Using in silico perturbational approach to identify critical areas in schizophrenia

Abstract

Schizophrenia is a debilitating neuropsychiatric disorder whose underlying correlates remain unclear despite decades of neuroimaging investigation. One contentious topic concerns the role of global signal (GS) fluctuations and how they affect more focal functional changes. Moreover, it has been difficult to pinpoint causal mechanisms of circuit disruption. Here, we analyzed resting-state fMRI data from 47 schizophrenia patients and 118 age-matched healthy controls and used dynamical analyses to investigate how global fluctuations and other functional metastable states are affected by this disorder. We found that brain dynamics in the schizophrenia group were characterized by an increased probability of globally coherent states and reduced recurrence of a substate dominated by coupled activity in the default mode and limbic networks. We then used the in silico perturbation of a whole-brain model to identify critical areas involved in the disease. Perturbing a set of temporo-parietal sensory and associative areas in a model of the healthy brain reproduced global pathological dynamics. Healthy brain dynamics were instead restored by perturbing a set of medial fronto-temporal and cingulate regions in the model of pathology. These results highlight the relevance of GS alterations in schizophrenia and identify a set of vulnerable areas involved in determining a shift in brain state.

Brain network connectivity underlying remission in early psychosis: a whole brain model approach

“…Moreover, our findings suggest the presence of a potential compensatory mechanism in patients who achieve remission. The increased functional connectivity observed, previously reported in psychotic disorders 26,39,40 , especially in early stages, may represent an over compensatory attempt to restore clinical functioning by rebalancing the structural-functional interplay 41,42 . As discussed by Fornito and Bullmore, the dissociation between reduced structural connectivity and increased functional connectivity can be interpreted as a neural activity differentiation, involving a disruption of the typical segregation of neural functions or as a compensatory process.…”

Virtual brain twins: from basic neuroscience to clinical use

“…The local parameters and regional connections are inferred and compared using dynamic causal modeling based on EEG and fMRI features. Similar approaches, not exclusive to schizophrenia, have already been experimented in several studies, to explore the dysconnection hypothesis [ 119 , 120 ], the neuromodulatory effect of a psychoactive drug on brain function in healthy subjects [ 121 ] or in a stimulation paradigm [ 122 ]. The advent of multiscale brain models will add further granularity to the control parameters and bring hope in disentangling the complex interplay of mechanisms responsible for the emergence of psychiatric disorders.…”

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation

“…Nevertheless, such mechanisms still remain elusive and a deeper comprehension would facilitate the design of novel treatments for brain disorders and possibly for the loss of consciousness like coma. Recently, directly perturbing the brain in silico has been proposed to investigate the dynamical mechanisms of brain states in health and disease [2][3][4][5]. Furthermore, such perturbations could be used to study the sensitivity of brain areas and identify model-based biomarkers.…”

“…The model-based approach consists of building whole-brain models composed of a network of coupled local nodes to simulate the empirical PMS and artificially perturb the resulting PMS model to force the transition to a desired control state. This framework has been successfully applied in other brain states, showing transitions from aging [2], patients with depression [59] and schizophrenia [4] towards more healthy regimes.…”