Network properties of structural-functional interplay across disease stages in early psychosis (EP): a whole brain model approach

Psychotic disorders are characterized by heterogeneity in etiopathology, clinical presentation and individual trajectory, complicating diagnosis and treatment. Despite the increasing amount of studies investigating significant alterations, the mechanisms underlying the emergence and progression of these disorders remains unclear. It is therefore fundamental to improve our ability to differentiate between clinical subgroups and to move towards a more personalised approach. Here, we aim to highlight critical neural correlates in early stages of psychosis, and to identify relevant biomarkers correlating with clinical staging. In this study, we included resting-state fMRI and DTI data from a cohort of 129 healthy controls and 94 patients with early psychosis stratified into distinct groups based on the severity of their condition and their ability to recover after the first episode (stage 2, 3a, 3b, 3c). We investigated whether global and local measures of functional connectivity and network properties significantly differ according to the stages. Local differences in functional connectivity could be found in subgroups of patients as compared to controls. While patients in stage 2 didn’t differ from the healthy controls, we could highlight two opposite neural behaviours in two subgroups of stage 3 patients. In non-remitting patients (stage 3a) we observed a reduction of functional connectivity, aligned with the reduced structural connectivity found in previous studies. On the contrary, remitting patients (stage 3b and c), showed a functional-structural dissociation characterized by a reduced structural connectivity and increased functional connectivity, potentially indicating a relevant compensatory mechanism. Additionally, we built a whole-brain model to fit the empirical data of the healthy controls and to extract hidden properties of the network, and the correlates underlying the interplay of brain dynamics and connectomes. Specifically, the model combines functional dynamics and anatomical structure and describes local dynamics of single brain regions using the normal form of a Hopf bifurcation. With the help of a toy model, we enlighten the role of connectivity hubs in filtering out irrelevant stimuli (internal or external) and preventing an over synchronisation of the network. Finally, we built a model of 3 subgroups of patients (stage2, stage3 REM, stage3 non-REM), which allowed us to investigate the damaging mechanisms relevant for emergence of the disease as well as the compensatory mechanism underlying the functional-structural dissociation observed in the remitting patients (stage3 REM). These preliminary results allow us to progress in understanding some of the mechanisms underlying the emergence and the progression of psychosis and could open the way for possible future therapeutic applications.