Whole-brain modeling to predict optimal deep brain stimulation targeting
Fernandes HM., Deco G., Kringelbach ML.
Over the last decades, important advances in neuroimaging have prompted remarkable progress in mapping the human brain; from characterizing the structural scaffolds underlying brain communication to revealing the signatures of spatiotemporal dynamics underlying different brain states. In particular, statistical descriptions of brain states have started to show promise as robust biomarkers of brain functioning. Increasing evidence of the strong link between specific patterns of brain network disruption and the symptoms of different brain disorders combined with causal whole-brain modeling have raised great expectations of bringing about rational, novel ways to predict optimal rebalancing of affected brain circuitry.