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matlab-based 'berlin brain connectivity benchmark' (bbcb) framework  (MathWorks Inc)


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    Structured Review

    MathWorks Inc matlab-based 'berlin brain connectivity benchmark' (bbcb) framework
    From modelling source dynamics to EEG field patterns. Intra- and inter-hemispheric interactions between two source pairs were modelled: the first source was placed either in left (LIPL) or right (RIPL) inferior parietal lobule, while the second source was kept in the right middle frontal gyrus (RMFG). Source amplitudes are shown using a lateral view of the brain, while resulting EEG field potentials are plotted using a top view of the scalp (A.U. stands for arbitrary unit). The brain images were plotted using <t>the</t> <t>Matlab</t> functions provided in the <t>BBCB</t> toolbox .
    Matlab Based 'berlin Brain Connectivity Benchmark' (Bbcb) Framework, 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/result/matlab-based 'berlin brain connectivity benchmark' (bbcb) framework/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based 'berlin brain connectivity benchmark' (bbcb) framework - by Bioz Stars, 2026-03
    90/100 stars

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    1) Product Images from "EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions"

    Article Title: EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions

    Journal: Scientific Reports

    doi: 10.1038/s41598-019-45289-7

    From modelling source dynamics to EEG field patterns. Intra- and inter-hemispheric interactions between two source pairs were modelled: the first source was placed either in left (LIPL) or right (RIPL) inferior parietal lobule, while the second source was kept in the right middle frontal gyrus (RMFG). Source amplitudes are shown using a lateral view of the brain, while resulting EEG field potentials are plotted using a top view of the scalp (A.U. stands for arbitrary unit). The brain images were plotted using the Matlab functions provided in the BBCB toolbox .
    Figure Legend Snippet: From modelling source dynamics to EEG field patterns. Intra- and inter-hemispheric interactions between two source pairs were modelled: the first source was placed either in left (LIPL) or right (RIPL) inferior parietal lobule, while the second source was kept in the right middle frontal gyrus (RMFG). Source amplitudes are shown using a lateral view of the brain, while resulting EEG field potentials are plotted using a top view of the scalp (A.U. stands for arbitrary unit). The brain images were plotted using the Matlab functions provided in the BBCB toolbox .

    Techniques Used:

    ( A ) Mean whole-brain detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Whole-brain detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.
    Figure Legend Snippet: ( A ) Mean whole-brain detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Whole-brain detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.

    Techniques Used:

    ( A ) Mean topographic detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Topographic detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.
    Figure Legend Snippet: ( A ) Mean topographic detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Topographic detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.

    Techniques Used:



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    matlab-based 'berlin brain connectivity benchmark' (bbcb) framework  (MathWorks Inc)
    90
    MathWorks Inc matlab-based 'berlin brain connectivity benchmark' (bbcb) framework
    From modelling source dynamics to EEG field patterns. Intra- and inter-hemispheric interactions between two source pairs were modelled: the first source was placed either in left (LIPL) or right (RIPL) inferior parietal lobule, while the second source was kept in the right middle frontal gyrus (RMFG). Source amplitudes are shown using a lateral view of the brain, while resulting EEG field potentials are plotted using a top view of the scalp (A.U. stands for arbitrary unit). The brain images were plotted using <t>the</t> <t>Matlab</t> functions provided in the <t>BBCB</t> toolbox .
    Matlab Based 'berlin Brain Connectivity Benchmark' (Bbcb) Framework, 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/result/matlab-based 'berlin brain connectivity benchmark' (bbcb) framework/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    matlab-based 'berlin brain connectivity benchmark' (bbcb) framework - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    From modelling source dynamics to EEG field patterns. Intra- and inter-hemispheric interactions between two source pairs were modelled: the first source was placed either in left (LIPL) or right (RIPL) inferior parietal lobule, while the second source was kept in the right middle frontal gyrus (RMFG). Source amplitudes are shown using a lateral view of the brain, while resulting EEG field potentials are plotted using a top view of the scalp (A.U. stands for arbitrary unit). The brain images were plotted using the Matlab functions provided in the BBCB toolbox .

    Journal: Scientific Reports

    Article Title: EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions

    doi: 10.1038/s41598-019-45289-7

    Figure Lengend Snippet: From modelling source dynamics to EEG field patterns. Intra- and inter-hemispheric interactions between two source pairs were modelled: the first source was placed either in left (LIPL) or right (RIPL) inferior parietal lobule, while the second source was kept in the right middle frontal gyrus (RMFG). Source amplitudes are shown using a lateral view of the brain, while resulting EEG field potentials are plotted using a top view of the scalp (A.U. stands for arbitrary unit). The brain images were plotted using the Matlab functions provided in the BBCB toolbox .

    Article Snippet: The MATLAB-based (The MathWorks, Inc., Natick, Massachusetts, USA) ‘Berlin Brain Connectivity Benchmark’ (BBCB) framework was used to simulate scalp-level hd-EEG recordings (108 channels, 500 Hz, 120 s) including bivariate relationships between two cortical sources.

    Techniques:

    ( A ) Mean whole-brain detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Whole-brain detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.

    Journal: Scientific Reports

    Article Title: EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions

    doi: 10.1038/s41598-019-45289-7

    Figure Lengend Snippet: ( A ) Mean whole-brain detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Whole-brain detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.

    Article Snippet: The MATLAB-based (The MathWorks, Inc., Natick, Massachusetts, USA) ‘Berlin Brain Connectivity Benchmark’ (BBCB) framework was used to simulate scalp-level hd-EEG recordings (108 channels, 500 Hz, 120 s) including bivariate relationships between two cortical sources.

    Techniques:

    ( A ) Mean topographic detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Topographic detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.

    Journal: Scientific Reports

    Article Title: EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions

    doi: 10.1038/s41598-019-45289-7

    Figure Lengend Snippet: ( A ) Mean topographic detection accuracy for all nine different relationships between the chosen source location pairings (L-R = left IPL to right MFG; R-R = right IPL to right MFG). The green vertical lines mark significant differences between wPLI and wSMI (permutation tests, p < 0.05) for each type of interaction, pairing of source locations and SNR. The brain images were plotted using the Matlab functions provided in the BBCB toolbox . ( B ) Topographic detection accuracy for all nine different relationships between the chosen source location pairings as a function of SNRs. Black dots at the top of each graph mark significant accuracy differences between wPLI and wSMI for each specific SNR that were observed for both intra- and inter-hemispheric conditions.

    Article Snippet: The MATLAB-based (The MathWorks, Inc., Natick, Massachusetts, USA) ‘Berlin Brain Connectivity Benchmark’ (BBCB) framework was used to simulate scalp-level hd-EEG recordings (108 channels, 500 Hz, 120 s) including bivariate relationships between two cortical sources.

    Techniques: