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Brain-Behavior Links in Normative and Clinical Samples

Elaborating links between the brain network and behavior is critical for better understanding normative development as well as deviations from this normative pattern in clinical samples. We develop methods to computationally characterize links between the brain and behavior.


Classification accuracy (y-axis) with different age groups in years (x-axis), when using structural connectivity patterns (a) and behavioural patterns (b). Box plots depict the range of the classification accuracy as estimated using 10-fold cross validation, repeated by100 randomization. For both cases, the average classification accuracy increases steadily across development, although the structural scores show a higher increase.
Abnormal edges are shown for (a) traumatic brain injury (TBI) sample and (b) healthy controls (HC) sample. Edge width is proportional to the number of times (across participants) that an edge is identified as being abnormal. The weights of edges (c) as computed by edge betweenness centrality are shown for top weighted 200 edges. The most affected edges are those that connect important hub regions including thalamus, putamen, hippocampus, and insula.
Correlation between Disruption Index of the Structural Connectome (DISC) and cognitive measures for participants with TBI. Four approaches for edge weights when calculating DISC were compared.

Source Codes
DISC: Disruption Index of the Structural Connectome

Publications
Tunç B, Solmaz B, Parker D, Satterthwaite T D, Elliott M A, Calkins M E, Ruparel K, Gur R E, Gur R C, Verma R, Establishing a link between sex-related differences in the structural connectome and behaviour, Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 371:1688, 20150111, 2016
Solmaz B, Tunç B, Parker D, Whyte J, Hart T, Rabinowitz A, Rohrbach M, Kim J, Verma R, Assessing connectivity related injury burden in diffuse traumatic brain injury, Human brain mapping, 38:6, 2913-2922, 2017

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