tapas toolbox Search Results


tapas rdcm toolbox in matlab  (MathWorks Inc)
96
MathWorks Inc tapas rdcm toolbox in matlab
Distribution of QC-FC correlations across all methods for quantifying FC/EC for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → <t>rDCM.</t> Distribution means (μ) are presented in orange text, while population variance (02) is presented in purple text.
Tapas Rdcm Toolbox In Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 96 stars, based on 1 article reviews
tapas rdcm toolbox in matlab - by Bioz Stars, 2026-05
96/100 stars
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tapas toolbox  (MathWorks Inc)
96
MathWorks Inc tapas toolbox
Distribution of QC-FC correlations across all methods for quantifying FC/EC for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → <t>rDCM.</t> Distribution means (μ) are presented in orange text, while population variance (02) is presented in purple text.
Tapas Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/tapas toolbox/product/MathWorks Inc
Average 96 stars, based on 1 article reviews
tapas toolbox - by Bioz Stars, 2026-05
96/100 stars
  Buy from Supplier

Image Search Results


Distribution of QC-FC correlations across all methods for quantifying FC/EC for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → rDCM. Distribution means (μ) are presented in orange text, while population variance (02) is presented in purple text.

Journal: bioRxiv

Article Title: The Motion Sensitivity and Predictive Utility of Different Estimates of Inter-regional Functional Coupling in Resting-state Functional MRI

doi: 10.1101/2025.07.13.664614

Figure Lengend Snippet: Distribution of QC-FC correlations across all methods for quantifying FC/EC for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → rDCM. Distribution means (μ) are presented in orange text, while population variance (02) is presented in purple text.

Article Snippet: All analyses were implemented using the TAPAS rDCM toolbox in MATLAB ( a; b).

Techniques: Control

QC-FC distance-dependence correlations across datasets. Bars show the distance dependence value for each connectivity metric for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → rDCM.

Journal: bioRxiv

Article Title: The Motion Sensitivity and Predictive Utility of Different Estimates of Inter-regional Functional Coupling in Resting-state Functional MRI

doi: 10.1101/2025.07.13.664614

Figure Lengend Snippet: QC-FC distance-dependence correlations across datasets. Bars show the distance dependence value for each connectivity metric for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → rDCM.

Article Snippet: All analyses were implemented using the TAPAS rDCM toolbox in MATLAB ( a; b).

Techniques: Control

KRR prediction accuracies across datasets. The boxplots show the median and interquartile ranges for accuracies averaged over cross validation folds, repetitions, and behaviours. Mean predictive accuracy for each connectivity measure is shown with a white triangle. Prediction accuracies are shown for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → rDCM

Journal: bioRxiv

Article Title: The Motion Sensitivity and Predictive Utility of Different Estimates of Inter-regional Functional Coupling in Resting-state Functional MRI

doi: 10.1101/2025.07.13.664614

Figure Lengend Snippet: KRR prediction accuracies across datasets. The boxplots show the median and interquartile ranges for accuracies averaged over cross validation folds, repetitions, and behaviours. Mean predictive accuracy for each connectivity measure is shown with a white triangle. Prediction accuracies are shown for ( A ) HCP participants meeting stringent motion criteria, ( B ) ABCD participants passing standard quality control inclusion criteria, and ( C ) ABCD participants meeting stringent motion exclusion thresholds. Measures are ordered as: Correlation → Partial correlation → Mutual Information → Coherence → PID → rDCM

Article Snippet: All analyses were implemented using the TAPAS rDCM toolbox in MATLAB ( a; b).

Techniques: Biomarker Discovery, Control