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Whole-brain computational modelling is now at the stage where it may help generate and predict the dynamic interactions and consequences of brain networks over many timescales. It shows remarkable accuracy in mapping and predicting both spontaneous and task-based healthy network dynamics and may provide an entry point for understanding brain disorders at a causal mechanistic level

Whole brain computational modelling can be used to understand neuropsychiatric disorders

Neuropsychiatric disorders can be devastating not only to individuals, but also increasingly affect society. While there has been some progress, the paucity of reliable animal models and inadequacies of current treatments indicate that new research strategies are needed. The review outlines how whole-brain computational modelling can be used to generate new insights into fundamental mechanisms of neuropsychiatric disorders and possibly provide novel, more effective therapeutic interventions, e.g. through drug discovery and new targets for deep brain stimulation.

See also the video abstract on youtube.