quality assessment of brian images in SPECT system. There are the following standards for quality control in nuclear medicine: American Association of Physicists in Medicine, National Electrical Manufacturers Association, International Electromechanical Commission, International Atomic Energy Agency. Each of the above standards has the following important orders: Physical inspection, Acceptance and Reference Testing, Periodic Q C tests (Daily, Weekly, Monthly, Quarterly, Annually). The above tests are simple physics measures. To more meaningful ones based on performance of some tasks related to clinical application it is better to use from organs' phantoms, such as: brain, cardiac, etc. In this research we made a comparison between normal and abnormal states of Hoffman brain phantom. Methods of Hoffman brain phantom was filled with a solution of Tc- 99 m (5 mCi) and water (1300 cc). this results: The investigation of small abnormalities strongly related to the operating conditions and deviation from best tuning state of the system

Autonomy and Accountability in Standards-Based Reform

Directory of Open Access Journals (Sweden)

Susan Watson

2001-08-01

Full Text Available In this article we discuss the effects of one urban school district's efforts to increase the autonomy and accountability of schools and teams of teachers through a standards-based reform known as team- based schooling. Team-based schooling is designed to devolve decision-making authority down to the school level by increasing teachers' autonomy to make decisions. Increased accountability is enacted in the form of a state-level standards-based initiative. Based on our evaluation over a two-year period involving extensive fieldwork and quantitative analysis, we describe the ways that teachers, teams and school administrators responded to the implementation of team-based schooling. What are the effects of increasing school-level autonomy and accountability in the context of standards- based reform? Our analysis highlights several issues: the "lived reality" of teaming as it interacts with the existing culture within schools, the ways that teachers respond to the pressures created by increased internal and external accountability, and the effects of resource constraints on the effectiveness of implementation. We conclude by using our findings to consider more broadly the trade-off between increased autonomy and accountability on which standards-based reforms like team-based schooling are based.

Telemetry Standards, IRIG Standard 106-17, Chapter 22, Network Based Protocol Suite

Science.gov (United States)

2017-07-01

requirements. 22.2 Network Access Layer 22.2.1 Physical Layer Connectors and cable media should meet the electrical or optical properties required by the...Telemetry Standards, IRIG Standard 106-17 Chapter 22, July 2017 i CHAPTER 22 Network -Based Protocol Suite Acronyms...iii Chapter 22. Network -Based Protocol Suite

Gadolinium-based Contrast Agent Accumulates in the Brain Even in Subjects without Severe Renal Dysfunction: Evaluation of Autopsy Brain Specimens with Inductively Coupled Plasma Mass Spectroscopy.

Science.gov (United States)

Kanda, Tomonori; Fukusato, Toshio; Matsuda, Megumi; Toyoda, Keiko; Oba, Hiroshi; Kotoku, Jun'ichi; Haruyama, Takahiro; Kitajima, Kazuhiro; Furui, Shigeru

2015-07-01

To use inductively coupled plasma mass spectroscopy (ICP-MS) to evaluate gadolinium accumulation in brain tissues, including the dentate nucleus (DN) and globus pallidus (GP), in subjects who received a gadolinium-based contrast agent (GBCA). Institutional review board approval was obtained for this study. Written informed consent for postmortem investigation was obtained either from the subject prior to his or her death or afterward from the subject's relatives. Brain tissues obtained at autopsy in five subjects who received a linear GBCA (GBCA group) and five subjects with no history of GBCA administration (non-GBCA group) were examined with ICP-MS. Formalin-fixed DN tissue, the inner segment of the GP, cerebellar white matter, the frontal lobe cortex, and frontal lobe white matter were obtained, and their gadolinium concentrations were measured. None of the subjects had received a diagnosis of severely compromised renal function (estimated glomerular filtration rate brain regions. Gadolinium was detected in all specimens in the GBCA agent group (mean, 0.25 µg per gram of brain tissue ± 0.44 [standard deviation]), with significantly higher concentrations in each region (P = .004 vs the non-GBCA group for all regions). In the GBCA group, the DN and GP showed significantly higher gadolinium concentrations (mean, 0.44 µg/g ± 0.63) than other regions (0.12 µg/g ± 0.16) (P = .029). Even in subjects without severe renal dysfunction, GBCA administration causes gadolinium accumulation in the brain, especially in the DN and GP.

Computer- and Suggestion-based Cognitive Rehabilitation following Acquired Brain Injury

DEFF Research Database (Denmark)

Lindeløv, Jonas Kristoffer

. That is, training does not cause cognitive transfer and thus does not constitute “brain training” or “brain exercise” of any clinical relevance. A larger study found more promising results for a suggestion-based treatment in a hypnotic procedure. Patients improved to above population average in a matter...... of 4-8 hours, making this by far the most effective treatment compared to computer-based training, physical exercise, phamaceuticals, meditation, and attention process training. The contrast between computer-based methods and the hypnotic suggestion treatment may be reflect a more general discrepancy...

Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning.

Science.gov (United States)

Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-01-01

This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the diseased region in brain MR images. Two-dimensional stationary wavelet transform is harnessed to extract features from the preprocessed images. The feature vector is constructed using the energy and entropy values, computed from the level- 2 SWT coefficients. Then, the relevant and uncorrelated features are selected using symmetric uncertainty ranking filter. Subsequently, the selected features are given input to the proposed AdaBoost with support vector machine classifier, where SVM is used as the base classifier of AdaBoost algorithm. To validate the proposed system, three standard MR image datasets, Dataset-66, Dataset-160, and Dataset- 255 have been utilized. The 5 runs of k-fold stratified cross validation results indicate the suggested scheme offers better performance than other existing schemes in terms of accuracy and number of features. The proposed system earns ideal classification over Dataset-66 and Dataset-160; whereas, for Dataset- 255, an accuracy of 99.45% is achieved. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Electroencephalography(EEG)-based instinctive brain-control of a quadruped locomotion robot.

Science.gov (United States)

Jia, Wenchuan; Huang, Dandan; Luo, Xin; Pu, Huayan; Chen, Xuedong; Bai, Ou

2012-01-01

Artificial intelligence and bionic control have been applied in electroencephalography (EEG)-based robot system, to execute complex brain-control task. Nevertheless, due to technical limitations of the EEG decoding, the brain-computer interface (BCI) protocol is often complex, and the mapping between the EEG signal and the practical instructions lack of logic associated, which restrict the user's actual use. This paper presents a strategy that can be used to control a quadruped locomotion robot by user's instinctive action, based on five kinds of movement related neurophysiological signal. In actual use, the user drives or imagines the limbs/wrists action to generate EEG signal to adjust the real movement of the robot according to his/her own motor reflex of the robot locomotion. This method is easy for real use, as the user generates the brain-control signal through the instinctive reaction. By adopting the behavioral control of learning and evolution based on the proposed strategy, complex movement task may be realized by instinctive brain-control.

Predicting standard-dose PET image from low-dose PET and multimodal MR images using mapping-based sparse representation

International Nuclear Information System (INIS)

Wang, Yan; Zhou, Jiliu; Zhang, Pei; An, Le; Ma, Guangkai; Kang, Jiayin; Shi, Feng; Shen, Dinggang; Wu, Xi; Lalush, David S; Lin, Weili

2016-01-01

Positron emission tomography (PET) has been widely used in clinical diagnosis for diseases and disorders. To obtain high-quality PET images requires a standard-dose radionuclide (tracer) injection into the human body, which inevitably increases risk of radiation exposure. One possible solution to this problem is to predict the standard-dose PET image from its low-dose counterpart and its corresponding multimodal magnetic resonance (MR) images. Inspired by the success of patch-based sparse representation (SR) in super-resolution image reconstruction, we propose a mapping-based SR (m-SR) framework for standard-dose PET image prediction. Compared with the conventional patch-based SR, our method uses a mapping strategy to ensure that the sparse coefficients, estimated from the multimodal MR images and low-dose PET image, can be applied directly to the prediction of standard-dose PET image. As the mapping between multimodal MR images (or low-dose PET image) and standard-dose PET images can be particularly complex, one step of mapping is often insufficient. To this end, an incremental refinement framework is therefore proposed. Specifically, the predicted standard-dose PET image is further mapped to the target standard-dose PET image, and then the SR is performed again to predict a new standard-dose PET image. This procedure can be repeated for prediction refinement of the iterations. Also, a patch selection based dictionary construction method is further used to speed up the prediction process. The proposed method is validated on a human brain dataset. The experimental results show that our method can outperform benchmark methods in both qualitative and quantitative measures. (paper)

Autopsy consent, brain collection, and standardized neuropathologic assessment of ADNI participants: the essential role of the neuropathology core.

Science.gov (United States)

Cairns, Nigel J; Taylor-Reinwald, Lisa; Morris, John C

2010-05-01

Our objectives are to facilitate autopsy consent, brain collection, and perform standardized neuropathologic assessments of all Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who come to autopsy at the 58 ADNI sites in the USA and Canada. Building on the expertise and resources of the existing Alzheimer's Disease Research Center (ADRC) at Washington University School of Medicine, St. Louis, MO, a Neuropathology Core (NPC) to serve ADNI was established with one new highly motivated research coordinator. The ADNI-NPC coordinator provides training materials and protocols to assist clinicians at ADNI sites in obtaining voluntary consent for brain autopsy in ADNI participants. Secondly, the ADNI-NPC maintains a central laboratory to provide uniform neuropathologic assessments using the operational criteria for the classification of AD and other pathologies defined by the National Alzheimer Coordinating Center (NACC). Thirdly, the ADNI-NPC maintains a state-of-the-art brain bank of ADNI-derived brain tissue to promote biomarker and multi-disciplinary clinicopathologic studies. During the initial year of funding of the ADNI Neuropathology Core, there was notable improvement in the autopsy rate to 44.4%. In the most recent year of funding (September 1(st), 2008 to August 31(st) 2009), our autopsy rate improved to 71.5%. Although the overall numbers to date are small, these data demonstrate that the Neuropathology Core has established the administrative organization with the participating sites to harvest brains from ADNI participants who come to autopsy. Within two years of operation, the Neuropathology Core has: (1) implemented a protocol to solicit permission for brain autopsy in ADNI participants at all 58 sites who die and (2) to send appropriate brain tissue from the decedents to the Neuropathology Core for a standardized, uniform, and state-of-the-art neuropathologic assessment. The benefit to ADNI of the implementation of the NPC is very clear

Evaluating anorexia-related brain atrophy using MP2RAGE-based morphometry

International Nuclear Information System (INIS)

Boto, Jose; Loevblad, Karl-Olof; Vargas, Maria Isabel; Gkinis, Georgios; Ortiz, Nadia; Roche, Alexis; Kober, Tobias; Marechal, Benedicte; University Hospital; Ecole Polytechnique Federale de Lausanne; Lazeyras, Francois

2017-01-01

To evaluate brain atrophy in anorexic patients by automated cerebral segmentation with the magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) MRI sequence. Twenty patients (female; mean age, 27.9 years), presenting consecutively for brain MRI between August 2014-December 2016 with clinical suspicion of anorexia nervosa and BMI<18.5 kg/m 2 were included. Controls were ten healthy females (mean age, 26.5 years). Automated brain morphometry was performed based on MP2RAGE. Means of morphometric results in the two groups were compared and correlation with BMI was analysed. Significantly lower volumes of total brain, grey matter (GM), white matter (WM), cerebellum and insula were found in anorexic patients. Anorexics had higher volumes of CSF, ventricles, lateral ventricles and third ventricle. When adjusted means for weight and height were compared, the volume of WM and cerebellum were not significantly different. However, volume of WM was significantly affected by weight and positively correlated with BMI. Significant positive correlations were found between BMI and volumes of total brain, GM, cortical GM and WM. BMI was negatively correlated with volumes of CSF and third ventricle. Brain atrophy was demonstrated in anorexic patients with MP2RAGE-based automated segmentation, which seems to reliably estimate brain volume. (orig.)

Evaluating anorexia-related brain atrophy using MP2RAGE-based morphometry

Energy Technology Data Exchange (ETDEWEB)

Boto, Jose; Loevblad, Karl-Olof; Vargas, Maria Isabel [Geneva University Hospital (Switzerland). Div. of Neuroradiology and Faculty of Medicine of Geneva; Gkinis, Georgios; Ortiz, Nadia [Geneva University Hospital (Switzerland). Dept. of Mental Health and Psychiatry; Roche, Alexis; Kober, Tobias; Marechal, Benedicte [Siemens Healthcare HC CEMEA SUI DI BM PI, Lausanne (Switzerland). Siemens ACIT, Advanced Clinical Imaging Technology; University Hospital (CHUV), Lausanne (Switzerland). Dept. of Radiology; Ecole Polytechnique Federale de Lausanne (Switzerland). LTS5; Lazeyras, Francois [Geneva University Hospital (Switzerland). Div. of Radiology and Faculty of Medicine of Geneva

2017-12-15

To evaluate brain atrophy in anorexic patients by automated cerebral segmentation with the magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) MRI sequence. Twenty patients (female; mean age, 27.9 years), presenting consecutively for brain MRI between August 2014-December 2016 with clinical suspicion of anorexia nervosa and BMI<18.5 kg/m{sup 2} were included. Controls were ten healthy females (mean age, 26.5 years). Automated brain morphometry was performed based on MP2RAGE. Means of morphometric results in the two groups were compared and correlation with BMI was analysed. Significantly lower volumes of total brain, grey matter (GM), white matter (WM), cerebellum and insula were found in anorexic patients. Anorexics had higher volumes of CSF, ventricles, lateral ventricles and third ventricle. When adjusted means for weight and height were compared, the volume of WM and cerebellum were not significantly different. However, volume of WM was significantly affected by weight and positively correlated with BMI. Significant positive correlations were found between BMI and volumes of total brain, GM, cortical GM and WM. BMI was negatively correlated with volumes of CSF and third ventricle. Brain atrophy was demonstrated in anorexic patients with MP2RAGE-based automated segmentation, which seems to reliably estimate brain volume. (orig.)

Technical bases for criticality safety standards

International Nuclear Information System (INIS)

Clayton, E.D.

1980-01-01

An American National Standard implies a consensus of those substantially concerned with its scope and provisions. The technical basis, or foundation, on which the consensus rests, must in turn, be firmly established and documented for public review. The technical bases are discussed and reviewed of several standards in different stages of completion and acceptance: ANSI/ANS-8.12, 1978, Nuclear Criticality Control and Safety of Homogeneous Plutonium - Uranium Mixtures Outside Reactors (Approved July 17, 1978); ANS-815, Nuclear Criticality Control of Special Actinide Elements (Draft No. 5 of newly proposed standard); ANS-8.14, Use of Solutions of Neutron Absorbers for Criticality Control (Draft No. 4 of newly proposed standard); ANS-8.5 (Revision of N16.4, 1971), Use of Borosilicate-Glass Raschig Rings as a Neutron Absorber in Solutions of Fissile Material (Draft No. 5 as a result of prescribed five-year review and update of old standard). In each of the preceding, the newly proposed (or revised) limits are based on the extension of experimental data via well established calculations, or by means of independent calculations with adequate margins for uncertainties. The four cases serve to illustrate the insight of the work group members in the establishment of the technical bases for the limits and the level of activity required on their part in the preparation of ANSI Standards. A time span of from four up to seven years has not been uncommon for the preparation, review, and acceptance of an ANSI Standard. 8 figures. 7 tables

Brain-Based Indices for User System Symbiosis

NARCIS (Netherlands)

Erp, J.B.F. van; Veltman, J.A.; Grootjen, M.

2010-01-01

The future generation user system interfaces need to be user-centric which goes beyond user-friendly and includes understanding and anticipating user intentions. We introduce the concept of operator models, their role in implementing user-system symbiosis, and the usefulness of brain-based indices

Biosocial Spaces and Neurocomputational Governance: Brain-Based and Brain-Targeted Technologies in Education

Science.gov (United States)

Williamson, Ben; Pykett, Jessica; Nemorin, Selena

2018-01-01

Recently, technologies based on neuroscientific insights into brain function and structure have been promoted for application in education. The novel practices and environments produced by these technologies require new forms of "biosocial" analysis to unpack their implications for education, learning and governance. This article…

Reconcilable Differences: Standards-based Teaching and Differentiation.

Science.gov (United States)

Tomlinson, Carol Ann

2000-01-01

There is no contradiction between effective standards-based instruction and differentiation. Curriculum tells teachers what to teach; differentiation tells how. Teachers can challenge all learners by providing standards-based materials and tasks calling for varied difficulty levels, scaffolding, instructional styles, and learning times. (MLH)

An algorithm based on OmniView technology to reconstruct sagittal and coronal planes of the fetal brain from volume datasets acquired by three-dimensional ultrasound.

Science.gov (United States)

Rizzo, G; Capponi, A; Pietrolucci, M E; Capece, A; Aiello, E; Mammarella, S; Arduini, D

2011-08-01

To describe a novel algorithm, based on the new display technology 'OmniView', developed to visualize diagnostic sagittal and coronal planes of the fetal brain from volumes obtained by three-dimensional (3D) ultrasonography. We developed an algorithm to image standard neurosonographic planes by drawing dissecting lines through the axial transventricular view of 3D volume datasets acquired transabdominally. The algorithm was tested on 106 normal fetuses at 18-24 weeks of gestation and the visualization rates of brain diagnostic planes were evaluated by two independent reviewers. The algorithm was also applied to nine cases with proven brain defects. The two reviewers, using the algorithm on normal fetuses, found satisfactory images with visualization rates ranging between 71.7% and 96.2% for sagittal planes and between 76.4% and 90.6% for coronal planes. The agreement rate between the two reviewers, as expressed by Cohen's kappa coefficient, was > 0.93 for sagittal planes and > 0.89 for coronal planes. All nine abnormal volumes were identified by a single observer from among a series including normal brains, and eight of these nine cases were diagnosed correctly. This novel algorithm can be used to visualize standard sagittal and coronal planes in the fetal brain. This approach may simplify the examination of the fetal brain and reduce dependency of success on operator skill. Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.

Parameters influencing SPET regional brain uptake of technetium-99m hexamethylpropylene amine oxime measured by calibrated point sources as an external standard

International Nuclear Information System (INIS)

Dierckx, R.A.; Dobbeleir, A.; Maes, M.; Pickut, B.A.; Vervaet, A.; Deyn, P.P. de

1994-01-01

Using calibrated point sources as an external standard to convert SPET brain counts into absolute values of regional brain uptake (rBU) of technetium-99m hexamethylpropylene amine oxime (HMPAO), the relative contribution of different parameters to interindividual variability of cerebellar rBU was examined in 33 healthy volunteers. Stepwise regression analysis identified body surface as the most important factor underlying interindividual variability, when compared with brain volume. In the normal volunteer population presented, age decrement of rBU corrected for body surface and brain volume equalled 60.5-0.20xage. Based on the data of eight normal volunteers, including four test-retest studies with heart rate (HR) differences greater than 5 units and four test-stress studies with doubling of heart rate after bicycle exercise, influence of heart rate may be expressed by the equation ΔrBU = 0.35 ΔHR. Clinically, estimation of the relative influence of different factors allows normalization and extension of the applicability of the rBU quantification method used from longitudinal studies to group comparisons. Interestingly, results of the Daily Stress Inventory Scale and a subjective rating scale suggest the absence of a significant influence of minor stress on rBU. When using one vial per patient, chromatography may be omitted in clinical routine practice and lipophilicity may be estimated as 90% of the injected dose, if administered within 10 min after preparation. Finally, sensitivity of the quantification method was tested in eight volunteers using acetazolamide brain activation and showed a mean increase in cerebellar rBU of 30.2%, varying between 14.1% and 75.9%. (orig./MG)

Toward a brain-based theory of beauty.

Science.gov (United States)

Ishizu, Tomohiro; Zeki, Semir

2011-01-01

We wanted to learn whether activity in the same area(s) of the brain correlate with the experience of beauty derived from different sources. 21 subjects took part in a brain-scanning experiment using functional magnetic resonance imaging. Prior to the experiment, they viewed pictures of paintings and listened to musical excerpts, both of which they rated on a scale of 1-9, with 9 being the most beautiful. This allowed us to select three sets of stimuli--beautiful, indifferent and ugly--which subjects viewed and heard in the scanner, and rated at the end of each presentation. The results of a conjunction analysis of brain activity showed that, of the several areas that were active with each type of stimulus, only one cortical area, located in the medial orbito-frontal cortex (mOFC), was active during the experience of musical and visual beauty, with the activity produced by the experience of beauty derived from either source overlapping almost completely within it. The strength of activation in this part of the mOFC was proportional to the strength of the declared intensity of the experience of beauty. We conclude that, as far as activity in the brain is concerned, there is a faculty of beauty that is not dependent on the modality through which it is conveyed but which can be activated by at least two sources--musical and visual--and probably by other sources as well. This has led us to formulate a brain-based theory of beauty.

Closed Loop Brain Model of Neocortical Information Based Exchange

Directory of Open Access Journals (Sweden)

James eKozloski

2016-01-01

Full Text Available Here we describe an information based exchange' model of brain function that ascribes to neocortex, basal ganglia, and thalamus distinct network functions. The model allows us to analyze whole brain system set point measures, such as the rate and heterogeneity of transitions in striatum and neocortex, in the context of neuromodulation and other perturbations. Our closed-loop model is grounded in neuroanatomical observations, proposing a novel Grand Loop through neocortex, and invokes different forms of plasticity at specific tissue interfaces and their principle cell synapses to achieve these transitions. By implementing a system for maximum information based exchange of action potentials between modeled neocortical areas, we observe changes to these measures in simulation. We hypothesize that similar dynamic set points and modulations exist in the brain's resting state activity, and that different modifications to information based exchange may shift the risk profile of different component tissues, resulting in different neurodegenerative diseases. This model is targeted for further development using IBM's Neural Tissue Simulator, which allows scalable elaboration of networks, tissues, and their neural and synaptic components towards ever greater complexity and biological realism.

Research on segmentation based on multi-atlas in brain MR image

Science.gov (United States)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Deep Learning and Texture-Based Semantic Label Fusion for Brain Tumor Segmentation.

Science.gov (United States)

Vidyaratne, L; Alam, M; Shboul, Z; Iftekharuddin, K M

2018-01-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Deep learning and texture-based semantic label fusion for brain tumor segmentation

Science.gov (United States)

Vidyaratne, L.; Alam, M.; Shboul, Z.; Iftekharuddin, K. M.

2018-02-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Evidence-based guideline update: determining brain death in adults: report of the Quality Standards Subcommittee of the American Academy of Neurology.

Science.gov (United States)

Wijdicks, Eelco F M; Varelas, Panayiotis N; Gronseth, Gary S; Greer, David M

2010-06-08

To provide an update of the 1995 American Academy of Neurology guideline with regard to the following questions: Are there patients who fulfill the clinical criteria of brain death who recover neurologic function? What is an adequate observation period to ensure that cessation of neurologic function is permanent? Are complex motor movements that falsely suggest retained brain function sometimes observed in brain death? What is the comparative safety of techniques for determining apnea? Are there new ancillary tests that accurately identify patients with brain death? A systematic literature search was conducted and included a review of MEDLINE and EMBASE from January 1996 to May 2009. Studies were limited to adults. In adults, there are no published reports of recovery of neurologic function after a diagnosis of brain death using the criteria reviewed in the 1995 American Academy of Neurology practice parameter. Complex-spontaneous motor movements and false-positive triggering of the ventilator may occur in patients who are brain dead. There is insufficient evidence to determine the minimally acceptable observation period to ensure that neurologic functions have ceased irreversibly. Apneic oxygenation diffusion to determine apnea is safe, but there is insufficient evidence to determine the comparative safety of techniques used for apnea testing. There is insufficient evidence to determine if newer ancillary tests accurately confirm the cessation of function of the entire brain.

Standardized computer-based organized reporting of EEG

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...

How to Train an Injured Brain? A Pilot Feasibility Study of Home-Based Computerized Cognitive Training.

Science.gov (United States)

Verhelst, Helena; Vander Linden, Catharine; Vingerhoets, Guy; Caeyenberghs, Karen

2017-02-01

Computerized cognitive training programs have previously shown to be effective in improving cognitive abilities in patients suffering from traumatic brain injury (TBI). These studies often focused on a single cognitive function or required expensive hardware, making it difficult to be used in a home-based environment. This pilot feasibility study aimed to evaluate the feasibility of a newly developed, home-based, computerized cognitive training program for adolescents who suffered from TBI. Additionally, feasibility of study design, procedures, and measurements were examined. Case series, longitudinal, pilot, feasibility intervention study with one baseline and two follow-up assessments. Nine feasibility outcome measures and criteria for success were defined, including accessibility, training motivation/user experience, technical smoothness, training compliance, participation willingness, participation rates, loss to follow-up, assessment timescale, and assessment procedures. Five adolescent patients (four boys, mean age = 16 years 7 months, standard deviation = 9 months) with moderate to severe TBI in the chronic stage were recruited and received 8 weeks of cognitive training with BrainGames. Effect sizes (Cohen's d) were calculated to determine possible training-related effects. The new cognitive training intervention, BrainGames, and study design and procedures proved to be feasible; all nine feasibility outcome criteria were met during this pilot feasibility study. Estimates of effect sizes showed small to very large effects on cognitive measures and questionnaires, which were retained after 6 months. Our pilot study shows that a longitudinal intervention study comprising our novel, computerized cognitive training program and two follow-up assessments is feasible in adolescents suffering from TBI in the chronic stage. Future studies with larger sample sizes will evaluate training-related effects on cognitive functions and underlying brain structures.

High-fat diet based on dried bovine brain: an effective animal model of dyslipidemia and insulin resistance.

Science.gov (United States)

Araújo, Tiago Gomes; Leite, Ana Catarina Rezende; Martins da Fonseca, Caíque Silveira; Carvalho, Bruno Melo; Schuler, Alexandre Ricardo Pereira; Lima, Vera Lúcia de Menezes

2011-09-01

Currently, there are no reports in the literature demonstrating any animal model that ingests one of the fattiest animal food source, the bovine brain. We hypothesized that a high-fat diet (HFD), based on dried bovine brain, could be used to develop an animal model possessing a spectrum of insulin resistance-related features. The HFD was formulated with 40% dried bovine brain plus 16.4% butter fat, prepared in-house. Furthermore, the diet contained 52% calories as fat and 73% of total fatty acids were saturated. Swiss mice weighing about 40 g were assigned to two dietary groups (n=6/group), one group received a standard chow diet and the other was given HFD for 3 months. The body weight and biochemical parameters of the animals were measured initially and at monthly intervals until the end of the experiment. Animals fed on a HFD showed a significant increase in the body and adipose tissue weight, serum total cholesterol and triglyceride levels, when compared with mice fed on the control diet. Additionally, the HFD group showed higher circulating levels of liver transaminases, such as alanine aminotransferase and aspartate aminotransferase, compared with the control group. Finally, to illustrate the usefulness of this model, we report that the HFD induced mild hyperglycemia, fasting hyperinsulinemia, and increased the homeostasis model of assessment (HOMA-IR), in comparison with the control group. In conclusion, our results show that HFD, based on dried bovine brain, causes insulin resistance-related metabolic disturbances. Thus, this may be a suitable model to study disturbances in energy metabolism and their consequences.

Transcranial brain stimulation: closing the loop between brain and stimulation

DEFF Research Database (Denmark)

Karabanov, Anke; Thielscher, Axel; Siebner, Hartwig Roman

2016-01-01

-related and state-related variability. Fluctuations in brain-states can be traced online with functional brain imaging and inform the timing or other settings of transcranial brain stimulation. State-informed open-loop stimulation is aligned to the expression of a predefined brain state, according to prespecified......PURPOSE OF REVIEW: To discuss recent strategies for boosting the efficacy of noninvasive transcranial brain stimulation to improve human brain function. RECENT FINDINGS: Recent research exposed substantial intra- and inter-individual variability in response to plasticity-inducing transcranial brain...... stimulation. Trait-related and state-related determinants contribute to this variability, challenging the standard approach to apply stimulation in a rigid, one-size-fits-all fashion. Several strategies have been identified to reduce variability and maximize the plasticity-inducing effects of noninvasive...

A subject-independent pattern-based Brain-Computer Interface

Directory of Open Access Journals (Sweden)

Andreas Markus Ray

2015-10-01

Full Text Available While earlier Brain-Computer Interface (BCI studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e. happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to match their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders.

MRI-based radiologic scoring system for extent of brain injury in children with hemiplegia.

Science.gov (United States)

Shiran, S I; Weinstein, M; Sirota-Cohen, C; Myers, V; Ben Bashat, D; Fattal-Valevski, A; Green, D; Schertz, M

2014-12-01

Brain MR imaging is recommended in children with cerebral palsy. Descriptions of MR imaging findings lack uniformity, due to the absence of a validated quantitative approach. We developed a quantitative scoring method for brain injury based on anatomic MR imaging and examined the reliability and validity in correlation to motor function in children with hemiplegia. Twenty-seven children with hemiplegia underwent MR imaging (T1, T2-weighted sequences, DTI) and motor assessment (Manual Ability Classification System, Gross Motor Functional Classification System, Assisting Hand Assessment, Jebsen Taylor Test of Hand Function, and Children's Hand Experience Questionnaire). A scoring system devised in our center was applied to all scans. Radiologic score covered 4 domains: number of affected lobes, volume and type of white matter injury, extent of gray matter damage, and major white matter tract injury. Inter- and intrarater reliability was evaluated and the relationship between radiologic score and motor assessments determined. Mean total radiologic score was 11.3 ± 4.5 (range 4-18). Good inter- (ρ = 0.909, P classification systems (ρ = 0.708, P high inter- and intrarater reliability and significant associations with manual ability classification systems and motor evaluations. This score provides a standardized radiologic assessment of brain injury extent in hemiplegic patients with predominantly unilateral injury, allowing comparison between groups, and providing an additional tool for counseling families. © 2014 by American Journal of Neuroradiology.

The Global Aspects of Brain-Based Learning

Science.gov (United States)

Connell, J. Diane

2009-01-01

Brain-Based Learning (BBL) can be viewed as techniques gleaned from research in neurology and cognitive science used to enhance teacher instruction. These strategies can also be used to enhance students' ability to learn using ways in which they feel most comfortable, neurologically speaking. Jensen (1995/2000) defines BBL as "learning in…

A new microcontroller-based human brain hypothermia system.

Science.gov (United States)

Kapidere, Metin; Ahiska, Raşit; Güler, Inan

2005-10-01

Many studies show that artificial hypothermia of brain in conditions of anesthesia with the rectal temperature lowered down to 33 degrees C produces pronounced prophylactic effect protecting the brain from anoxia. Out of the methods employed now in clinical practice for reducing the oxygen consumption by the cerebral tissue, the most efficacious is craniocerebral hypothermia (CCH). It is finding even more extensive application in cardiovascular surgery, neurosurgery, neurorenimatology and many other fields of medical practice. In this study, a microcontroller-based designed human brain hypothermia system (HBHS) is designed and constructed. The system is intended for cooling and heating the brain. HBHS consists of a thermoelectric hypothermic helmet, a control and a power unit. Helmet temperature is controlled by 8-bit PIC16F877 microcontroller which is programmed using MPLAB editor. Temperature is converted to 10-bit digital and is controlled automatically by the preset values which have been already entered in the microcontroller. Calibration is controlled and the working range is tested. Temperature of helmet is controlled between -5 and +46 degrees C by microcontroller, with the accuracy of +/-0.5 degrees C.

EEG Based Inference of Spatio-Temporal Brain Dynamics

DEFF Research Database (Denmark)

Hansen, Sofie Therese

Electroencephalography (EEG) provides a measure of brain activity and has improved our understanding of the brain immensely. However, there is still much to be learned and the full potential of EEG is yet to be realized. In this thesis we suggest to improve the information gain of EEG using three...... different approaches; 1) by recovery of the EEG sources, 2) by representing and inferring the propagation path of EEG sources, and 3) by combining EEG with functional magnetic resonance imaging (fMRI). The common goal of the methods, and thus of this thesis, is to improve the spatial dimension of EEG...... recovery ability. The forward problem describes the propagation of neuronal activity in the brain to the EEG electrodes on the scalp. The geometry and conductivity of the head layers are normally required to model this path. We propose a framework for inferring forward models which is based on the EEG...

Tensor-based morphometry of fibrous structures with application to human brain white matter.

Science.gov (United States)

Zhang, Hui; Yushkevich, Paul A; Rueckert, Daniel; Gee, James C

2009-01-01

Tensor-based morphometry (TBM) is a powerful approach for examining shape changes in anatomy both across populations and in time. Our work extends the standard TBM for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. It leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. In this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. Our results show that additional insights can be gained with the proposed analysis.

Stealth lipid polymer hybrid nanoparticles loaded with rutin for effective brain delivery - comparative study with the gold standard (Tween 80): optimization, characterization and biodistribution.

Science.gov (United States)

Ishak, Rania A H; Mostafa, Nada M; Kamel, Amany O

2017-11-01

The blood-brain barrier is considered the leading physiological obstacle hindering the transport of neurotherapeutics to brain cells. The application of nanotechnology coupled with surfactant coating is one of the efficacious tactics overcoming this barrier. The aim of this study was to develop lipid polymer hybrid nanoparticles (LPHNPs), composed of a polymeric core and a phospholipid shell entangled, for the first time, with PEG-based surfactants (SAA) viz. TPGS or Solutol HS 15 in comparison with the gold standard Tween 80, aiming to enhance brain delivery and escape opsonization. LPHNPs were successfully prepared using modified single-step nanoprecipitation technique, loaded with the flavonoid rutin (RU), extracted from the flowers of Calendula officinalis L., and recently proved as a promising anti-Alzheimer. The effect of the critical process parameters (CPP) viz. PLGA amount, W lecithin /W PLGA ratio, and Tween 80 concentration on critical quality attributes (CQA); entrapment, size and size distribution, was statistically analyzed via design of experiments, and optimized using the desirability function. The optimized CPP were maintained while substituting Tween 80 with other PEG-SAA. All hybrid particles exhibited spherical shape with perceptible lipid shells. The biocompatibility of the prepared NPs was confirmed by hemolysis test. The pharmacokinetic assessments, post-intravenous administration to rats, revealed a significant higher RU bioavailability for NPs relative to drug solution. Biodistribution studies proved non-significant differences in RU accumulation within brain, but altered phagocytic uptake among various LPHNPs. The present study endorses the successful development of LPHNPs using PEG-SAA, and confirms the prospective applicability of TPGS and Solutol in enhancing brain delivery.

77 FR 39385 - Receipts-Based, Small Business Size Standard

Science.gov (United States)

2012-07-03

.... The NRC is increasing its receipts-based, small business size standard from $6.5 million to $7 million...-based, small business size standard increasing from $6.5 million to $7.0 million. This adjustment is to... regulatory programs. The NRC is increasing its receipts-based, small business size standard from $6.5 million...

Brain size and urbanization in birds

Institute of Scientific and Technical Information of China (English)

Anders; Pape; M?ller; Johannes; Erritz?e

2015-01-01

Background: Brain size may affect the probability of invasion of urban habitats if a relatively larger brain entails superior ability to adapt to novel environments. However, once urbanized urban environments may provide poor quality food that has negative consequences for normal brain development resulting in an excess of individuals with small brains.Methods: Here we analyze the independent effects of mean, standard deviation and skewness in brain mass for invasion of urban habitats by 108 species of birds using phylogenetic multiple regression analyses weighted by sample size.Results: There was no significant difference in mean brain mass between urbanized and non-urbanized species or between urban and rural populations of the same species, and mean brain mass was not significantly correlated with time since urbanization. Bird species that became urbanized had a greater standard deviation in brain mass than non-urbanized species, and the standard deviation in brain mass increased with time since urbanization. Brain mass was significantly left skewed in species that remained rural, while there was no significant skew in urbanized species. The degree of left skew was greater in urban than in rural populations of the same species, and successfully urbanized species decreased the degree of left skew with time since urbanization. This is consistent with the hypothesis that sub-optimal brain development was more common in rural habitats resulting in disproportionately many individuals with very smal brains.Conclusions: These findings do not support the hypothesis that large brains promote urbanization, but suggest that skewness has played a role in the initial invasion of urban habitats, and that variance and skew in brain mass have increased as species have become urbanized.

Brain size and urbanization in birds

Institute of Scientific and Technical Information of China (English)

Anders Pape Mller; Johannes Erritze

2015-01-01

Background:Brain size may affect the probability of invasion of urban habitats if a relatively larger brain entails superior ability to adapt to novel environments. However, once urbanized urban environments may provide poor quality food that has negative consequences for normal brain development resulting in an excess of individuals with small brains. Methods:Here we analyze the independent effects of mean, standard deviation and skewness in brain mass for invasion of urban habitats by 108 species of birds using phylogenetic multiple regression analyses weighted by sample size. Results:There was no significant difference in mean brain mass between urbanized and non-urbanized species or between urban and rural populations of the same species, and mean brain mass was not significantly correlated with time since urbanization. Bird species that became urbanized had a greater standard deviation in brain mass than non-urbanized species, and the standard deviation in brain mass increased with time since urbanization. Brain mass was significantly left skewed in species that remained rural, while there was no significant skew in urbanized species. The degree of left skew was greater in urban than in rural populations of the same species, and successfully urbanized species decreased the degree of left skew with time since urbanization. This is consistent with the hypothesis that sub-optimal brain development was more common in rural habitats resulting in disproportionately many individuals with very smal brains. Conclusions:These findings do not support the hypothesis that large brains promote urbanization, but suggest that skewness has played a role in the initial invasion of urban habitats, and that variance and skew in brain mass have increased as species have become urbanized.

Toward a standardized structural-functional group connectome in MNI space.

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Horn, Andreas; Blankenburg, Felix

2016-01-01

The analysis of the structural architecture of the human brain in terms of connectivity between its subregions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute-Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. In a second analysis, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to others' findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) performing fiber tracking directly within MNI space. Such an approach may be used for various purposes like the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step toward a standard DTI template of the human brain

A Symbiotic Brain-Machine Interface through Value-Based Decision Making

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Mahmoudi, Babak; Sanchez, Justin C.

2011-01-01

Background In the development of Brain Machine Interfaces (BMIs), there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC). Methodology The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc) contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1) and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. Conclusions Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and reward

A symbiotic brain-machine interface through value-based decision making.

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Babak Mahmoudi

Full Text Available BACKGROUND: In the development of Brain Machine Interfaces (BMIs, there is a great need to enable users to interact with changing environments during the activities of daily life. It is expected that the number and scope of the learning tasks encountered during interaction with the environment as well as the pattern of brain activity will vary over time. These conditions, in addition to neural reorganization, pose a challenge to decoding neural commands for BMIs. We have developed a new BMI framework in which a computational agent symbiotically decoded users' intended actions by utilizing both motor commands and goal information directly from the brain through a continuous Perception-Action-Reward Cycle (PARC. METHODOLOGY: The control architecture designed was based on Actor-Critic learning, which is a PARC-based reinforcement learning method. Our neurophysiology studies in rat models suggested that Nucleus Accumbens (NAcc contained a rich representation of goal information in terms of predicting the probability of earning reward and it could be translated into an evaluative feedback for adaptation of the decoder with high precision. Simulated neural control experiments showed that the system was able to maintain high performance in decoding neural motor commands during novel tasks or in the presence of reorganization in the neural input. We then implanted a dual micro-wire array in the primary motor cortex (M1 and the NAcc of rat brain and implemented a full closed-loop system in which robot actions were decoded from the single unit activity in M1 based on an evaluative feedback that was estimated from NAcc. CONCLUSIONS: Our results suggest that adapting the BMI decoder with an evaluative feedback that is directly extracted from the brain is a possible solution to the problem of operating BMIs in changing environments with dynamic neural signals. During closed-loop control, the agent was able to solve a reaching task by capturing the action and

20 Ways To Promote Brain-Based Teaching and Learning.

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Prigge, Debra J.

2002-01-01

Based on current knowledge about cognitive processes, this article presents strategies for preparing the learner, managing the environment to motivate students, gaining and keeping learner attention, and increasing memory and recall by making learning personally relevant to students. Resources are listed for brain-based teaching and learning. (CR)

A biometric analysis of brain size in micrencephalics.

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Hofman, M A

1984-01-01

Brain weight and head circumference in micrencephalic patients were analysed as a function of age, height and sex in relation to normal human standards. A quantitative definition of micrencephaly is proposed, which is based on these analyses. Evidence is presented, furthermore, that micrencephalics have a significantly lower brain weight in adolescence than in early childhood, and that this cerebral dystrophy continues throughout adulthood, leading to death in more than 85% of the males and 78% of the females before they reach the age of 30 years. Since this decline in brain weight after approximately 3-5 years of age is not accompanied by a similar reduction in head circumference, the brains of elderly micrencephalic patients no longer occupy the entire cranial cavity. It is evident, therefore, that head circumference in the case of micrencephaly is an unsuitable parameter for estimating brain size.

FCM Clustering Algorithms for Segmentation of Brain MR Images

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Yogita K. Dubey

2016-01-01

Full Text Available The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF, Gray Matter (GM, and White Matter (WM, has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed.

Revisiting Einstein's brain in Brain Awareness Week.

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Chen, Hao; Chen, Su; Zeng, Lidan; Zhou, Lin; Hou, Shengtao

2014-10-01

Albert Einstein's brain has long been an object of fascination to both neuroscience specialists and the general public. However, without records of advanced neuro-imaging of his brain, conclusions regarding Einstein's extraordinary cognitive capabilities can only be drawn based on the unique external features of his brain and through comparison of the external features with those of other human brain samples. The recent discovery of 14 previously unpublished photographs of Einstein's brain taken at unconventional angles by Dr. Thomas Stoltz Harvey, the pathologist, ignited a renewed frenzy about clues to explain Einstein's genius. Dr. Dean Falk and her colleagues, in their landmark paper published in Brain (2013; 136:1304-1327), described in such details about the unusual features of Einstein's brain, which shed new light on Einstein's intelligence. In this article, we ask what are the unique structures of his brain? What can we learn from this new information? Can we really explain his extraordinary cognitive capabilities based on these unique brain structures? We conclude that studying the brain of a remarkable person like Albert Einstein indeed provides us a better example to comprehensively appreciate the relationship between brain structures and advanced cognitive functions. However, caution must be exercised so as not to over-interpret his intelligence solely based on the understanding of the surface structures of his brain.

Control of a nursing bed based on a hybrid brain-computer interface.

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Nengneng Peng; Rui Zhang; Haihua Zeng; Fei Wang; Kai Li; Yuanqing Li; Xiaobin Zhuang

2016-08-01

In this paper, we propose an intelligent nursing bed system which is controlled by a hybrid brain-computer interface (BCI) involving steady-state visual evoked potential (SSVEP) and P300. Specifically, the hybrid BCI includes an asynchronous brain switch based on SSVEP and P300, and a P300-based BCI. The brain switch is used to turn on/off the control system of the electric nursing bed through idle/control state detection, whereas the P300-based BCI is for operating the nursing bed. At the beginning, the user may focus on one group of flashing buttons in the graphic user interface (GUI) of the brain switch, which can simultaneously evoke SSVEP and P300, to switch on the control system. Here, the combination of SSVEP and P300 is used for improving the performance of the brain switch. Next, the user can control the nursing bed using the P300-based BCI. The GUI of the P300-based BCI includes 10 flashing buttons, which correspond to 10 functional operations, namely, left-side up, left-side down, back up, back down, bedpan open, bedpan close, legs up, legs down, right-side up, and right-side down. For instance, he/she can focus on the flashing button "back up" in the GUI of the P300-based BCI to activate the corresponding control such that the nursing bed is adjusted up. Eight healthy subjects participated in our experiment, and obtained an average accuracy of 93.75% and an average false positive rate (FPR) of 0.15 event/min. The effectiveness of our system was thus demonstrated.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

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Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Anisotropic Diffusion based Brain MRI Segmentation and 3D Reconstruction

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M. Arfan Jaffar

2012-06-01

Full Text Available In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive 3D visualization of the brain to the radiologist. Detection and 3D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed system detects and presents a 3D visualization model of the brain and tumor inside which greatly helps the radiologist to effectively diagnose and analyze the brain tumor. We proposed a multi-phase segmentation and visualization technique which overcomes the many problems of 3D volume segmentation methods like lake of fine details. In this system segmentation is done in three different phases which reduces the error chances. The system finds contours for skull, brain and tumor. These contours are stacked over and two novel methods are used to find the 3D visualization models. The results of these techniques, particularly of interpolation based, are impressive. Proposed system is tested against publically available data set [41] and MRI datasets available from MRI aamp; CT center Rawalpindi, Pakistan [42].

Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

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Chen, Yu-Jen; Liu, Chih-Min; Hsu, Yung-Chin; Lo, Yu-Chun; Hwang, Tzung-Jeng; Hwu, Hai-Gwo; Lin, Yi-Tin; Tseng, Wen-Yih Isaac

2018-01-01

A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity. The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis. The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients. The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Understanding the Role of Neuroscience in Brain Based Products: A Guide for Educators and Consumers

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Sylvan, Lesley J.; Christodoulou, Joanna A.

2010-01-01

The term "brain" based is often used to describe learning theories, principles, and products. Although there have been calls urging educators to be cautious in interpreting and using such material, consumers may find it challenging to understand the role of the brain and to discriminate among brain based products to determine which would be…

David Ferrier: brain drawings and brain maps.

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Lazar, J Wayne

2013-01-01

This chapter has two emphases, one is about the men who influenced the visual representations that David Ferrier (1843-1928) used to illustrate his work on localization of brain functions during the years 1873-1875, namely, Alexander Ecker, John C. Galton, and Ernest Waterlow, and the other is about the nature of medical representations and of Ferrier's illustrations in particular. Medical illustrations are characterized either as pictures, line drawings, or brain maps. Ferrier's illustrations will be shown to be increasingly sophisticated brain maps that contrast with early nineteenth-century standards of medical illustrations, as exemplified by John Bell (1763-1829). © 2013 Elsevier B.V. All rights reserved.

A novel algorithm for segmentation of brain MR images

International Nuclear Information System (INIS)

Sial, M.Y.; Yu, L.; Chowdhry, B.S.; Rajput, A.Q.K.; Bhatti, M.I.

2006-01-01

Accurate and fully automatic segmentation of brain from magnetic resonance (MR) scans is a challenging problem that has received an enormous amount of . attention lately. Many researchers have applied various techniques however a standard fuzzy c-means algorithm has produced better results compared to other methods. In this paper, we present a modified fuzzy c-means (FCM) based algorithm for segmentation of brain MR images. Our algorithm is formulated by modifying the objective function of the standard FCM and uses a special spread method to get a smooth and slow varying bias field This method has the advantage that it can be applied at an early stage in an automated data analysis before a tissue model is available. The results on MRI images show that this method provides better results compared to standard FCM algorithms. (author)

Support vector machine-based classification of Alzheimer's disease from whole-brain anatomical MRI

International Nuclear Information System (INIS)

Magnin, Benoit; Mesrob, Lilia; Kinkingnehun, Serge; Pelegrini-Issac, Melanie; Colliot, Olivier; Sarazin, Marie; Dubois, Bruno; Lehericy, Stephane; Benali, Habib

2009-01-01

We present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients with Alzheimer's disease (AD) and elderly control subjects. We studied 16 patients with AD [mean age ± standard deviation (SD)=74.1 ±5.2 years, mini-mental score examination (MMSE) = 23.1 ± 2.9] and 22 elderly controls (72.3±5.0 years, MMSE=28.5± 1.3). Three-dimensional T1-weighted MR images of each subject were automatically parcellated into regions of interest (ROIs). Based upon the characteristics of gray matter extracted from each ROI, we used an SVM algorithm to classify the subjects and statistical procedures based on bootstrap resampling to ensure the robustness of the results. We obtained 94.5% mean correct classification for AD and control subjects (mean specificity, 96.6%; mean sensitivity, 91.5%). Our method has the potential in distinguishing patients with AD from elderly controls and therefore may help in the early diagnosis of AD. (orig.)

Assessing a Faculty Development Program for the Adoption of Brain-Based Learning Strategies

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Lavis, Catherine C.; Williams, Kimberly A.; Fallin, Jana; Barnes, Pamela K.; Fishback, Sarah J.; Thien, Stephen

2016-01-01

Kansas State University designed a 20-month faculty development program with the goal of fostering broad, institution-wide adoption of teaching practices that focus on brain-based learning. Components of the program included annual teaching and learning workshops, reading and discussion groups based on content of a book about how the brain learns…

Standardized computer-based organized reporting of EEG

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C.

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE...... are used to report the features of clinical relevance, extracted while assessing the EEGs. Selection of the terms is context sensitive: initial choices determine the subsequently presented sets of additional choices. This process automatically generates a report and feeds these features into a database...

PENGARUH PENDEKATAN BRAIN-BASED TEACHING TERHADAP HASIL BELAJAR KIMIA

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Hermawan Agung Prasetya

2015-11-01

Full Text Available This study aimed to determine the effect of inquiry method assisted e-module on the student learning outcomes of chemistry. Population in this study is XI grader in Senior High School (SHS in Kudus, school year 2011/2012. Student learning activity is less varied, so it need to improve the variety methods to help students to be more interested in studying chemistry. The determination of the sample with cluster random sampling system obtained two classes, one class as a experiment class that are treated using the approach of Brain-Based and one as a control class who received treatment using conventional method. The data in this research obtained by documentation, tests, questionnaires, observation method. The result showed that the experimental class had an average of 85,06 and a control class had an average of 79.03. The data analysis, showed that the experimental class is better than the control class, it is shown by t count (3.159> t table (1.999. The conclusions of this research is the approach of Brain-Based Teaching gave the significant effect on student learning outcomes on colloid chemistry subject, which is indicated by the coefficient of correlation (rb  of 0.47 and the influence of 22,50%.Keyword: Brain-Based Teaching Approach

A brain-based account of "basic-level" concepts.

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Bauer, Andrew James; Just, Marcel Adam

2017-11-01

This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts. Copyright © 2017 Elsevier Inc. All rights reserved.

fNIRS-based brain-computer interfaces: a review

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Noman eNaseer

2015-01-01

Full Text Available A brain-computer interface (BCI is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing the peripheral nervous system, provide a means of communication for people suffering from severe motor disabilities or in a persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques for fNIRS-based BCI are reviewed. The most common brain areas for fNIRS BCI are the primary motor cortex and the prefrontal cortex. In relation to the motor cortex, motor imagery tasks were preferred to motor execution tasks since possible proprioceptive feedback could be avoided. In relation to the prefrontal cortex, fNIRS showed a significant advantage due to no hair in detecting the cognitive tasks like mental arithmetic, music imagery, emotion induction, etc. In removing physiological noise in fNIRS data, band-pass filtering was mostly used. However, more advanced techniques like adaptive filtering, independent component analysis, multi optodes arrangement, etc. are being pursued to overcome the problem that a band-pass filter cannot be used when both brain and physiological signals occur within a close band. In extracting features related to the desired brain signal, the mean, variance, peak value, slope, skewness, and kurtosis of the noised-removed hemodynamic response were used. For classification, the linear discriminant analysis method provided simple but good performance among others: support vector machine, hidden Markov model, artificial neural network, etc. fNIRS will be more widely used to monitor the occurrence of neuro-plasticity after neuro-rehabilitation and neuro-stimulation. Technical breakthroughs in the future are expected via bundled-type probes, hybrid EEG-fNIRS BCI, and through the detection of initial dips.

Automated voxel-based analysis of brain perfusion SPECT for vasospasm after subarachnoid haemorrhage

International Nuclear Information System (INIS)

Iwabuchi, S.; Yokouchi, T.; Hayashi, M.; Kimura, H.; Tomiyama, A.; Hirata, Y.; Saito, N.; Harashina, J.; Nakayama, H.; Sato, K.; Aoki, K.; Samejima, H.; Ueda, M.; Terada, H.; Hamazaki, K.

2008-01-01

We evaluated regional cerebral blood flow (rCBF) during vasospasm after subarachnoid haemorrhage ISAH) using automated voxel-based analysis of brain perfusion single-photon emission computed tomography (SPELT). Brain perfusion SPECT was performed 7 to 10 days after onset of SAH. Automated voxel-based analysis of SPECT used a Z-score map that was calculated by comparing the patients data with a control database. In cases where computed tomography (CT) scans detected an ischemic region due to vasospasm, automated voxel-based analysis of brain perfusion SPECT revealed dramatically reduced rCBF (Z-score ≤ -4). No patients with mildly or moderately diminished rCBF (Z-score > -3) progressed to cerebral infarction. Some patients with a Z-score < -4 did not progress to cerebral infarction after active treatment with a angioplasty. Three-dimensional images provided detailed anatomical information and helped us to distinguish surgical sequelae from vasospasm. In conclusion, automated voxel-based analysis of brain perfusion SPECT using a Z-score map is helpful in evaluating decreased rCBF due to vasospasm. (author)

Brain injury in sports.

Science.gov (United States)

Lloyd, John; Conidi, Frank

2016-03-01

Helmets are used for sports, military, and transportation to protect against impact forces and associated injuries. The common belief among end users is that the helmet protects the whole head, including the brain. However, current consensus among biomechanists and sports neurologists indicates that helmets do not provide significant protection against concussion and brain injuries. In this paper the authors present existing scientific evidence on the mechanisms underlying traumatic head and brain injuries, along with a biomechanical evaluation of 21 current and retired football helmets. The National Operating Committee on Standards for Athletic Equipment (NOCSAE) standard test apparatus was modified and validated for impact testing of protective headwear to include the measurement of both linear and angular kinematics. From a drop height of 2.0 m onto a flat steel anvil, each football helmet was impacted 5 times in the occipital area. Skull fracture risk was determined for each of the current varsity football helmets by calculating the percentage reduction in linear acceleration relative to a 140-g skull fracture threshold. Risk of subdural hematoma was determined by calculating the percentage reduction in angular acceleration relative to the bridging vein failure threshold, computed as a function of impact duration. Ranking the helmets according to their performance under these criteria, the authors determined that the Schutt Vengeance performed the best overall. The study findings demonstrated that not all football helmets provide equal or adequate protection against either focal head injuries or traumatic brain injuries. In fact, some of the most popular helmets on the field ranked among the worst. While protection is improving, none of the current or retired varsity football helmets can provide absolute protection against brain injuries, including concussions and subdural hematomas. To maximize protection against head and brain injuries for football players of

Region based Brain Computer Interface for a home control application.

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Akman Aydin, Eda; Bay, Omer Faruk; Guler, Inan

2015-08-01

Environment control is one of the important challenges for disabled people who suffer from neuromuscular diseases. Brain Computer Interface (BCI) provides a communication channel between the human brain and the environment without requiring any muscular activation. The most important expectation for a home control application is high accuracy and reliable control. Region-based paradigm is a stimulus paradigm based on oddball principle and requires selection of a target at two levels. This paper presents an application of region based paradigm for a smart home control application for people with neuromuscular diseases. In this study, a region based stimulus interface containing 49 commands was designed. Five non-disabled subjects were attended to the experiments. Offline analysis results of the experiments yielded 95% accuracy for five flashes. This result showed that region based paradigm can be used to select commands of a smart home control application with high accuracy in the low number of repetitions successfully. Furthermore, a statistically significant difference was not observed between the level accuracies.

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

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White, David J.; Congedo, Marco; Ciorciari, Joseph

2014-01-01

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation (BSS) of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using BSS may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes where individual brain sources may be targeted by source-based EEG neurofeedback. PMID

Brain-Based Learning and Educational Neuroscience: Boundary Work

NARCIS (Netherlands)

Edelenbosch, R.M.; Kupper, J.F.H.; Krabbendam, A.C.; Broerse, J.E.W.

2015-01-01

Much attention has been given to "bridging the gap" between neuroscience and educational practice. In order to gain better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning

Studying variability in human brain aging in a population-based German cohort – Rationale and design of 1000BRAINS

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Svenja eCaspers

2014-07-01

Full Text Available The ongoing 1000 brains study (1000BRAINS is an epidemiological and neuroscientific investigation of structural and functional variability in the human brain during aging. The two recruitment sources are the 10-year follow-up cohort of the German Heinz Nixdorf Recall (HNR Study, and the HNR MultiGeneration Study cohort, which comprises spouses and offspring of HNR subjects. The HNR is a longitudinal epidemiological investigation of cardiovascular risk factors, with a comprehensive collection of clinical, laboratory, socioeconomic, and environmental data from population-based subjects aged 45-75 years on inclusion. HNR subjects underwent detailed assessments in 2000, 2006, and 2011, and completed annual postal questionnaires on health status. 1000BRAINS accesses these HNR data and applies a separate protocol comprising: neuropsychological tests of attention, memory, executive functions & language; examination of motor skills; ratings of personality, life quality, mood & daily activities; analysis of laboratory and genetic data; and state-of-the-art magnetic resonance imaging (MRI, 3 Tesla of the brain. The latter includes (i 3D-T1- and 3D-T2-weighted scans for structural analyses and myelin mapping; (ii three diffusion imaging sequences optimized for diffusion tensor imaging, high-angular resolution diffusion imaging for detailed fibre tracking and for diffusion kurtosis imaging; (iii resting-state and task-based functional MRI; and (iv fluid-attenuated inversion recovery and MR angiography for the detection of vascular lesions and the mapping of white matter lesions. The unique design of 1000BRAINS allows: (i comprehensive investigation of various influences including genetics, environment and health status on variability in brain structure and function during aging; and (ii identification of the impact of selected influencing factors on specific cognitive subsystems and their anatomical correlates.

77 FR 39442 - Receipts-Based, Small Business Size Standard

Science.gov (United States)

2012-07-03

... RIN 3150-AJ14 [NRC-2012-0062] Receipts-Based, Small Business Size Standard AGENCY: Nuclear Regulatory... Regulatory Flexibility Act of 1980, as amended. The NRC is proposing to increase its receipts-based, small business size standard from $6.5 million to $7 million to conform to the standard set by the Small Business...

Reliability of semiquantitative 18F-FDG PET parameters derived from simultaneous brain PET/MRI: A feasibility study

International Nuclear Information System (INIS)

Jena, Amarnath; Taneja, Sangeeta; Goel, Reema; Renjen, Pushpendranath; Negi, Pradeep

2014-01-01

Purpose: Simultaneous brain PET/MRI faces an important issue of validation of accurate MRI based attenuation correction (AC) method for precise quantitation of brain PET data unlike in PET/CT systems where the use of standard, validated CT based AC is routinely available. The aim of this study was to investigate the feasibility of evaluation of semiquantitative 18 F-FDG PET parameters derived from simultaneous brain PET/MRI using ultrashort echo time (UTE) sequences for AC and to assess their agreement with those obtained from PET/CT examination. Methods: Sixteen patients (age range 18–73 years; mean age 49.43 (19.3) years; 13 men 3 women) underwent simultaneous brain PET/MRI followed immediately by PET/CT. Quantitative analysis of brain PET images obtained from both studies was undertaken using Scenium v.1 brain analysis software package. Twenty ROIs for various brain regions were system generated and 6 semiquantitative parameters including maximum standardized uptake value (SUV max), SUV mean, minimum SUV (SUV min), minimum standard deviation (SD min), maximum SD (SD max) and SD from mean were calculated for both sets of PET data for each patient. Intra-class correlation coefficients (ICCs) were determined to assess agreement between the various semiquantitative parameters for the two PET data sets. Results: Intra-class co-relation between the two PET data sets for SUV max, SUV mean and SD max was highly significant (p < 0.00) for all the 20 predefined brain regions with ICC > 0.9. SD from mean was also found to be statistically significant for all the predefined brain regions with ICC > 0.8. However, SUV max and SUV mean values obtained from PET/MRI were significantly lower compared to those of PET/CT for all the predefined brain regions. Conclusion: PET quantitation accuracy using the MRI based UTE sequences for AC in simultaneous brain PET/MRI is reliable in a clinical setting, being similar to that obtained using PET/CT

A Web-based cost-effective training tool with possible application to brain injury rehabilitation.

Science.gov (United States)

Wang, Peijun; Kreutzer, Ina Anna; Bjärnemo, Robert; Davies, Roy C

2004-06-01

Virtual reality (VR) has provoked enormous interest in the medical community. In particular, VR offers therapists new approaches for improving rehabilitation effects. However, most of these VR assistant tools are not very portable, extensible or economical. Due to the vast amount of 3D data, they are not suitable for Internet transfer. Furthermore, in order to run these VR systems smoothly, special hardware devices are needed. As a result, existing VR assistant tools tend to be available in hospitals but not in patients' homes. To overcome these disadvantages, as a case study, this paper proposes a Web-based Virtual Ticket Machine, called WBVTM, using VRML [VRML Consortium, The Virtual Reality Modeling Language: International Standard ISO/IEC DIS 14772-1, 1997, available at ], Java and EAI (External Authoring Interface) [Silicon Graphics, Inc., The External Authoring Interface (EAI), available at ], to help people with acquired brain injury (ABI) to relearn basic living skills at home at a low cost. As these technologies are open standard and feature usability on the Internet, WBVTM achieves the goals of portability, easy accessibility and cost-effectiveness.

Task-based core-periphery organization of human brain dynamics.

Directory of Open Access Journals (Sweden)

Danielle S Bassett

Full Text Available As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain's putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior.

77 FR 68717 - Updating OSHA Standards Based on National Consensus Standards; Head Protection

Science.gov (United States)

2012-11-16

..., 1918, and 1926 [Docket No. OSH-2011-0184] RIN 1218-AC65 Updating OSHA Standards Based on National Consensus Standards; Head Protection AGENCY: Occupational Safety and Health Administration (OSHA), Labor. ACTION: Proposed rule; withdrawal. SUMMARY: With this notice, OSHA is withdrawing the proposed rule that...

Mapping brain function to brain anatomy

International Nuclear Information System (INIS)

Valentino, D.J.; Huang, H.K.; Mazziotta, J.C.

1988-01-01

In Imaging the human brain, MRI is commonly used to reveal anatomical structure, while PET is used to reveal tissue function. This paper presents a protocol for correlating data between these two imaging modalities; this correlation can provide in vivo regional measurements of brain function which are essential to our understanding of the human brain. The authors propose a general protocol to standardize the acquisition and analysis of functional image data. First, MR and PET images are collected to form three-dimensional volumes of structural and functional image data. Second, these volumes of image data are corrected for distortions inherent in each imaging modality. Third, the image volumes are correlated to provide correctly aligned structural and functional images. The functional images are then mapped onto the structural images in both two-dimensional and three-dimensional representations. Finally, morphometric techniques can be used to provide statistical measures of the structure and function of the human brain

CT-based attenuation correction and resolution compensation for I-123 IMP brain SPECT normal database: a multicenter phantom study.

Science.gov (United States)

Inui, Yoshitaka; Ichihara, Takashi; Uno, Masaki; Ishiguro, Masanobu; Ito, Kengo; Kato, Katsuhiko; Sakuma, Hajime; Okazawa, Hidehiko; Toyama, Hiroshi

2018-03-19

Statistical image analysis of brain SPECT images has improved diagnostic accuracy for brain disorders. However, the results of statistical analysis vary depending on the institution even when they use a common normal database (NDB), due to different intrinsic spatial resolutions or correction methods. The present study aimed to evaluate the correction of spatial resolution differences between equipment and examine the differences in skull bone attenuation to construct a common NDB for use in multicenter settings. The proposed acquisition and processing protocols were those routinely used at each participating center with additional triple energy window (TEW) scatter correction (SC) and computed tomography (CT) based attenuation correction (CTAC). A multicenter phantom study was conducted on six imaging systems in five centers, with either single photon emission computed tomography (SPECT) or SPECT/CT, and two brain phantoms. The gray/white matter I-123 activity ratio in the brain phantoms was 4, and they were enclosed in either an artificial adult male skull, 1300 Hounsfield units (HU), a female skull, 850 HU, or an acrylic cover. The cut-off frequency of the Butterworth filters was adjusted so that the spatial resolution was unified to a 17.9 mm full width at half maximum (FWHM), that of the lowest resolution system. The gray-to-white matter count ratios were measured from SPECT images and compared with the actual activity ratio. In addition, mean, standard deviation and coefficient of variation images were calculated after normalization and anatomical standardization to evaluate the variability of the NDB. The gray-to-white matter count ratio error without SC and attenuation correction (AC) was significantly larger for higher bone densities (p correction. The proposed protocol showed potential for constructing an appropriate common NDB from SPECT images with SC, AC and spatial resolution compensation.

Flashing characters with famous faces improves ERP-based brain-computer interface performance

Science.gov (United States)

Kaufmann, T.; Schulz, S. M.; Grünzinger, C.; Kübler, A.

2011-10-01

Currently, the event-related potential (ERP)-based spelling device, often referred to as P300-Speller, is the most commonly used brain-computer interface (BCI) for enhancing communication of patients with impaired speech or motor function. Among numerous improvements, a most central feature has received little attention, namely optimizing the stimulus used for eliciting ERPs. Therefore we compared P300-Speller performance with the standard stimulus (flashing characters) against performance with stimuli known for eliciting particularly strong ERPs due to their psychological salience, i.e. flashing familiar faces transparently superimposed on characters. Our results not only indicate remarkably increased ERPs in response to familiar faces but also improved P300-Speller performance due to a significant reduction of stimulus sequences needed for correct character classification. These findings demonstrate a promising new approach for improving the speed and thus fluency of BCI-enhanced communication with the widely used P300-Speller.

Brain cancer associated with environmental lead exposure: evidence from implementation of a National Petrol-Lead Phase-Out Program (PLPOP) in Taiwan between 1979 and 2007.

Science.gov (United States)

Wu, Wei-Te; Lin, Yu-Jen; Liou, Saou-Hsing; Yang, Chun-Yuh; Cheng, Kuang-Fu; Tsai, Perng-Jy; Wu, Trong-Neng

2012-04-01

In 1981, a Petrol-Lead Phase-Out Program (PLPOP) was launched in Taiwan for the abatement of environmental lead emissions. The present study was intended to examine whether the high Petrol-Lead Emission Areas (PLEA) would result in an increase in the incidence rate of brain cancer based on a national data bank. The national brain cancer incidence data was obtained from the Taiwan National Cancer Registry. Age standardized incidence rates were calculated based on the 2000 WHO world standard population, and gasoline consumption data was obtained from the Bureau of Energy. The differences in the trend tests for age-standardized incidence rates of brain cancer between high, median, low, and small PLEA were analyzed. A significant increase was found from small to high PLEA in age-standardized incidence rates of brain cancer. By taking six possible confounders into account, the age-standardized incidence rates for brain cancer were highly correlated with the median and high PLEA by reference to the small PLEA. After being adjusted for a number of relevant confounders, it could be concluded that high PLEA might result in an increase in the incidence rate of brain cancer resulting from high lead exposures. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms

International Nuclear Information System (INIS)

Conson, Manuel; Cella, Laura; Pacelli, Roberto; Comerci, Marco; Liuzzi, Raffaele; Salvatore, Marco; Quarantelli, Mario

2014-01-01

Purpose: To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). Patients and methods: 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient – DSC). Dosimetric parameters from dose–volume-histograms were also generated and compared. Results: Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSC ABAS = 1 (95% CI, 0.97–1.0) vs. DSC MANUAL = 0.90 (0.73–0.98)], acceptable accuracy [DSC ABAS = 0.81 (0.68–0.94) vs. DSC MANUAL = 0.90 (0.76–0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. Conclusions: The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose–volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures

Brain waves-based index for workload estimation and mental effort engagement recognition

Science.gov (United States)

Zammouri, A.; Chraa-Mesbahi, S.; Ait Moussa, A.; Zerouali, S.; Sahnoun, M.; Tairi, H.; Mahraz, A. M.

2017-10-01

The advent of the communication systems and considering the complexity that some impose in their use, it is necessary to incorporate and equip these systems with a certain intelligence which takes into account the cognitive and mental capacities of the human operator. In this work, we address the issue of estimating the mental effort of an operator according to the cognitive tasks difficulty levels. Based on the Electroencephalogram (EEG) measurements, the proposed approach analyzes the user’s brain activity from different brain regions while performing cognitive tasks with several levels of difficulty. At a first time, we propose a variances comparison-based classifier (VCC) that makes use of the Power Spectral Density (PSD) of the EEG signal. The aim of using such a classifier is to highlight the brain regions that enter into interaction according to the cognitive task difficulty. In a second time, we present and describe a new EEG-based index for the estimation of mental efforts. The designed index is based on information recorded from two EEG channels. Results from the VCC demonstrate that powers of the Theta [4-7 Hz] (θ) and Alpha [8-12 Hz] (α) oscillations decrease while increasing the cognitive task difficulty. These decreases are mainly located in parietal and temporal brain regions. Based on the Kappa coefficients, decisions of the introduced index are compared to those obtained from an existing index. This performance assessment method revealed strong agreements. Hence the efficiency of the introduced index.

77 FR 68684 - Updating OSHA Standards Based on National Consensus Standards; Head Protection

Science.gov (United States)

2012-11-16

..., 1918, and 1926 [Docket No. OSHA-2011-0184] RIN 1218-AC65 Updating OSHA Standards Based on National Consensus Standards; Head Protection AGENCY: Occupational Safety and Health Administration (OSHA), Labor. ACTION: Final rule; confirmation of effective date. SUMMARY: OSHA is confirming the effective date of its...

Brain-Based Learning and Educational Neuroscience: Boundary Work

Science.gov (United States)

Edelenbosch, Rosanne; Kupper, Frank; Krabbendam, Lydia; Broerse, Jacqueline E. W.

2015-01-01

Much attention has been given to "bridging the gap" between neuroscience and educational practice. In order to gain better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning approach, focusing on…

Correlation between subacute sensorimotor deficits and brain water content after surgical brain injury in rats.

Science.gov (United States)

McBride, Devin W; Wang, Yuechun; Sherchan, Prativa; Tang, Jiping; Zhang, John H

2015-09-01

Brain edema is a major contributor to poor outcome and reduced quality of life after surgical brain injury (SBI). Although SBI pathophysiology is well-known, the correlation between cerebral edema and neurological deficits has not been thoroughly examined in the rat model of SBI. Thus, the purpose of this study was to determine the correlation between brain edema and deficits in standard sensorimotor neurobehavior tests for rats subjected to SBI. Sixty male Sprague-Dawley rats were subjected to either sham surgery or surgical brain injury via partial frontal lobectomy. All animals were tested for neurological deficits 24 post-SBI and fourteen were also tested 72 h after surgery using seven common behavior tests: modified Garcia neuroscore (Neuroscore), beam walking, corner turn test, forelimb placement test, adhesive removal test, beam balance test, and foot fault test. After assessing the functional outcome, animals were euthanized for brain water content measurement. Surgical brain injury resulted in significantly elevated frontal lobe brain water content 24 and 72 h after surgery compared to that of sham animals. In all behavior tests, significance was observed between sham and SBI animals. However, a correlation between brain water content and functional outcome was observed for all tests except Neuroscore. The selection of behavior tests is critical to determine the effectiveness of therapeutics. Based on this study's results, we recommend using beam walking, the corner turn test, the beam balance test, and the foot fault test since correlations with brain water content were observed at both 24 and 72 h post-SBI. Copyright © 2015 Elsevier B.V. All rights reserved.

Correlation between subacute sensorimotor deficits and brain water content after surgical brain injury in rats

Science.gov (United States)

McBride, Devin W.; Wang, Yuechun; Sherchan, Prativa; Tang, Jiping; Zhang, John H.

2015-01-01

Brain edema is a major contributor to poor outcome and reduced quality of life after surgical brain injury (SBI). Although SBI pathophysiology is well-known, the correlation between cerebral edema and neurological deficits has not been thoroughly examined in the rat model of SBI. Thus, the purpose of this study was to determine the correlation between brain edema and deficits in standard sensorimotor neurobehavior tests for rats subjected to SBI. Sixty male Sprague-Dawley rats were subjected to either sham surgery or surgical brain injury via partial frontal lobectomy. All animals were tested for neurological deficits 24 post-SBI and fourteen were also tested 72 hours after surgery using seven common behavior tests: modified Garcia neuroscore (Neuroscore), beam walking, corner turn test, forelimb placement test, adhesive removal test, beam balance test, and foot fault test. After assessing the functional outcome, animals were euthanized for brain water content measurement. Surgical brain injury resulted in a significantly elevated frontal lobe brain water content 24 and 72 hours after surgery compared to that of sham animals. In all behavior tests, significance was observed between sham and SBI animals. However, a correlation between brain water content and functional outcome was observed for all tests except Neuroscore. The selection of behavior tests is critical to determine the effectiveness of therapeutics. Based on this study’s results, we recommend using beam walking, the corner turn test, the beam balance test, and the foot fault test since correlations with brain water content were observed at both 24 and 72 hours post-SBI. PMID:25975171

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

Science.gov (United States)

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…

Effects of virtual reality-based bilateral upper-extremity training on brain activity in post-stroke patients.

Science.gov (United States)

Lee, Su-Hyun; Kim, Yu-Mi; Lee, Byoung-Hee

2015-07-01

[Purpose] This study investigated the therapeutic effects of virtual reality-based bilateral upper-extremity training on brain activity in patients with stroke. [Subjects and Methods] Eighteen chronic stroke patients were divided into two groups: the virtual reality-based bilateral upper-extremity training group (n = 10) and the bilateral upper-limb training group (n = 8). The virtual reality-based bilateral upper-extremity training group performed bilateral upper-extremity exercises in a virtual reality environment, while the bilateral upper-limb training group performed only bilateral upper-extremity exercise. All training was conducted 30 minutes per day, three times per week for six weeks, followed by brain activity evaluation. [Results] Electroencephalography showed significant increases in concentration in the frontopolar 2 and frontal 4 areas, and significant increases in brain activity in the frontopolar 1 and frontal 3 areas in the virtual reality-based bilateral upper-extremity training group. [Conclusion] Virtual reality-based bilateral upper-extremity training can improve the brain activity of stroke patients. Thus, virtual reality-based bilateral upper-extremity training is feasible and beneficial for improving brain activation in stroke patients.

Sensorimotor rhythm-based brain-computer interface training: the impact on motor cortical responsiveness

Science.gov (United States)

Pichiorri, F.; De Vico Fallani, F.; Cincotti, F.; Babiloni, F.; Molinari, M.; Kleih, S. C.; Neuper, C.; Kübler, A.; Mattia, D.

2011-04-01

The main purpose of electroencephalography (EEG)-based brain-computer interface (BCI) technology is to provide an alternative channel to support communication and control when motor pathways are interrupted. Despite the considerable amount of research focused on the improvement of EEG signal detection and translation into output commands, little is known about how learning to operate a BCI device may affect brain plasticity. This study investigated if and how sensorimotor rhythm-based BCI training would induce persistent functional changes in motor cortex, as assessed with transcranial magnetic stimulation (TMS) and high-density EEG. Motor imagery (MI)-based BCI training in naïve participants led to a significant increase in motor cortical excitability, as revealed by post-training TMS mapping of the hand muscle's cortical representation; peak amplitude and volume of the motor evoked potentials recorded from the opponens pollicis muscle were significantly higher only in those subjects who develop a MI strategy based on imagination of hand grasping to successfully control a computer cursor. Furthermore, analysis of the functional brain networks constructed using a connectivity matrix between scalp electrodes revealed a significant decrease in the global efficiency index for the higher-beta frequency range (22-29 Hz), indicating that the brain network changes its topology with practice of hand grasping MI. Our findings build the neurophysiological basis for the use of non-invasive BCI technology for monitoring and guidance of motor imagery-dependent brain plasticity and thus may render BCI a viable tool for post-stroke rehabilitation.

Service Learning to Promote Brain-Based Learning in Undergraduate Teaching

Science.gov (United States)

Nwokah, Eva E.; Leafblad, Stefanie

2013-01-01

In this study 44 undergraduate students in a language development course participated in service learning with preschool homeless and low-income children as a course requirement. Students completed a survey, questionnaires, reflective journaling, and small-group debriefing sessions. Based on current views on brain-based learning from cortical…

76 FR 42395 - Business Conduct Standards for Security-Based Swap Dealers and Major Security-Based Swap...

Science.gov (United States)

2011-07-18

... Business Conduct Standards for Security-Based Swap Dealers and Major Security-Based Swap Participants...-11] RIN 3235-AL10 Business Conduct Standards for Security-Based Swap Dealers and Major Security-Based...'') relating to external business conduct standards for security-based swap dealers (``SBS Dealers'') and major...

The brain's silent messenger: using selective attention to decode human thought for brain-based communication.

Science.gov (United States)

Naci, Lorina; Cusack, Rhodri; Jia, Vivian Z; Owen, Adrian M

2013-05-29

The interpretation of human thought from brain activity, without recourse to speech or action, is one of the most provoking and challenging frontiers of modern neuroscience. In particular, patients who are fully conscious and awake, yet, due to brain damage, are unable to show any behavioral responsivity, expose the limits of the neuromuscular system and the necessity for alternate forms of communication. Although it is well established that selective attention can significantly enhance the neural representation of attended sounds, it remains, thus far, untested as a response modality for brain-based communication. We asked whether its effect could be reliably used to decode answers to binary (yes/no) questions. Fifteen healthy volunteers answered questions (e.g., "Do you have brothers or sisters?") in the fMRI scanner, by selectively attending to the appropriate word ("yes" or "no"). Ninety percent of the answers were decoded correctly based on activity changes within the attention network. The majority of volunteers conveyed their answers with less than 3 min of scanning, suggesting that this technique is suited for communication in a reasonable amount of time. Formal comparison with the current best-established fMRI technique for binary communication revealed improved individual success rates and scanning times required to detect responses. This novel fMRI technique is intuitive, easy to use in untrained participants, and reliably robust within brief scanning times. Possible applications include communication with behaviorally nonresponsive patients.

Biodistribution of ultra small gadolinium-based nanoparticles as theranostic agent: application to brain tumors.

Science.gov (United States)

Miladi, Imen; Duc, Géraldine Le; Kryza, David; Berniard, Aurélie; Mowat, Pierre; Roux, Stéphane; Taleb, Jacqueline; Bonazza, Pauline; Perriat, Pascal; Lux, François; Tillement, Olivier; Billotey, Claire; Janier, Marc

2013-09-01

Gadolinium-based nanoparticles are novel objects with interesting physical properties, allowing their use for diagnostic and therapeutic applications. Gadolinium-based nanoparticles were imaged following intravenous injection in healthy rats and rats grafted with 9L gliosarcoma tumors using magnetic resonance imaging and scintigraphic imaging. Quantitative biodistribution using gamma-counting of each sampled organ confirmed that these nanoparticles were rapidly cleared essentially by renal excretion. Accumulation of these nanoparticles in 9L gliosarcoma tumors implanted in the rat brain was quantitated. This passive and long-duration accumulation of gadolinium-based nanoparticles in tumor, which is related to disruption of the blood-brain barrier, is in good agreement with the use of these nanoparticles as radiosensitizers for brain tumors.

A flocking based method for brain tractography.

Science.gov (United States)

Aranda, Ramon; Rivera, Mariano; Ramirez-Manzanares, Alonso

2014-04-01

We propose a new method to estimate axonal fiber pathways from Multiple Intra-Voxel Diffusion Orientations. Our method uses the multiple local orientation information for leading stochastic walks of particles. These stochastic particles are modeled with mass and thus they are subject to gravitational and inertial forces. As result, we obtain smooth, filtered and compact trajectory bundles. This gravitational interaction can be seen as a flocking behavior among particles that promotes better and robust axon fiber estimations because they use collective information to move. However, the stochastic walks may generate paths with low support (outliers), generally associated to incorrect brain connections. In order to eliminate the outlier pathways, we propose a filtering procedure based on principal component analysis and spectral clustering. The performance of the proposal is evaluated on Multiple Intra-Voxel Diffusion Orientations from two realistic numeric diffusion phantoms and a physical diffusion phantom. Additionally, we qualitatively demonstrate the performance on in vivo human brain data. Copyright © 2014 Elsevier B.V. All rights reserved.

Brain core temperature of patients with mild traumatic brain injury as assessed by DWI-thermometry

International Nuclear Information System (INIS)

Tazoe, Jun; Yamada, Kei; Akazawa, Kentaro; Sakai, Koji; Mineura, Katsuyoshi

2014-01-01

The aim of this study was to assess the brain core temperature of patients with mild traumatic brain injury (mTBI) using a noninvasive temperature measurement technique based on the diffusion coefficient of the cerebrospinal fluid. This retrospective study used the data collected from April 2008 to June 2011. The patient group comprised 20 patients with a Glasgow Coma Scale score of 14 or 15 who underwent magnetic resonance imaging within 30 days after head trauma. The normal control group comprised 14 subjects who volunteered for a brain checkup (known in Japan as ''brain dock''). We compared lateral ventricular (LV) temperature between patient and control groups. Follow-up studies were performed for four patients. LV temperature measurements were successfully performed for both patients and controls. Mean (±standard deviation) measured LV temperature was 36.9 ± 1.5 C in patients, 38.7 ± 1.8 C in follow-ups, and 37.9 ± 1.2 C in controls, showing a significant difference between patients and controls (P = 0.017). However, no significant difference was evident between patients and follow-ups (P = 0.595) or between follow-ups and controls (P = 0.465). A reduction in brain core temperature was observed in patients with mTBI, possibly due to a global decrease in metabolism. (orig.)

Digital atlas of fetal brain MRI

Energy Technology Data Exchange (ETDEWEB)

Chapman, Teresa; Weinberger, E. [Department of Radiology, Seattle Children' s Hospital, Seattle, WA (United States); Matesan, Manuela [University of Washington, Department of Radiology, Seattle, WA (United States); Bulas, Dorothy I. [Division of Diagnostic Imaging and Radiology, Children' s National Medical Center, Washington, DC (United States)

2010-02-15

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download. Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development. (orig.)

Digital atlas of fetal brain MRI

International Nuclear Information System (INIS)

Chapman, Teresa; Weinberger, E.; Matesan, Manuela; Bulas, Dorothy I.

2010-01-01

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download. Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development. (orig.)

PIXE analysis of cerebrospinal fluid before and after brain transplantation

International Nuclear Information System (INIS)

Ma Xinpei; Wang Junke.

1992-01-01

Considering methodology of PIXE quantitative analysis based on Inner-standard, we provide a simple and convenient method to measure the elemental relative sensitivity curve. The concentrations of 16 various elements in cerebrospinal fluid samples before and after brain transplantation have been investigated and compared with those of normal person's and transplanted tissues. The experimental results show that the brain transplantation results in apparently curative effects in compensating and regulating the element concentrations in cerebrospinal fluid and improvement of elemental physiological metabolism. It illustrates that the appropriate concentrations of trace elements in cerebrospinal fluid play an undoubtedly important role in keeping the normal physiological function of brain and central nervous system. (author)

Rehabilitative interventions and brain plasticity in autism spectrum disorders: focus on MRI-based studies

Directory of Open Access Journals (Sweden)

Sara eCalderoni

2016-03-01

Full Text Available Clinical and research evidence supports the efficacy of rehabilitative intervention for improving targeted skills or global outcomes in individuals with autism spectrum disorder (ASD. However, putative mechanisms of structural and functional brain changes are poorly understood. This review aims to investigate the research literature on the neural circuit modifications after non-pharmacological intervention. For this purpose, longitudinal studies that used magnetic resonance imaging (MRI-based techniques at the start and at the end of the trial to evaluate the neural effects of rehabilitative treatment in subjects with ASD were identified. The six included studies involved a limited number of patients in the active group (from 2 to 16, and differed by acquisition method (task-related and resting-state functional MRI as well as by functional MRI tasks. Overall, the results produced by the selected investigations demonstrated brain plasticity during the treatment interval that results in an activation/functional connectivity more similar to those of subjects with typical development. Repeated MRI evaluation may represent a promising tool for the detection of neural changes in response to treatment in patients with ASD. However, large-scale randomized controlled trials after standardized rehabilitative intervention are required before translating these preliminary results into clinical use.

Nonlinear dynamics of the brain: emotion and cognition

Energy Technology Data Exchange (ETDEWEB)

Rabinovich, Mikhail I; Muezzinoglu, M K [Institute for Nonlinear Science, University of California, San Diego, CA (United States)

2010-07-08

Experimental investigations of neural system functioning and brain activity are standardly based on the assumption that perceptions, emotions, and cognitive functions can be understood by analyzing steady-state neural processes and static tomographic snapshots. The new approaches discussed in this review are based on the analysis of transient processes and metastable states. Transient dynamics is characterized by two basic properties, structural stability and information sensitivity. The ideas and methods that we discuss provide an explanation for the occurrence of and successive transitions between metastable states observed in experiments, and offer new approaches to behavior analysis. Models of the emotional and cognitive functions of the brain are suggested. The mathematical object that represents the observed transient brain processes in the phase space of the model is a structurally stable heteroclinic channel. The possibility of using the suggested models to construct a quantitative theory of some emotional and cognitive functions is illustrated. (reviews of topical problems)

Nonlinear dynamics of the brain: emotion and cognition

International Nuclear Information System (INIS)

Rabinovich, Mikhail I; Muezzinoglu, M K

2010-01-01

Experimental investigations of neural system functioning and brain activity are standardly based on the assumption that perceptions, emotions, and cognitive functions can be understood by analyzing steady-state neural processes and static tomographic snapshots. The new approaches discussed in this review are based on the analysis of transient processes and metastable states. Transient dynamics is characterized by two basic properties, structural stability and information sensitivity. The ideas and methods that we discuss provide an explanation for the occurrence of and successive transitions between metastable states observed in experiments, and offer new approaches to behavior analysis. Models of the emotional and cognitive functions of the brain are suggested. The mathematical object that represents the observed transient brain processes in the phase space of the model is a structurally stable heteroclinic channel. The possibility of using the suggested models to construct a quantitative theory of some emotional and cognitive functions is illustrated. (reviews of topical problems)

A Thomistic defense of whole-brain death.

Science.gov (United States)

Eberl, Jason T

2015-08-01

Michel Accad critiques the currently accepted whole-brain criterion for determining the death of a human being from a Thomistic metaphysical perspective and, in so doing, raises objections to a particular argument defending the whole-brain criterion by Patrick Lee and Germain Grisez. In this paper, I will respond to Accad's critique of the whole-brain criterion and defend its continued validity as a criterion for determining when a human being's death has occurred in accord with Thomistic metaphysical principles. I will, however, join Accad in criticizing Lee and Grisez's proposed defense of the whole-brain criterion as potentially leading to erroneous conclusions regarding the determination of human death. Lay summary: Catholic physicians and bioethicists currently debate the legally accepted clinical standard for determining when a human being has died-known as the "wholebrain criterion"-which has also been morally affirmed by the Magisterium. This paper responds to physician Michel Accad's critique of the whole-brain criterion based upon St. Thomas Aquinas's metaphysical account of human nature as a union of a rational soul and a material body. I defend the whole-brain criterion from the same Thomistic philosophical perspective, while agreeing with Accad's objection to an alternative Thomistic defense of whole-brain death by philosophers Patrick Lee and Germain Grisez.

Primary brain tumours, meningiomas and brain metastases in pregnancy

DEFF Research Database (Denmark)

Verheecke, Magali; Halaska, Michael J; Lok, Christianne A

2014-01-01

to obtain better insight into outcome and possibilities of treatment in pregnancy. METHODS: We collected all intracranial tumours (primary brain tumour, cerebral metastasis, or meningioma) diagnosed during pregnancy, registered prospectively and retrospectively by international collaboration since 1973......, respectively. Eight patients (30%) underwent brain surgery, seven patients (26%) had radiotherapy and in three patients (11%) chemotherapy was administered during gestation. Two patients died during pregnancy and four pregnancies were terminated. In 16 (59%) patients elective caesarean section was performed...... were reassuring. CONCLUSION: Adherence to standard protocol for the treatment of brain tumours during pregnancy appears to allow a term delivery and a higher probability of a vaginal delivery....

Social reward improves the voluntary control over localized brain activity in fMRI-based neurofeedback training

Directory of Open Access Journals (Sweden)

Krystyna Anna Mathiak

2015-06-01

Full Text Available Neurofeedback (NF based on real-time functional magnetic resonance imaging (rt-fMRI allows voluntary regulation of the activity in a selected brain region. For the training of this regulation, a well-designed feedback system is required. Social reward may serve as an effective incentive in NF paradigms, but its efficiency has not yet been tested. Therefore, we developed a social reward NF paradigm and assessed it in comparison with a typical visual NF paradigm (moving bar.We trained 24 healthy participants, on three consecutive days, to control activation in dorsal anterior cingulate cortex (ACC with fMRI-based NF. In the social feedback group, an avatar gradually smiled when ACC activity increased, whereas in the standard feedback group, a moving bar indicated the activation level. To assess a transfer of the NF training both groups were asked to up-regulate their brain activity without receiving feedback immediately before and after the NF training (pre- and post-test. Finally, the effect of the acquired NF training on ACC function was evaluated in a cognitive interference task (Simon task during the pre- and post-test.Social reward led to stronger activity in the ACC and reward-related areas during the NF training when compared to standard feedback. After the training, both groups were able to regulate ACC without receiving feedback, with a trend for stronger responses in the social feedback group. Moreover, despite a lack of behavioral differences, significant higher ACC activations emerged in the cognitive interference task, reflecting a stronger generalization of the NF training on cognitive interference processing after social feedback.Social reward can increase self-regulation in fMRI-based NF and strengthen its effects on neural processing in related tasks, such as cognitive interference. An advantage of social feedback is that a direct external reward is provided as in natural social interactions, opening perspectives for implicit

Fun cube based brain gym cognitive function assessment system.

Science.gov (United States)

Zhang, Tao; Lin, Chung-Chih; Yu, Tsang-Chu; Sun, Jing; Hsu, Wen-Chuin; Wong, Alice May-Kuen

2017-05-01

The aim of this study is to design and develop a fun cube (FC) based brain gym (BG) cognitive function assessment system using the wireless sensor network and multimedia technologies. The system comprised (1) interaction devices, FCs and a workstation used as interactive tools for collecting and transferring data to the server, (2) a BG information management system responsible for managing the cognitive games and storing test results, and (3) a feedback system used for conducting the analysis of cognitive functions to assist caregivers in screening high risk groups with mild cognitive impairment. Three kinds of experiments were performed to evaluate the developed FC-based BG cognitive function assessment system. The experimental results showed that the Pearson correlation coefficient between the system's evaluation outcomes and the traditional Montreal Cognitive Assessment scores was 0.83. The average Technology Acceptance Model 2 score was close to six for 31 elderly subjects. Most subjects considered that the brain games are interesting and the FC human-machine interface is easy to learn and operate. The control group and the cognitive impairment group had statistically significant difference with respect to the accuracy of and the time taken for the brain cognitive function assessment games, including Animal Naming, Color Search, Trail Making Test, Change Blindness, and Forward / Backward Digit Span. Copyright © 2017 Elsevier Ltd. All rights reserved.

CHAOS-BASED ADVANCED ENCRYPTION STANDARD

KAUST Repository

Abdulwahed, Naif B.

2013-05-01

This thesis introduces a new chaos-based Advanced Encryption Standard (AES). The AES is a well-known encryption algorithm that was standardized by U.S National Institute of Standard and Technology (NIST) in 2001. The thesis investigates and explores the behavior of the AES algorithm by replacing two of its original modules, namely the S-Box and the Key Schedule, with two other chaos- based modules. Three chaos systems are considered in designing the new modules which are Lorenz system with multiplication nonlinearity, Chen system with sign modules nonlinearity, and 1D multiscroll system with stair case nonlinearity. The three systems are evaluated on their sensitivity to initial conditions and as Pseudo Random Number Generators (PRNG) after applying a post-processing technique to their output then performing NIST SP. 800-22 statistical tests. The thesis presents a hardware implementation of dynamic S-Boxes for AES that are populated using the three chaos systems. Moreover, a full MATLAB package to analyze the chaos generated S-Boxes based on graphical analysis, Walsh-Hadamard spectrum analysis, and image encryption analysis is developed. Although these S-Boxes are dynamic, meaning they are regenerated whenever the encryption key is changed, the analysis results show that such S-Boxes exhibit good properties like the Strict Avalanche Criterion (SAC) and the nonlinearity and in the application of image encryption. Furthermore, the thesis presents a new Lorenz-chaos-based key expansion for the AES. Many researchers have pointed out that there are some defects in the original key expansion of AES and thus have motivated such chaos-based key expansion proposal. The new proposed key schedule is analyzed and assessed in terms of confusion and diffusion by performing the frequency and SAC test respectively. The obtained results show that the new proposed design is more secure than the original AES key schedule and other proposed designs in the literature. The proposed

Digital atlas of fetal brain MRI.

Science.gov (United States)

Chapman, Teresa; Matesan, Manuela; Weinberger, Ed; Bulas, Dorothy I

2010-02-01

Fetal MRI can be performed in the second and third trimesters. During this time, the fetal brain undergoes profound structural changes. Interpretation of appropriate development might require comparison with normal age-based models. Consultation of a hard-copy atlas is limited by the inability to compare multiple ages simultaneously. To provide images of normal fetal brains from weeks 18 through 37 in a digital format that can be reviewed interactively. This will facilitate recognition of abnormal brain development. T2-W images for the atlas were obtained from fetal MR studies of normal brains scanned for other indications from 2005 to 2007. Images were oriented in standard axial, coronal and sagittal projections, with laterality established by situs. Gestational age was determined by last menstrual period, earliest US measurements and sonogram performed on the same day as the MR. The software program used for viewing the atlas, written in C#, permits linked scrolling and resizing the images. Simultaneous comparison of varying gestational ages is permissible. Fetal brain images across gestational ages 18 to 37 weeks are provided as an interactive digital atlas and are available for free download from http://radiology.seattlechildrens.org/teaching/fetal_brain . Improved interpretation of fetal brain abnormalities can be facilitated by the use of digital atlas cataloging of the normal changes throughout fetal development. Here we provide a description of the atlas and a discussion of normal fetal brain development.

Transmission control unit drive based on the AUTOSAR standard

Science.gov (United States)

Guo, Xiucai; Qin, Zhen

2018-03-01

It is a trend of automotive electronics industry in the future that automotive electronics embedded system development based on the AUTOSAR standard. AUTOSAR automotive architecture standard has proposed the transmission control unit (TCU) development architecture and designed its interfaces and configurations in detail. This essay has discussed that how to drive the TCU based on AUTOSAR standard architecture. The results show that driving the TCU with the AUTOSAR system improves reliability and shortens development cycles.

SU-E-J-171: Surface Imaging Based Intrafraction Motion Assessments for Whole Brain Radiotherapy

International Nuclear Information System (INIS)

Wiant, D; Vanderstraeten, C; Maurer, J; Pursley, J; Terrell, J; Sintay, B

2014-01-01

Purpose: To quantify and characterize intrafraction motion for whole brain radiotherapy treatments in open face masks using 3D surface imaging. Methods: Fifteen whole brain patients were monitored with 3D surface imaging over a total of 202 monitoring sessions. Mean translations and rotations were calculated over each minute, each session, and over all sessions combined. The percentage of each session that the root mean square (RMS) of the linear translations were outside of 2 mm, 3 mm, 4 mm, and 5 mm were determined for each patient. Correlations between mean translations per minute and time and between standard deviation per minute and time were evaluated using Pearson's r value. Results: The mean RMS translation averaged over all patients was 1.45 mm +/− 1.52 mm. The patients spent an average of 18%, 10%, 6%, and 3% of the monitoring time outside of 2 mm, 3 mm, 4 mm, and 5 mm RMS tolerances, respectively. The RMS values averaged over all patients were 1.31 mm +/− 0.98 mm, 1.52 +/- 1.04, and 1.30 mm +/− 0.71 mm over the 1th, 5th, and 10th minutes of monitoring, respectively. Neither, the RMS values (p = 0.15) or the standard deviations of the RMS values (p = 0.16) showed significant correlations with time. Conclusion: The patients were positioned within 2 mm of isocenter, which was the initial set-up tolerance, for the majority of their treatments. The average position changed by < 0.3 mm over 10 minutes of monitoring. Short term movements, reflected by the standard deviations, where on the order of 1 mm. This immobilization system provides adequate immobilization over a course of treatment for whole brain radiotherapy. This system may also be suitable for head and neck or stereotactic radiosurgery treatments as well

Volumetric multimodality neural network for brain tumor segmentation

Science.gov (United States)

Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

The Effect of Standardized Interviews on Organ Donation.

Science.gov (United States)

Corman Dincer, Pelin; Birtan, Deniz; Arslantas, Mustafa Kemal; Tore Altun, Gulbin; Ayanoglu, Hilmi Omer

2018-03-01

Organ donation is the most important stage for organ transplant. Studies reveal that attitudes of families of brain-dead patients toward donation play a significant role in their decision. We hypothesized that supporting family awareness about the meaning of organ donation, including saving lives while losing a loved one, combined with being informed about brain death and the donation process must be maintained by intensive care unit physicians through standardized interviews and questionnaires to increase the donation rate. We retrospectively evaluated the final decisions of families of 52 brain-dead donors treated at our institution between 2014 and 2017. Data underwent descriptive analyses. The standard interview content was generated after literature search results were reviewed by the authors. Previously, we examined the impact of standardized interviews done by intensive care unit physicians with relatives of potential brain-dead donors regarding decisions to donate or reasons for refusing organ donation. After termination of that study, interviews were done according to the intensivist's orientation, resulting in significantly decreased donation rates. Standardized interviews were then started again, resulting in increased donation rates. Of 17 families who participated in standardized interviews, 5 families (29.4%) agreed to donate organs of their brain-dead relatives. In the other group of families, intensivists governed informing the families of donation without standardized interviews. In this group of 35 families, 5 families (14.3%) approved organ donation. The decision regarding whether to agree to organ donation was statistically different between the 2 family groups (P donation process resulted in an increased rate of organ donation compared with routine protocols.

VA's National PTSD Brain Bank: a National Resource for Research.

Science.gov (United States)

Friedman, Matthew J; Huber, Bertrand R; Brady, Christopher B; Ursano, Robert J; Benedek, David M; Kowall, Neil W; McKee, Ann C

2017-08-25

The National PTSD Brain Bank (NPBB) is a brain tissue biorepository established to support research on the causes, progression, and treatment of PTSD. It is a six-part consortium led by VA's National Center for PTSD with participating sites at VA medical centers in Boston, MA; Durham, NC; Miami, FL; West Haven, CT; and White River Junction, VT along with the Uniformed Services University of Health Sciences. It is also well integrated with VA's Boston-based brain banks that focus on Alzheimer's disease, ALS, chronic traumatic encephalopathy, and other neurological disorders. This article describes the organization and operations of NPBB with specific attention to: tissue acquisition, tissue processing, diagnostic assessment, maintenance of a confidential data biorepository, adherence to ethical standards, governance, accomplishments to date, and future challenges. Established in 2014, NPBB has already acquired and distributed brain tissue to support research on how PTSD affects brain structure and function.

Research-based standards for accessible housing

DEFF Research Database (Denmark)

Helle, Tina; Iwarsson, Susanne; Brandt, Åse

Since standards for accessible housing seldom are manifestly based on research and vary cross nationally, it is important to examine if there exists any scientific evidence, supporting these standards. Thus, one aim of this study was to review the literature in search of such scientific evidence...... data on older citizens and their housing environment in Sweden, Germany and Latvia (n=1150), collected with the Housing Enabler instrument. Applying statistical simulation we explored how different national standards for housing design influenced the prevalence of common environmental barriers. Kaplan...... by the database search (n= 2,577), resulting in the inclusion of one publication. Contacts to leading researchers in the field identified five publications. The hand search of 22 journals led to one publication. We have exemplified how the prevalence of common environmental problems in housing environments...

Study on a Threat-Countermeasure Model Based on International Standard Information

Directory of Open Access Journals (Sweden)

Guillermo Horacio Ramirez Caceres

2008-12-01

Full Text Available Many international standards exist in the field of IT security. This research is based on the ISO/IEC 15408, 15446, 19791, 13335 and 17799 standards. In this paper, we propose a knowledge base comprising a threat countermeasure model based on international standards for identifying and specifying threats which affect IT environments. In addition, the proposed knowledge base system aims at fusing similar security control policies and objectives in order to create effective security guidelines for specific IT environments. As a result, a knowledge base of security objectives was developed on the basis of the relationships inside the standards as well as the relationships between different standards. In addition, a web application was developed which displays details about the most common threats to information systems, and for each threat presents a set of related security control policies from different international standards, including ISO/IEC 27002.

Radiotherapy for pediatric brain tumors: Standard of care, current clinical trials and new directions

International Nuclear Information System (INIS)

Kun, Larry E.

1997-01-01

Objectives: To review the clinical characteristics of childhood brain tumors, including neurologic signs, neuroimaging and neuropathology. To critically assess indications for therapy relevant to presenting characteristics, age, and disease status. To discuss current management strategies including neurosurgery, radiation therapy, and chemotherapy. To analyze current clinical trials and future directions of clinical research. Brain tumors account for 20% of neoplastic diseases in children. The most common tumors include astrocytoma and malignant gliomas, medulloblastoma and supratentorial PNET's, ependymoma, craniopharyngioma, and intracranial germ cell tumors. The clinical characteristics and disease extent largely determine the relative merits of available 'standard' and investigational therapeutic approaches. Treatment outcome, including disease control and functional integrity, is dependent upon tumor type and site, age at presentation, and disease extent. An understanding of the clinical, neuroimaging, and histologic characteristics as they relate to decisions regarding therapy is critical to the radiation oncologist. Appropriate radiation therapy is central to curative therapy for a majority of pediatric brain tumor presentations. Technical advances in neurosurgery provide greater safety for 'gross total resection' in a majority of hemispheric astrocytomas and medulloblastomas. The relative roles of radiation therapy and chemotherapy for centrally located astrocytomas (e.g., diencephalic, optic pathway) need to be analyzed in the context of initial and overall disease control, neurotoxicities, and potential modifications in the risk:benefit ratio apparent in the introduction of 3-dimensional radiation techniques. Modifications in radiation delivery are important components of current investigations in medulloblastoma; the rationale for contemporary cooperative group trials will be presented as well as the background data re surgical, radiotherapeutic, and

Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface

Science.gov (United States)

Ceballos, G. A.; Hernández, L. F.

2015-04-01

Objective. The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. Approach. Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). Main results. The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. Significance. We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.

Hypertonic saline (HTS versus standard (isotonic fluid therapy for traumatic brain injuries: a systematic review

Directory of Open Access Journals (Sweden)

Andrit Lourens

2014-12-01

Full Text Available Traumatic Brain Injury (TBI is one of the foremost causes of mortality secondary to trauma. Poorer outcomes are associated with secondary insults, after the initial brain injury occurred. The management goal of TBI is to prevent or minimise the effects of secondary brain injuries. The primary objective of this systematic review/meta-analysis was to assess the effects of Hypertonic Saline (HTS compared to Standard Fluid Therapy (SFT in the treatment and resuscitation of TBI patients. We searched CENTRAL, MEDLINE (from 1966, EBSCOhost, Scopus, ScienceDirect, Proquest Medical Library and EMBASE (from 1980 in May 2010 and updated searches in February 2011. Data were assessed and extracted by two independent authors. Risk ratios (RR with a 95% confidence interval (CI were used as the effect measure. The review included three RCTs (1184 participants of which two were of high to moderate quality (1005 participants. HTS was not found to be associated with a reduction in mortality (3 RCTs, 1184 participants, RR 0.91, 95%CI 0.76 to 1.09 and morbidity in TBI patients. No significant improvement in haemodynamical stability was found whereas insufficient data were available to indicate a reduction in the intracranial pressure (ICP. In the HTS group, cerebral perfusion pressure (CPP (MD 3.83 mmHg, 95%CI 1.08 to 6.57 and serum sodium level (MD 8 mEq/L, 95%CI 7.47 to 8.53 were higher. Existing studies show no indication that HTS, in comparison to SFT, reduces mortality or morbidity after the occurrence of TBI. Against this backdrop, some uncertainties still exist in terms of the use of different concentrations and volumes of HTS, the timing of administration as well as the benefit in specific injury profiles. As a result, formulating conclusive recommendations is complex.

aMAP is a validated pipeline for registration and segmentation of high-resolution mouse brain data

Science.gov (United States)

Niedworok, Christian J.; Brown, Alexander P. Y.; Jorge Cardoso, M.; Osten, Pavel; Ourselin, Sebastien; Modat, Marc; Margrie, Troy W.

2016-01-01

The validation of automated image registration and segmentation is crucial for accurate and reliable mapping of brain connectivity and function in three-dimensional (3D) data sets. While validation standards are necessarily high and routinely met in the clinical arena, they have to date been lacking for high-resolution microscopy data sets obtained from the rodent brain. Here we present a tool for optimized automated mouse atlas propagation (aMAP) based on clinical registration software (NiftyReg) for anatomical segmentation of high-resolution 3D fluorescence images of the adult mouse brain. We empirically evaluate aMAP as a method for registration and subsequent segmentation by validating it against the performance of expert human raters. This study therefore establishes a benchmark standard for mapping the molecular function and cellular connectivity of the rodent brain. PMID:27384127

Landmark-based deep multi-instance learning for brain disease diagnosis.

Science.gov (United States)

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Brain-Based Learning and Classroom Practice: A Study Investigating Instructional Methodologies of Urban School Teachers

Science.gov (United States)

Morris, Lajuana Trezette

2010-01-01

The purpose of this study was to examine the implementation of brain-based instructional strategies by teachers serving at Title I elementary, middle, and high schools within the Memphis City School District. This study was designed to determine: (a) the extent to which Title I teachers applied brain-based strategies, (b) the differences in…

Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

DEFF Research Database (Denmark)

Bender, Thomas; Kjaer, Troels W.; Thomsen, Carsten E.

2013-01-01

This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Naïve-Bayes classifier (NBC). The system uses nine characters...

EKG-based detection of deep brain stimulation in fMRI studies.

Science.gov (United States)

Fiveland, Eric; Madhavan, Radhika; Prusik, Julia; Linton, Renee; Dimarzio, Marisa; Ashe, Jeffrey; Pilitsis, Julie; Hancu, Ileana

2018-04-01

To assess the impact of synchronization errors between the assumed functional MRI paradigm timing and the deep brain stimulation (DBS) on/off cycling using a custom electrocardiogram-based triggering system METHODS: A detector for measuring and predicting the on/off state of cycling deep brain stimulation was developed and tested in six patients in office visits. Three-electrode electrocardiogram measurements, amplified by a commercial bio-amplifier, were used as input for a custom electronics box (e-box). The e-box transformed the deep brain stimulation waveforms into transistor-transistor logic pulses, recorded their timing, and propagated it in time. The e-box was used to trigger task-based deep brain stimulation functional MRI scans in 5 additional subjects; the impact of timing accuracy on t-test values was investigated in a simulation study using the functional MRI data. Following locking to each patient's individual waveform, the e-box was shown to predict stimulation onset with an average absolute error of 112 ± 148 ms, 30 min after disconnecting from the patients. The subsecond accuracy of the e-box in predicting timing onset is more than adequate for our slow varying, 30-/30-s on/off stimulation paradigm. Conversely, the experimental deep brain stimulation onset prediction accuracy in the absence of the e-box, which could be off by as much as 4 to 6 s, could significantly decrease activation strength. Using this detector, stimulation can be accurately synchronized to functional MRI acquisitions, without adding any additional hardware in the MRI environment. Magn Reson Med 79:2432-2439, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

The Effectiveness of the Brain Based Teaching Approach in Enhancing Scientific Understanding of Newtonian Physics among Form Four Students

Science.gov (United States)

Saleh, Salmiza

2012-01-01

The aim of this study was to assess the effectiveness of Brain Based Teaching Approach in enhancing students' scientific understanding of Newtonian Physics in the context of Form Four Physics instruction. The technique was implemented based on the Brain Based Learning Principles developed by Caine & Caine (1991, 2003). This brain compatible…

A capillary-based perfusion phantom for simulation of brain perfusion for MRI; Ein kapillarbasiertes Phantom zur Simulation der Gehirnperfusion mit der Magnet-Resonanz-Tomografie

Energy Technology Data Exchange (ETDEWEB)

Maciak, A.; Kronfeld, A.; Mueller-Forell, W. [Universitaetsklinikum Mainz (Germany). Inst. fuer Neuroradiologie; Wille, C. [Fachhochschule Bingen (Germany). Inst. fuer Informatik; Kempski, O. [Universitaetsklinikum Mainz (Germany). Inst. fuer Neurochirurgische Pathophysiologie; Stoeter, P. [CEDIMAT, Santo Domingo (Dominican Republic). Inst. of Neuroradiology

2010-10-15

Purpose: The measurement of the CBF is a non-standardized procedure and there are no reliable gold standards. This abstract shows a capillary-based perfusion-phantom for CE-DSC-MRI. It has equivalent flow properties to those within the tissue capillary system of the human brain and allows the validation of the Siemens Perfusion (MR) software. Materials and Methods: The perfusion phantom consists of a dialyzer for the simulation of the capillary system, a feeding tube for simulation of the AIF and a pulsatile pump for simulation of the heart. Using this perfusion phantom, the exact determination of the gold standard CBF due to the well-known geometry of the phantom is easy. It was validated based on different perfusion measurements. These measurements were investigated with standard software (Siemens Perfusion MR). The software determined the CBF within the capillary system. Based on this CBF, a comparison to the gold standard was made with several different flow speeds. After AIF selection, a total of 726 CBF data points were automatically extracted by the software. Results: This results in a comparison of the gold standard CBF to these 726 CBF values. Therefore, a reproducible and reliable deviation estimation between gold standard CBF and measured CBF using the software was computed. It can be shown that the deviation between gold standard and software-based evaluation ranges between 1 and 31 %. Conclusion: There is no significance for any correlation between flow speed and amount of deviation. The mean measured CBF is 11.4 % higher than the gold standard CBF (p-value < 0.001). Using this kind of perfusion-phantom, the validation of different software systems allows reliable conclusions about their quality. (orig.)

Proprietary, standard, and government-supported nuclear data bases

International Nuclear Information System (INIS)

Poncelet, C.G.; Ozer, O.; Harris, D.R.

1975-07-01

This study presents an assessment of the complex situation surrounding nuclear data bases for nuclear power technology. Requirements for nuclear data bases are identified as regards engineering functions and system applications for the many and various user groups that rely on nuclear data bases. Current practices in the development and generation of nuclear data sets are described, and the competitive aspect of design nuclear data set development is noted. The past and current role of the federal government in nuclear data base development is reviewed, and the relative merits of continued government involvement are explored. National policies of the United States and other industrial countries regarding the availability of nationally supported nuclear data information are reviewed. Current proprietary policies of reactor vendors regarding design library data sets are discussed along with the basis for such proprietary policies. The legal aspects of protective policies are explored as are their impacts on the nuclear power industry as a whole. The effect of the regulatory process on the availability and documentation of nuclear data bases is examined. Current nuclear data standard developments are reviewed, including a discussion of the standard preparation process. Standards currently proposed or in preparation that directly relate to nuclear data bases are discussed in some detail. (auth)

Longitudinal volumetric changes following traumatic brain injury: a tensor-based morphometry study.

Science.gov (United States)

Farbota, Kimberly D M; Sodhi, Aparna; Bendlin, Barbara B; McLaren, Donald G; Xu, Guofan; Rowley, Howard A; Johnson, Sterling C

2012-11-01

After traumatic injury, the brain undergoes a prolonged period of degenerative change that is paradoxically accompanied by cognitive recovery. The spatiotemporal pattern of atrophy and the specific relationships of atrophy to cognitive changes are ill understood. The present study used tensor-based morphometry and neuropsychological testing to examine brain volume loss in 17 traumatic brain injury (TBI) patients and 13 controls over a 4-year period. Patients were scanned at 2 months, 1 year, and 4 years post-injury. High-dimensional warping procedures were used to create change maps of each subject's brain for each of the two intervals. TBI patients experienced volume loss in both cortical areas and white matter regions during the first interval. We also observed continuing volume loss in extensive regions of white matter during the second interval. Neuropsychological correlations indicated that cognitive tasks were associated with subsequent volume loss in task-relevant regions. The extensive volume loss in brain white matter observed well beyond the first year post-injury suggests that the injured brain remains malleable for an extended period, and the neuropsychological relationships suggest that this volume loss may be associated with subtle cognitive improvements.

Near-infrared spectroscopy (NIRS - electroencephalography (EEG based brain-state dependent electrotherapy (BSDE: A computational approach based on excitation-inhibition balance hypothesis

Directory of Open Access Journals (Sweden)

Snigdha Dagar

2016-08-01

Full Text Available Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The post stroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG and functional-near-infrared spectroscopy (fNIRS can be leveraged for Brain State Dependent Electrotherapy (BSDE. In this hypothesis and theory article, we propose a computational approach based on excitation-inhibition (E-I balance hypothesis to objectively quantify the post stroke individual brain state using online fNIRS-EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local excitation-inhibition (that is the ratio of Glutamate/GABA which may be targeted with NIBS using a computational pipeline that includes individual forward models to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons which can be captured with excitation-inhibition based brain models. Furthermore, E-I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing which can then be implicated in changes in function. We first review evidence that shows how this local imbalance between excitation-inhibition leading to functional dysfunction can be restored in targeted sites with NIBS (Motor Cortex, Somatosensory Cortex resulting in large scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Secondly, we show evidence how BSDE based on inhibition–excitation balance hypothesis may target a specific brain site or network as an adjuvant treatment

Brain core temperature of patients with mild traumatic brain injury as assessed by DWI-thermometry

Energy Technology Data Exchange (ETDEWEB)

Tazoe, Jun; Yamada, Kei; Akazawa, Kentaro [Kyoto Prefectural University of Medicine, Department of Radiology, Graduate School of Medical Science, Kyoto City, Kyoto (Japan); Sakai, Koji [Kyoto University, Department of Human Health Science, Graduate School of Medicine, Kyoto (Japan); Mineura, Katsuyoshi [Kyoto Prefectural University of Medicine, Department of Neurosurgery, Graduate School of Medical Science, Kyoto City, Kyoto (Japan)

2014-10-15

The aim of this study was to assess the brain core temperature of patients with mild traumatic brain injury (mTBI) using a noninvasive temperature measurement technique based on the diffusion coefficient of the cerebrospinal fluid. This retrospective study used the data collected from April 2008 to June 2011. The patient group comprised 20 patients with a Glasgow Coma Scale score of 14 or 15 who underwent magnetic resonance imaging within 30 days after head trauma. The normal control group comprised 14 subjects who volunteered for a brain checkup (known in Japan as ''brain dock''). We compared lateral ventricular (LV) temperature between patient and control groups. Follow-up studies were performed for four patients. LV temperature measurements were successfully performed for both patients and controls. Mean (±standard deviation) measured LV temperature was 36.9 ± 1.5 C in patients, 38.7 ± 1.8 C in follow-ups, and 37.9 ± 1.2 C in controls, showing a significant difference between patients and controls (P = 0.017). However, no significant difference was evident between patients and follow-ups (P = 0.595) or between follow-ups and controls (P = 0.465). A reduction in brain core temperature was observed in patients with mTBI, possibly due to a global decrease in metabolism. (orig.)

Brain Based Learning in Science Education in Turkey: Descriptive Content and Meta Analysis of Dissertations

Science.gov (United States)

Yasar, M. Diyaddin

2017-01-01

This study aimed at performing content analysis and meta-analysis on dissertations related to brain-based learning in science education to find out the general trend and tendency of brain-based learning in science education and find out the effect of such studies on achievement and attitude of learners with the ultimate aim of raising awareness…

Effect of cocaine on structural changes in brain: MRI volumetry using tensor-based morphometry.

Science.gov (United States)

Narayana, Ponnada A; Datta, Sushmita; Tao, Guozhi; Steinberg, Joel L; Moeller, F Gerard

2010-10-01

Magnetic resonance imaging (MRI) was performed in cocaine-dependent subjects to determine the structural changes in brain compared to non-drug using controls. Cocaine-dependent subjects and controls were carefully screened to rule out brain pathology of undetermined origin. Magnetic resonance images were analyzed using tensor-based morphometry (TBM) and voxel-based morphometry (VBM) without and with modulation to adjust for volume changes during normalization. For TBM analysis, unbiased atlases were generated using two different inverse consistent and diffeomorphic nonlinear registration techniques. Two different control groups were used for generating unbiased atlases. Independent of the nonlinear registration technique and normal cohorts used for creating the unbiased atlases, our analysis failed to detect any statistically significant effect of cocaine on brain volumes. These results show that cocaine-dependent subjects do not show differences in regional brain volumes compared to non-drug using controls. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Focusing on neuronal cell-type specific mechanisms for brain circuit organization, function and dysfunction

Institute of Scientific and Technical Information of China (English)

Lu Li

2017-01-01

Mammalian brain circuits consist of dynamically interconnected neurons with characteristic morphology, physiology, connectivity and genetics which are often called neuronal cell types. Neuronal cell types have been considered as building blocks of brain circuits, but knowledge of how neuron types or subtypes connect to and interact with each other to perform neural computation is still lacking. Such mechanistic insights are critical not only to our understanding of normal brain functions, such as perception, motion and cognition, but also to brain disorders including Alzheimer's disease, Schizophrenia and epilepsy, to name a few. Thus it is necessary to carry out systematic and standardized studies on neuronal cell-type specific mechanisms for brain circuit organization and function, which will provide good opportunities to bridge basic and clinical research. Here based on recent technology advancements, we discuss the strategy to target and manipulate specific populations of neuronsin vivo to provide unique insights on how neuron types or subtypes behave, interact, and generate emergent properties in a fully connected brain network. Our approach is highlighted by combining transgenic animal models, targeted electrophysiology and imaging with robotics, thus complete and standardized mapping ofin vivo properties of genetically defined neuron populations can be achieved in transgenic mouse models, which will facilitate the development of novel therapeutic strategies for brain disorders.

Covert orienting in the split brain: Right hemisphere specialization for object-based attention.

Science.gov (United States)

Kingstone, Alan

2015-12-18

The present paper takes as its starting point Phil Bryden's long-standing interest in human attention and the role it can play in laterality effects. Past split-brain research has suggested that object-based attention is lateralized to the left hemisphere [e.g., Egly, R., Rafal, R. D., Driver, J., & Starreveld, Y. (1994). Covert orienting in the split brain reveals hemispheric specialization for object-based attention. Psychological Science, 5(6), 380-382]. The task used to isolate object-based attention in that previous work, however, has been found wanting [Vecera, S. P. (1994). Grouped locations and object-based attention: Comment on Egly, Driver, and Rafal (1994). Journal of Experimental Psychology: General, 123(3), 316-320]; and indeed, subsequent research with healthy participants using a different task has suggested that object-based attention is lateralized to the opposite right hemisphere (RH) [Valsangkar-Smyth, M. A., Donovan, C. L., Sinnett, S., Dawson, M. R., & Kingstone, A. (2004). Hemispheric performance in object-based attention. Psychonomic Bulletin & Review, 11(1), 84-91]. The present study tested the same split-brain as Egly, Rafal, et al. (1994) but used the object-based attention task introduced by Valsangkar-Smyth et al. (2004). The results confirm that object-based attention is lateralized to the RH. They also suggest that subcortical interhemispheric competition may occur and be dominated by the RH.

Automated brain structure segmentation based on atlas registration and appearance models

DEFF Research Database (Denmark)

van der Lijn, Fedde; de Bruijne, Marleen; Klein, Stefan

2012-01-01

Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic resonance images that combines information about a structure’s location and appearance. The spatial...... with different magnetic resonance sequences, in which the hippocampus and cerebellum were segmented by an expert. Furthermore, the method is compared to two other segmentation techniques that were applied to the same data. Results show that the atlas- and appearance-based method produces accurate results...

Validation of In Vitro Cell-Based Human Blood-Brain Barrier Model Using Clinical Positron Emission Tomography Radioligands To Predict In Vivo Human Brain Penetration

International Nuclear Information System (INIS)

Mabondzo, A.; Guyot, A.C.; Bottlaender, M.; Deverre, J.R.; Tsaouin, K.; Balimane, P.V.

2010-01-01

We have evaluated a novel in vitro cell-based human blood-brain barrier (BBB) model that could predict in vivo human brain penetration for compounds with different BBB permeabilities using the clinical positron emission tomography (PET) data. Comparison studies were also performed to demonstrate that the in vitro cell-based human BBB model resulted in better predictivity over the traditional permeability model in discovery organizations, Caco-2 cells. We evaluated the in vivo BBB permeability of [ 18 F] and [ 11 C]-compounds in humans by PET imaging. The in vivo plasma-brain exchange parameters used for comparison were determined in humans by PET using a kinetic analysis of the radiotracer binding. For each radiotracer, the parameters were determined by fitting the brain kinetics of the radiotracer using a two-tissue compartment model of the ligand-receptor interaction. Bidirectional transport studies with the same compounds as in in vivo studies were carried out using the in vitro cell-based human BBB model as well as Caco-2 cells. The in vitro cell-based human BBB model has important features of the BBB in vivo and is suitable for discriminating between CNS and non-CNS marketed drugs. A very good correlation (r 2 =0.90; P≤0.001) was demonstrated between in vitro BBB permeability and in vivo permeability coefficient. In contrast, a poor correlation (r 2 = 0.17) was obtained between Caco-2 data and in vivo human brain penetration. This study highlights the potential of this in vitro cell-based human BBB model in drug discovery and shows that it can be an extremely effective screening tool for CNS programs. (authors)

Assessing paedophilia based on the haemodynamic brain response to face images

DEFF Research Database (Denmark)

Ponseti, Jorge; Granert, Oliver; Van Eimeren, Thilo

2016-01-01

that human face processing is tuned to sexual age preferences. This observation prompted us to test whether paedophilia can be inferred based on the haemodynamic brain responses to adult and child faces. METHODS: Twenty-four men sexually attracted to prepubescent boys or girls (paedophiles) and 32 men......OBJECTIVES: Objective assessment of sexual preferences may be of relevance in the treatment and prognosis of child sexual offenders. Previous research has indicated that this can be achieved by pattern classification of brain responses to sexual child and adult images. Our recent research showed...... sexually attracted to men or women (teleiophiles) were exposed to images of child and adult, male and female faces during a functional magnetic resonance imaging (fMRI) session. RESULTS: A cross-validated, automatic pattern classification algorithm of brain responses to facial stimuli yielded four...

Personality Trait and Facial Expression Filter-Based Brain-Computer Interface

Directory of Open Access Journals (Sweden)

Seongah Chin

2013-02-01

Full Text Available In this paper, we present technical approaches that bridge the gap in the research related to the use of brain-computer interfaces for entertainment and facial expressions. Such facial expressions that reflect an individual's personal traits can be used to better realize artificial facial expressions in a gaming environment based on a brain-computer interface. First, an emotion extraction filter is introduced in order to classify emotions on the basis of the users' brain signals in real time. Next, a personality trait filter is defined to classify extrovert and introvert types, which manifest as five traits: very extrovert, extrovert, medium, introvert and very introvert. In addition, facial expressions derived from expression rates are obtained by an extrovert-introvert fuzzy model through its defuzzification process. Finally, we confirm this validation via an analysis of the variance of the personality trait filter, a k-fold cross validation of the emotion extraction filter, an accuracy analysis, a user study of facial synthesis and a test case game.

AUDIT OF FINANCIAL REPORTS, BASED ON INTERNATIONAL ACCOUNTING STANDARDS

OpenAIRE

Islom Kuziev

2011-01-01

In this article are given main notion about international standard of financial reporting, order of the auditing on the base of IFRS, scheduling the report of the auditor, auditor conclusions and are given analysis of reporting based on the auditor procedures. At the audit of financial reporting are taken into account international standard to financial reporting 29 "Financial reporting in hyperinflationary economies".

The case for regime-based water quality standards

Science.gov (United States)

G.C. Poole; J.B. Dunham; D.M. Keenan; S.T. Sauter; D.A. McCullough; C. Mebane; J.C. Lockwood; D.A. Essig; M.P. Hicks; D.J. Sturdevant; E.J. Materna; S.A. Spalding; J. Risley; M. Deppman

2004-01-01

Conventional water quality standards have been successful in reducing the concentration of toxic substances in US waters. However, conventional standards are based on simple thresholds and are therefore poorly structured to address human-caused imbalances in dynamic, natural water quality parameters, such as nutrients, sediment, and temperature. A more applicable type...

Hyperbaric oxygen therapy in spontaneous brain abscess patients

DEFF Research Database (Denmark)

Bartek, Jiri; Jakola, Asgeir S; Skyrman, Simon

2016-01-01

BACKGROUND: There is a need to improve outcome in patients with brain abscesses and hyperbaric oxygen therapy (HBOT) is a promising treatment modality. The objective of this study was to evaluate HBOT in the treatment of intracranial abscesses. METHOD: This population-based, comparative cohort...... study included 40 consecutive adult patients with spontaneous brain abscess treated surgically between January 2003 and May 2014 at our institution. Twenty patients received standard therapy with surgery and antibiotics (non-HBOT group), while the remaining 20 patients also received adjuvant HBOT (HBOT...... group). RESULTS: Resolution of brain abscesses and infection was seen in all patients. Two patients had reoperations after HBOT initiation (10 %), while nine patients (45 %) in the non-HBOT group underwent reoperations (p = 0.03). Of the 26 patients who did not receive HBOT after the first surgery, 15...

The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

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Mekarina, M.; Ningsih, Y. P.

2017-09-01

This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.

Experimental investigation of the accuracy for absolute quantification of brain creatine concentration using long time echo point resolved spectroscopy sequence with an external standard and linear combination of model spectra

International Nuclear Information System (INIS)

Lin Yan; Shen Zhiwei; Xiao Yeyu; Zheng Wenbin; Wu Renhua; Li Hui; Xiao Zhuanwei

2008-01-01

Objective: To investigate the accuracy for absolute quantification of brain creatine (Cr) concentration using long time echo (TE) point resolved spectroscopy (PRESS) sequence performed with an extemal standard and postprocessed with the linear combination of model spectra ( LCModel). Methods: Ten swine (3.1 ± 0.6 kg) and an external standard phantom containing detectable compounds of known concentration were investigated in this study by using 1.5 T GE Signa scanner and a standard head coil. The single-voxel proton magnetic resonance spectroscopy ( 1 H-MRS) data were acquired from the two ROIs (2 cm x 2 cm x 2 cm) placed in swine brain and external standard solution using PRESS sequence with TE 135 ms, TR 1500 ms, and 128 scan averages. The in vivo quantification of Cr was accomplished by LCModel. After 1 H-MRS examination, each animal was sacrificed immediately. In vitro Cr concentration was analyzed by high performance liquid chromatography (HPLC). Results: In the 1 H-MRS group, the Cr concentration was (9.37±0.14)mmol/kg. In the HPLC group, the Cr concentration was (8.91± 0.13)mmol/kg. Good agreement was obtained between these two methods (t=9.038, P=0.491). Conclusion: The long echo time PRESS sequence performed with an external standard and processed with LCModel is proven to be an accurate technique to detect the in vivo brain Cr concentration. (authors)

Promoting Culturally Responsive Standards-Based Teaching

Science.gov (United States)

Saifer, Steffen; Barton, Rhonda

2007-01-01

Culturally responsive standards-based (CRSB) teaching can help bring diverse school communities together and make learning meaningful. Unlike multicultural education--which is an important way to incorporate the world's cultural and ethnic diversity into lessons--CRSB teaching draws on the experiences, understanding, views, concepts, and ways of…

Accessing the Common Core Standards for Students with Learning Disabilities: Strategies for Writing Standards-Based IEP Goals

Science.gov (United States)

Caruana, Vicki

2015-01-01

Since the reauthorization of the Individuals With Disabilities Education Act (IDEA) in 2004, standards-based individualized education plans (IEPs) have been an expectation for serving students with disabilities in the K-12 public school setting. Nearly a decade after the mandates calling for standards-based IEPs, special educators still struggle…

45 CFR 1308.16 - Eligibility criteria: Traumatic brain injury.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 4 2010-10-01 2010-10-01 false Eligibility criteria: Traumatic brain injury. 1308... DISABILITIES Health Services Performance Standards § 1308.16 Eligibility criteria: Traumatic brain injury. A child is classified as having traumatic brain injury whose brain injuries are caused by an external...

Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity.

Science.gov (United States)

Ewert, Siobhan; Plettig, Philip; Li, Ningfei; Chakravarty, M Mallar; Collins, D Louis; Herrington, Todd M; Kühn, Andrea A; Horn, Andreas

2018-04-15

Three-dimensional atlases of subcortical brain structures are valuable tools to reference anatomy in neuroscience and neurology. For instance, they can be used to study the position and shape of the three most common deep brain stimulation (DBS) targets, the subthalamic nucleus (STN), internal part of the pallidum (GPi) and ventral intermediate nucleus of the thalamus (VIM) in spatial relationship to DBS electrodes. Here, we present a composite atlas based on manual segmentations of a multimodal high resolution brain template, histology and structural connectivity. In a first step, four key structures were defined on the template itself using a combination of multispectral image analysis and manual segmentation. Second, these structures were used as anchor points to coregister a detailed histological atlas into standard space. Results show that this approach significantly improved coregistration accuracy over previously published methods. Finally, a sub-segmentation of STN and GPi into functional zones was achieved based on structural connectivity. The result is a composite atlas that defines key nuclei on the template itself, fills the gaps between them using histology and further subdivides them using structural connectivity. We show that the atlas can be used to segment DBS targets in single subjects, yielding more accurate results compared to priorly published atlases. The atlas will be made publicly available and constitutes a resource to study DBS electrode localizations in combination with modern neuroimaging methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Accurate and robust brain image alignment using boundary-based registration.

Science.gov (United States)

Greve, Douglas N; Fischl, Bruce

2009-10-15

The fine spatial scales of the structures in the human brain represent an enormous challenge to the successful integration of information from different images for both within- and between-subject analysis. While many algorithms to register image pairs from the same subject exist, visual inspection shows that their accuracy and robustness to be suspect, particularly when there are strong intensity gradients and/or only part of the brain is imaged. This paper introduces a new algorithm called Boundary-Based Registration, or BBR. The novelty of BBR is that it treats the two images very differently. The reference image must be of sufficient resolution and quality to extract surfaces that separate tissue types. The input image is then aligned to the reference by maximizing the intensity gradient across tissue boundaries. Several lower quality images can be aligned through their alignment with the reference. Visual inspection and fMRI results show that BBR is more accurate than correlation ratio or normalized mutual information and is considerably more robust to even strong intensity inhomogeneities. BBR also excels at aligning partial-brain images to whole-brain images, a domain in which existing registration algorithms frequently fail. Even in the limit of registering a single slice, we show the BBR results to be robust and accurate.

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

Science.gov (United States)

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.

Brain based learning with contextual approach to mathematics achievement

Directory of Open Access Journals (Sweden)

V Kartikaningtyas

2017-12-01

Full Text Available The aim of this study was to know the effect of Brain Based Learning (BBL with a contextual approach to mathematics achievement. BBL-contextual is the learning model that designed to develop and optimize the brain ability for getting a new concept and solving the real life problem. This study method was a quasi-experiment. The population was the junior high school students. The sample chosen by using stratified cluster random sampling. The sample was 109 students. The data collected through a mathematics achievement test that was given after the treatment. The data analyzed by using one way ANOVA. The results of the study showed that BBL-contextual is better than direct learning on mathematics achievement. It means BBL-contextual could be an effective and innovative model.

The ASEAN community-based tourism standards: looking beyond certification

OpenAIRE

Novelli, M.; Klatte, N.; Dolezal, C.

2017-01-01

This paper reports findings from an opportunity study on the appropriateness of implementing community-based tourism standards (CBTS) certification through the Association of Southeast Asian Nations (ASEAN) criteria, as a way to improve sustainable tourism provision in the region. Framed by critical reflections on community-based tourism (CBT) literature and existing sustainable tourism standards (STS) practices, qualitative research consisting of interviews with six key industry experts prov...

Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

Science.gov (United States)

Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

2017-08-01

Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

Brain-(Not) Based Education: Dangers of Misunderstanding and Misapplication of Neuroscience Research

Science.gov (United States)

Alferink, Larry A.; Farmer-Dougan, Valeri

2010-01-01

Oversimplification or inappropriate interpretation of complex neuroscience research is widespread among curricula claiming that brain-based approaches are effective for improved learning and retention. We examine recent curricula claiming to be based on neuroscience research, discuss the implications of such misinterpretation for special…

Spatial patterns of progressive brain volume loss after moderate-severe traumatic brain injury

Science.gov (United States)

Jolly, Amy; de Simoni, Sara; Bourke, Niall; Patel, Maneesh C; Scott, Gregory; Sharp, David J

2018-01-01

Abstract Traumatic brain injury leads to significant loss of brain volume, which continues into the chronic stage. This can be sensitively measured using volumetric analysis of MRI. Here we: (i) investigated longitudinal patterns of brain atrophy; (ii) tested whether atrophy is greatest in sulcal cortical regions; and (iii) showed how atrophy could be used to power intervention trials aimed at slowing neurodegeneration. In 61 patients with moderate-severe traumatic brain injury (mean age = 41.55 years ± 12.77) and 32 healthy controls (mean age = 34.22 years ± 10.29), cross-sectional and longitudinal (1-year follow-up) brain structure was assessed using voxel-based morphometry on T1-weighted scans. Longitudinal brain volume changes were characterized using a novel neuroimaging analysis pipeline that generates a Jacobian determinant metric, reflecting spatial warping between baseline and follow-up scans. Jacobian determinant values were summarized regionally and compared with clinical and neuropsychological measures. Patients with traumatic brain injury showed lower grey and white matter volume in multiple brain regions compared to controls at baseline. Atrophy over 1 year was pronounced following traumatic brain injury. Patients with traumatic brain injury lost a mean (± standard deviation) of 1.55% ± 2.19 of grey matter volume per year, 1.49% ± 2.20 of white matter volume or 1.51% ± 1.60 of whole brain volume. Healthy controls lost 0.55% ± 1.13 of grey matter volume and gained 0.26% ± 1.11 of white matter volume; equating to a 0.22% ± 0.83 reduction in whole brain volume. Atrophy was greatest in white matter, where the majority (84%) of regions were affected. This effect was independent of and substantially greater than that of ageing. Increased atrophy was also seen in cortical sulci compared to gyri. There was no relationship between atrophy and time since injury or age at baseline. Atrophy rates were related to memory performance at the end of the

Detecting brain growth patterns in normal children using tensor-based morphometry.

Science.gov (United States)

Hua, Xue; Leow, Alex D; Levitt, Jennifer G; Caplan, Rochelle; Thompson, Paul M; Toga, Arthur W

2009-01-01

Previous magnetic resonance imaging (MRI)-based volumetric studies have shown age-related increases in the volume of total white matter and decreases in the volume of total gray matter of normal children. Recent adaptations of image analysis strategies enable the detection of human brain growth with improved spatial resolution. In this article, we further explore the spatio-temporal complexity of adolescent brain maturation with tensor-based morphometry. By utilizing a novel non-linear elastic intensity-based registration algorithm on the serial structural MRI scans of 13 healthy children, individual Jacobian growth maps are generated and then registered to a common anatomical space. Statistical analyses reveal significant tissue growth in cerebral white matter, contrasted with gray matter loss in parietal, temporal, and occipital lobe. In addition, a linear regression with age and gender suggests a slowing down of the growth rate in regions with the greatest white matter growth. We demonstrate that a tensor-based Jacobian map is a sensitive and reliable method to detect regional tissue changes during development. (c) 2007 Wiley-Liss, Inc.

Correlation between subacute sensorimotor deficits and brain water content after surgical brain injury in rats

OpenAIRE

McBride, Devin W.; Wang, Yuechun; Sherchan, Prativa; Tang, Jiping; Zhang, John H.

2015-01-01

Brain edema is a major contributor to poor outcome and reduced quality of life after surgical brain injury (SBI). Although SBI pathophysiology is well-known, the correlation between cerebral edema and neurological deficits has not been thoroughly examined in the rat model of SBI. Thus, the purpose of this study was to determine the correlation between brain edema and deficits in standard sensorimotor neurobehavior tests for rats subjected to SBI. Sixty male Sprague-Dawley rats were subjected ...

Brain involvement in patients with inflammatory bowel disease: a voxel-based morphometry and diffusion tensor imaging study.

Science.gov (United States)

Zikou, Anastasia K; Kosmidou, Maria; Astrakas, Loukas G; Tzarouchi, Loukia C; Tsianos, Epameinondas; Argyropoulou, Maria I

2014-10-01

To investigate structural brain changes in inflammatory bowel disease (IBD). Brain magnetic resonance imaging (MRI) was performed on 18 IBD patients (aged 45.16 ± 14.71 years) and 20 aged-matched control subjects. The imaging protocol consisted of a sagittal-FLAIR, a T1-weighted high-resolution three-dimensional spoiled gradient-echo sequence, and a multisession spin-echo echo-planar diffusion-weighted sequence. Differences between patients and controls in brain volume and diffusion indices were evaluated using the voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) methods, respectively. The presence of white-matter hyperintensities (WMHIs) was evaluated on FLAIR images. VBM revealed decreased grey matter (GM) volume in patients in the fusiform and the inferior temporal gyrus bilaterally, the right precentral gyrus, the right supplementary motor area, the right middle frontal gyrus and the left superior parietal gyrus (p tensor imaging detects microstructural brain abnormalities in IBD. • Voxel based morphometry reveals brain atrophy in IBD.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

Science.gov (United States)

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

Allen Brain Atlas-Driven Visualizations: a web-based gene expression energy visualization tool.

Science.gov (United States)

Zaldivar, Andrew; Krichmar, Jeffrey L

2014-01-01

The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

Allen Brain Atlas-Driven Visualizations: A Web-Based Gene Expression Energy Visualization Tool

Directory of Open Access Journals (Sweden)

Andrew eZaldivar

2014-05-01

Full Text Available The Allen Brain Atlas-Driven Visualizations (ABADV is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources.

Design and validation of a standards-based science teacher efficacy instrument

Science.gov (United States)

Kerr, Patricia Reda

National standards for K--12 science education address all aspects of science education, with their main emphasis on curriculum---both science subject matter and the process involved in doing science. Standards for science teacher education programs have been developing along a parallel plane, as is self-efficacy research involving classroom teachers. Generally, studies about efficacy have been dichotomous---basing the theoretical underpinnings on the work of either Rotter's Locus of Control theory or on Bandura's explanations of efficacy beliefs and outcome expectancy. This study brings all three threads together---K--12 science standards, teacher education standards, and efficacy beliefs---in an instrument designed to measure science teacher efficacy with items based on identified critical attributes of standards-based science teaching and learning. Based on Bandura's explanation of efficacy being task-specific and having outcome expectancy, a developmental, systematic progression from standards-based strategies and activities to tasks to critical attributes was used to craft items for a standards-based science teacher efficacy instrument. Demographic questions related to school characteristics, teacher characteristics, preservice background, science teaching experience, and post-certification professional development were included in the instrument. The instrument was completed by 102 middle level science teachers, with complete data for 87 teachers. A principal components analysis of the science teachers' responses to the instrument resulted in two components: Standards-Based Science Teacher Efficacy: Beliefs About Teaching (BAT, reliability = .92) and Standards-Based Science Teacher Efficacy: Beliefs About Student Achievement (BASA, reliability = .82). Variables that were characteristic of professional development activities, science content preparation, and school environment were identified as members of the sets of variables predicting the BAT and BASA

Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface

Science.gov (United States)

Chen, Xiaogang; Wang, Yijun; Gao, Shangkai; Jung, Tzyy-Ping; Gao, Xiaorong

2015-08-01

Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. Approach. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. Main results. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ˜33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min-1. Significance. By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.

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.

Structural MRI-based discrimination between autistic and typically developing brain

Energy Technology Data Exchange (ETDEWEB)

Fahmi, R; Hassan, H; Farag, A A [CVIP Lab., Univ. of Louisville, KY (United States); Elbaz, A [Dept. of Bioengineering, Univ. of Louisville, KY (United States); Casanova, M F [Dept. of Psychiatry and Behavioral science, Univ. of Louisville, KY (United States)

2007-06-15

Autism is a neurodevelopmental disorder characterized by marked deficits in communication, social interaction, and interests. Various studies of autism have suggested abnormalities in several brain regions, with an increasing agreement on the abnormal anatomy of the white matter (WM) and on deficits in the size of the corpus callosum (CC) and its sub-regions in autism. In this paper, we aim at using these abnormalities in order to devise robust classification methods of autistic vs. typically developing brains by analyzing their respective MRIs. Our analysis is based on shape descriptions and geometric models. We compute the 3D distance map to describe the shape of the WM, and use it as a statistical feature to discriminate between the two groups. We also use our recently proposed non-rigid registration technique to devise another classification approach by statistically analyzing and comparing the deformation fields generated from registering segmented CC's onto each others. The proposed techniques are tested on postmortem and on in-vivo brain MR data. At the 85% confidence level the WM-based classification algorithm correctly classified 14/14 postmortem-autistics and 12/12 in-vivo autistics, a 100% accuracy rate, and 13/15 postmortem controls (86% accuracy rate) and 30/30 in-vivo controls (100% accuracy rate). The technique based on the analysis of the CC was applied only on the in vivo data. At the 85% confidence rate, this technique correctly classified 10/15 autistics, a 0.66 accuracy rate, and 29/30 controls, a 0.96 accuracy rate. These results are very promising and show that, contrary to traditional methods, the proposed techniques are less sensitive to age and volume effects. (orig.)

Structural MRI-based discrimination between autistic and typically developing brain

International Nuclear Information System (INIS)

Fahmi, R.; Hassan, H.; Farag, A.A.; Elbaz, A.; Casanova, M.F.

2007-01-01

Autism is a neurodevelopmental disorder characterized by marked deficits in communication, social interaction, and interests. Various studies of autism have suggested abnormalities in several brain regions, with an increasing agreement on the abnormal anatomy of the white matter (WM) and on deficits in the size of the corpus callosum (CC) and its sub-regions in autism. In this paper, we aim at using these abnormalities in order to devise robust classification methods of autistic vs. typically developing brains by analyzing their respective MRIs. Our analysis is based on shape descriptions and geometric models. We compute the 3D distance map to describe the shape of the WM, and use it as a statistical feature to discriminate between the two groups. We also use our recently proposed non-rigid registration technique to devise another classification approach by statistically analyzing and comparing the deformation fields generated from registering segmented CC's onto each others. The proposed techniques are tested on postmortem and on in-vivo brain MR data. At the 85% confidence level the WM-based classification algorithm correctly classified 14/14 postmortem-autistics and 12/12 in-vivo autistics, a 100% accuracy rate, and 13/15 postmortem controls (86% accuracy rate) and 30/30 in-vivo controls (100% accuracy rate). The technique based on the analysis of the CC was applied only on the in vivo data. At the 85% confidence rate, this technique correctly classified 10/15 autistics, a 0.66 accuracy rate, and 29/30 controls, a 0.96 accuracy rate. These results are very promising and show that, contrary to traditional methods, the proposed techniques are less sensitive to age and volume effects. (orig.)

Structural MRI-based discrimination between autistic and typically developing brain

Energy Technology Data Exchange (ETDEWEB)

Fahmi, R.; Hassan, H.; Farag, A.A. [CVIP Lab., Univ. of Louisville, KY (United States); Elbaz, A. [Dept. of Bioengineering, Univ. of Louisville, KY (United States); Casanova, M.F. [Dept. of Psychiatry and Behavioral science, Univ. of Louisville, KY (United States)

2007-06-15

Autism is a neurodevelopmental disorder characterized by marked deficits in communication, social interaction, and interests. Various studies of autism have suggested abnormalities in several brain regions, with an increasing agreement on the abnormal anatomy of the white matter (WM) and on deficits in the size of the corpus callosum (CC) and its sub-regions in autism. In this paper, we aim at using these abnormalities in order to devise robust classification methods of autistic vs. typically developing brains by analyzing their respective MRIs. Our analysis is based on shape descriptions and geometric models. We compute the 3D distance map to describe the shape of the WM, and use it as a statistical feature to discriminate between the two groups. We also use our recently proposed non-rigid registration technique to devise another classification approach by statistically analyzing and comparing the deformation fields generated from registering segmented CC's onto each others. The proposed techniques are tested on postmortem and on in-vivo brain MR data. At the 85% confidence level the WM-based classification algorithm correctly classified 14/14 postmortem-autistics and 12/12 in-vivo autistics, a 100% accuracy rate, and 13/15 postmortem controls (86% accuracy rate) and 30/30 in-vivo controls (100% accuracy rate). The technique based on the analysis of the CC was applied only on the in vivo data. At the 85% confidence rate, this technique correctly classified 10/15 autistics, a 0.66 accuracy rate, and 29/30 controls, a 0.96 accuracy rate. These results are very promising and show that, contrary to traditional methods, the proposed techniques are less sensitive to age and volume effects. (orig.)

Extendable supervised dictionary learning for exploring diverse and concurrent brain activities in task-based fMRI.

Science.gov (United States)

Zhao, Shijie; Han, Junwei; Hu, Xintao; Jiang, Xi; Lv, Jinglei; Zhang, Tuo; Zhang, Shu; Guo, Lei; Liu, Tianming

2018-06-01

Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional magnetic resonance imaging (tfMRI) analysis approach, i.e., the general linear model (GLM), might have difficulty in discovering those diverse and concurrent brain responses sufficiently. This subtraction-based model-driven approach focuses on the brain activities evoked directly from the task paradigm, thus likely overlooks other possible concurrent brain activities evoked during the information processing. To deal with this problem, in this paper, we propose a novel hybrid framework, called extendable supervised dictionary learning (E-SDL), to explore diverse and concurrent brain activities under task conditions. A critical difference between E-SDL framework and previous methods is that we systematically extend the basic task paradigm regressor into meaningful regressor groups to account for possible regressor variation during the information processing procedure in the brain. Applications of the proposed framework on five independent and publicly available tfMRI datasets from human connectome project (HCP) simultaneously revealed more meaningful group-wise consistent task-evoked networks and common intrinsic connectivity networks (ICNs). These results demonstrate the advantage of the proposed framework in identifying the diversity of concurrent brain activities in tfMRI datasets.

Citizen Observatories: A Standards Based Architecture

Science.gov (United States)

Simonis, Ingo

2015-04-01

A number of large-scale research projects are currently under way exploring the various components of citizen observatories, e.g. CITI-SENSE (http://www.citi-sense.eu), Citclops (http://citclops.eu), COBWEB (http://cobwebproject.eu), OMNISCIENTIS (http://www.omniscientis.eu), and WeSenseIt (http://www.wesenseit.eu). Common to all projects is the motivation to develop a platform enabling effective participation by citizens in environmental projects, while considering important aspects such as security, privacy, long-term storage and availability, accessibility of raw and processed data and its proper integration into catalogues and international exchange and collaboration systems such as GEOSS or INSPIRE. This paper describes the software architecture implemented for setting up crowdsourcing campaigns using standardized components, interfaces, security features, and distribution capabilities. It illustrates the Citizen Observatory Toolkit, a software suite that allows defining crowdsourcing campaigns, to invite registered and unregistered participants to participate in crowdsourcing campaigns, and to analyze, process, and visualize raw and quality enhanced crowd sourcing data and derived products. The Citizen Observatory Toolkit is not a single software product. Instead, it is a framework of components that are built using internationally adopted standards wherever possible (e.g. OGC standards from Sensor Web Enablement, GeoPackage, and Web Mapping and Processing Services, as well as security and metadata/cataloguing standards), defines profiles of those standards where necessary (e.g. SWE O&M profile, SensorML profile), and implements design decisions based on the motivation to maximize interoperability and reusability of all components. The toolkit contains tools to set up, manage and maintain crowdsourcing campaigns, allows building on-demand apps optimized for the specific sampling focus, supports offline and online sampling modes using modern cell phones with

BEaST: brain extraction based on nonlocal segmentation technique

NARCIS (Netherlands)

Eskildsen, Simon F.; Coupé, Pierrick; Fonov, Vladimir; Manjón, José V.; Leung, Kelvin K.; Guizard, Nicolas; Wassef, Shafik N.; Østergaard, Lasse Riis; Collins, D. Louis; Saradha, A.; Abdi, Hervé; Abdulkadir, Ahmed; Acharya, Deepa; Achuthan, Anusha; Adluru, Nagesh; Aghajanian, Jania; Agrusti, Antonella; Agyemang, Alex; Ahdidan, Jamila; Ahmad, Duaa; Ahmed, Shiek; Aisen, Paul; Akhondi-Asl, Alireza; Aksu, Yaman; Alberca, Roman; Alcauter, Sarael; Alexander, Daniel; Alin, Aylin; Almeida, Fabio; Alvarez-Linera, Juan; Amlien, Inge; Anand, Shyam; Anderson, Dallas; Ang, Amma; Angersbach, Steve; Ansarian, Reza; Aoyama, Eiji; Appannah, Arti; Arfanakis, Konstantinos; Armor, Tom; Arrighi, Michael; Arumughababu, S. Vethanayaki; Arunagiri, Vidhya; Ashe-McNalley, Cody; Ashford, Wes; Le Page, Aurelie; Avants, Brian; Chen, Wei; Richard, Edo; Schmand, Ben

2012-01-01

Brain extraction is an important step in the analysis of brain images. The variability in brain morphology and the difference in intensity characteristics due to imaging sequences make the development of a general purpose brain extraction algorithm challenging. To address this issue, we propose a

Addition of visual noise boosts evoked potential-based brain-computer interface.

Science.gov (United States)

Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili

2014-05-14

Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7-36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs.

Quantum-like model of processing of information in the brain based on classical electromagnetic field.

Science.gov (United States)

Khrennikov, Andrei

2011-09-01

We propose a model of quantum-like (QL) processing of mental information. This model is based on quantum information theory. However, in contrast to models of "quantum physical brain" reducing mental activity (at least at the highest level) to quantum physical phenomena in the brain, our model matches well with the basic neuronal paradigm of the cognitive science. QL information processing is based (surprisingly) on classical electromagnetic signals induced by joint activity of neurons. This novel approach to quantum information is based on representation of quantum mechanics as a version of classical signal theory which was recently elaborated by the author. The brain uses the QL representation (QLR) for working with abstract concepts; concrete images are described by classical information theory. Two processes, classical and QL, are performed parallely. Moreover, information is actively transmitted from one representation to another. A QL concept given in our model by a density operator can generate a variety of concrete images given by temporal realizations of the corresponding (Gaussian) random signal. This signal has the covariance operator coinciding with the density operator encoding the abstract concept under consideration. The presence of various temporal scales in the brain plays the crucial role in creation of QLR in the brain. Moreover, in our model electromagnetic noise produced by neurons is a source of superstrong QL correlations between processes in different spatial domains in the brain; the binding problem is solved on the QL level, but with the aid of the classical background fluctuations. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Teachers' Perceptions of the Efficacy of Standards-Based IEP Goals

Science.gov (United States)

Smith, Traci Nicole

2013-01-01

Although standards-based IEP goals have been mandated in many states for almost a decade, their effectiveness is unknown. Standards-based IEP goals were first created to meet the requirements of No Child Left Behind and Individuals with Disabilities Education Improvement Act, which increased accountability for all students as well as those with…

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

Science.gov (United States)

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Standardized computer-based organized reporting of EEG SCORE - Second version

DEFF Research Database (Denmark)

Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C

2017-01-01

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the se......Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted...... in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE....... In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE...

Spatial patterns of progressive brain volume loss after moderate-severe traumatic brain injury.

Science.gov (United States)

Cole, James H; Jolly, Amy; de Simoni, Sara; Bourke, Niall; Patel, Maneesh C; Scott, Gregory; Sharp, David J

2018-01-04

Traumatic brain injury leads to significant loss of brain volume, which continues into the chronic stage. This can be sensitively measured using volumetric analysis of MRI. Here we: (i) investigated longitudinal patterns of brain atrophy; (ii) tested whether atrophy is greatest in sulcal cortical regions; and (iii) showed how atrophy could be used to power intervention trials aimed at slowing neurodegeneration. In 61 patients with moderate-severe traumatic brain injury (mean age = 41.55 years ± 12.77) and 32 healthy controls (mean age = 34.22 years ± 10.29), cross-sectional and longitudinal (1-year follow-up) brain structure was assessed using voxel-based morphometry on T1-weighted scans. Longitudinal brain volume changes were characterized using a novel neuroimaging analysis pipeline that generates a Jacobian determinant metric, reflecting spatial warping between baseline and follow-up scans. Jacobian determinant values were summarized regionally and compared with clinical and neuropsychological measures. Patients with traumatic brain injury showed lower grey and white matter volume in multiple brain regions compared to controls at baseline. Atrophy over 1 year was pronounced following traumatic brain injury. Patients with traumatic brain injury lost a mean (± standard deviation) of 1.55% ± 2.19 of grey matter volume per year, 1.49% ± 2.20 of white matter volume or 1.51% ± 1.60 of whole brain volume. Healthy controls lost 0.55% ± 1.13 of grey matter volume and gained 0.26% ± 1.11 of white matter volume; equating to a 0.22% ± 0.83 reduction in whole brain volume. Atrophy was greatest in white matter, where the majority (84%) of regions were affected. This effect was independent of and substantially greater than that of ageing. Increased atrophy was also seen in cortical sulci compared to gyri. There was no relationship between atrophy and time since injury or age at baseline. Atrophy rates were related to memory performance at the end of the follow

Neuromyelitis optica immunoglobulin G in Chinese patients detected by immunofluorescence assay on a monkey brain substrate.

Science.gov (United States)

Long, Youming; Hu, Xueqiang; Peng, Fuhua; Lu, Zhengqi; Wang, Yuge; Yang, Yu; Qiu, Wei

2012-01-01

Serum neuromyelitis optica immunoglobulin G (NMO-IgG) is used as a biomarker to differentiate between neuromyelitis optica (NMO) and multiple sclerosis (MS). However, the original assay is expensive and complex and shows low sensitivity. Here, we investigated the potential of NMO-IgG detection using an indirect immunofluorescence (IIF) assay on monkey brains. NMO-IgG seroprevalence was determined in 168 samples by an IIF assay on a monkey brain substrate. The data were compared with those from a standard mouse brain IIF assay using McNemar and kappa tests. Thirty-one of 50 (62%) NMO patients, 7 of 18 (38.9%) longitudinally extensive transverse myelitis patients, 6 of 57 (10.5%) MS patients, and 5 of 10 (50%) optic neuritis patients were seropositive for NMO-IgG. None of the acute partial transverse myelitis patients (n = 3) or healthy controls (n = 20) was positive. Thus, the sensitivity of the test was 62% for the patients with clinically definite NMO. The specificity was 89.5%, considering the 57 MS patients as the control group. The modified IIF assay on monkey brains and the standard IIF assay based on mouse brains were not significantly different (McNemar test; p = 1.000). The two assays were concordant in 39 seropositive samples and 100 seronegative samples (kappa test; kappa = 0.592, p monkey brain assay was no better than the standard mouse brain IIF assay, we affirmed that NMO-IgG is a sensitive and specific biomarker to differentiate between NMO and MS. Copyright © 2011 S. Karger AG, Basel.

Monitoring and Prognosis System Based on the ICF for People with Traumatic Brain Injury

Directory of Open Access Journals (Sweden)

Laia Subirats

2015-08-01

Full Text Available The objective of this research is to provide a standardized platform to monitor and predict indicators of people with traumatic brain injury using the International Classification of Functioning, Disability and Health, and analyze its potential benefits for people with disabilities, health centers and administrations. We developed a platform that allows automatic standardization and automatic graphical representations of indicators of the status of individuals and populations. We used data from 730 people with acquired brain injury performing periodic comprehensive evaluations in the years 2006–2013. Health professionals noted that the use of color-coded graphical representation is useful for quickly diagnose failures, limitations or restrictions in rehabilitation. The prognosis system achieves 41% of accuracy and sensitivity in the prediction of emotional functions, and 48% of accuracy and sensitivity in the prediction of executive functions. This monitoring and prognosis system has the potential to: (1 save costs and time, (2 provide more information to make decisions, (3 promote interoperability, (4 facilitate joint decision-making, and (5 improve policies of socioeconomic evaluation of the burden of disease. Professionals found the monitoring system useful because it generates a more comprehensive understanding of health oriented to the profile of the patients, instead of their diseases and injuries.

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

Directory of Open Access Journals (Sweden)

Gaoxing Zheng

2018-03-01

Full Text Available The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST has been increasingly applied, while the average reference (AR was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening. The analysis results revealed the following observations: (1 there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2 there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3 the global brain functional connectivity density (FCD and local FCD have higher values for REST than for AR under different behavior states; and (4 the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.

Partial synthesis of ganglioside and lysoganglioside lipoforms as internal standards for MS quantification.

Science.gov (United States)

Gantner, Martin; Schwarzmann, Günter; Sandhoff, Konrad; Kolter, Thomas

2014-12-01

Within recent years, ganglioside patterns have been increasingly analyzed by MS. However, internal standards for calibration are only available for gangliosides GM1, GM2, and GM3. For this reason, we prepared homologous internal standards bearing nonnatural fatty acids of the major mammalian brain gangliosides GM1, GD1a, GD1b, GT1b, and GQ1b, and of the tumor-associated gangliosides GM2 and GD2. The fatty acid moieties were incorporated after selective chemical or enzymatic deacylation of bovine brain gangliosides. For modification of the sphingoid bases, we developed a new synthetic method based on olefin cross metathesis. This method was used for the preparation of a lyso-GM1 and a lyso-GM2 standard. The total yield of this method was 8.7% for the synthesis of d17:1-lyso-GM1 from d20:1/18:0-GM1 in four steps. The title compounds are currently used as calibration substances for MS quantification and are also suitable for functional studies. Copyright © 2014 by the American Society for Biochemistry and Molecular Biology, Inc.

Mathematical model in post-mortem estimation of brain edema using morphometric parameters.

Science.gov (United States)

Radojevic, Nemanja; Radnic, Bojana; Vucinic, Jelena; Cukic, Dragana; Lazovic, Ranko; Asanin, Bogdan; Savic, Slobodan

2017-01-01

Current autopsy principles for evaluating the existence of brain edema are based on a macroscopic subjective assessment performed by pathologists. The gold standard is a time-consuming histological verification of the presence of the edema. By measuring the diameters of the cranial cavity, as individually determined morphometric parameters, a mathematical model for rapid evaluation of brain edema was created, based on the brain weight measured during the autopsy. A cohort study was performed on 110 subjects, divided into two groups according to the histological presence or absence of (the - deleted from the text) brain edema. In all subjects, the following measures were determined: the volume and the diameters of the cranial cavity (longitudinal and transverse distance and height), the brain volume, and the brain weight. The complex mathematical algorithm revealed a formula for the coefficient ε, which is useful to conclude whether a brain edema is present or not. The average density of non-edematous brain is 0.967 g/ml, while the average density of edematous brain is 1.148 g/ml. The resulting formula for the coefficient ε is (5.79 x longitudinal distance x transverse distance)/brain weight. Coefficient ε can be calculated using measurements of the diameters of the cranial cavity and the brain weight, performed during the autopsy. If the resulting ε is less than 0.9484, it could be stated that there is cerebral edema with a reliability of 98.5%. The method discussed in this paper aims to eliminate the burden of relying on subjective assessments when determining the presence of a brain edema. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Correction of the acid-base balance in the presence of the hypoxic-ischemic brain damage in newborns

Directory of Open Access Journals (Sweden)

K. S. Kiriakov

2018-01-01

Full Text Available One of the current problems of perinatal neurology is the hypoxic-ischemic brain damage in newborns associated with the influence of the hypoxia upon the fetus, intranatal and postnatal asphyxia on one hand and a lack of the efficient therapy schemes on the other hand. Due to this, the purpose of this pilotstudy isto identify the effects of drug Cytoflavin, included into the complex therapy scheme for the newborns with the cerebral ischemia of II-III stages, on the blood acid-base balance. A retrospective analysis of the results of the complex therapy for 16 newborns with the moderate (14 children and severe (2 children brain ischemia was performed. Cytoflavin was included in the standard therapy schemes for all children at a dose of 2 ml/kg per day at a dilution of 5% glucose solution at the ratio of 1:5, intravenously, microfluidically for 20 hours for 3 days. In addition to the standard examination, the blood acid-base balance assessment using the follow-up microgasometric method was included (after 60 min and then every 6 hours until 72 hours of observation. All children had positive tendency to the arresting of the metabolic acidosis (in the form of the decrease of the base deficiency after 24 hours and increase of pH level (the level of 7.30 was reached by 12 hours of age in full-term newborns and 24 hour of age in the preterm newborns. The revealed positive changes in the time of the metabolic acidosis arresting along with the small volumes of the infusion and good tolerability are the cause for the planning of the subsequent, more large-scale studies. 

Flexible deep brain neural probes based on a parylene tube structure

Science.gov (United States)

Zhao, Zhiguo; Kim, Eric; Luo, Hao; Zhang, Jinsheng; Xu, Yong

2018-01-01

Most microfabricated neural probes have limited shank length, which prevents them from reaching many deep brain structures. This paper reports deep brain neural probes with ultra-long penetrating shanks based on a simple but novel parylene tube structure. The mechanical strength of the parylene tube shank is temporarily enhanced during implantation by inserting a metal wire. The metal wire can be removed after implantation, making the implanted probe very flexible and thus minimizing the stress caused by micromotions of brain tissues. Optogenetic stimulation and chemical delivery capabilities can be potentially integrated by taking advantage of the tube structure. Single-shank prototypes with a shank length of 18.2 mm have been developed. The microfabrication process comprises of deep reactive ion etching (DRIE) of silicon, parylene conformal coating/refilling, and XeF2 isotropic silicon etching. In addition to bench-top insertion characterization, the functionality of developed probes has been preliminarily demonstrated by implanting into the amygdala of a rat and recording neural signals.

Brain-volume changes in young and middle-aged smokers: a DARTEL-based voxel-based morphometry study.

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Peng, Peng; Wang, Zhenchang; Jiang, Tao; Chu, Shuilian; Wang, Shuangkun; Xiao, Dan

2017-09-01

Many studies have reported brain volume changes in smokers. However, the volume differences of grey matter (GM) and white matter (WM) in young and middle-aged male smokers with different lifetime tobacco consumption (pack-years) remain uncertain. To examine the brain volume change, especially whether more pack-years smoking would be associated with smaller gray matter and white matter volume in young and middle-aged male smokers. We used a 3T MR scanner and performed Diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL)-based voxel-based morphometry on 53 long-term male smokers (30.72 ± 4.19 years) and 53 male healthy non-smokers (30.83 ± 5.18 years). We separated smokers to light and heavy smokers by pack-years and compared brain volume between different smoker groups and non-smokers. And then we did analysis of covariance (ANCOVA) between smokers and non-smokers by setting pack-years as covariates. Light and heavy smokers all displayed smaller GM and WM volume than non-smokers and more obviously in heavy smokers. The main smaller areas in light and heavy smokers were superior temporal gyrus, insula, middle occipital gyrus, posterior cingulate, precuneus in GM and posterior cingulate, thalamus and midbrain in WM, in addition, we also observed more pack-years smoking was associated with some certain smaller GM and WM volumes by ANCOVA. Young and middle-aged male smokers had many smaller brain areas than non-smokers. Some of these areas' volume had negative correlation with pack-years, while some had not. These may due to different pathophysiological role of smokings. © 2015 John Wiley & Sons Ltd.

An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

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Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-12-07

Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

REVIEWS OF TOPICAL PROBLEMS: Nonlinear dynamics of the brain: emotion and cognition

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Rabinovich, Mikhail I.; Muezzinoglu, M. K.

2010-07-01

Experimental investigations of neural system functioning and brain activity are standardly based on the assumption that perceptions, emotions, and cognitive functions can be understood by analyzing steady-state neural processes and static tomographic snapshots. The new approaches discussed in this review are based on the analysis of transient processes and metastable states. Transient dynamics is characterized by two basic properties, structural stability and information sensitivity. The ideas and methods that we discuss provide an explanation for the occurrence of and successive transitions between metastable states observed in experiments, and offer new approaches to behavior analysis. Models of the emotional and cognitive functions of the brain are suggested. The mathematical object that represents the observed transient brain processes in the phase space of the model is a structurally stable heteroclinic channel. The possibility of using the suggested models to construct a quantitative theory of some emotional and cognitive functions is illustrated.

Comparison between MRI-based attenuation correction methods for brain PET in dementia patients

International Nuclear Information System (INIS)

Cabello, Jorge; Lukas, Mathias; Pyka, Thomas; Nekolla, Stephan G.; Ziegler, Sibylle I.; Rota Kops, Elena; Shah, N. Jon; Ribeiro, Andre; Yakushev, Igor

2016-01-01

The combination of Positron Emission Tomography (PET) with magnetic resonance imaging (MRI) in hybrid PET/MRI scanners offers a number of advantages in investigating brain structure and function. A critical step of PET data reconstruction is attenuation correction (AC). Accounting for bone in attenuation maps (μ-map) was shown to be important in brain PET studies. While there are a number of MRI-based AC methods, no systematic comparison between them has been performed so far. The aim of this work was to study the different performance obtained by some of the recent methods presented in the literature. To perform such a comparison, we focused on [ 18 F]-Fluorodeoxyglucose-PET/MRI neurodegenerative dementing disorders, which are known to exhibit reduced levels of glucose metabolism in certain brain regions. Four novel methods were used to calculate μ-maps from MRI data of 15 patients with Alzheimer's dementia (AD). The methods cover two atlas-based methods, a segmentation method, and a hybrid template/segmentation method. Additionally, the Dixon-based and a UTE-based method, offered by a vendor, were included in the comparison. Performance was assessed at three levels: tissue identification accuracy in the μ-map, quantitative accuracy of reconstructed PET data in specific brain regions, and precision in diagnostic images at identifying hypometabolic areas. Quantitative regional errors of -20-10 % were obtained using the vendor's AC methods, whereas the novel methods produced errors in a margin of ±5 %. The obtained precision at identifying areas with abnormally low levels of glucose uptake, potentially regions affected by AD, were 62.9 and 79.5 % for the two vendor AC methods, the former ignoring bone and the latter including bone information. The precision increased to 87.5-93.3 % in average for the four new methods, exhibiting similar performances. We confirm that the AC methods based on the Dixon and UTE sequences provided by the vendor are inferior

Comparison between MRI-based attenuation correction methods for brain PET in dementia patients

Energy Technology Data Exchange (ETDEWEB)

Cabello, Jorge; Lukas, Mathias; Pyka, Thomas; Nekolla, Stephan G.; Ziegler, Sibylle I. [Technische Universitaet Muenchen, Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Munich (Germany); Rota Kops, Elena; Shah, N. Jon [Forschungszentrum Juelich GmbH, Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Juelich (Germany); Ribeiro, Andre [Forschungszentrum Juelich GmbH, Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Juelich (Germany); Institute of Biophysics and Biomedical Engineering, Lisbon (Portugal); Yakushev, Igor [Technische Universitaet Muenchen, Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Munich (Germany); Institute TUM Neuroimaging Center (TUM-NIC), Munich (Germany)

2016-11-15

The combination of Positron Emission Tomography (PET) with magnetic resonance imaging (MRI) in hybrid PET/MRI scanners offers a number of advantages in investigating brain structure and function. A critical step of PET data reconstruction is attenuation correction (AC). Accounting for bone in attenuation maps (μ-map) was shown to be important in brain PET studies. While there are a number of MRI-based AC methods, no systematic comparison between them has been performed so far. The aim of this work was to study the different performance obtained by some of the recent methods presented in the literature. To perform such a comparison, we focused on [{sup 18}F]-Fluorodeoxyglucose-PET/MRI neurodegenerative dementing disorders, which are known to exhibit reduced levels of glucose metabolism in certain brain regions. Four novel methods were used to calculate μ-maps from MRI data of 15 patients with Alzheimer's dementia (AD). The methods cover two atlas-based methods, a segmentation method, and a hybrid template/segmentation method. Additionally, the Dixon-based and a UTE-based method, offered by a vendor, were included in the comparison. Performance was assessed at three levels: tissue identification accuracy in the μ-map, quantitative accuracy of reconstructed PET data in specific brain regions, and precision in diagnostic images at identifying hypometabolic areas. Quantitative regional errors of -20-10 % were obtained using the vendor's AC methods, whereas the novel methods produced errors in a margin of ±5 %. The obtained precision at identifying areas with abnormally low levels of glucose uptake, potentially regions affected by AD, were 62.9 and 79.5 % for the two vendor AC methods, the former ignoring bone and the latter including bone information. The precision increased to 87.5-93.3 % in average for the four new methods, exhibiting similar performances. We confirm that the AC methods based on the Dixon and UTE sequences provided by the vendor are

Removing barriers to rehabilitation: Theory-based family intervention in community settings after brain injury.

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Stejskal, Taryn M

2012-01-01

Rehabilitation professionals have become increasingly aware that family members play a critical role in the recovery process of individuals after brain injury. In addition, researchers have begun to identify a relationship between family member caregivers' well-being and survivors' outcomes. The idea of a continuum of care or following survivors from inpatient care to community reintegration has become an important model of treatment across many hospital and community-based settings. In concert with the continuum of care, present research literature indicates that family intervention may be a key component to successful rehabilitation after brain injury. Yet, clinicians interacting with family members and survivors often feel confounded about how exactly to intervene with the broader family system beyond the individual survivor. Drawing on the systemic nature of the field of marriage and family therapy (MFT), this article provides information to assist clinicians in effectively intervening with families using theory-based interventions in community settings. First, a rationale for the utilization of systems-based, as opposed to individual-based, therapies will be uncovered. Second, historically relevant publications focusing on family psychotherapy and intervention after brain injury are reviewed and their implications discussed. Recommendations for the utilization of systemic theory-based principles and strategies, specifically cognitive behavioral therapy (CBT), narrative therapy (NT), and solution-focused therapy (SFT) will be examined. Descriptions of common challenges families and couples face will be presented along with case examples to illustrate how these theoretical frameworks might be applied to these special concerns postinjury. Finally, the article concludes with an overview of the ideas presented in this manuscript to assist practitioners and systems of care in community-based settings to more effectively intervene with the family system as a whole

A computed tomography-based spatial normalization for the analysis of [18F] fluorodeoxyglucose positron emission tomography of the brain.

Science.gov (United States)

Cho, Hanna; Kim, Jin Su; Choi, Jae Yong; Ryu, Young Hoon; Lyoo, Chul Hyoung

2014-01-01

We developed a new computed tomography (CT)-based spatial normalization method and CT template to demonstrate its usefulness in spatial normalization of positron emission tomography (PET) images with [(18)F] fluorodeoxyglucose (FDG) PET studies in healthy controls. Seventy healthy controls underwent brain CT scan (120 KeV, 180 mAs, and 3 mm of thickness) and [(18)F] FDG PET scans using a PET/CT scanner. T1-weighted magnetic resonance (MR) images were acquired for all subjects. By averaging skull-stripped and spatially-normalized MR and CT images, we created skull-stripped MR and CT templates for spatial normalization. The skull-stripped MR and CT images were spatially normalized to each structural template. PET images were spatially normalized by applying spatial transformation parameters to normalize skull-stripped MR and CT images. A conventional perfusion PET template was used for PET-based spatial normalization. Regional standardized uptake values (SUV) measured by overlaying the template volume of interest (VOI) were compared to those measured with FreeSurfer-generated VOI (FSVOI). All three spatial normalization methods underestimated regional SUV values by 0.3-20% compared to those measured with FSVOI. The CT-based method showed slightly greater underestimation bias. Regional SUV values derived from all three spatial normalization methods were correlated significantly (p normalization may be an alternative method for structure-based spatial normalization of [(18)F] FDG PET when MR imaging is unavailable. Therefore, it is useful for PET/CT studies with various radiotracers whose uptake is expected to be limited to specific brain regions or highly variable within study population.

Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory.

Science.gov (United States)

Malec, James F; Parrot, Devan; Altman, Irwin M; Swick, Shannon

2015-01-01

The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

Plasma based markers of [11C] PiB-PET brain amyloid burden.

Directory of Open Access Journals (Sweden)

Steven John Kiddle

Full Text Available Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [(11C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden--c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E--were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE [Symbol: see text] 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.

Preliminary application of voxel-based morphometry technique on brain changes in neuromyelitis

International Nuclear Information System (INIS)

Xiao Hui; Ma Lin; Chen Ziqian; Lou Xin; Chen Zhiye

2011-01-01

Objective: To investigate the changes of brain volumes in neuromyelitis optica (NMO) patients using voxel-based morphometry (VBM) method, and preliminarily explore the pattern of cerebral anatomical impairment. Methods: Twenty-three clinically defined NMO patients and 15 gender and age matched healthy volunteers underwent 3-dimensional (3D) fast spoiled gradient echo (FSPGR) sequence scanning on 3.0 Tesla MR system. Raw data was processed and analyzed using statistical parametric mapping (SPM) 5. Whole brain volumes included grey matter volume (GMV), white matter volume (WMV), total intracranial volume (TIV), grey matter fraction (GMF), white matter fraction (WMF), brain tissue fraction (BTF) and regional brain volumes between the two groups were compared by independent samples t-test and an Pearson were performed to compare the regional brain volumes and the ages. Results: GMV of NMO group [(610.2±55.0) ml] was significantly decreased comparing to healthy control group [(657.2±36.3) ml] (t=-2.915, P<0.05). The age of NMO patients [(40±9) years old] showed negative correlation with GMF [(42.5±2.6) %] (r=-0.673, P<0.05). Regional brain volume analysis showed decreased GMV in left insula and bilateral posterior cingutates in NMO patients, while decreased WMV was found in left frontal and left parietal white matter. Conclusion: VBM could detect brain volume changes sensitively. Total grey matter volume in NMO patients was decreased comparing to HC group. Regional grey matter atrophy in NMO patients occurred in left insular and bilateral posterior cingutates, regional white matter atrophy occurred in left frontal and left parietal lobe. (authors)

Development of a brain MRI-based hidden Markov model for dementia recognition.

Science.gov (United States)

Chen, Ying; Pham, Tuan D

2013-01-01

Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia.

Confirming the diversity of the brain after normalization: an approach based on identity authentication.

Directory of Open Access Journals (Sweden)

Fanglin Chen

Full Text Available During the development of neuroimaging, numerous analyses were performed to identify population differences, such as studies on age, gender, and diseases. Researchers first normalized the brain image and then identified features that represent key differences between groups. In these studies, the question of whether normalization (a pre-processing step widely used in neuroimaging studies reduces the diversity of brains was largely ignored. There are a few studies that identify the differences between individuals after normalization. In the current study, we analyzed brain diversity on an individual level, both qualitatively and quantitatively. The main idea was to utilize brain images for identity authentication. First, the brain images were normalized and registered. Then, a pixel-level matching method was developed to compute the identity difference between different images for matching. Finally, by analyzing the performance of the proposed brain recognition strategy, the individual differences in brain images were evaluated. Experimental results on a 150-subject database showed that the proposed approach could achieve a 100% identification ratio, which indicated distinct differences between individuals after normalization. Thus, the results proved that after the normalization stage, brain images retain their main distinguishing information and features. Based on this result, we suggest that diversity (individual differences should be considered when conducting group analysis, and that this approach may facilitate group pattern classification.

The use of customised versus population-based birthweight standards in predicting perinatal mortality.

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Zhang, X; Platt, R W; Cnattingius, S; Joseph, K S; Kramer, M S

2007-04-01

The objective of this study was to critically examine potential artifacts and biases underlying the use of 'customised' standards of birthweight for gestational age (GA). Population-based cohort study. Sweden. A total of 782,303 singletons > or =28 weeks of gestation born in 1992-2001 to Nordic mothers with complete data on birthweight; GA; and maternal age, parity, height, and pre-pregnancy weight. We compared perinatal mortality in four groups of infants based on the following classification of small for gestational age (SGA): non-SGA based on either population-based or customised standards (the reference group), SGA based on the population-based standard only, SGA based on the customised standard only, and SGA according to both standards. We used graphical methods to compare GA-specific birthweight cutoffs for SGA using the two standards and also used logistic regression to control for differences in GA and maternal pre-pregnancy body mass index (BMI) in the four groups. Perinatal mortality, including stillbirth and neonatal death. Customisation led to a large artifactual increase in the proportion of SGA infants born preterm. Adjustment for differences in GA and maternal BMI markedly reduced the excess risk among infants classified as SGA by customised standards only. The large increase in perinatal mortality risk among infants classified as SGA based on customised standards is largely an artifact due to inclusion of more preterm births.

Measurement of P-31 MR relaxation times and concentrations in human brain and brain tumors

International Nuclear Information System (INIS)

Roth, K.; Naruse, S.; Hubesch, B.; Gober, I.; Lawry, T.; Boska, M.; Matson, G.B.; Weiner, M.W.

1987-01-01

Measurements of high-energy phosphates and pH were made in human brain and brain tumors using P-31 MR imaging. Using a Philips Gyroscan 1.5-T MRMRS, MR images were used to select a cuboidal volume of interest and P-31 MR spectra were obtained from that volume using the ISIS technique. An external quantitation standard was used. T 1 s were measured by inversion recovery. Quantitative values for metabolites were calculated using B 1 field plot of the head coil. The results for normal brain phosphates are as follows; adenosine triphosphate, 2.2 mM; phosphocreatin, 5.3 mM; inorganic phosphate, 1.6 mM. Preliminary studies with human brain tumors show a decrease of all phosphate compounds. These experiments are the first to quantitate metabolites in human brain

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods

DEFF Research Database (Denmark)

van der Kleij, Lisa A.; de Bresser, Jeroen; Hendrikse, Jeroen

2018-01-01

ObjectiveIn previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T-2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim...... of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T-1-based brain segmentation methods.Materials and methodsTen healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice......cc) and CSF HR (5 +/- 5/4 +/- 2cc) were comparable to FSL HR (9 +/- 11/19 +/- 23cc), FSL LR (7 +/- 4,6 +/- 5cc),FreeSurfer HR (5 +/- 3/14 +/- 8cc), FreeSurfer LR (9 +/- 8,12 +/- 10cc), and SPM HR (5 +/- 3/4 +/- 7cc), and SPM LR (5 +/- 4,5 +/- 3cc). The correlation between the measured volumes...

Sensitivity analysis of brain morphometry based on MRI-derived surface models

Science.gov (United States)

Klein, Gregory J.; Teng, Xia; Schoenemann, P. T.; Budinger, Thomas F.

1998-07-01

Quantification of brain structure is important for evaluating changes in brain size with growth and aging and for characterizing neurodegeneration disorders. Previous quantification efforts using ex vivo techniques suffered considerable error due to shrinkage of the cerebrum after extraction from the skull, deformation of slices during sectioning, and numerous other factors. In vivo imaging studies of brain anatomy avoid these problems and allow repetitive studies following progression of brain structure changes due to disease or natural processes. We have developed a methodology for obtaining triangular mesh models of the cortical surface from MRI brain datasets. The cortex is segmented from nonbrain tissue using a 2D region-growing technique combined with occasional manual edits. Once segmented, thresholding and image morphological operations (erosions and openings) are used to expose the regions between adjacent surfaces in deep cortical folds. A 2D region- following procedure is then used to find a set of contours outlining the cortical boundary on each slice. The contours on all slices are tiled together to form a closed triangular mesh model approximating the cortical surface. This model can be used for calculation of cortical surface area and volume, as well as other parameters of interest. Except for the initial segmentation of the cortex from the skull, the technique is automatic and requires only modest computation time on modern workstations. Though the use of image data avoids many of the pitfalls of ex vivo and sectioning techniques, our MRI-based technique is still vulnerable to errors that may impact the accuracy of estimated brain structure parameters. Potential inaccuracies include segmentation errors due to incorrect thresholding, missed deep sulcal surfaces, falsely segmented holes due to image noise and surface tiling artifacts. The focus of this paper is the characterization of these errors and how they affect measurements of cortical surface

Tensor-Based Morphometry Reveals Volumetric Deficits in Moderate=Severe Pediatric Traumatic Brain Injury.

Science.gov (United States)

Dennis, Emily L; Hua, Xue; Villalon-Reina, Julio; Moran, Lisa M; Kernan, Claudia; Babikian, Talin; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2016-05-01

Traumatic brain injury (TBI) can cause widespread and prolonged brain degeneration. TBI can affect cognitive function and brain integrity for many years after injury, often with lasting effects in children, whose brains are still immature. Although TBI varies in how it affects different individuals, image analysis methods such as tensor-based morphometry (TBM) can reveal common areas of brain atrophy on magnetic resonance imaging (MRI), secondary effects of the initial injury, which will differ between subjects. Here we studied 36 pediatric moderate to severe TBI (msTBI) participants in the post-acute phase (1-6 months post-injury) and 18 msTBI participants who returned for their chronic assessment, along with well-matched controls at both time-points. Participants completed a battery of cognitive tests that we used to create a global cognitive performance score. Using TBM, we created three-dimensional (3D) maps of individual and group differences in regional brain volumes. At both the post-acute and chronic time-points, the greatest group differences were expansion of the lateral ventricles and reduction of the lingual gyrus in the TBI group. We found a number of smaller clusters of volume reduction in the cingulate gyrus, thalamus, and fusiform gyrus, and throughout the frontal, temporal, and parietal cortices. Additionally, we found extensive associations between our cognitive performance measure and regional brain volume. Our results indicate a pattern of atrophy still detectable 1-year post-injury, which may partially underlie the cognitive deficits frequently found in TBI.

Development of a new statistical evaluation method for brain SPECT images

International Nuclear Information System (INIS)

Kawashima, Ryuta; Sato, Kazunori; Ito, Hiroshi; Koyama, Masamichi; Goto, Ryoui; Yoshioka, Seiro; Ono, Shuichi; Sato, Tachio; Fukuda, Hiroshi

1996-01-01

The purpose of this study was to develop a new statistical evaluation method for brain SPECT images. First, we made normal brain image databases using 99m Tc-ECD and SPECT in 10 normal subjects as described previously. Each SPECT images were globally normalized and anatomically standardized to the standard brain shape using Human Brain Atlas (HBA) of Roland et al. and each subject's X-CT. Then, mean and SD images were calculated voxel by voxel. For the next step, 99m Tc-ECD SPECT images of a patient were obtained, and global normalization and anatomical standardization were performed as the same way. Then, a statistical map was calculated as following voxel by voxel; (P-Mean)/SDx10+50, where P, mean and SD indicate voxel value of patient, mean and SD images of normal databases, respectively. We found this statistical map was helpful for clinical diagnosis of brain SPECT studies. (author)

Structural brain aging and speech production: a surface-based brain morphometry study.

Science.gov (United States)

Tremblay, Pascale; Deschamps, Isabelle

2016-07-01

While there has been a growing number of studies examining the neurofunctional correlates of speech production over the past decade, the neurostructural correlates of this immensely important human behaviour remain less well understood, despite the fact that previous studies have established links between brain structure and behaviour, including speech and language. In the present study, we thus examined, for the first time, the relationship between surface-based cortical thickness (CT) and three different behavioural indexes of sublexical speech production: response duration, reaction times and articulatory accuracy, in healthy young and older adults during the production of simple and complex meaningless sequences of syllables (e.g., /pa-pa-pa/ vs. /pa-ta-ka/). The results show that each behavioural speech measure was sensitive to the complexity of the sequences, as indicated by slower reaction times, longer response durations and decreased articulatory accuracy in both groups for the complex sequences. Older adults produced longer speech responses, particularly during the production of complex sequence. Unique age-independent and age-dependent relationships between brain structure and each of these behavioural measures were found in several cortical and subcortical regions known for their involvement in speech production, including the bilateral anterior insula, the left primary motor area, the rostral supramarginal gyrus, the right inferior frontal sulcus, the bilateral putamen and caudate, and in some region less typically associated with speech production, such as the posterior cingulate cortex.

Maintenance Staffing Standards for Zero-Based Budgeting.

Science.gov (United States)

Adams, Matthew C.; And Others

1998-01-01

Discusses school preventive maintenance and the variables associated with maintenance staffing standards that address a zero-based budgeting environment. Explores preventive-maintenance measurement for staffing requirements, defines staffing levels and job descriptions, and outlines the factors to consider when creating a maintenance program and…

Autoradiographic analysis of iodoamphetamine redistribution in experimental brain ischemia

International Nuclear Information System (INIS)

Matsuda, H.; Tsuji, S.; Oba, H.; Shiba, K.; Terada, H.; Kinuya, K.; Mori, H.; Sumiya, H.; Hisada, K.

1990-01-01

The pathophysiologic significance of iodoamphetamine (IMP) redistribution was analyzed using a double radionuclide autoradiography technique in experimental brain ischemia in the rat. Within 4 hr after unilateral arterial occlusion, IMP almost completely redistributed at 150 min postinjection in the affected areas. At 2 min postinjection, both a remarkable decrease of IMP accumulation and histopathologic change of diminished staining were observed in these areas. The redistribution amplitude was higher in the affected hemisphere, especially in the regions surrounding the ischemic core than in the unaffected hemisphere. These findings were consistent with computer simulation studies of the time course of brain activity based on the standard diffusible tracer model. The results suggest that IMP redistribution in the ischemic area is due to differences of the temporal changes of the brain activity between the unaffected and affected areas and that it is a physical phenomenon (only flow related) rather than a biologic one

A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain-computer interface

Science.gov (United States)

Chen, Yi-Feng; Atal, Kiran; Xie, Sheng-Quan; Liu, Quan

2017-08-01

Objective. Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications. Approach. Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts. This paper presents an improved method to detect the frequency component associated with SSVEP using multivariate empirical mode decomposition (MEMD) and CCA (MEMD-CCA). EEG signals from nine healthy volunteers were recorded to evaluate the performance of the proposed method for SSVEP recognition. Main results. We compared our method with CCA and temporally local multivariate synchronization index (TMSI). The results suggest that the MEMD-CCA achieved significantly higher accuracy in contrast to standard CCA and TMSI. It gave the improvements of 1.34%, 3.11%, 3.33%, 10.45%, 15.78%, 18.45%, 15.00% and 14.22% on average over CCA at time windows from 0.5 s to 5 s and 0.55%, 1.56%, 7.78%, 14.67%, 13.67%, 7.33% and 7.78% over TMSI from 0.75 s to 5 s. The method outperformed the filter-based decomposition (FB), empirical mode decomposition (EMD) and wavelet decomposition (WT) based CCA for SSVEP recognition. Significance. The results demonstrate the ability of our proposed MEMD-CCA to improve the performance of SSVEP-based BCI.

Adult Professional Development: Can Brain-Based Teaching Strategies Increase Learning Effectiveness?

Science.gov (United States)

Tilton, Wendy

2011-01-01

Brain-based teaching strategies, compared to facilitative student-centered teaching strategies, were employed with 62 real estate professionals in a quasi-mixed-methods study. Participants attended a 2-day proprietary real estate continuing education course. Both the experimental and control groups received the same facilitative instruction, as…

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

Science.gov (United States)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Effect of Experimental Thyrotoxicosis on Brain Gray Matter: A Voxel-Based Morphometry Study.

Science.gov (United States)

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

2015-09-01

Hyper-as well hypothyroidism have an effect on behavior and brain function. Moreover, during development thyroid hormones influence brain structure. This study aimed to demonstrate an effect of experimentally induced hyperthyroidism on brain gray matter in healthy adult humans. High-resolution 3D T1-weighted images were acquired in 29 healthy young subjects prior to as well as after receiving 250 µg of T4 per day for 8 weeks. Voxel-based morphometry analysis was performed using Statistical Parametric Mapping 8 (SPM8). Laboratory testing confirmed the induction of hyperthyroidism. In the hyperthyroid condition, gray matter volumes were increased in the right posterior cerebellum (lobule VI) and decreased in the bilateral visual cortex and anterior cerebellum (lobules I-IV) compared to the euthyroid condition. Our study provides evidence that short periods of hyperthyroidism induce distinct alterations in brain structures of cerebellar regions that have been associated with sensorimotor functions as well as working memory in the literature.

Defining nuclear medical file formal based on DICOM standard

International Nuclear Information System (INIS)

He Bin; Jin Yongjie; Li Yulan

2001-01-01

With the wide application of computer technology in medical area, DICOM is becoming the standard of digital imaging and communication. The author discusses how to define medical imaging file formal based on DICOM standard. It also introduces the format of ANMIS system the authors defined the validity and integrality of this format

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods

NARCIS (Netherlands)

van der Kleij, Lisa A; de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C W; Petersen, Esben T; De Vis, Jill B

2018-01-01

OBJECTIVE: In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of

Effects of active music therapy on the normal brain: fMRI based evidence.

Science.gov (United States)

Raglio, Alfredo; Galandra, Caterina; Sibilla, Luisella; Esposito, Fabrizio; Gaeta, Francesca; Di Salle, Francesco; Moro, Luca; Carne, Irene; Bastianello, Stefano; Baldi, Maurizia; Imbriani, Marcello

2016-03-01

The aim of this study was to investigate the neurophysiological bases of Active Music Therapy (AMT) and its effects on the normal brain. Twelve right-handed, healthy, non-musician volunteers were recruited. The subjects underwent 2 AMT sessions based on the free sonorous-music improvisation using rhythmic and melodic instruments. After these sessions, each subject underwent 2 fMRI scan acquisitions while listening to a Syntonic (SP) and an A-Syntonic (AP) Production from the AMT sessions. A 3 T Discovery MR750 scanner with a 16-channel phased array head coil was used, and the image analysis was performed with Brain Voyager QX 2.8. The listening to SP vs AP excerpts mainly activated: (1) the right middle temporal gyrus and right superior temporal sulcus, (2) the right middle frontal gyrus and in particular the right precentral gyrus, (3) the bilateral precuneus, (4) the left superior temporal sulcus and (5) the left middle temporal gyrus. These results are consistent with the psychological bases of the AMT approach and with the activation of brain areas involved in memory and autobiographical processes, and also in personal or interpersonal significant experiences. Further studies are required to confirm these findings and to explain possible effects of AMT in clinical settings.

What will this do to me and my brain? Ethical issues in brain-to-brain interfacing

Directory of Open Access Journals (Sweden)

Elisabeth eHildt

2015-02-01

Full Text Available For several years now, brain-computer interfaces (BCIs in which brain signals are used to navigate a computer, a prostheses or a technical device, have been developed in various experimental contexts (Wolpaw & Wolpaw 2012; Grübler & Hildt 2014. Researchers have recently taken the next step and run experiments based on connections between two brains. These so-called brain-to-brain interfaces (abbreviation: BBIs or BTBIs involve not only a BCI component deriving information from a brain and sending it to a computer, but also a computer-brain interface (CBI component delivering information to another brain. What results is technology-mediated brain-to-brain communication (B2B communication, i.e. direct communication between two brains that does not involve any activity of the peripheral nervous system. In what follows, ethical issues that arise in neural interfacing will be discussed after a short introduction to recent BBI experiments. In this, the focus will be on the implications BBIs may have on the individual at the CBI side of the BBI, i.e. on the recipient.

Electromagnetic fields and the public: EMF standards and estimation of risk

Science.gov (United States)

Grigoriev, Yury

2010-04-01

Mobile communications are a relatively new and additional source of electromagnetic exposure for the population. Standard daily mobile-phone use is known to increase RF-EMF (radiofrequency electromagnetic field) exposure to the brains of users of all ages, whilst mobile-phone base stations, and base station units for cordless phones, can regularly increase the exposures of large numbers of the population to RF-EMF radiation in everyday life. The need to determine appropriate standards stipulating the maximum acceptable short-term and long-term RF-EMF levels encountered by the public, and set such levels as general guidelines, is of great importance in order to help preserve the general public's health and that of the next generation of humanity.

Electromagnetic fields and the public: EMF standards and estimation of risk

International Nuclear Information System (INIS)

Grigoriev, Yury

2010-01-01

Mobile communications are a relatively new and additional source of electromagnetic exposure for the population. Standard daily mobile-phone use is known to increase RF-EMF (radiofrequency electromagnetic field) exposure to the brains of users of all ages, whilst mobile-phone base stations, and base station units for cordless phones, can regularly increase the exposures of large numbers of the population to RF-EMF radiation in everyday life. The need to determine appropriate standards stipulating the maximum acceptable short-term and long-term RF-EMF levels encountered by the public, and set such levels as general guidelines, is of great importance in order to help preserve the general public's health and that of the next generation of humanity.

Learned self-regulation of the lesioned brain with epidural electrocorticography

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Alireza eGharabaghi

2014-12-01

Full Text Available Introduction: Different techniques for neurofeedback of voluntary brain activations are currently being explored for clinical application in brain-related disorders. One of the most frequently used approaches is the self-regulation of oscillatory signals recorded with electroencephalography (EEG. Many patients are, however, not in a position to use such tools. This could be due to the specific anatomical and physiological properties of the patient's brain after the lesion, as well as to methodological issues related to the technique chosen for recording brain signals.Methods: A patient with extended ischemic lesions of the cortex was unable to gain volitional control of sensorimotor oscillations when using a standard EEG-based approach. We provided him with a neurofeedback set-up with which his brain activity could be recorded from the epidural space by electrocorticography (ECoG.Results: Ipsilesional epidural recordings of field potentials facilitated learned self-regulation of brain oscillations in an online closed-loop paradigm and allowed swift and reliable neurofeedback training for a period of four weeks on a daily basis.Conclusion: Epidural implants may decode and train brain activity even when the cortical physiology is distorted following severe brain injury. Such practice would allow for reinforcement learning of preserved neural networks and may well provide restorative tools for those patients who are worst afflicted.

An Example-Based Brain MRI Simulation Framework.

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He, Qing; Roy, Snehashis; Jog, Amod; Pham, Dzung L

2015-02-21

The simulation of magnetic resonance (MR) images plays an important role in the validation of image analysis algorithms such as image segmentation, due to lack of sufficient ground truth in real MR images. Previous work on MRI simulation has focused on explicitly modeling the MR image formation process. However, because of the overwhelming complexity of MR acquisition these simulations must involve simplifications and approximations that can result in visually unrealistic simulated images. In this work, we describe an example-based simulation framework, which uses an "atlas" consisting of an MR image and its anatomical models derived from the hard segmentation. The relationships between the MR image intensities and its anatomical models are learned using a patch-based regression that implicitly models the physics of the MR image formation. Given the anatomical models of a new brain, a new MR image can be simulated using the learned regression. This approach has been extended to also simulate intensity inhomogeneity artifacts based on the statistical model of training data. Results show that the example based MRI simulation method is capable of simulating different image contrasts and is robust to different choices of atlas. The simulated images resemble real MR images more than simulations produced by a physics-based model.

Mining Time-Resolved Functional Brain Graphs to an EEG-Based Chronnectomic Brain Aged Index (CBAI

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Stavros I. Dimitriadis

2017-09-01

Full Text Available The brain at rest consists of spatially and temporal distributed but functionally connected regions that called intrinsic connectivity networks (ICNs. Resting state electroencephalography (rs-EEG is a way to characterize brain networks without confounds associated with task EEG such as task difficulty and performance. A novel framework of how to study dynamic functional connectivity under the notion of functional connectivity microstates (FCμstates and symbolic dynamics is further discussed. Furthermore, we introduced a way to construct a single integrated dynamic functional connectivity graph (IDFCG that preserves both the strength of the connections between every pair of sensors but also the type of dominant intrinsic coupling modes (DICM. The whole methodology is demonstrated in a significant and unexplored task for EEG which is the definition of an objective Chronnectomic Brain Aged index (CBAI extracted from resting-state data (N = 94 subjects with both eyes-open and eyes-closed conditions. Novel features have been defined based on symbolic dynamics and the notion of DICM and FCμstates. The transition rate of FCμstates, the symbolic dynamics based on the evolution of FCμstates (the Markovian Entropy, the complexity index, the probability distribution of DICM, the novel Flexibility Index that captures the dynamic reconfiguration of DICM per pair of EEG sensors and the relative signal power constitute a valuable pool of features that can build the proposed CBAI. Here we applied a feature selection technique and Extreme Learning Machine (ELM classifier to discriminate young adults from middle-aged and a Support Vector Regressor to build a linear model of the actual age based on EEG-based spatio-temporal features. The most significant type of features for both prediction of age and discrimination of young vs. adults age groups was the dynamic reconfiguration of dominant coupling modes derived from a subset of EEG sensor pairs. Specifically

Brain-Based Teaching: Does It Really Work?

Science.gov (United States)

Calhoun, Christie F.

2012-01-01

In an effort to keep up with today's advanced students, methods and strategies used in modern classrooms are ever-changing. In this manuscript, one method is discussed. Whole brain teaching has recently come to the forefront of education research. How does the brain affect learning? How can teachers ensure that students are actively engaged in the…

Feasibility of a skills-based substance abuse prevention program following traumatic brain injury.

Science.gov (United States)

Vungkhanching, Martha; Heinemann, Allen W; Langley, Mervin J; Ridgely, Mary; Kramer, Karen M

2007-01-01

To demonstrate the feasibility of a skills-based substance abuse prevention counseling program in a community setting for adults who sustained traumatic brain injury. Convenience sample of 117 participants (mean age=35 years) with preinjury history of alcohol or other drug use. Intervention group participants (n=36) from 3 vocational rehabilitation programs; a no-intervention comparison group (n=81) from an outpatient rehabilitation service. 12 individual counseling sessions featuring skills-based intervention. Changes in self-reported alcohol and other drug use, coping skillfulness, affect, and employment status from baseline to 9 months postintervention. Significant differences were noted at baseline for the intervention and comparison groups on ethnicity, time postinjury, marital status, and employment (Pcoping skillfulness (Pskills-based intervention provides a promising approach to promoting abstinence from all substances and increasing readiness for employment for adults with traumatic brain injuries in outpatient settings.

Fixel-based analysis reveals alterations is brain microstructure and macrostructure of preterm-born infants at term equivalent age

Directory of Open Access Journals (Sweden)

Kerstin Pannek

Full Text Available Preterm birth causes significant disruption in ongoing brain development, frequently resulting in adverse neurodevelopmental outcomes. Brain imaging using diffusion MRI may provide valuable insight into microstructural properties of the developing brain. The aim of this study was to establish whether the recently introduced fixel-based analysis method, with its associated measures of fibre density (FD, fibre bundle cross-section (FC, and fibre density and bundle cross-section (FDC, is suitable for the investigation of the preterm infant brain at term equivalent age. High-angular resolution diffusion weighted images (HARDI of 55 preterm-born infants and 20 term-born infants, scanned around term-equivalent age, were included in this study (3 T, 64 directions, b = 2000 s/mm2. Postmenstrual age at the time of MRI, and intracranial volume (FC and FDC only, were identified as confounding variables. Gestational age at birth was correlated with all fixel measures in the splenium of the corpus callosum. Compared to term-born infants, preterm infants showed reduced FD, FC, and FDC in a number of regions, including the corpus callosum, anterior commissure, cortico-spinal tract, optic radiations, and cingulum. Preterm infants with minimal macroscopic brain abnormality showed more extensive reductions than preterm infants without any macroscopic brain abnormality; however, little differences were observed between preterm infants with no and with minimal brain abnormality. FC showed significant reductions in preterm versus term infants outside regions identified with FD and FDC, highlighting the complementary role of these measures. Fixel-based analysis identified both microstructural and macrostructural abnormalities in preterm born infants, providing a more complete picture of early brain development than previous diffusion tensor imaging (DTI based approaches. Keywords: Fixel-based analysis, Diffusion, Prematurity, Neonate

Development of a LED based standard for luminous flux

Science.gov (United States)

Sardinha, André; Ázara, Ivo; Torres, Miguel; Menegotto, Thiago; Grieneisen, Hans Peter; Borghi, Giovanna; Couceiro, Iakyra; Zim, Alexandre; Muller, Filipe

2018-03-01

Incandescent lamps, simple artifacts with radiation spectrum very similar to a black-body emitter, are traditional standards in photometry. Nowadays LEDs are broadly used in lighting, with great variety of spectra, and it is convenient to use standards for photometry with spectral distribution similar to that of the measured artifact. Research and development of such standards occur in several National Metrology Institutes. In Brazil, Inmetro is working on a practical solution for providing a LED based standard to be used for luminous flux measurements in the field of general lighting. This paper shows the measurements made for the developing of a prototype, that in sequence will be characterized in photometric quantities.

PET/MR brain imaging: evaluation of clinical UTE-based attenuation correction

International Nuclear Information System (INIS)

Aasheim, Lars Birger; Karlberg, Anna; Goa, Paal Erik; Haaberg, Asta; Soerhaug, Sveinung; Fagerli, Unn-Merete; Eikenes, Live

2015-01-01

One of the greatest challenges in PET/MR imaging is that of accurate MR-based attenuation correction (AC) of the acquired PET data, which must be solved if the PET/MR modality is to reach its full potential. The aim of this study was to investigate the performance of Siemens' most recent version (VB20P) of MR-based AC of head PET data, by comparing it to CT-based AC. Methods: 18 F-FDG PET data from seven lymphoma and twelve lung cancer patients examined with a Biograph mMR PET/MR system were reconstructed with both CT-based and MR-based AC, avoiding sources of error arising when comparing PET data from different systems. The resulting images were compared quantitatively by measuring changes in mean SUV in ten different brain regions in both hemispheres, as well as the brainstem. In addition, the attenuation maps (μ maps) were compared regarding volume and localization of cranial bone. The UTE μ maps clearly overestimate the amount of bone in the neck, while slightly underestimating the amount of bone in the cranium, and the localization of bone in the cranial region also differ from the CT μ maps. In air/tissue interfaces in the sinuses and ears, the MRAC method struggles to correctly classify the different tissues. The misclassification of tissue is most likely caused by a combination of artefacts and the insufficiency of the UTE method to accurately separate bone. Quantitatively, this results in a combination of overestimation (0.5-3.6 %) and underestimation (2.7-5.2 %) of PET activity throughout the brain, depending on the proximity to the inaccurate regions. Our results indicate that the performance of the UTE method as implemented in VB20P is close to the theoretical maximum of such an MRAC method in the brain, while it does not perform satisfactorily in the neck or face/nasal area. Further improvement of the UTE MRAC or other available methods for more accurate segmentation of bone should be incorporated. (orig.)

Comparison of doses received by the hippocampus in patients treated with single isocenter– vs multiple isocenter–based stereotactic radiation therapy to the brain for multiple brain metastases

International Nuclear Information System (INIS)

Algan, Ozer; Giem, Jared; Young, Julie; Ali, Imad; Ahmad, Salahuddin; Hossain, Sabbir

2015-01-01

To investigate the doses received by the hippocampus and normal brain tissue during a course of stereotactic radiation therapy using a single isocenter (SI)–based or multiple isocenter (MI)–based treatment planning in patients with less than 4 brain metastases. In total, 10 patients with magnetic resonance imaging (MRI) demonstrating 2-3 brain metastases were included in this retrospective study, and 2 sets of stereotactic intensity-modulated radiation therapy (IMRT) treatment plans (SI vs MI) were generated. The hippocampus was contoured on SPGR sequences, and doses received by the hippocampus and the brain were calculated and compared between the 2 treatment techniques. A total of 23 lesions in 10 patients were evaluated. The median tumor volume, the right hippocampus volume, and the left hippocampus volume were 3.15, 3.24, and 2.63 mL, respectively. In comparing the 2 treatment plans, there was no difference in the planning target volume (PTV) coverage except in the tail for the dose-volume histogram (DVH) curve. The only statistically significant dosimetric parameter was the V_1_0_0. All of the other measured dosimetric parameters including the V_9_5, V_9_9, and D_1_0_0 were not significantly different between the 2 treatment planning techniques. None of the dosimetric parameters evaluated for the hippocampus revealed any statistically significant difference between the MI and SI plans. The total brain doses were slightly higher in the SI plans, especially in the lower dose region, although this difference was not statistically different. The use of SI-based treatment plan resulted in a 35% reduction in beam-on time. The use of SI treatments for patients with up to 3 brain metastases produces similar PTV coverage and similar normal tissue doses to the hippocampus and the brain when compared with MI plans. SI treatment planning should be considered in patients with multiple brain metastases undergoing stereotactic treatment.

Comparison of doses received by the hippocampus in patients treated with single isocenter- vs multiple isocenter-based stereotactic radiation therapy to the brain for multiple brain metastases.

Science.gov (United States)

Algan, Ozer; Giem, Jared; Young, Julie; Ali, Imad; Ahmad, Salahuddin; Hossain, Sabbir

2015-01-01

To investigate the doses received by the hippocampus and normal brain tissue during a course of stereotactic radiation therapy using a single isocenter (SI)-based or multiple isocenter (MI)-based treatment planning in patients with less than 4 brain metastases. In total, 10 patients with magnetic resonance imaging (MRI) demonstrating 2-3 brain metastases were included in this retrospective study, and 2 sets of stereotactic intensity-modulated radiation therapy (IMRT) treatment plans (SI vs MI) were generated. The hippocampus was contoured on SPGR sequences, and doses received by the hippocampus and the brain were calculated and compared between the 2 treatment techniques. A total of 23 lesions in 10 patients were evaluated. The median tumor volume, the right hippocampus volume, and the left hippocampus volume were 3.15, 3.24, and 2.63mL, respectively. In comparing the 2 treatment plans, there was no difference in the planning target volume (PTV) coverage except in the tail for the dose-volume histogram (DVH) curve. The only statistically significant dosimetric parameter was the V100. All of the other measured dosimetric parameters including the V95, V99, and D100 were not significantly different between the 2 treatment planning techniques. None of the dosimetric parameters evaluated for the hippocampus revealed any statistically significant difference between the MI and SI plans. The total brain doses were slightly higher in the SI plans, especially in the lower dose region, although this difference was not statistically different. The use of SI-based treatment plan resulted in a 35% reduction in beam-on time. The use of SI treatments for patients with up to 3 brain metastases produces similar PTV coverage and similar normal tissue doses to the hippocampus and the brain when compared with MI plans. SI treatment planning should be considered in patients with multiple brain metastases undergoing stereotactic treatment. Copyright © 2015 American Association of

Comparison of doses received by the hippocampus in patients treated with single isocenter– vs multiple isocenter–based stereotactic radiation therapy to the brain for multiple brain metastases

Energy Technology Data Exchange (ETDEWEB)

Algan, Ozer, E-mail: oalgan@ouhsc.edu; Giem, Jared; Young, Julie; Ali, Imad; Ahmad, Salahuddin; Hossain, Sabbir

2015-01-01

To investigate the doses received by the hippocampus and normal brain tissue during a course of stereotactic radiation therapy using a single isocenter (SI)–based or multiple isocenter (MI)–based treatment planning in patients with less than 4 brain metastases. In total, 10 patients with magnetic resonance imaging (MRI) demonstrating 2-3 brain metastases were included in this retrospective study, and 2 sets of stereotactic intensity-modulated radiation therapy (IMRT) treatment plans (SI vs MI) were generated. The hippocampus was contoured on SPGR sequences, and doses received by the hippocampus and the brain were calculated and compared between the 2 treatment techniques. A total of 23 lesions in 10 patients were evaluated. The median tumor volume, the right hippocampus volume, and the left hippocampus volume were 3.15, 3.24, and 2.63 mL, respectively. In comparing the 2 treatment plans, there was no difference in the planning target volume (PTV) coverage except in the tail for the dose-volume histogram (DVH) curve. The only statistically significant dosimetric parameter was the V{sub 100}. All of the other measured dosimetric parameters including the V{sub 95}, V{sub 99}, and D{sub 100} were not significantly different between the 2 treatment planning techniques. None of the dosimetric parameters evaluated for the hippocampus revealed any statistically significant difference between the MI and SI plans. The total brain doses were slightly higher in the SI plans, especially in the lower dose region, although this difference was not statistically different. The use of SI-based treatment plan resulted in a 35% reduction in beam-on time. The use of SI treatments for patients with up to 3 brain metastases produces similar PTV coverage and similar normal tissue doses to the hippocampus and the brain when compared with MI plans. SI treatment planning should be considered in patients with multiple brain metastases undergoing stereotactic treatment.

Brain-based mind reading in forensic psychiatry: exploring possibilities and perils

NARCIS (Netherlands)

Meynen, G.

2017-01-01

One of the areas in which brain-based mind reading (BMR) may be applied is forensic psychiatry. The purpose of this paper is to identify opportunities and challenges for forensic psychiatry regarding BMR. In order to do so, a conceptual framework for BMR will be introduced, which distinguishes

An emergency call system for patients in locked-in state using an SSVEP-based brain switch.

Science.gov (United States)

Lim, Jeong-Hwan; Kim, Yong-Wook; Lee, Jun-Hak; An, Kwang-Ok; Hwang, Han-Jeong; Cha, Ho-Seung; Han, Chang-Hee; Im, Chang-Hwan

2017-11-01

Patients in a locked-in state (LIS) due to severe neurological disorders such as amyotrophic lateral sclerosis (ALS) require seamless emergency care by their caregivers or guardians. However, it is a difficult job for the guardians to continuously monitor the patients' state, especially when direct communication is not possible. In the present study, we developed an emergency call system for such patients using a steady-state visual evoked potential (SSVEP)-based brain switch. Although there have been previous studies to implement SSVEP-based brain switch system, they have not been applied to patients in LIS, and thus their clinical value has not been validated. In this study, we verified whether the SSVEP-based brain switch system can be practically used as an emergency call system for patients in LIS. The brain switch used for our system adopted a chromatic visual stimulus, which proved to be visually less stimulating than conventional checkerboard-type stimuli but could generate SSVEP responses strong enough to be used for brain-computer interface (BCI) applications. To verify the feasibility of our emergency call system, 14 healthy participants and 3 patients with severe ALS took part in online experiments. All three ALS patients successfully called their guardians to their bedsides in about 6.56 seconds. Furthermore, additional experiments with one of these patients demonstrated that our emergency call system maintains fairly good performance even up to 4 weeks after the first experiment without renewing initial calibration data. Our results suggest that our SSVEP-based emergency call system might be successfully used in practical scenarios. © 2017 Society for Psychophysiological Research.

Whole-brain voxel-based morphometry of white matter in mild cognitive impairment

International Nuclear Information System (INIS)

Wang Zhiqun; Guo Xiaojuan; Qi Zhigang; Yao Li; Li Kuncheng

2010-01-01

Purpose: The purpose of this study was to analyze whole-brain white matter changes in mild cognitive impairment (MCI). Materials and methods: We studied 14 patients with MCI and 14 age- and sex-matched healthy control subjects using voxel-based morphometry (VBM) on T1-weighted 3D datasets. The data were collected on a 3T MR system and analyzed by SPM2 to generate white matter volume maps. Results: Voxel-based morphometry revealed diffusively reduced white matter in MCI prominently including the bilateral temporal gyrus, the right anterior cingulate, the bilateral superior and medial frontal gyrus and right parietal angular gyrus. White matter reduction was more prominent in anterior regions than that in posterior regions. Conclusion: Whole-brain white matter reduction in MCI patients detected with VBM has special distribution which is in line with the white matter pathology of MCI.

Whole-brain voxel-based morphometry of white matter in mild cognitive impairment

Energy Technology Data Exchange (ETDEWEB)

Wang Zhiqun [Department of Radiology, Xuanwu Hospital of Capital Medical University, 100053, Beijing (China); Guo Xiaojuan [College of Information Science and Technology, Beijing Normal University, 100875, Beijing (China); National Key Laboratory for Cognitive Neuroscience and Learning, Beijing Normal University, 100875, Beijing (China); Qi Zhigang [Department of Radiology, Xuanwu Hospital of Capital Medical University, 100053, Beijing (China); Yao Li [College of Information Science and Technology, Beijing Normal University, 100875, Beijing (China); National Key Laboratory for Cognitive Neuroscience and Learning, Beijing Normal University, 100875, Beijing (China); Li Kuncheng, E-mail: likuncheng@xwh.ccmu.edu.c [Department of Radiology, Xuanwu Hospital of Capital Medical University, 100053, Beijing (China)

2010-08-15

Purpose: The purpose of this study was to analyze whole-brain white matter changes in mild cognitive impairment (MCI). Materials and methods: We studied 14 patients with MCI and 14 age- and sex-matched healthy control subjects using voxel-based morphometry (VBM) on T1-weighted 3D datasets. The data were collected on a 3T MR system and analyzed by SPM2 to generate white matter volume maps. Results: Voxel-based morphometry revealed diffusively reduced white matter in MCI prominently including the bilateral temporal gyrus, the right anterior cingulate, the bilateral superior and medial frontal gyrus and right parietal angular gyrus. White matter reduction was more prominent in anterior regions than that in posterior regions. Conclusion: Whole-brain white matter reduction in MCI patients detected with VBM has special distribution which is in line with the white matter pathology of MCI.

Normalization of similarity-based individual brain networks from gray matter MRI and its association with neurodevelopment in infants with intrauterine growth restriction.

Science.gov (United States)

Batalle, Dafnis; Muñoz-Moreno, Emma; Figueras, Francesc; Bargallo, Nuria; Eixarch, Elisenda; Gratacos, Eduard

2013-12-01

Obtaining individual biomarkers for the prediction of altered neurological outcome is a challenge of modern medicine and neuroscience. Connectomics based on magnetic resonance imaging (MRI) stands as a good candidate to exhaustively extract information from MRI by integrating the information obtained in a few network features that can be used as individual biomarkers of neurological outcome. However, this approach typically requires the use of diffusion and/or functional MRI to extract individual brain networks, which require high acquisition times and present an extreme sensitivity to motion artifacts, critical problems when scanning fetuses and infants. Extraction of individual networks based on morphological similarity from gray matter is a new approach that benefits from the power of graph theory analysis to describe gray matter morphology as a large-scale morphological network from a typical clinical anatomic acquisition such as T1-weighted MRI. In the present paper we propose a methodology to normalize these large-scale morphological networks to a brain network with standardized size based on a parcellation scheme. The proposed methodology was applied to reconstruct individual brain networks of 63 one-year-old infants, 41 infants with intrauterine growth restriction (IUGR) and 22 controls, showing altered network features in the IUGR group, and their association with neurodevelopmental outcome at two years of age by means of ordinal regression analysis of the network features obtained with Bayley Scale for Infant and Toddler Development, third edition. Although it must be more widely assessed, this methodology stands as a good candidate for the development of biomarkers for altered neurodevelopment in the pediatric population. © 2013 Elsevier Inc. All rights reserved.

A real-time standard parts inspection based on deep learning

Science.gov (United States)

Xu, Kuan; Li, XuDong; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Since standard parts are necessary components in mechanical structure like bogie and connector. These mechanical structures will be shattered or loosen if standard parts are lost. So real-time standard parts inspection systems are essential to guarantee their safety. Researchers would like to take inspection systems based on deep learning because it works well in image with complex backgrounds which is common in standard parts inspection situation. A typical inspection detection system contains two basic components: feature extractors and object classifiers. For the object classifier, Region Proposal Network (RPN) is one of the most essential architectures in most state-of-art object detection systems. However, in the basic RPN architecture, the proposals of Region of Interest (ROI) have fixed sizes (9 anchors for each pixel), they are effective but they waste much computing resources and time. In standard parts detection situations, standard parts have given size, thus we can manually choose sizes of anchors based on the ground-truths through machine learning. The experiments prove that we could use 2 anchors to achieve almost the same accuracy and recall rate. Basically, our standard parts detection system could reach 15fps on NVIDIA GTX1080 (GPU), while achieving detection accuracy 90.01% mAP.

Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease

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LIU Xue-na

2012-08-01

Full Text Available Alzheimer's disease (AD, a progressive neurodegenerative disease, is clinically characterized by impaired memory and many other cognitive functions. However, the pathophysiological mechanisms underlying the disease are not thoroughly understood. In recent years, using functional magnetic resonance imaging (fMRI as well as advanced graph theory based network analysis approach, several studies of patients with AD suggested abnormal topological organization in both global and regional properties of functional brain networks, specifically, as demonstrated by a loss of small-world network characteristics. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis. In this paper we introduce the essential concepts of complex brain networks theory, and review recent advances of the study on human functional brain networks in AD, especially focusing on the graph theoretical analysis of small-world network based on fMRI. We also propound the existent problems and research orientation.

[The P300 based brain-computer interface: effect of stimulus position in a stimulus train].

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Ganin, I P; Shishkin, S L; Kochetova, A G; Kaplan, A Ia

2012-01-01

The P300 brain-computer interface (BCI) is currently the most efficient BCI. This interface is based on detection of the P300 wave of the brain potentials evoked when a symbol related to the intended input is highlighted. To increase operation speed of the P300 BCI, reduction of the number of stimuli repetitions is needed. This reduction leads to increase of the relative contribution to the input symbol detection from the reaction to the first target stimulus. It is known that the event-related potentials (ERP) to the first stimulus presentations can be different from the ERP to stimuli presented latter. In particular, the amplitude of responses to the first stimulus presentations is often increased, which is beneficial for their recognition by the BCI. However, this effect was not studied within the BCI framework. The current study examined the ERP obtained from healthy participants (n = 14) in the standard P300 BCI paradigm using 10 trials, as well as in the modified P300 BCI with stimuli presented on moving objects in triple-trial (n = 6) and single-trial (n = 6) stimulation modes. Increased ERP amplitude was observed in response to the first target stimuli in both conditions, as well as in the single-trial mode comparing to triple-trial. We discuss the prospects of using the specific features of the ERP to first stimuli and the single-trial ERP for optimizing the high-speed modes in the P300 BCIs.

The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.

Science.gov (United States)

Brumberg, Jonathan S; Lorenz, Sean D; Galbraith, Byron V; Guenther, Frank H

2012-01-01

In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software "app" development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 50-60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis.

Accounting standards and earnings management : The role of rules-based and principles-based accounting standards and incentives on accounting and transaction decisions

NARCIS (Netherlands)

Beest, van F.

2012-01-01

This book examines the effect that rules-based and principles-based accounting standards have on the level and nature of earnings management decisions. A cherry picking experiment is conducted to test the hypothesis that a substitution effect is expected from accounting decisions to transaction

PENDEKATAN BRAIN BASED LEARNING DALAM PENANAMAN NILAI BUDAYA MELALUI PENDIDIKAN FORMAL

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Zulfikri Anas

2013-04-01

Full Text Available Tujuan penelitian ini adalah untuk mengeksplorasi gagasan penggunaan pendekatan brain based learning dalam penanaman nilai budaya melalui pendidikan formal. Undang-Undang  menyatakan dengan tegas bahwa pendidikan adalah upaya sadar untuk mengembangkan potensi setiap siswa agar menjadi warga negara yang cerdas, kreatif dan berakhlak mulia.  Nilai-nilai budaya  mengkondisikan manusia untuk hidup saling menghargai dengan berbagai nilai-nilai yang diyakini bersama. Seyogyanya kehidupan menjadi harmonis karena semua yang melingkupi kehidupan manusia menggiring ke arah sana. Akan tetapi mengapa tatakrama, kreatifitas, kemandirian dan ciri-ciri kemanusiaan lainnya menjadi memudar? Dunia pendidikan termasuk yang paling disoroti. Berbagai pendapat ekstrim menyatakan, pendidikan telah mencabut anak dari akar budayanya. Penyebabnya adalah pembelajaran yang monoton, mengekang, dan mempoisisikan anak sebagai obyek pembelajaran, bukan subyek yang aktif. Untuk mengembalikan fungsi pendidikan ke arah yang diharapkan, harus diciptakan iklim pembelajaran yang semirip mungkin dengan kehidupan nyata serta pengintegrasian kurikulum dengan hal-hal nyata dalam kehidupan. Kondisi ini akan mendorong  peserta didik  untuk berkembang dan menjadi anak-anak yang cerdas, kreatif, dan berakhlak mulia. Hal inilah yang menjadi salah satu sasaran penerapan brain based learning. The objective of this study is to explore ​​the use of brain based learning approach in character education ​​through formal education. Law insists that education is a conscious effort to develop the potential of every student to become a smart, creative, and noble citizen. Cultural values suggest human condition to live with mutual respect with different values ​​shared together. If this condition is achieved, a harmonious life for all human life can be realized. However, why manners, creativity, independence and other human traits is fading

An Investigation of the Engagement of Elementary Students in the NCTM Process Standards after One Year of Standards-Based Instruction

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Fillingim, Jennifer Gale

2010-01-01

Contemporary mathematics education reform has placed increased emphasis on K-12 mathematics curriculum. Reform-based curricula, often referred to as "Standards-based" due to philosophical alignment with the NCTM Process Standards, have generated controversy among families, educators, and researchers. The mathematics education research…

Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology

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Vollmer Ekkehard

2008-04-01

Full Text Available Abstract Background Progress in automated image analysis, virtual microscopy, hospital information systems, and interdisciplinary data exchange require image standards to be applied in tissue-based diagnosis. Aims To describe the theoretical background, practical experiences and comparable solutions in other medical fields to promote image standards applicable for diagnostic pathology. Theory and experiences Images used in tissue-based diagnosis present with pathology – specific characteristics. It seems appropriate to discuss their characteristics and potential standardization in relation to the levels of hierarchy in which they appear. All levels can be divided into legal, medical, and technological properties. Standards applied to the first level include regulations or aims to be fulfilled. In legal properties, they have to regulate features of privacy, image documentation, transmission, and presentation; in medical properties, features of disease – image combination, human – diagnostics, automated information extraction, archive retrieval and access; and in technological properties features of image acquisition, display, formats, transfer speed, safety, and system dynamics. The next lower second level has to implement the prescriptions of the upper one, i.e. describe how they are implemented. Legal aspects should demand secure encryption for privacy of all patient related data, image archives that include all images used for diagnostics for a period of 10 years at minimum, accurate annotations of dates and viewing, and precise hardware and software information. Medical aspects should demand standardized patients' files such as DICOM 3 or HL 7 including history and previous examinations, information of image display hardware and software, of image resolution and fields of view, of relation between sizes of biological objects and image sizes, and of access to archives and retrieval. Technological aspects should deal with image

Tensor-Based Morphometry Reveals Volumetric Deficits in Moderate=Severe Pediatric Traumatic Brain Injury

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Hua, Xue; Villalon-Reina, Julio; Moran, Lisa M.; Kernan, Claudia; Babikian, Talin; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C.; Thompson, Paul M.; Asarnow, Robert F.

2016-01-01

Abstract Traumatic brain injury (TBI) can cause widespread and prolonged brain degeneration. TBI can affect cognitive function and brain integrity for many years after injury, often with lasting effects in children, whose brains are still immature. Although TBI varies in how it affects different individuals, image analysis methods such as tensor-based morphometry (TBM) can reveal common areas of brain atrophy on magnetic resonance imaging (MRI), secondary effects of the initial injury, which will differ between subjects. Here we studied 36 pediatric moderate to severe TBI (msTBI) participants in the post-acute phase (1–6 months post-injury) and 18 msTBI participants who returned for their chronic assessment, along with well-matched controls at both time-points. Participants completed a battery of cognitive tests that we used to create a global cognitive performance score. Using TBM, we created three-dimensional (3D) maps of individual and group differences in regional brain volumes. At both the post-acute and chronic time-points, the greatest group differences were expansion of the lateral ventricles and reduction of the lingual gyrus in the TBI group. We found a number of smaller clusters of volume reduction in the cingulate gyrus, thalamus, and fusiform gyrus, and throughout the frontal, temporal, and parietal cortices. Additionally, we found extensive associations between our cognitive performance measure and regional brain volume. Our results indicate a pattern of atrophy still detectable 1-year post-injury, which may partially underlie the cognitive deficits frequently found in TBI. PMID:26393494

99mTc-HMPAO SPECT in brain death

International Nuclear Information System (INIS)

Tsuchida, Tatsuro; Sadato, Norihiro; Nishizawa, Sadahiko

1993-01-01

Brain single photon emission computed tomography (SPECT) with 99m Tc-d,l-hexamethyl-propyleneamine oxime (HMPAO) was performed twice in a 78-year-old man clinically diagnosed as brain death according to the standard criteria of the Japanese Ministry of Welfare. The first brain SPECT demonstrated the tracer accumulation in the brain, indicating preserved cerebral blood flow. The second brain SPECT performed 3 days later revealed cessation of the blood flow. In patients with preserved cerebral blood flow, the diagnosis of brain death cannot be made, even if they meet the existing criteria, because previous report noted the recovery in some of those patients. Brain perfusion SPECT plays an important role as a confirmatory test for the diagnosis of brain death. (author)

Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

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Mohseni Salehi, Seyed Sadegh; Erdogmus, Deniz; Gholipour, Ali

2017-11-01

Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and the robustness of brain extraction, therefore, are crucial for the accuracy of the entire brain analysis process. The state-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry, and therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent, and registration-free brain extraction tool, in this paper, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2-D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2-D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3-D image information without the need for computationally expensive 3-D convolutions and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark data sets, namely, LPBA40 and OASIS, in which we obtained the Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily oriented fetal brains in reconstructed fetal brain magnetic

Mixed acid-base disorder secondary to topiramate use in traumatic brain injury

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S Golla

2016-01-01

Full Text Available We report a case of a man with traumatic brain injury. He was started on to prophylactic topiramate which led to a mixed acid-base disorder. He had severe metabolic acidosis secondary to renal tubular acidification defect and respiratory alkalosis secondary to hyperventilation. Withdrawal of the offending drug led to the prompt resolution of the acid-base disturbance.

A study of science leadership and science standards in exemplary standards-based science programs

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Carpenter, Wendy Renae

The purpose for conducting this qualitative study was to explore best practices of exemplary standards-based science programs and instructional leadership practices in a charter high school and in a traditional high school. The focus of this study included how twelve participants aligned practices to National Science Education Standards to describe their science programs and science instructional practices. This study used a multi-site case study qualitative design. Data were obtained through a review of literature, interviews, observations, review of educational documents, and researcher's notes collected in a field log. The methodology used was a multi-site case study because of the potential, through cross analysis, for providing greater explanation of the findings in the study (Merriam, 1988). This study discovered six characteristics about the two high school's science programs that enhance the literature found in the National Science Education Standards; (a) Culture of expectations for learning-In exemplary science programs teachers are familiar with a wide range of curricula. They have the ability to examine critically and select activities to use with their students to promote the understanding of science; (b) Culture of varied experiences-In exemplary science programs students are provided different paths to learning, which help students, take in information and make sense of concepts and skills that are set forth by the standards; (c) Culture of continuous feedback-In exemplary science programs teachers and students work together to engage students in ongoing assessments of their work and that of others as prescribed in the standards; (d) Culture of Observations-In exemplary science programs students, teachers, and principals reflect on classroom instructional practices; teachers receive ongoing evaluations about their teaching and apply feedback towards improving practices as outlined in the standards; (e) Culture of continuous learning-In exemplary

Novel treatments of mood disorders based on brain circuitry (ECT, MST, TMS, VNS, DBS).

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George, Mark S; Nahas, Ziad; Li, Xiangbao; Kozel, F Andrew; Anderson, Berry; Yamanaka, Kaori; Chae, Jeong-Ho; Foust, Milton J

2002-10-01

Advances in understanding the functional and structural anatomy of depression outlined in this issue set the stage for attempting to manipulate implicated brain regions as potential antidepressant therapies. On the one hand, these circuit- and device-based approaches to treating depression are not new. Electroconvulsive therapy (ECT) dates back to the beginning of modern biologic psychiatry with the discovery and rapid increase of first chemical (around 1910), and then later ECT. On the other hand, this area represents an important paradigm shift with treatments that are radical and different. A dizzying array of diverse technologies now allows researchers to stimulate the brain in undreamed of ways. However, the approaches described in this article are still considered experimental and are not approved for use in the United States by the Food and Drug Administration (FDA), except ECT, which predates the FDA. These device-based approaches to brain stimulation offer promise as potential acute and even longterm treatments. Additionally, the research determining whether and how these devices work to influence mood promises to help unravel the neurophysiology of mood regulation. These novel treatments are thus the translational tools to bridge from advances in brain imaging, into new treatments for depressed patients. Copyright 2002, Elsevier Science (USA). All rights reserved.

Six Tips for Brain-Based Learning: Plus, a Bonus Class Project, Resources, and a Reading List

Science.gov (United States)

George Lucas Educational Foundation, 2011

2011-01-01

By understanding how the brain works, educators are better equipped to help students with everything from focusing attention to increasing retention. That's the promise of brain-based learning, which draws insights from neurology, psychology, technology, and other fields. Bringing this information to the classroom can help teachers engage diverse…

Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface.

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Laura Acqualagna

Full Text Available In the last years Brain Computer Interface (BCI technology has benefited from the development of sophisticated machine leaning methods that let the user operate the BCI after a few trials of calibration. One remarkable example is the recent development of co-adaptive techniques that proved to extend the use of BCIs also to people not able to achieve successful control with the standard BCI procedure. Especially for BCIs based on the modulation of the Sensorimotor Rhythm (SMR these improvements are essential, since a not negligible percentage of users is unable to operate SMR-BCIs efficiently. In this study we evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session. Different psychological interventions were performed prior the BCI session in order to investigate how motor coordination training and relaxation could influence BCI performance. A neurophysiological indicator based on the Power Spectral Density (PSD was extracted by the recording of few minutes of resting state brain activity and tested as predictor of BCI performances. Results show that high accuracies in operating the BCI could be reached by the majority of the participants before the end of the session. BCI performances could be significantly predicted by the neurophysiological indicator, consolidating the validity of the model previously developed. Anyway, we still found about 22% of users with performance significantly lower than the threshold of efficient BCI control at the end of the session. Being the inter-subject variability still the major problem of BCI technology, we pointed out crucial issues for those who did not achieve sufficient control. Finally, we propose valid developments to move a step forward to the applicability of the promising co-adaptive methods.

Comparison of the precision of two standardized co-ordinate systems for the quantitation of brain anatomy: preliminary results.

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Sandor, T; Tieman, J; Ong, H T; Moss, M B; Jolesz, F; Albert, M

1994-10-01

We assessed reproducible definition of two standardized co-ordinate systems for intersubject analysis of brain images. The baselines in the two co-ordinate systems were a modification of the canthomeatal (mCM) line and the anterior-posterior commissural (AC-PC) line. Axial spin-echo MR images of four subjects at 1.5T were used. Operator error was computed from the replicate analyses of two operators. The mCM line was determined by the lens of the eye and the internal auditory canal, and the AC-PC line was determined by the intersection of AC and PC with the interhemispheric fissure. Reproducibility of the mCM markers (SD = 0.59 mm) did not differ significantly from that of the AC-PC line (SD = 0.68 mm). The measurement error of the angle of the baseline (delta alpha), however, was more than 7 times as large for the AC-PC line as for the mCM line. An additional error affecting the rostrocaudal rotation of the co-ordinate systems, attributable to the distance between the anatomic markers, was 2.1 and 3.6 degrees (3 mm and 5 mm slice thickness) for the mCM co-ordinate system and 8.2 and 11.0 degrees (3 mm and 5 mm slice thickness) for the AC-PC system. The AC-PC line based co-ordinate system is therefore, less reproducible than the mCM line based system. This could be improved if a combination of axial and sagittal images were used for the definition of the AC-PC line.

The application of brain-based learning principles aided by GeoGebra to improve mathematical representation ability

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Priatna, Nanang

2017-08-01

The use of Information and Communication Technology (ICT) in mathematics instruction will help students in building conceptual understanding. One of the software products used in mathematics instruction is GeoGebra. The program enables simple visualization of complex geometric concepts and helps improve students' understanding of geometric concepts. Instruction applying brain-based learning principles is one oriented at the efforts of naturally empowering the brain potentials which enable students to build their own knowledge. One of the goals of mathematics instruction in school is to develop mathematical communication ability. Mathematical representation is regarded as a part of mathematical communication. It is a description, expression, symbolization, or modeling of mathematical ideas/concepts as an attempt of clarifying meanings or seeking for solutions to the problems encountered by students. The research aims to develop a learning model and teaching materials by applying the principles of brain-based learning aided by GeoGebra to improve junior high school students' mathematical representation ability. It adopted a quasi-experimental method with the non-randomized control group pretest-posttest design and the 2x3 factorial model. Based on analysis of the data, it is found that the increase in the mathematical representation ability of students who were treated with mathematics instruction applying the brain-based learning principles aided by GeoGebra was greater than the increase of the students given conventional instruction, both as a whole and based on the categories of students' initial mathematical ability.

3D PATTERN OF BRAIN ABNORMALITIES IN WILLIAMS SYNDROME VISUALIZED USING TENSOR-BASED MORPHOMETRY

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Chiang, Ming-Chang; Reiss, Allan L.; Lee, Agatha D.; Bellugi, Ursula; Galaburda, Albert M.; Korenberg, Julie R.; Mills, Debra L.; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

Williams syndrome (WS) is a neurodevelopmental disorder associated with deletion of ~20 contiguous genes in chromosome band 7q11.23. Individuals with WS exhibit mild to moderate mental retardation, but are relatively more proficient in specific language and musical abilities. We used tensor-based morphometry (TBM) to visualize the complex pattern of gray/white matter reductions in WS, based on fluid registration of structural brain images. Methods 3D T1-weighted brain MRIs of 41 WS subjects (age: 29.2±9.2SD years; 23F/18M) and 39 age-matched healthy controls (age: 27.5±7.4 years; 23F/16M) were fluidly registered to a minimum deformation target. Fine-scale volumetric differences were mapped between diagnostic groups. Local regions were identified where regional structure volumes were associated with diagnosis, and with intelligence quotient (IQ) scores. Brain asymmetry was also mapped and compared between diagnostic groups. Results WS subjects exhibited widely distributed brain volume reductions (~10–15% reduction; P < 0.0002, permutation test). After adjusting for total brain volume, the frontal lobes, anterior cingulate, superior temporal gyrus, amygdala, fusiform gyrus and cerebellum were found to be relatively preserved in WS, but parietal and occipital lobes, thalamus and basal ganglia, and midbrain were disproportionally decreased in volume (P < 0.0002). These regional volumes also correlated positively with performance IQ in adult WS subjects (age ≥ 30 years, P = 0.038). Conclusion TBM facilitates 3D visualization of brain volume reductions in WS. Reduced parietal/occipital volumes may be associated with visuospatial deficits in WS. By contrast, frontal lobes, amygdala, and cingulate gyrus are relatively preserved or even enlarged, consistent with unusual affect regulation and language production in WS. PMID:17512756

Study on Control of Brain Temperature for Brain Hypothermia Treatment

Science.gov (United States)

Gaohua, Lu; Wakamatsu, Hidetoshi

The brain hypothermia treatment is an attractive therapy for the neurologist because of its neuroprotection in hypoxic-ischemic encephalopathy patients. The present paper deals with the possibility of controlling the brain and other viscera in different temperatures from the viewpoint of system control. It is theoretically attempted to realize the special brain hypothermia treatment to cool only the head but to warm the body by using the simple apparatus such as the cooling cap, muffler and warming blanket. For this purpose, a biothermal system concerning the temperature difference between the brain and the other thoracico-abdominal viscus is synthesized from the biothermal model of hypothermic patient. The output controllability and the asymptotic stability of the system are examined on the basis of its structure. Then, the maximum temperature difference to be realized is shown dependent on the temperature range of the apparatus and also on the maximum gain determined from the coefficient matrices A, B and C of the biothermal system. Its theoretical analysis shows the realization of difference of about 2.5°C, if there is absolutely no constraint of the temperatures of the cooling cap, muffler and blanket. It is, however, physically unavailable. Those are shown by simulation example of the optimal brain temperature regulation using a standard adult database. It is thus concluded that the surface cooling and warming apparatus do no make it possible to realize the special brain hypothermia treatment, because the brain temperature cannot be cooled lower than those of other viscera in an appropriate temperature environment. This study shows that the ever-proposed good method of clinical treatment is in principle impossible in the actual brain hypothermia treatment.

Multivariate tensor-based brain anatomical surface morphometry via holomorphic one-forms.

Science.gov (United States)

Wang, Yalin; Chan, Tony F; Toga, Arthur W; Thompson, Paul M

2009-01-01

Here we introduce multivariate tensor-based surface morphometry using holomorphic one-forms to study brain anatomy. We computed new statistics from the Riemannian metric tensors that retain the full information in the deformation tensor fields. We introduce two different holomorphic one-forms that induce different surface conformal parameterizations. We applied this framework to 3D MRI data to analyze hippocampal surface morphometry in Alzheimer's Disease (AD; 26 subjects), lateral ventricular surface morphometry in HIV/AIDS (19 subjects) and cortical surface morphometry in Williams Syndrome (WS; 80 subjects). Experimental results demonstrated that our method powerfully detected brain surface abnormalities. Multivariate statistics on the local tensors outperformed other TBM methods including analysis of the Jacobian determinant, the largest eigenvalue, or the pair of eigenvalues, of the surface Jacobian matrix.

A tensor-based morphometry analysis of regional differences in brain volume in relation to prenatal alcohol exposure.

Science.gov (United States)

Meintjes, E M; Narr, K L; van der Kouwe, A J W; Molteno, C D; Pirnia, T; Gutman, B; Woods, R P; Thompson, P M; Jacobson, J L; Jacobson, S W

2014-01-01

Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD). Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM) methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6-11.0 years) and controls (n = 16, 9.5-11.0 years). Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1) the thalamus, midbrain, and ventromedial frontal lobe, (2) the superior cerebellum and inferior occipital lobe, (3) the dorsolateral frontal cortex, and (4) the precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA) regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent.

A tensor-based morphometry analysis of regional differences in brain volume in relation to prenatal alcohol exposure

Directory of Open Access Journals (Sweden)

E.M. Meintjes

2014-01-01

Full Text Available Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD. Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6–11.0 years and controls (n = 16, 9.5–11.0 years. Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1 the thalamus, midbrain, and ventromedial frontal lobe, (2 the superior cerebellum and inferior occipital lobe, (3 the dorsolateral frontal cortex, and (4 the precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent.

Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase-II: A Phase II Randomized Trial.

Science.gov (United States)

Okonkwo, David O; Shutter, Lori A; Moore, Carol; Temkin, Nancy R; Puccio, Ava M; Madden, Christopher J; Andaluz, Norberto; Chesnut, Randall M; Bullock, M Ross; Grant, Gerald A; McGregor, John; Weaver, Michael; Jallo, Jack; LeRoux, Peter D; Moberg, Dick; Barber, Jason; Lazaridis, Christos; Diaz-Arrastia, Ramon R

2017-11-01

A relationship between reduced brain tissue oxygenation and poor outcome following severe traumatic brain injury has been reported in observational studies. We designed a Phase II trial to assess whether a neurocritical care management protocol could improve brain tissue oxygenation levels in patients with severe traumatic brain injury and the feasibility of a Phase III efficacy study. Randomized prospective clinical trial. Ten ICUs in the United States. One hundred nineteen severe traumatic brain injury patients. Patients were randomized to treatment protocol based on intracranial pressure plus brain tissue oxygenation monitoring versus intracranial pressure monitoring alone. Brain tissue oxygenation data were recorded in the intracranial pressure -only group in blinded fashion. Tiered interventions in each arm were specified and impact on intracranial pressure and brain tissue oxygenation measured. Monitors were removed if values were normal for 48 hours consecutively, or after 5 days. Outcome was measured at 6 months using the Glasgow Outcome Scale-Extended. A management protocol based on brain tissue oxygenation and intracranial pressure monitoring reduced the proportion of time with brain tissue hypoxia after severe traumatic brain injury (0.45 in intracranial pressure-only group and 0.16 in intracranial pressure plus brain tissue oxygenation group; p injury after severe traumatic brain injury based on brain tissue oxygenation and intracranial pressure values was consistent with reduced mortality and increased proportions of patients with good recovery compared with intracranial pressure-only management; however, the study was not powered for clinical efficacy. Management of severe traumatic brain injury informed by multimodal intracranial pressure and brain tissue oxygenation monitoring reduced brain tissue hypoxia with a trend toward lower mortality and more favorable outcomes than intracranial pressure-only treatment. A Phase III randomized trial to assess

Towards a physiology-based measure of pain: patterns of human brain activity distinguish painful from non-painful thermal stimulation.

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Justin E Brown

Full Text Available Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessment has long been self-report. Because the inability to verbally communicate can prevent effective pain management, research efforts have focused on the development of a tool that accurately assesses pain without depending on self-report. Those previous efforts have not proven successful at substituting self-report with a clinically valid, physiology-based measure of pain. Recent neuroimaging data suggest that functional magnetic resonance imaging (fMRI and support vector machine (SVM learning can be jointly used to accurately assess cognitive states. Therefore, we hypothesized that an SVM trained on fMRI data can assess pain in the absence of self-report. In fMRI experiments, 24 individuals were presented painful and nonpainful thermal stimuli. Using eight individuals, we trained a linear SVM to distinguish these stimuli using whole-brain patterns of activity. We assessed the performance of this trained SVM model by testing it on 16 individuals whose data were not used for training. The whole-brain SVM was 81% accurate at distinguishing painful from non-painful stimuli (p<0.0000001. Using distance from the SVM hyperplane as a confidence measure, accuracy was further increased to 84%, albeit at the expense of excluding 15% of the stimuli that were the most difficult to classify. Overall performance of the SVM was primarily affected by activity in pain-processing regions of the brain including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex. Region of interest (ROI analyses revealed that whole-brain patterns of activity led to more accurate classification than localized activity from individual brain regions. Our findings demonstrate that fMRI with SVM learning can assess pain without requiring any communication from the person being tested. We outline tasks that should be

Multimodal surface-based morphometry reveals diffuse cortical atrophy in traumatic brain injury.

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Sorenson Donna J

2009-12-01

Full Text Available Abstract Background Patients with traumatic brain injury (TBI often present with significant cognitive deficits without corresponding evidence of cortical damage on neuroradiological examinations. One explanation for this puzzling observation is that the diffuse cortical abnormalities that characterize TBI are difficult to detect with standard imaging procedures. Here we investigated a patient with severe TBI-related cognitive impairments whose scan was interpreted as normal by a board-certified radiologist in order to determine if quantitative neuroimaging could detect cortical abnormalities not evident with standard neuroimaging procedures. Methods Cortical abnormalities were quantified using multimodal surfaced-based morphometry (MSBM that statistically combined information from high-resolution structural MRI and diffusion tensor imaging (DTI. Normal values of cortical anatomy and cortical and pericortical DTI properties were quantified in a population of 43 healthy control subjects. Corresponding measures from the patient were obtained in two independent imaging sessions. These data were quantified using both the average values for each lobe and the measurements from each point on the cortical surface. The results were statistically analyzed as z-scores from the mean with a p Results The TBI patient showed significant regional abnormalities in cortical thickness, gray matter diffusivity and pericortical white matter integrity that replicated across imaging sessions. Consistent with the patient's impaired performance on neuropsychological tests of executive function, cortical abnormalities were most pronounced in the frontal lobes. Conclusions MSBM is a promising tool for detecting subtle cortical abnormalities with high sensitivity and selectivity. MSBM may be particularly useful in evaluating cortical structure in TBI and other neurological conditions that produce diffuse abnormalities in both cortical structure and tissue properties.

77 FR 43018 - Updating OSHA Construction Standards Based on National Consensus Standards; Head Protection...

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2012-07-23

.... OSHA-2011-0184] RIN 1218-AC65 Updating OSHA Construction Standards Based on National Consensus... Health Administration (OSHA), Department of Labor. ACTION: Notice of proposed rulemaking; correction. SUMMARY: OSHA is correcting a notice of proposed rulemaking (NPRM) with regard to the construction...

Delineating Neural Structures of Developmental Human Brains with Diffusion Tensor Imaging

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Hao Huang

2010-01-01

Full Text Available The human brain anatomy is characterized by dramatic structural changes during fetal development. It is extraordinarily complex and yet its origin is a simple tubular structure. Revealing detailed anatomy at different stages of brain development not only aids in understanding this highly ordered process, but also provides clues to detect abnormalities caused by genetic or environmental factors. However, anatomical studies of human brain development during the fetal period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor imaging (DTI measures water diffusion to delineate the underlying neural structures. The high contrasts derived from DTI can be used to establish the brain atlas. With DTI tractography, coherent neural structures, such as white matter tracts, can be three-dimensionally reconstructed. The primary eigenvector of the diffusion tensor can be further explored to characterize microstructures in the cerebral wall of the developmental brains. In this mini-review, the application of DTI in order to reveal the structures of developmental fetal brains has been reviewed in the above-mentioned aspects. The fetal brain DTI provides a unique insight for delineating the neural structures in both macroscopic and microscopic levels. The resultant DTI database will provide structural guidance for the developmental study of human fetal brains in basic neuroscience, and reference standards for diagnostic radiology of premature newborns.

77 FR 53769 - Receipts-Based, Small Business Size Standard; Confirmation of Effective Date

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2012-09-04

... Flexibility Act of 1980, as amended. The NRC is increasing its receipts-based, small business size standard from $6.5 million to $7 million to conform to the standard set by the Small Business Administration...-Based, Small Business Size Standard; Confirmation of Effective Date AGENCY: Nuclear Regulatory...

Optimization of stereotactically-guided conformal treatment planning of sellar and parasellar tumors, based on normal brain dose volume histograms

International Nuclear Information System (INIS)

Perks, Julian R.; Jalali, Rakesh; Cosgrove, Vivian P.; Adams, Elizabeth J.; Shepherd, Stephen F.; Warrington, Alan P.; Brada, Michael

1999-01-01

Purpose: To investigate the optimal treatment plan for stereo tactically-guided conformal radiotherapy (SCRT) of sellar and parasellar lesions, with respect to sparing normal brain tissue, in the context of routine treatment delivery, based on dose volume histogram analysis. Methods and Materials: Computed tomography (CT) data sets for 8 patients with sellar- and parasellar-based tumors (6 pituitary adenomas and 2 meningiomas) have been used in this study. Treatment plans were prepared for 3-coplanar and 3-, 4-, 6-, and 30-noncoplanar-field arrangements to obtain 95% isodose coverage of the planning target volume (PTV) for each plan. Conformal shaping was achieved by customized blocks generated with the beams eye view (BEV) facility. Dose volume histograms (DVH) were calculated for the normal brain (excluding the PTV), and comparisons made for normal tissue sparing for all treatment plans at ≥80%, ≥60%, and ≥40% of the prescribed dose. Results: The mean volume of normal brain receiving ≥80% and ≥60% of the prescribed dose decreased by 22.3% (range 14.8-35.1%, standard deviation σ = 7.5%) and 47.6% (range 25.8-69.1%, σ 13.2%), respectively, with a 4-field noncoplanar technique when compared with a conventional 3-field coplanar technique. Adding 2 further fields, from 4-noncoplanar to 6-noncoplanar fields reduced the mean normal brain volume receiving ≥80% of the prescribed dose by a further 4.1% (range -6.5-11.8%, σ = 6.4%), and the volume receiving ≥60% by 3.3% (range -5.5-12.2%, σ = 5.4%), neither of which were statistically significant. Each case must be considered individually however, as a wide range is seen in the volume spared when increasing the number of fields from 4 to 6. Comparing the 4- and 6-field noncoplanar techniques to a 30-field conformal field approach (simulating a dynamic arc plan) revealed near-equivalent normal tissue sparing. Conclusion: Four to six widely spaced, fixed-conformal fields provide the optimum class solution

A Standardized Generalized Dimensionality Discrepancy Measure and a Standardized Model-Based Covariance for Dimensionality Assessment for Multidimensional Models

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Levy, Roy; Xu, Yuning; Yel, Nedim; Svetina, Dubravka

2015-01-01

The standardized generalized dimensionality discrepancy measure and the standardized model-based covariance are introduced as tools to critique dimensionality assumptions in multidimensional item response models. These tools are grounded in a covariance theory perspective and associated connections between dimensionality and local independence.…

Bayesian Modelling of Functional Whole Brain Connectivity

DEFF Research Database (Denmark)

Røge, Rasmus

the prevalent strategy of standardizing of fMRI time series and model data using directional statistics or we model the variability in the signal across the brain and across multiple subjects. In either case, we use Bayesian nonparametric modeling to automatically learn from the fMRI data the number......This thesis deals with parcellation of whole-brain functional magnetic resonance imaging (fMRI) using Bayesian inference with mixture models tailored to the fMRI data. In the three included papers and manuscripts, we analyze two different approaches to modeling fMRI signal; either we accept...... of funcional units, i.e. parcels. We benchmark the proposed mixture models against state of the art methods of brain parcellation, both probabilistic and non-probabilistic. The time series of each voxel are most often standardized using z-scoring which projects the time series data onto a hypersphere...

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.

Morphometric changes of whole brain in patients with alcohol addiction: a voxel-based morphometry study

International Nuclear Information System (INIS)

Li Jinfeng; Chen Zhiye; Ma Lin

2011-01-01

Objective: To evaluate morphometric changes of brain in patients with alcohol addiction by voxel-based morphometry. Methods: Fifteen patients with alcohol addiction and 15 health controls were recruited and underwent fluid attenuated inversion recovery (FLAIR) and 3D fast spoiled gradient echo (FSPGR) T 1 -weighted sequences on a 3.0 T MRI system. 3D FSPGR T 1 structure images were normalized, segmented and smoothed, and then underwent voxel-based morphometry. An ANCOVA was applied with age, body mass index (BMI), and education years as covariates because of exact sex match. A statistical threshold of P 0.05). Conclusions: Regional gray and white matter atrophy can be the initial changes in patients with alcohol addiction and the frontal region is a relative specific damaged brain region. VBM has a potential value for the detection of subtle brain atrophy in patients with alcohol addiction. (authors)

Memory as the "whole brain work": a large-scale model based on "oscillations in super-synergy".

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Başar, Erol

2005-01-01

According to recent trends, memory depends on several brain structures working in concert across many levels of neural organization; "memory is a constant work-in progress." The proposition of a brain theory based on super-synergy in neural populations is most pertinent for the understanding of this constant work in progress. This report introduces a new model on memory basing on the processes of EEG oscillations and Brain Dynamics. This model is shaped by the following conceptual and experimental steps: 1. The machineries of super-synergy in the whole brain are responsible for formation of sensory-cognitive percepts. 2. The expression "dynamic memory" is used for memory processes that evoke relevant changes in alpha, gamma, theta and delta activities. The concerted action of distributed multiple oscillatory processes provides a major key for understanding of distributed memory. It comprehends also the phyletic memory and reflexes. 3. The evolving memory, which incorporates reciprocal actions or reverberations in the APLR alliance and during working memory processes, is especially emphasized. 4. A new model related to "hierarchy of memories as a continuum" is introduced. 5. The notions of "longer activated memory" and "persistent memory" are proposed instead of long-term memory. 6. The new analysis to recognize faces emphasizes the importance of EEG oscillations in neurophysiology and Gestalt analysis. 7. The proposed basic framework called "Memory in the Whole Brain Work" emphasizes that memory and all brain functions are inseparable and are acting as a "whole" in the whole brain. 8. The role of genetic factors is fundamental in living system settings and oscillations and accordingly in memory, according to recent publications. 9. A link from the "whole brain" to "whole body," and incorporation of vegetative and neurological system, is proposed, EEG oscillations and ultraslow oscillations being a control parameter.

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play.

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Savitz, J B; Rauch, S L; Drevets, W C

2013-05-01

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders.

Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play

Science.gov (United States)

Savitz, J B; Rauch, S L; Drevets, W C

2013-01-01

In response to queries about whether brain imaging technology has reached the point where it is useful for making a clinical diagnosis and for helping to guide treatment selection, the American Psychiatric Association (APA) has recently written a position paper on the Clinical Application of Brain Imaging in Psychiatry. The following perspective piece is based on our contribution to this APA position paper, which specifically emphasized the application of neuroimaging in mood disorders. We present an introductory overview of the challenges faced by researchers in developing valid and reliable biomarkers for psychiatric disorders, followed by a synopsis of the extant neuroimaging findings in mood disorders, and an evidence-based review of the current research on brain imaging biomarkers in adult mood disorders. Although there are a number of promising results, by the standards proposed below, we argue that there are currently no brain imaging biomarkers that are clinically useful for establishing diagnosis or predicting treatment outcome in mood disorders. PMID:23546169

Joint source based analysis of multiple brain structures in studying major depressive disorder

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Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Resection of highly language-eloquent brain lesions based purely on rTMS language mapping without awake surgery.

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Ille, Sebastian; Sollmann, Nico; Butenschoen, Vicki M; Meyer, Bernhard; Ringel, Florian; Krieg, Sandro M

2016-12-01

The resection of left-sided perisylvian brain lesions harbours the risk of postoperative language impairment. Therefore the individual patient's language distribution is investigated by intraoperative direct cortical stimulation (DCS) during awake surgery. Yet, not all patients qualify for awake surgery. Non-invasive language mapping by repetitive navigated transcranial magnetic stimulation (rTMS) has frequently shown a high correlation in comparison with the results of DCS language mapping in terms of language-negative brain regions. The present study analyses the extent of resection (EOR) and functional outcome of patients who underwent left-sided perisylvian resection of brain lesions based purely on rTMS language mapping. Four patients with left-sided perisylvian brain lesions (two gliomas WHO III, one glioblastoma, one cavernous angioma) underwent rTMS language mapping prior to surgery. Data from rTMS language mapping and rTMS-based diffusion tensor imaging fibre tracking (DTI-FT) were transferred to the intraoperative neuronavigation system. Preoperatively, 5 days after surgery (POD5), and 3 months after surgery (POM3) clinical follow-up examinations were performed. No patient suffered from a new surgery-related aphasia at POM3. Three patients underwent complete resection immediately, while one patient required a second rTMS-based resection some days later to achieve the final, complete resection. The present study shows for the first time the feasibility of successfully resecting language-eloquent brain lesions based purely on the results of negative language maps provided by rTMS language mapping and rTMS-based DTI-FT. In very select cases, this technique can provide a rescue strategy with an optimal functional outcome and EOR when awake surgery is not feasible.

How Alzheimer's Changes the Brain

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Full Text Available ... ideas to treat and prevent the disease. Category Science & Technology License Standard ... Keep Your Brain Healthy for the Rest of Your Life - Duration: 57:30. University of California Television (UCTV) ...

An Increasing of Primary School Teachers' Competency in Brain-Based Learning

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Waree, Chaiwat

2017-01-01

The purpose of the study was to develop a powerful and empowering guide (CBT) of elementary school teachers, to compare the ability of elementary school teachers. Management learning uses brain as a base. The experimental group with a control group the experimental group used in this research was a teacher at the grade level. 4-6 in province By…

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

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Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

Cranial CT with 64-, 16-, 4- and single-slice CT systems-comparison of image quality and posterior fossa artifacts in routine brain imaging with standard protocols

Energy Technology Data Exchange (ETDEWEB)

Ertl-Wagner, Birgit; Eftimov, Lara; Becker, Christoph; Reiser, Maximilian [University of Munich, Grosshadern (Germany). Institute of Clinical Radiology; Blume, Jeffrey; Cormack, Jean [Brown University, Center for Statistical Sciences, Providence, RI (United States); Bruening, Roland; Brueckmann, Hartmut [University of Munich, Grosshadern (Germany). Department of Neuroradiology

2008-08-15

Posterior fossa artifacts constitute a characteristic limitation of cranial CT. To identify practical benefits and drawbacks of newer CT systems with reduced collimation in routine cranial imaging, we aimed to investigate image quality, posterior fossa artifacts and parenchymal delineation in non-enhanced CT (NECT) with 1-, 4-, 16- and 64-slice scanners using standard scan protocols. We prospectively enrolled 25 consecutive patients undergoing NECT on a 64-slice CT. Three groups with 25 patients having undergone NECT on 1-, 4- and 16-slice CT machines were matched regarding age and sex. Standard routine CT parameters were used on each CT system with helical acquisition in the posterior fossa; the parameters varied regarding collimation and radiation dose. Three blinded readers independently assessed the cases regarding image quality, infra- and supratentorial artifacts and delineation of brain parenchymal structures on a five-point ordinal scale. Reading orders were randomized. A proportional odds model that accounted for the correlated nature of the data was fit using generalized estimating equations. Posterior fossa artifacts were significantly reduced, and the delineation of infratentorial brain structures was significantly improved with the thinner collimation used for the newer CT systems (p<0.001). No significant differences were observed for midbrain structures (p>0.5). The thinner collimation available on modern CT systems leads to reduced posterior fossa artifacts and to a better delineation of brain parenchyma in the posterior fossa. (orig.)

Virtual standards of vibration-based defects diagnostics in railway industry

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Vladimir TETTER

2009-01-01

Full Text Available The issues related to testing the functionality stated by producers of vibration-based diagnostic equipment have been considered. The introduction of virtual standards of defects found in bearing and geared assemblies of rolling stock is offered. The variants of virtual standards realization have been considered.

Computation of reliable textural indices from multimodal brain MRI: suggestions based on a study of patients with diffuse intrinsic pontine glioma

Science.gov (United States)

Goya-Outi, Jessica; Orlhac, Fanny; Calmon, Raphael; Alentorn, Agusti; Nioche, Christophe; Philippe, Cathy; Puget, Stéphanie; Boddaert, Nathalie; Buvat, Irène; Grill, Jacques; Frouin, Vincent; Frouin, Frederique

2018-05-01

Few methodological studies regarding widely used textural indices robustness in MRI have been reported. In this context, this study aims to propose some rules to compute reliable textural indices from multimodal 3D brain MRI. Diagnosis and post-biopsy MR scans including T1, post-contrast T1, T2 and FLAIR images from thirty children with diffuse intrinsic pontine glioma (DIPG) were considered. The hybrid white stripe method was adapted to standardize MR intensities. Sixty textural indices were then computed for each modality in different regions of interest (ROI), including tumor and white matter (WM). Three types of intensity binning were compared : constant bin width and relative bounds; constant number of bins and relative bounds; constant number of bins and absolute bounds. The impact of the volume of the region was also tested within the WM. First, the mean Hellinger distance between patient-based intensity distributions decreased by a factor greater than 10 in WM and greater than 2.5 in gray matter after standardization. Regarding the binning strategy, the ranking of patients was highly correlated for 188/240 features when comparing with , but for only 20 when comparing with , and nine when comparing with . Furthermore, when using or texture indices reflected tumor heterogeneity as assessed visually by experts. Last, 41 features presented statistically significant differences between contralateral WM regions when ROI size slightly varies across patients, and none when using ROI of the same size. For regions with similar size, 224 features were significantly different between WM and tumor. Valuable information from texture indices can be biased by methodological choices. Recommendations are to standardize intensities in MR brain volumes, to use intensity binning with constant bin width, and to define regions with the same volumes to get reliable textural indices.

Brain Emotional Learning Based Intelligent Decoupler for Nonlinear Multi-Input Multi-Output Distillation Columns

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M. H. El-Saify

2017-01-01

Full Text Available The distillation process is vital in many fields of chemical industries, such as the two-coupled distillation columns that are usually highly nonlinear Multi-Input Multi-Output (MIMO coupled processes. The control of MIMO process is usually implemented via a decentralized approach using a set of Single-Input Single-Output (SISO loop controllers. Decoupling the MIMO process into group of single loops requires proper input-output pairing and development of decoupling compensator unit. This paper proposes a novel intelligent decoupling approach for MIMO processes based on new MIMO brain emotional learning architecture. A MIMO architecture of Brain Emotional Learning Based Intelligent Controller (BELBIC is developed and applied as a decoupler for 4 input/4 output highly nonlinear coupled distillation columns process. Moreover, the performance of the proposed Brain Emotional Learning Based Intelligent Decoupler (BELBID is enhanced using Particle Swarm Optimization (PSO technique. The performance is compared with the PSO optimized steady state decoupling compensation matrix. Mathematical models of the distillation columns and the decouplers are built and tested in simulation environment by applying the same inputs. The results prove remarkable success of the BELBID in minimizing the loops interactions without degrading the output that every input has been paired with.

Comparison of template registration methods for multi-site meta-analysis of brain morphometry

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Faskowitz, Joshua; de Zubicaray, Greig I.; McMahon, Katie L.; Wright, Margaret J.; Thompson, Paul M.; Jahanshad, Neda

2016-03-01

Neuroimaging consortia such as ENIGMA can significantly improve power to discover factors that affect the human brain by pooling statistical inferences across cohorts to draw generalized conclusions from populations around the world. Voxelwise analyses such as tensor-based morphometry also allow an unbiased search for effects throughout the brain. Even so, such consortium-based analyses are limited by a lack of high-powered methods to harmonize voxelwise information across study populations and scanners. While the simplest approach may be to map all images to a single standard space, the benefits of cohort-specific templates have long been established. Here we studied methods to pool voxel-wise data across sites using templates customized for each cohort but providing a meaningful common space across all studies for voxelwise comparisons. As non-linear 3D MRI registrations represent mappings between images at millimeter resolution, we need to consider the reliability of these mappings. To evaluate these mappings, we calculated test-retest statistics on the volumetric maps of expansion and contraction. Further, we created study-specific brain templates for ten T1-weighted MRI datasets, and a common space from four study-specific templates. We evaluated the efficacy of using a two-step registration framework versus a single standard space. We found that the two-step framework more reliably mapped subjects to a common space.

How Alzheimer's Changes the Brain

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Full Text Available ... This 4-minute video shows how Alzheimer’s affects the human brain and looks at promising ideas to treat and prevent the disease. Category Science & Technology License Standard YouTube License ...

How Alzheimer's Changes the Brain

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Full Text Available ... ideas to treat and prevent the disease. Category Science & Technology License Standard ... Program: Keep Your Brain Healthy for the Rest of Your Life - Duration: 57:30. University of California Television (UCTV) ...

Evaluation of factors influencing 18F-FET uptake in the brain

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Antoine Verger

2018-01-01

Full Text Available PET using the amino-acid O-(2-18F-fluoroethyl-l-tyrosine (18F-FET is gaining increasing interest for brain tumour management. Semi-quantitative analysis of tracer uptake in brain tumours is based on the standardized uptake value (SUV and the tumour-to-brain ratio (TBR. The aim of this study was to explore physiological factors that might influence the relationship of SUV of 18F-FET uptake in various brain areas, and thus affect quantification of 18F-FET uptake in brain tumours. Negative 18F-FET PET scans of 107 subjects, showing an inconspicuous brain distribution of 18F-FET, were evaluated retrospectively. Whole-brain quantitative analysis with Statistical Parametric Mapping (SPM using parametric SUV PET images, and volumes of interest (VOIs analysis with fronto-parietal, temporal, occipital, and cerebellar SUV background areas were performed to study the effect of age, gender, height, weight, injected activity, body mass index (BMI, and body surface area (BSA. After multivariate analysis, female gender and high BMI were found to be two independent factors associated with increased SUV of 18F-FET uptake in the brain. In women, SUVmean of 18F-FET uptake in the brain was 23% higher than in men (p < 0.01. SUVmean of 18F-FET uptake in the brain was positively correlated with BMI (r = 0.29; p < 0.01. The influence of these factors on SUV of 18F-FET was similar in all brain areas. In conclusion, SUV of 18F-FET in the normal brain is influenced by gender and weakly by BMI, but changes are similar in all brain areas.

Examining Brain Morphometry Associated with Self-Esteem in Young Adults Using Multilevel-ROI-Features-Based Classification Method

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Bo Peng

2017-05-01

Full Text Available Purpose: This study is to exam self-esteem related brain morphometry on brain magnetic resonance (MR images using multilevel-features-based classification method.Method: The multilevel region of interest (ROI features consist of two types of features: (i ROI features, which include gray matter volume, white matter volume, cerebrospinal fluid volume, cortical thickness, and cortical surface area, and (ii similarity features, which are based on similarity calculation of cortical thickness between ROIs. For each feature type, a hybrid feature selection method, comprising of filter-based and wrapper-based algorithms, is used to select the most discriminating features. ROI features and similarity features are integrated by using multi-kernel support vector machines (SVMs with appropriate weighting factor.Results: The classification performance is improved by using multilevel ROI features with an accuracy of 96.66%, a specificity of 96.62%, and a sensitivity of 95.67%. The most discriminating ROI features that are related to self-esteem spread over occipital lobe, frontal lobe, parietal lobe, limbic lobe, temporal lobe, and central region, mainly involving white matter and cortical thickness. The most discriminating similarity features are distributed in both the right and left hemisphere, including frontal lobe, occipital lobe, limbic lobe, parietal lobe, and central region, which conveys information of structural connections between different brain regions.Conclusion: By using ROI features and similarity features to exam self-esteem related brain morphometry, this paper provides a pilot evidence that self-esteem is linked to specific ROIs and structural connections between different brain regions.

Brain without anatomy: construction and comparison of fully network-driven structural MRI connectomes.

Directory of Open Access Journals (Sweden)

Olga Tymofiyeva

Full Text Available MRI connectomics methods treat the brain as a network and provide new information about its organization, efficiency, and mechanisms of disruption. The most commonly used method of defining network nodes is to register the brain to a standardized anatomical atlas based on the Brodmann areas. This approach is limited by inter-subject variability and can be especially problematic in the context of brain maturation or neuroplasticity (cerebral reorganization after brain damage. In this study, we combined different image processing and network theory methods and created a novel approach that enables atlas-free construction and connection-wise comparison of diffusion MRI-based brain networks. We illustrated the proposed approach in three age groups: neonates, 6-month-old infants, and adults. First, we explored a data-driven method of determining the optimal number of equal-area nodes based on the assumption that all cortical areas of the brain are connected and, thus, no part of the brain is structurally isolated. Second, to enable a connection-wise comparison, alignment to a "reference brain" was performed in the network domain within each group using a matrix alignment algorithm with simulated annealing. The correlation coefficients after pair-wise network alignment ranged from 0.6102 to 0.6673. To test the method's reproducibility, one subject from the 6-month-old group and one from the adult group were scanned twice, resulting in correlation coefficients of 0.7443 and 0.7037, respectively. While being less than 1 due to parcellation and noise, statistically, these values were significantly higher than inter-subject values. Rotation of the parcellation largely explained the variability. Through the abstraction from anatomy, the developed framework allows for a fully network-driven analysis of structural MRI connectomes and can be applied to subjects at any stage of development and with substantial differences in cortical anatomy.

Applying Acoustical and Musicological Analysis to Detect Brain Responses to Realistic Music: A Case Study

Directory of Open Access Journals (Sweden)

Niels Trusbak Haumann

2018-05-01

Full Text Available Music information retrieval (MIR methods offer interesting possibilities for automatically identifying time points in music recordings that relate to specific brain responses. However, how the acoustical features and the novelty of the music structure affect the brain response is not yet clear. In the present study, we tested a new method for automatically identifying time points of brain responses based on MIR analysis. We utilized an existing database including brain recordings of 48 healthy listeners measured with electroencephalography (EEG and magnetoencephalography (MEG. While we succeeded in capturing brain responses related to acoustical changes in the modern tango piece Adios Nonino, we obtained less reliable brain responses with a metal rock piece and a modern symphony orchestra musical composition. However, brain responses might also relate to the novelty of the music structure. Hence, we added a manual musicological analysis of novelty in the musical structure to the computational acoustic analysis, obtaining strong brain responses even to the rock and modern pieces. Although no standardized method yet exists, these preliminary results suggest that analysis of novelty in music is an important aid to MIR analysis for investigating brain responses to realistic music.

Query Health: standards-based, cross-platform population health surveillance.

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Klann, Jeffrey G; Buck, Michael D; Brown, Jeffrey; Hadley, Marc; Elmore, Richard; Weber, Griffin M; Murphy, Shawn N

2014-01-01

Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects. Query Health defined a standards-based approach for distributed population health queries, using an ontology based on the Quality Data Model and Consolidated Clinical Document Architecture, Health Quality Measures Format (HQMF) as the query language, the Query Envelope as the secure transport layer, and the Quality Reporting Document Architecture as the result language. We implemented this approach using Informatics for Integrating Biology and the Bedside (i2b2) and hQuery for data analytics and PopMedNet for access control, secure query distribution, and response. We deployed the reference implementation at three pilot sites: two public health departments (New York City and Massachusetts) and one pilot designed to support Food and Drug Administration post-market safety surveillance activities. The pilots were successful, although improved cross-platform data normalization is needed. This initiative resulted in a standards-based methodology for population health queries, a reference implementation, and revision of the HQMF standard. It also informed future directions regarding interoperability and data access for ONC's Data Access Framework initiative. Query Health was a test of the learning health system that supplied a functional methodology and reference implementation for distributed population health queries that has been validated at three sites. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under

Structural brain alterations in hemifacial spasm: A voxel-based morphometry and diffusion tensor imaging study.

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Tu, Ye; Yu, Tian; Wei, Yongxu; Sun, Kun; Zhao, Weiguo; Yu, Buwei

2016-02-01

Hemifacial spasm (HFS) is characterized by involuntary, irregular clonic or tonic movement of muscles innervated by the facial nerve. We evaluated structural reorganization in brain gray matter and white matter and whether neuroplasticity is linked to clinical features in HFS patients. High-resolution structural magnetic resonance imaging and diffusion tensor imaging data were acquired by 3.0 T MRI from 42 patients with HFS and 30 healthy subjects. The severity of the spasm was assessed according to Jankovic disability rating scale. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) analysis were performed to identify regional grey matter volume (GMV) changes and whole-brain microstructural integrity disruption measured by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD). The VBM analysis showed that patients with HFS reduced GMV in the right inferior parietal lobule and increased GMV in the cerebellar lobule VIII, when compared with healthy subjects. Furthermore, within the HFS disease group, GMV decreased with the disease duration in the right inferior parietal lobule. TBSS did not identify group differences in diffusivity parameters. While no white matter integrity disruption was detected in the brain of patients with HFS, our study identified evident GMV changes in brain areas which were known to be involved in motor control. Our results suggest that HFS, a chronic neurovascular conflict disease, is related to structural reorganization in the brain. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An SPM8-based Approach for Attenuation Correction Combining Segmentation and Non-rigid Template Formation: Application to Simultaneous PET/MR Brain Imaging

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Izquierdo-Garcia, David; Hansen, Adam E.; Förster, Stefan; Benoit, Didier; Schachoff, Sylvia; Fürst, Sebastian; Chen, Kevin T.; Chonde, Daniel B.; Catana, Ciprian

2014-01-01

We present an approach for head MR-based attenuation correction (MR-AC) based on the Statistical Parametric Mapping (SPM8) software that combines segmentation- and atlas-based features to provide a robust technique to generate attenuation maps (µ-maps) from MR data in integrated PET/MR scanners. Methods Coregistered anatomical MR and CT images acquired in 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray and white matter, cerebro-spinal fluid, bone and soft tissue, and air), which were then non-rigidly coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomical MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients (LACs) to be used for AC of PET data. The method was validated on sixteen new subjects with brain tumors (N=12) or mild cognitive impairment (N=4) who underwent CT and PET/MR scans. The µ-maps and corresponding reconstructed PET images were compared to those obtained using the gold standard CT-based approach and the Dixon-based method available on the Siemens Biograph mMR scanner. Relative change (RC) images were generated in each case and voxel- and region of interest (ROI)-based analyses were performed. Results The leave-one-out cross-validation analysis of the data from the 15 atlas-generation subjects showed small errors in brain LACs (RC=1.38%±4.52%) compared to the gold standard. Similar results (RC=1.86±4.06%) were obtained from the analysis of the atlas-validation datasets. The voxel- and ROI-based analysis of the corresponding reconstructed PET images revealed quantification errors of 3.87±5.0% and 2.74±2.28%, respectively. The Dixon-based method performed substantially worse (the mean RC values were 13.0±10.25% and 9.38±4.97%, respectively). Areas closer to skull showed the largest

Radiotherapy for pediatric brain tumors: Standards of care, current clinical trials, and new directions

International Nuclear Information System (INIS)

Goldwein, Joel W.

1995-01-01

The objectives of the course are to evaluate the role of radiation therapy in the treatment of pediatric brain tumors. Areas where the role is evolving will be identified, and the results of clinical trials which been mounted to clarify radiotherapy's role will be reviewed. Brain tumors are the second most common malignancy of childhood after leukemias and lymphomas. However, they remain the most common group of childhood tumors to require radiation therapy. Therefore, a thorough understanding of these tumors, and the appropriate role of surgery, radiation and chemotherapy is critical. Issues surrounding the management of sequelae are no less important. The role of radiotherapy for the treatment of these tumors is far different from that for adults. These differences relate to the profound potential for sequelae from therapy, the higher overall cure rates, and the utility of multimodality therapies. In addition, the rarity of childhood brain tumors compared with adults' makes them more difficult to study. In this session, the following issues will be reviewed; 1. Incidence of pediatric brain tumors, 2. General issues regarding symptoms, diagnosis, diagnostic tests and evaluation, 3. Importance of a team approach, 4. General issues regarding treatment sequelae, 5. Specific tumor types/entities; a. Cerebellar Astrocytomas b. Benign and malignant Gliomas including brainstem and chiasmatic lesions c. Primitive Neuroectodermal Tumors (PNET) and Medulloblastoma d. Ependymomas e. Craniopharyngiomas f. Germ cell tumors g. Miscellaneous and rare pediatric brain tumors 6. Management of sequelae 7. New and future directions a. Treatment of infants b. The expanding role of chemotherapy c. Advances in radiotherapy. The attendees will complete the course with a better understanding of the role that radiation therapy plays in the treatment of pediatric brain tumors. They will be knowledgeable in the foundation for that role, and the changes which are likely to take place in the

Learning-based prediction of gestational age from ultrasound images of the fetal brain.

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Namburete, Ana I L; Stebbing, Richard V; Kemp, Bryn; Yaqub, Mohammad; Papageorghiou, Aris T; Alison Noble, J

2015-04-01

We propose an automated framework for predicting gestational age (GA) and neurodevelopmental maturation of a fetus based on 3D ultrasound (US) brain image appearance. Our method capitalizes on age-related sonographic image patterns in conjunction with clinical measurements to develop, for the first time, a predictive age model which improves on the GA-prediction potential of US images. The framework benefits from a manifold surface representation of the fetal head which delineates the inner skull boundary and serves as a common coordinate system based on cranial position. This allows for fast and efficient sampling of anatomically-corresponding brain regions to achieve like-for-like structural comparison of different developmental stages. We develop bespoke features which capture neurosonographic patterns in 3D images, and using a regression forest classifier, we characterize structural brain development both spatially and temporally to capture the natural variation existing in a healthy population (N=447) over an age range of active brain maturation (18-34weeks). On a routine clinical dataset (N=187) our age prediction results strongly correlate with true GA (r=0.98,accurate within±6.10days), confirming the link between maturational progression and neurosonographic activity observable across gestation. Our model also outperforms current clinical methods by ±4.57 days in the third trimester-a period complicated by biological variations in the fetal population. Through feature selection, the model successfully identified the most age-discriminating anatomies over this age range as being the Sylvian fissure, cingulate, and callosal sulci. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Creating the brain and interacting with the brain: an integrated approach to understanding the brain

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Morimoto, Jun; Kawato, Mitsuo

2015-01-01

In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. PMID:25589568

ROC [Receiver Operating Characteristics] study of maximum likelihood estimator human brain image reconstructions in PET [Positron Emission Tomography] clinical practice

International Nuclear Information System (INIS)

Llacer, J.; Veklerov, E.; Nolan, D.; Grafton, S.T.; Mazziotta, J.C.; Hawkins, R.A.; Hoh, C.K.; Hoffman, E.J.

1990-10-01

This paper will report on the progress to date in carrying out Receiver Operating Characteristics (ROC) studies comparing Maximum Likelihood Estimator (MLE) and Filtered Backprojection (FBP) reconstructions of normal and abnormal human brain PET data in a clinical setting. A previous statistical study of reconstructions of the Hoffman brain phantom with real data indicated that the pixel-to-pixel standard deviation in feasible MLE images is approximately proportional to the square root of the number of counts in a region, as opposed to a standard deviation which is high and largely independent of the number of counts in FBP. A preliminary ROC study carried out with 10 non-medical observers performing a relatively simple detectability task indicates that, for the majority of observers, lower standard deviation translates itself into a statistically significant detectability advantage in MLE reconstructions. The initial results of ongoing tests with four experienced neurologists/nuclear medicine physicians are presented. Normal cases of 18 F -- fluorodeoxyglucose (FDG) cerebral metabolism studies and abnormal cases in which a variety of lesions have been introduced into normal data sets have been evaluated. We report on the results of reading the reconstructions of 90 data sets, each corresponding to a single brain slice. It has become apparent that the design of the study based on reading single brain slices is too insensitive and we propose a variation based on reading three consecutive slices at a time, rating only the center slice. 9 refs., 2 figs., 1 tab

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

Directory of Open Access Journals (Sweden)

Kishan Andre Liyanage

Full Text Available Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap to 1 (complete overlap. For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

Infrasounds and biorhythms of the human brain

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Panuszka, Ryszard; Damijan, Zbigniew; Kasprzak, Cezary; McGlothlin, James

2002-05-01

Low Frequency Noise (LFN) and infrasound has begun a new public health hazard. Evaluations of annoyance of (LFN) on human occupational health were based on standards where reactions of human auditory system and vibrations of parts of human body were small. Significant sensitivity has been observed on the central nervous system from infrasonic waves especially below 10 Hz. Observed follow-up effects in the brain gives incentive to study the relationship between parameters of waves and reactions obtained of biorhythms (EEG) and heart action (EKG). New results show the impact of LFN on the electrical potentials of the brain are dependent on the pressure waves on the human body. Electrical activity of circulatory system was also affected. Signals recorded in industrial workplaces were duplicated by loudspeakers and used to record data from a typical LFN spectra with 5 and 7 Hz in a laboratory chamber. External noise, electromagnetic fields, temperature, dust, and other elements were controlled. Results show not only a follow-up effect in the brain but also a result similar to arrhythmia in the heart. Relaxations effects were observed of people impacted by waves generated from natural sources such as streams and waterfalls.

The validation of the standard Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire 30 (EORTC QLQ-C30 in pre-operative patients with brain tumor in China

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Zhang Hong-ying

2011-04-01

Full Text Available Abstract Background Health related quality of life (HRQOL has increasingly emphasized on cancer patients. The psychometric properties of the standard Chinese version of the European Organization for Research and Treatment of Cancer Quality of Life Core Questionnaire 30 (EORTC QLQ-C30, version 3.0 in brain tumor patients wasn't proven, and there was no baseline HRQOL in brain tumor patients prior to surgery. Methods The questionnaire EORTC QLQ-C30 (version 3.0 was administered at three time points: T1, the first or the second day that patients were hospitalized after the brain tumor suspected or diagnosed by MRI or CT; T2, 1 to 2 days after T1, (T1 and T2 were both before surgery; T3, the day before discharge. Clinical variables included disease histologic types, cognitive function, and Karnofsky Performance Status. Results Cronbach's alpha coefficients for multi-item scales were greater than .70 and multitrait scaling analysis showed that most of the item-scale correlation coefficients met the standards of convergent and discriminant validity, except for the cognitive functioning scale. All scales and items exhibited construct validity. Score changes over peri-operation were observed in physical and role functioning scales. Compared with mixed cancer patients assessed after surgery but before adjuvant treatment, brain tumor patients assessed pre-surgery presented better function and fewer symptoms. Conclusions The standard Chinese version of the EORTC QLQ-C30 was overall a valid instrument to assess HRQOL in brain tumor patients in China. The baseline HRQOL in brain tumor patients pre-surgery was better than that in mixed cancer patients post-surgery. Future study should modify cognitive functioning scale and examine test-retest reliability and response validity.

77 FR 42988 - Updating OSHA Construction Standards Based on National Consensus Standards; Head Protection...

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2012-07-23

.... OSHA-2011-0184] RIN 1218-AC65 Updating OSHA Construction Standards Based on National Consensus... Administration (OSHA), Department of Labor. ACTION: Direct final rule; correction. SUMMARY: OSHA is correcting a... confusion resulting from a drafting error. OSHA published the DFR on June 22, 2012 (77 FR 37587). OSHA also...

Gender similarities and differences in brain activation strategies: Voxel-based meta-analysis on fMRI studies.

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AlRyalat, Saif Aldeen

2017-01-01

Gender similarities and differences have long been a matter of debate in almost all human research, especially upon reaching the discussion about brain functions. This large scale meta-analysis was performed on functional MRI studies. It included more than 700 active brain foci from more than 70 different experiments to study gender related similarities and differences in brain activation strategies for three of the main brain functions: Visual-spatial cognition, memory, and emotion. Areas that are significantly activated by both genders (i.e. core areas) for the tested brain function are mentioned, whereas those areas significantly activated exclusively in one gender are the gender specific areas. During visual-spatial cognition task, and in addition to the core areas, males significantly activated their left superior frontal gyrus, compared with left superior parietal lobule in females. For memory tasks, several different brain areas activated by each gender, but females significantly activated two areas from the limbic system during memory retrieval tasks. For emotional task, males tend to recruit their bilateral prefrontal regions, whereas females tend to recruit their bilateral amygdalae. This meta-analysis provides an overview based on functional MRI studies on how males and females use their brain.

Visualizing whole-brain DTI tractography with GPU-based Tuboids and LoD management.

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Petrovic, Vid; Fallon, James; Kuester, Falko

2007-01-01

Diffusion Tensor Imaging (DTI) of the human brain, coupled with tractography techniques, enable the extraction of large-collections of three-dimensional tract pathways per subject. These pathways and pathway bundles represent the connectivity between different brain regions and are critical for the understanding of brain related diseases. A flexible and efficient GPU-based rendering technique for DTI tractography data is presented that addresses common performance bottlenecks and image-quality issues, allowing interactive render rates to be achieved on commodity hardware. An occlusion query-based pathway LoD management system for streamlines/streamtubes/tuboids is introduced that optimizes input geometry, vertex processing, and fragment processing loads, and helps reduce overdraw. The tuboid, a fully-shaded streamtube impostor constructed entirely on the GPU from streamline vertices, is also introduced. Unlike full streamtubes and other impostor constructs, tuboids require little to no preprocessing or extra space over the original streamline data. The supported fragment processing levels of detail range from texture-based draft shading to full raycast normal computation, Phong shading, environment mapping, and curvature-correct text labeling. The presented text labeling technique for tuboids provides adaptive, aesthetically pleasing labels that appear attached to the surface of the tubes. Furthermore, an occlusion query aggregating and scheduling scheme for tuboids is described that reduces the query overhead. Results for a tractography dataset are presented, and demonstrate that LoD-managed tuboids offer benefits over traditional streamtubes both in performance and appearance.

Whole brain helical Tomotherapy with integrated boost for brain metastases in patients with malignant melanoma–a randomized trial

International Nuclear Information System (INIS)

Hauswald, Henrik; Habl, Gregor; Krug, David; Kehle, Denise; Combs, Stephanie E; Bermejo, Justo Lorenzo; Debus, Jürgen; Sterzing, Florian

2013-01-01

Patients with malignant melanoma may develop brain metastases during the course of the disease, requiring radiotherapeutic treatment. In patients with 1–3 brain metastases, radiosurgery has been established as a treatment option besides surgery. For patients with 4 or more brain metastases, whole brain radiotherapy is considered the standard treatment. In certain patients with brain metastases, radiation treatment using whole brain helical Tomotherapy with integrated boost and hippocampal-sparing may improve prognosis of these patients. The present prospective, randomized two-armed trial aims to exploratory investigate the treatment response to conventional whole brain radiotherapy applying 30 Gy in 10 fractions versus whole brain helical Tomotherapy applying 30 Gy in 10 fractions with an integrated boost of 50 Gy to the brain metastases as well as hippocampal-sparing in patients with brain metastases from malignant melanoma. The main inclusion criteria include magnetic resonance imaging confirmed brain metastases from a histopathologically confirmed malignant melanoma in patients with a minimum age of 18 years. The main exclusion criteria include a previous radiotherapy of the brain and not having recovered from acute high-grade toxicities of prior therapies. The primary endpoint is treatment-related toxicity. Secondary endpoints include imaging response, local and loco-regional progression-free survival, overall survival and quality of life

Building IoT Services for Aging in Place Using Standard-Based IoT Platforms and Heterogeneous IoT Products

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Sheik Mohammad Mostakim Fattah

2017-10-01

Full Text Available An aging population and human longevity is a global trend. Many developed countries are struggling with the yearly increasing healthcare cost that dominantly affects their economy. At the same time, people living with old adults suffering from a progressive brain disorder such as Alzheimer’s disease are enduring even more stress and depression than those patients while caring for them. Accordingly, seniors’ ability to live independently and comfortably in their current home for as long as possible has been crucial to reduce the societal cost for caregiving and thus give family members peace of mind, called ‘aging in place’ (AIP. In this paper we present a way of building AIP services using standard-based IoT platforms and heterogeneous IoT products. An AIP service platform is designed and created by combining previous standard-based IoT platforms in a collaborative way. A service composition tool is also created that allows people to create AIP services in an efficient way. To show practical usability of our proposed system, we choose a service scenario for medication compliance and implement a prototype service which could give old adults medication reminder appropriately at the right time (i.e., when it is time to need to take pills through light and speaker at home but also wrist band and smartphone even outside the home.

Building IoT Services for Aging in Place Using Standard-Based IoT Platforms and Heterogeneous IoT Products.

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Fattah, Sheik Mohammad Mostakim; Sung, Nak-Myoung; Ahn, Il-Yeup; Ryu, Minwoo; Yun, Jaeseok

2017-10-11

An aging population and human longevity is a global trend. Many developed countries are struggling with the yearly increasing healthcare cost that dominantly affects their economy. At the same time, people living with old adults suffering from a progressive brain disorder such as Alzheimer's disease are enduring even more stress and depression than those patients while caring for them. Accordingly, seniors' ability to live independently and comfortably in their current home for as long as possible has been crucial to reduce the societal cost for caregiving and thus give family members peace of mind, called 'aging in place' (AIP). In this paper we present a way of building AIP services using standard-based IoT platforms and heterogeneous IoT products. An AIP service platform is designed and created by combining previous standard-based IoT platforms in a collaborative way. A service composition tool is also created that allows people to create AIP services in an efficient way. To show practical usability of our proposed system, we choose a service scenario for medication compliance and implement a prototype service which could give old adults medication reminder appropriately at the right time (i.e., when it is time to need to take pills) through light and speaker at home but also wrist band and smartphone even outside the home.

How Alzheimer's Changes the Brain

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Full Text Available ... minute video shows how Alzheimer’s affects the human brain and looks at promising ideas to treat and prevent the disease. Category Science & Technology License Standard YouTube License Show more Show less ...

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

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Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study.

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Sun, Yu; Chen, Yu; Lee, Renick; Bezerianos, Anastasios; Collinson, Simon L; Sim, Kang

2016-03-01

Despite convergent neuroimaging evidence indicating a wide range of brain abnormalities in schizophrenia, our understanding of alterations in the topological architecture of brain anatomical networks and how they are modulated over time, is still rudimentary. Here, we employed graph theoretical analysis of longitudinal diffusion tensor imaging data (DTI) over a 5-year period to investigate brain network topology in schizophrenia and its relationship with clinical manifestations of the illness. Using deterministic tractography, weighted brain anatomical networks were constructed from 31 patients experiencing schizophrenia and 28 age- and gender-matched healthy control subjects. Although the overall small-world characteristics were observed at both baseline and follow-up, a scan-point independent significant deficit of global integration was found in patients compared to controls, suggesting dysfunctional integration of the brain and supporting the notion of schizophrenia as a disconnection syndrome. Specifically, several brain regions (e.g., the inferior frontal gyrus and the bilateral insula) that are crucial for cognitive and emotional integration were aberrant. Furthermore, a significant group-by-longitudinal scan interaction was revealed in the characteristic path length and global efficiency, attributing to a progressive aberration of global integration in patients compared to healthy controls. Moreover, the progressive disruptions of the brain anatomical network topology were associated with the clinical symptoms of the patients. Together, our findings provide insights into the substrates of anatomical dysconnectivity patterns for schizophrenia and highlight the potential for connectome-based metrics as neural markers of illness progression and clinical change with treatment. Copyright © 2016 Elsevier B.V. All rights reserved.

[Global brain metastases management strategy: a multidisciplinary-based approach].

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Métellus, P; Tallet, A; Dhermain, F; Reyns, N; Carpentier, A; Spano, J-P; Azria, D; Noël, G; Barlési, F; Taillibert, S; Le Rhun, É

2015-02-01

Brain metastases management has evolved over the last fifteen years and may use varying strategies, including more or less aggressive treatments, sometimes combined, leading to an improvement in patient's survival and quality of life. The therapeutic decision is subject to a multidisciplinary analysis, taking into account established prognostic factors including patient's general condition, extracerebral disease status and clinical and radiological presentation of lesions. In this article, we propose a management strategy based on the state of current knowledge and available therapeutic resources. Copyright © 2015. Published by Elsevier SAS.

Intensity-Modulated Radiation Therapy for Primary Brain Tumors

Institute of Scientific and Technical Information of China (English)

Zhong-min Wang

2004-01-01

Radiation therapy has been used to treat primary brain tumors as standard primary and/or adjunctive therapies for decades. It is difficult for conventional radiotherapy to deliver a lethal dose of radiation to the tumors while sparing surrounding normal brain due to complicated structures and multifunction in human brain. With the understanding of radiation physics and computer technology, a number of novel and more precise radiotherapies have been developed in recent years. Intensity modulated radiotherapy (IMRT) is one of these strategies. The use of IMRT in the treatment of primary brain tumors is being increasing nowadays. It shows great promise for some of primary brain tumors and also presents some problems, This review highlights current IMRT in the treatment of mainly primary brain tumors.

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

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Yan Liu

Full Text Available Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS treatment planning. In this work, we developed a deep learning convolutional neural network (CNN algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

Semi-automatic ROI placement system for analysis of brain PET images based on elastic model. Application to diagnosis of Alzheimer's disease

International Nuclear Information System (INIS)

Ohyama, Masashi; Mishina, Masahiro; Kitamura, Shin; Katayama, Yasuo; Senda, Michio; Tanizaki, Naoki; Ishii, Kenji

2000-01-01

PET with 18F-fluorodeoxyglucose (FDG) is a useful technique to image cerebral glucose metabolism and to detect patients with Alzheimer's disease in the early stage, in which characteristic temporoparietal hypometabolism is visualized. We have developed a new system, in which the standard brain ROI atlas made of networks of segments is elastically transformed to match the subject brain images, so that standard ROIs defined on the segments are placed on the individual brain images and are used to measure radioactivity over each brain region. We applied this methods to Alzheimer's disease. This method was applied to the images of 10 normal subjects (ages 55 +/- 12) and 21 patients clinically diagnosed as Alzheimer's disease (age 61 +/- 10). The FDG uptake reflecting glucose metabolism was evaluated with SUV, i.e. decay corrected radioactivity divided by injected dose per body weight in (Bq/ml)/(Bq/g). The system worked all right in every subject including those with extensive hypometabolism. Alzheimer patients showed markedly lower in the parietal cortex (4.0-4.1). When the threshold value of FDG uptake in the parietal lobe was set as 5 (Bq/ml)/(Bq/g), we could discriminate the patients with Alzheimer's disease from the normal subjects. The sensitivity was 86% and the specificity was 90%. This system can assist diagnosis of FDG images and may be useful for treating data of a large number of subjects; e.g. when PET is applied to health screening. (author)

The development and investigation of a prototype three-dimensional compensator for whole brain radiation therapy

International Nuclear Information System (INIS)

Keall, Paul; Arief, Isti; Shamas, Sofia; Weiss, Elisabeth; Castle, Steven

2008-01-01

Whole brain radiation therapy (WBRT) is the standard treatment for patients with brain metastases, and is often used in conjunction with stereotactic radiotherapy for patients with a limited number of brain metastases, as well as prophylactic cranial irradiation. The use of open fields (conventionally used for WBRT) leads to higher doses to the brain periphery if dose is prescribed to the brain center at the largest lateral radius. These dose variations potentially compromise treatment efficacy and translate to increased side effects. The goal of this research was to design and construct a 3D 'brain wedge' to compensate dose heterogeneities in WBRT. Radiation transport theory was invoked to calculate the desired shape of a wedge to achieve a uniform dose distribution at the sagittal plane for an ellipsoid irradiated medium. The calculations yielded a smooth 3D wedge design to account for the missing tissue at the peripheral areas of the brain. A wedge was machined based on the calculation results. Three ellipsoid phantoms, spanning the mean and ± two standard deviations from the mean cranial dimensions were constructed, representing 95% of the adult population. Film was placed at the sagittal plane for each of the three phantoms and irradiated with 6 MV photons, with the wedge in place. Sagittal plane isodose plots for the three phantoms demonstrated the feasibility of this wedge to create a homogeneous distribution with similar results observed for the three phantom sizes, indicating that a single wedge may be sufficient to cover 95% of the adult population. The sagittal dose is a reasonable estimate of the off-axis dose for whole brain radiation therapy. Comparing the dose with and without the wedge the average minimum dose was higher (90% versus 86%), the maximum dose was lower (107% versus 113%) and the dose variation was lower (one standard deviation 2.7% versus 4.6%). In summary, a simple and effective 3D wedge for whole brain radiotherapy has been developed

Re-irradiation for metastatic brain tumors with whole-brain radiotherapy

International Nuclear Information System (INIS)

Akiba, Takeshi; Kunieda, Etsuo; Kogawa, Asuka; Komatsu, Tetsuya; Tamai, Yoshifumi; Ohizumi, Yukio

2012-01-01

The objective of this study was to determine whether second whole-brain irradiation is beneficial for patients previously treated with whole-brain irradiation. A retrospective analysis was done for 31 patients with brain metastases who had undergone re-irradiation. Initial whole-brain irradiation was performed with 30 Gy/10 fractions for 87% of these patients. Whole-brain re-irradiation was performed with 30 Gy/10 fractions for 42% of these patients (3-40 Gy/1-20 fractions). Three patients underwent a third whole-brain irradiation. The median interval between the initial irradiation and re-irradiation was 10 months (range: 2-69 months). The median survival time after re-irradiation was 4 months (range: 1-21 months). The symptomatic improvement rate after re-irradiation was 68%, and the partial and complete tumor response rate was 55%. Fifty-two percent of the patients developed Grade 1 acute reactions. On magnetic resonance imaging, brain atrophy was observed in 36% of these patients after the initial irradiation and 74% after re-irradiation. Grade ≥2 encephalopathy or cognitive disturbance was observed in 10 patients (32%) after re-irradiation. Based on univariate analysis, significant factors related to survival after re-irradiation were the location of the primary cancer (P=0.003) and the Karnofsky performance status at the time of re-irradiation (P=0.008). A Karnofsky performance status ≥70 was significant based on multivariate analysis (P=0.050). Whole-brain re-irradiation for brain metastases placed only a slight burden on patients and was effective for symptomatic improvement. However, their remaining survival time was limited and the incidence of cognitive disturbance was rather high. (author)

Cloud-Based Collaborative Writing and the Common Core Standards

Science.gov (United States)

Yim, Soobin; Warschauer, Mark; Zheng, Binbin; Lawrence, Joshua F.

2014-01-01

The Common Core State Standards emphasize the integration of technology skills into English Language Arts (ELA) instruction, recognizing the demand for technology-based literacy skills to be college- and career- ready. This study aims to examine how collaborative cloud-based writing is used in in a Colorado school district, where one-to-one…

Thermal-Diffusivity-Based Frequency References in Standard CMOS

NARCIS (Netherlands)

Kashmiri, S.M.

2012-01-01

In recent years, a lot of research has been devoted to the realization of accurate integrated frequency references. A thermal-diffusivity-based (TD) frequency reference provides an alternative method of on-chip frequency generation in standard CMOS technology. A frequency-locked loop locks the

6 CFR 27.230 - Risk-based performance standards.

Science.gov (United States)

2010-01-01

... 6 Domestic Security 1 2010-01-01 2010-01-01 false Risk-based performance standards. 27.230 Section 27.230 Domestic Security DEPARTMENT OF HOMELAND SECURITY, OFFICE OF THE SECRETARY CHEMICAL FACILITY... the facility and that discourages abuse through established disciplinary measures; (4) Deter, Detect...

Metal-based nanoparticle interactions with the nervous system: the challenge of brain entry and the risk of retention in the organism.

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Yokel, Robert; Grulke, Eric; MacPhail, Robert

2013-01-01

This review of metal-based nanoparticles focuses on factors influencing their distribution into the nervous system, evidence they enter brain parenchyma, and nervous system responses. Gold is emphasized as a model metal-based nanoparticle and for risk assessment in the companion review. The anatomy and physiology of the nervous system, basics of colloid chemistry, and environmental factors that influence what cells see are reviewed to provide background on the biological, physical-chemical, and internal milieu factors that influence nervous system nanoparticle uptake. The results of literature searches reveal little nanoparticle research included the nervous system, which about equally involved in vitro and in vivo methods, and very few human studies. The routes of uptake into the nervous system and mechanisms of nanoparticle uptake by cells are presented with examples. Brain nanoparticle uptake inversely correlates with size. The influence of shape has not been reported. Surface charge has not been clearly shown to affect flux across the blood-brain barrier. There is very little evidence for metal-based nanoparticle distribution into brain parenchyma. Metal-based nanoparticle disruption of the blood-brain barrier and adverse brain changes have been shown, and are more pronounced for spheres than rods. Study concentrations need to be put in exposure contexts. Work with dorsal root ganglion cells and brain cells in vitro show the potential for metal-based nanoparticles to produce toxicity. Interpretation of these results must consider the ability of nanoparticles to distribute across the barriers protecting the nervous system. Effects of the persistence of poorly soluble metal-based nanoparticles are of particular concern. Copyright © 2013 Wiley Periodicals, Inc.

Explaining brain size variation: from social to cultural brain.

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van Schaik, Carel P; Isler, Karin; Burkart, Judith M

2012-05-01

Although the social brain hypothesis has found near-universal acceptance as the best explanation for the evolution of extensive variation in brain size among mammals, it faces two problems. First, it cannot account for grade shifts, where species or complete lineages have a very different brain size than expected based on their social organization. Second, it cannot account for the observation that species with high socio-cognitive abilities also excel in general cognition. These problems may be related. For birds and mammals, we propose to integrate the social brain hypothesis into a broader framework we call cultural intelligence, which stresses the importance of the high costs of brain tissue, general behavioral flexibility and the role of social learning in acquiring cognitive skills. Copyright © 2012 Elsevier Ltd. All rights reserved.

Anisotropic Diffusion based Brain MRI Segmentation and 3D Reconstruction

OpenAIRE

M. Arfan Jaffar; Sultan Zia; Ghaznafar Latif; AnwarM. Mirza; Irfan Mehmood; Naveed Ejaz; Sung Wook Baik

2012-01-01

In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive 3D visualization of the brain to the radiologist. Detection and 3D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed system detects and presents a 3D visualization model of the brain and tumor inside which greatly helps the radiologist to effectively diagnose and ...

Distributed XQuery-Based Integration and Visualization of Multimodality Brain Mapping Data.

Science.gov (United States)

Detwiler, Landon T; Suciu, Dan; Franklin, Joshua D; Moore, Eider B; Poliakov, Andrew V; Lee, Eunjung S; Corina, David P; Ojemann, George A; Brinkley, James F

2009-01-01

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too "heavyweight" for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a "lightweight" distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts.

Distributed XQuery-based integration and visualization of multimodality brain mapping data

Directory of Open Access Journals (Sweden)

Landon T Detwiler

2009-01-01

Full Text Available This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts.

MRI/TRUS fusion software-based targeted biopsy: the new standard of care?

Science.gov (United States)

Manfredi, M; Costa Moretti, T B; Emberton, M; Villers, A; Valerio, M

2015-09-01

The advent of multiparametric MRI has made it possible to change the way in which prostate biopsy is done, allowing to direct biopsies to suspicious lesions rather than randomly. The subject of this review relates to a computer-assisted strategy, the MRI/US fusion software-based targeted biopsy, and to its performance compared to the other sampling methods. Different devices with different methods to register MR images to live TRUS are currently in use to allow software-based targeted biopsy. Main clinical indications of MRI/US fusion software-based targeted biopsy are re-biopsy in men with persistent suspicious of prostate cancer after first negative standard biopsy and the follow-up of patients under active surveillance. Some studies have compared MRI/US fusion software-based targeted versus standard biopsy. In men at risk with MRI-suspicious lesion, targeted biopsy consistently detects more men with clinically significant disease as compared to standard biopsy; some studies have also shown decreased detection of insignificant disease. Only two studies directly compared MRI/US fusion software-based targeted biopsy with MRI/US fusion visual targeted biopsy, and the diagnostic ability seems to be in favor of the software approach. To date, no study comparing software-based targeted biopsy against in-bore MRI biopsy is available. The new software-based targeted approach seems to have the characteristics to be added in the standard pathway for achieving accurate risk stratification. Once reproducibility and cost-effectiveness will be verified, the actual issue will be to determine whether MRI/TRUS fusion software-based targeted biopsy represents anadd-on test or a replacement to standard TRUS biopsy.

Arts-based social skills interventions for adolescents with acquired brain injuries: five case reports.

Science.gov (United States)

Agnihotri, Sabrina; Gray, Julia; Colantonio, Angela; Polatajko, Helene; Cameron, Deb; Wiseman-Hakes, Catherine; Rumney, Peter; Keightley, Michelle

2014-02-01

Previous research has demonstrated the value of arts-based programs for adolescents with childhood brain disorder to facilitate social skills and participation. The current study extends this work by examining the feasibility and effectiveness of an arts-based intervention for youth with acquired brain injuries (ABI). A case study approach was used with four adolescent participants and one case control. A battery of quantitative measures were administered four and one week pre-intervention, one week post-intervention, as well six to eight month post-intervention. Improvements in pragmatic communication skills and social and participation goals were observed across intervention participants. Similar improvements were not seen with the case control participant. Results support the use of an arts-based intervention for youth with ABI to facilitate social skills and participation. Findings also highlight the need for more sensitive measures of these skills for these youth. Suggested guidelines for program implementation are provided.

A Lattice-Based Identity-Based Proxy Blind Signature Scheme in the Standard Model

Directory of Open Access Journals (Sweden)

Lili Zhang

2014-01-01

Full Text Available A proxy blind signature scheme is a special form of blind signature which allowed a designated person called proxy signer to sign on behalf of original signers without knowing the content of the message. It combines the advantages of proxy signature and blind signature. Up to date, most proxy blind signature schemes rely on hard number theory problems, discrete logarithm, and bilinear pairings. Unfortunately, the above underlying number theory problems will be solvable in the postquantum era. Lattice-based cryptography is enjoying great interest these days, due to implementation simplicity and provable security reductions. Moreover, lattice-based cryptography is believed to be hard even for quantum computers. In this paper, we present a new identity-based proxy blind signature scheme from lattices without random oracles. The new scheme is proven to be strongly unforgeable under the standard hardness assumption of the short integer solution problem (SIS and the inhomogeneous small integer solution problem (ISIS. Furthermore, the secret key size and the signature length of our scheme are invariant and much shorter than those of the previous lattice-based proxy blind signature schemes. To the best of our knowledge, our construction is the first short lattice-based identity-based proxy blind signature scheme in the standard model.

Brain Injury After Proton Therapy or Carbon Ion Therapy for Head-and-Neck Cancer and Skull Base Tumors

International Nuclear Information System (INIS)

Miyawaki, Daisuke; Murakami, Masao; Demizu, Yusuke; Sasaki, Ryohei; Niwa, Yasue; Terashima, Kazuki; Nishimura, Hideki; Hishikawa, Yoshio; Sugimura, Kazuro

2009-01-01

Purpose: To assess the incidence of early delayed or late morbidity of Brain after particle therapy for skull base tumors and head-and-neck cancers. Methods and Materials: Between May 2001 and December 2005, 59 patients with cancerous invasion of the skull base were treated with proton or carbon ion therapy at the Hyogo Ion Beam Medical Center. Adverse events were assessed according to the magnetic resonance imaging findings (late effects of normal tissue-subjective, objective, management, analytic [LENT-SOMA]) and symptoms (Common Terminology Criteria for Adverse Events [CTCAE], version 3.0). Dose-volume histograms were used to analyze the relationship between the dose and volume of the irradiated brain and the occurrence of brain injury. The median follow-up time was 33 months. Results: Of the 48 patients treated with proton therapy and 11 patients treated with carbon ion radiotherapy, 8 (17%) and 7 (64%), respectively, developed radiation-induced brain changes (RIBCs) on magnetic resonance imaging (LENT-SOMA Grade 1-3). Four patients (7%) had some clinical symptoms, such as vertigo and headache (CTCAE Grade 2) or epilepsy (CTCAE Grade 3). The actuarial occurrence rate of RIBCs at 2 and 3 years was 20% and 39%, respectively, with a significant difference in the incidence between the proton and carbon ion radiotherapy groups. The dose-volume histogram analyses revealed significant differences between Brain lobes with and without RIBCs in the actuarial volume of brain lobes receiving high doses. Conclusion: Particle therapies produced minimal symptomatic brain toxicities, but sequential evaluation with magnetic resonance imaging detected a greater incidence of RIBCs. Significant differences were observed in the irradiated brain volume between Brain lobes with and without RIBCs.

Rat brain digital stereotaxic white matter atlas with fine tract delineation in Paxinos space and its automated applications in DTI data analysis.

Science.gov (United States)

Liang, Shengxiang; Wu, Shang; Huang, Qi; Duan, Shaofeng; Liu, Hua; Li, Yuxiao; Zhao, Shujun; Nie, Binbin; Shan, Baoci

2017-11-01

To automatically analyze diffusion tensor images of the rat brain via both voxel-based and ROI-based approaches, we constructed a new white matter atlas of the rat brain with fine tracts delineation in the Paxinos and Watson space. Unlike in previous studies, we constructed a digital atlas image from the latest edition of the Paxinos and Watson. This atlas contains 111 carefully delineated white matter fibers. A white matter network of rat brain based on anatomy was constructed by locating the intersection of all these tracts and recording the nuclei on the pathway of each white matter tract. Moreover, a compatible rat brain template from DTI images was created and standardized into the atlas space. To evaluate the automated application of the atlas in DTI data analysis, a group of rats with right-side middle cerebral artery occlusion (MCAO) and those without were enrolled in this study. The voxel-based analysis result shows that the brain region showing significant declines in signal in the MCAO rats was consistent with the occlusion position. We constructed a stereotaxic white matter atlas of the rat brain with fine tract delineation and a compatible template for the data analysis of DTI images of the rat brain. Copyright © 2017 Elsevier Inc. All rights reserved.

Parotid gland sparing effect by computed tomography-based modified lower field margin in whole brain radiotherapy

International Nuclear Information System (INIS)

Cho, Oyeon; Chun, Mi Son; Oh, Young Taek; Kim, Mi Hwa; Park, Hae Jin; Nam, Sang Soo; Heo, Jae Sung; Noh, O Kyu; Park, Sung Ho

2013-01-01

Parotid gland can be considered as a risk organ in whole brain radiotherapy (WBRT). The purpose of this study is to evaluate the parotid gland sparing effect of computed tomography (CT)-based WBRT compared to 2-dimensional plan with conventional field margin. From January 2008 to April 2011, 53 patients underwent WBRT using CT-based simulation. Bilateral two-field arrangement was used and the prescribed dose was 30 Gy in 10 fractions. We compared the parotid dose between 2 radiotherapy plans using different lower field margins: conventional field to the lower level of the atlas (CF) and modified field fitted to the brain tissue (MF). Averages of mean parotid dose of the 2 protocols with CF and MF were 17.4 Gy and 8.7 Gy, respectively (p 98% of prescribed dose were 99.7% for CF and 99.5% for MF. Compared to WBRT with CF, CT-based lower field margin modification is a simple and effective technique for sparing the parotid gland, while providing similar dose coverage of the whole brain.

Regional brain morphometry predicts memory rehabilitation outcome after traumatic brain injury

Directory of Open Access Journals (Sweden)

Gary E Strangman

2010-10-01

Full Text Available Cognitive deficits following traumatic brain injury (TBI commonly include difficulties with memory, attention, and executive dysfunction. These deficits are amenable to cognitive rehabilitation, but optimally selecting rehabilitation programs for individual patients remains a challenge. Recent methods for quantifying regional brain morphometry allow for automated quantification of tissue volumes in numerous distinct brain structures. We hypothesized that such quantitative structural information could help identify individuals more or less likely to benefit from memory rehabilitation. Fifty individuals with TBI of all severities who reported having memory difficulties first underwent structural MRI scanning. They then participated in a 12 session memory rehabilitation program emphasizing internal memory strategies (I-MEMS. Primary outcome measures (HVLT, RBMT were collected at the time of the MRI scan, immediately following therapy, and again at one month post-therapy. Regional brain volumes were used to predict outcome, adjusting for standard predictors (e.g., injury severity, age, education, pretest scores. We identified several brain regions that provided significant predictions of rehabilitation outcome, including the volume of the hippocampus, the lateral prefrontal cortex, the thalamus, and several subregions of the cingulate cortex. The prediction range of regional brain volumes were in some cases nearly equal in magnitude to prediction ranges provided by pretest scores on the outcome variable. We conclude that specific cerebral networks including these regions may contribute to learning during I-MEMS rehabilitation, and suggest that morphometric measures may provide substantial predictive value for rehabilitation outcome in other cognitive interventions as well.

Advanced MRI techniques of the fetal brain

International Nuclear Information System (INIS)

Schoepf, V.; Dittrich, E.; Berger-Kulemann, V.; Kasprian, G.; Kollndorfer, K.; Prayer, D.

2013-01-01

Evaluation of the normal and pathological fetal brain. Magnetic resonance imaging (MRI). Advanced MRI of the fetal brain. Diffusion tensor imaging (DTI) is used in clinical practice, all other methods are used at a research level. Serving as standard methods in the future. Combined structural and functional data for all gestational ages will allow more specific insight into the developmental processes of the fetal brain. This gain of information will help provide a common understanding of complex spatial and temporal procedures of early morphological features and their impact on cognitive and sensory abilities. (orig.) [de

Transformative Shifts in Art History Teaching: The Impact of Standards-Based Assessment

Science.gov (United States)

Ormond, Barbara

2011-01-01

This article examines pedagogical shifts in art history teaching that have developed as a response to the implementation of a standards-based assessment regime. The specific characteristics of art history standards-based assessment in the context of New Zealand secondary schools are explained to demonstrate how an exacting form of assessment has…

School Sector and Student Achievement in the Era of Standards Based Reforms

Science.gov (United States)