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The study of human brain networks with in vivo neuroimaging has given rise to the field of connectomics, furthered by advances in network science and graph theory informing our understanding of the topology and function of the healthy brain. Here our focus is on the disruption in neuropsychiatric disorders (pathoconnectomics) and how whole-brain computational models can help generate and predict the dynamical interactions and consequences of brain networks over many timescales. We review methods and emerging results that exhibit remarkable accuracy in mapping and predicting both spontaneous and task-based healthy network dynamics. This raises great expectations that whole-brain modeling and computational connectomics may provide an entry point for understanding brain disorders at a causal mechanistic level, and that computational neuropsychiatry can ultimately be leveraged to provide novel, more effective therapeutic interventions, e.g., through drug discovery and new targets for deep brain stimulation.

Original publication

DOI

10.1016/j.neuron.2014.08.034

Type

Journal article

Journal

Neuron

Publication Date

03/12/2014

Volume

84

Pages

892 - 905

Keywords

Brain, Brain Diseases, Computer Simulation, Connectome, Humans, Nerve Net, Neural Networks (Computer), Neural Pathways