Review



functions from brain connectivity toolbox  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    MathWorks Inc functions from brain connectivity toolbox
    Functions From Brain Connectivity Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/function+from+brain+connectivity+toolbox/pmc04554838-96-11-8
    Average 90 stars, based on 1 article reviews
    functions from brain connectivity toolbox - by Bioz Stars, 2026-10
    90/100 stars

    Images

    Related Articles

    other:

    Article Title: Neurobiological correlates of personality dimensions in borderline personality disorder using graph analysis of functional connectivity.
    Article Snippet: Graph analysis was performed via the Brain Connectivity Toolbox ( h t t p s : / / s i t e s . g o o g l e . c o m / s i t e / b c t n e t / ) in MATLAB R2019b.

    Article Title: High‐Density Electroencephalography Detects Spatiotemporal Abnormalities in Brain Networks in Patients With Glioma‐Related Epilepsy
    Article Snippet: The network graph theory metrics were calculated and processed by MATLAB using the Brain Connectivity Toolbox ( https://sites.google.com/site/bctnet ).

    Article Title: Developmental timing of adversity and neural network organization: An fNIRS study of the impact of refugee displacement
    Article Snippet: We applied graph theory metrics to analyze the neural networks of refugee children, using the Brain Connectivity Toolbox ( ) in MATLAB for comprehensive network analysis.

    Article Title: Neurobiological correlates of personality dimensions in borderline personality disorder using graph analysis of functional connectivity
    Article Snippet: Graph analysis was performed via the Brain Connectivity Toolbox ( https://sites.google.com/site/bctnet/ ) in MATLAB R2019b.

    Article Title: Efficiency of structural brain networks mediates age-associated differences in executive functioning in older adults
    Article Snippet: The Brain Connectivity Toolbox (Rubinov and Sporns, ), implemented in MATLAB (The MathWorks Inc., Natick, MA), was used to compute weighted, undirected network metrics including, global efficiency (E glob : E = 1 n ∑ i ∈ N E i = 1 n ∑ i ∈ N ∑ j ∈ N , j ≠ i d i j - 1 n - 1 , where E i is the efficiency of node i ; Rubinov and Sporns, ), regional efficiency (E reg ), and local efficiency (E loc : E l o c = 1 n ∑ i ∈ N E l o c , i = 1 n ∑ i ∈ N ∑ j , h ∈ N , j ≠ i a i j a i h [ d j h ( N i ) ] - 1 k i ( k i - 1 ) , where E loc, i is the local efficiency of node i , and d jh ( N i ) is the length of the shortest path between j and h , that contains only neighbors of i ; Rubinov and Sporns, ).

    Article Title: Abstracts from the 18 th European Headache Congress (EHC) : Rotterdam, The Netherlands. 4-7 December 2024.
    Article Snippet: Parcellated rs-fMRIs were then analysed with the Brain Connectivity Toolbox in Matlab to calculate graph theoretical metrics for each atlas area.

    Article Title: Case Report: Electro-cortical network effects of an acute stroke revealed by high-density electroencephalography
    Article Snippet: Brain connectivity toolbox ( ) in MATLAB was used to study the complex brain networks from the lagged coherence connectivity matrix.

    Functional Assay:

    Article Title: Saccades influence functional modularity in the human cortical vision network
    Article Snippet: .. For each participant, the resulting values were placed in 50 × 50 adjacency matrices whereby each row (and column) represents a ROI, and their intersection in the matrix communicated the normalized correlation value with each array indicating the functional connectivity between regions; GTA measures were then conducted on these matrices for each participant using the Brain Connectivity Toolbox for MATLAB . ..



    Similar Products

    functions from the brain connectivity toolbox  (MathWorks Inc)
    90
    MathWorks Inc functions from the brain connectivity toolbox
    Functions From The Brain Connectivity Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/function+from+brain+connectivity+toolbox/pmc08493952-87-14-10
    Average 90 stars, based on 1 article reviews
    functions from the brain connectivity toolbox - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    louvain’s algorithm function from the brain connectivity toolbox  (MathWorks Inc)
    90
    MathWorks Inc louvain’s algorithm function from the brain connectivity toolbox
    a Resting-state functional MRI pre-processing pipeline and time-series extraction from functional atlases. b Pearson correlation matrices. c Optimal local threshold estimation; the network edge density at which Q−Q rand is maximum. d Thresholded matrices by optimal density using local and global threshold network construction methods. e <t>Louvain’s</t> community and modular dissociation (MD) estimation, see also Supplementary Fig . f Modular variability (MV) using consensus community. g Group means MD; subcortical regions and cerebellum showed in all groups high MD while motor-sensory, frontal, temporal pole and occipital cortex show low MD. h Group mean MV; patterns of high and low MV were consistent across all groups. Motor-sensory, occipital, and temporal pole showed low MV while parietal, ventral frontal and insulo-opercular cortices showed high MV.
    Louvain’s Algorithm Function From The Brain Connectivity Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/function+from+brain+connectivity+toolbox/pmc08367990-309-27-37
    Average 90 stars, based on 1 article reviews
    louvain’s algorithm function from the brain connectivity toolbox - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    matlab-implemented functions from the brain connectivity toolbox  (MathWorks Inc)
    90
    MathWorks Inc matlab-implemented functions from the brain connectivity toolbox
    a Resting-state functional MRI pre-processing pipeline and time-series extraction from functional atlases. b Pearson correlation matrices. c Optimal local threshold estimation; the network edge density at which Q−Q rand is maximum. d Thresholded matrices by optimal density using local and global threshold network construction methods. e <t>Louvain’s</t> community and modular dissociation (MD) estimation, see also Supplementary Fig . f Modular variability (MV) using consensus community. g Group means MD; subcortical regions and cerebellum showed in all groups high MD while motor-sensory, frontal, temporal pole and occipital cortex show low MD. h Group mean MV; patterns of high and low MV were consistent across all groups. Motor-sensory, occipital, and temporal pole showed low MV while parietal, ventral frontal and insulo-opercular cortices showed high MV.
    Matlab Implemented Functions From The Brain Connectivity Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/function+from+brain+connectivity+toolbox/pmc05988394-121-15-11
    Average 90 stars, based on 1 article reviews
    matlab-implemented functions from the brain connectivity toolbox - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    function from brain connectivity toolbox  (MathWorks Inc)
    90
    MathWorks Inc function from brain connectivity toolbox
    a Resting-state functional MRI pre-processing pipeline and time-series extraction from functional atlases. b Pearson correlation matrices. c Optimal local threshold estimation; the network edge density at which Q−Q rand is maximum. d Thresholded matrices by optimal density using local and global threshold network construction methods. e <t>Louvain’s</t> community and modular dissociation (MD) estimation, see also Supplementary Fig . f Modular variability (MV) using consensus community. g Group means MD; subcortical regions and cerebellum showed in all groups high MD while motor-sensory, frontal, temporal pole and occipital cortex show low MD. h Group mean MV; patterns of high and low MV were consistent across all groups. Motor-sensory, occipital, and temporal pole showed low MV while parietal, ventral frontal and insulo-opercular cortices showed high MV.
    Function From Brain Connectivity Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/function+from+brain+connectivity+toolbox/pmc04554838-95-2-2
    Average 90 stars, based on 1 article reviews
    function from brain connectivity toolbox - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    functions from brain connectivity toolbox  (MathWorks Inc)
    90
    MathWorks Inc functions from brain connectivity toolbox
    a Resting-state functional MRI pre-processing pipeline and time-series extraction from functional atlases. b Pearson correlation matrices. c Optimal local threshold estimation; the network edge density at which Q−Q rand is maximum. d Thresholded matrices by optimal density using local and global threshold network construction methods. e <t>Louvain’s</t> community and modular dissociation (MD) estimation, see also Supplementary Fig . f Modular variability (MV) using consensus community. g Group means MD; subcortical regions and cerebellum showed in all groups high MD while motor-sensory, frontal, temporal pole and occipital cortex show low MD. h Group mean MV; patterns of high and low MV were consistent across all groups. Motor-sensory, occipital, and temporal pole showed low MV while parietal, ventral frontal and insulo-opercular cortices showed high MV.
    Functions From Brain Connectivity Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/function+from+brain+connectivity+toolbox/pmc04554838-96-11-8
    Average 90 stars, based on 1 article reviews
    functions from brain connectivity toolbox - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    a Resting-state functional MRI pre-processing pipeline and time-series extraction from functional atlases. b Pearson correlation matrices. c Optimal local threshold estimation; the network edge density at which Q−Q rand is maximum. d Thresholded matrices by optimal density using local and global threshold network construction methods. e Louvain’s community and modular dissociation (MD) estimation, see also Supplementary Fig . f Modular variability (MV) using consensus community. g Group means MD; subcortical regions and cerebellum showed in all groups high MD while motor-sensory, frontal, temporal pole and occipital cortex show low MD. h Group mean MV; patterns of high and low MV were consistent across all groups. Motor-sensory, occipital, and temporal pole showed low MV while parietal, ventral frontal and insulo-opercular cortices showed high MV.

    Journal: Communications Biology

    Article Title: The functional brain favours segregated modular connectivity at old age unless affected by neurodegeneration

    doi: 10.1038/s42003-021-02497-0

    Figure Lengend Snippet: a Resting-state functional MRI pre-processing pipeline and time-series extraction from functional atlases. b Pearson correlation matrices. c Optimal local threshold estimation; the network edge density at which Q−Q rand is maximum. d Thresholded matrices by optimal density using local and global threshold network construction methods. e Louvain’s community and modular dissociation (MD) estimation, see also Supplementary Fig . f Modular variability (MV) using consensus community. g Group means MD; subcortical regions and cerebellum showed in all groups high MD while motor-sensory, frontal, temporal pole and occipital cortex show low MD. h Group mean MV; patterns of high and low MV were consistent across all groups. Motor-sensory, occipital, and temporal pole showed low MV while parietal, ventral frontal and insulo-opercular cortices showed high MV.

    Article Snippet: For this, the Hadamard product between the binarised matrix and the original weighted matrix was computed, and used for community structure and modularity statistic estimation using the Louvain’s algorithm function from the Brain Connectivity Toolbox (BCT) in Matlab (Mathworks Inc, R2017a).

    Techniques: Functional Assay, Extraction