Increased excursions to functional networks in schizophrenia in the absence of task

Abstract

Brain activity during rest has been demonstrated to evolve through a repertoire of functional connectivity (FC) patterns, whose alterations may provide biomarkers of schizophrenia - a psychotic disorder characterized by dysfunctional brain connectivity. In this study, differences between the dynamic exploration of resting-state networks using functional magnetic resonance imaging (fMRI) data from 71 schizophrenia patients and 74 healthy controls were investigated using a method focusing on the dominant fMRI signal phase coherence pattern at each time point. Through the lens of dynamical systems theory, brain activity in the form of temporal FC state trajectories was examined for intergroup differences by calculating the fractional occupancy, dwell time, limiting probability of each state and the transition probabilities between states. Results showed reduced fractional occupancy of a globally synchronized state in schizophrenia. Conversely, FC states overlapping with canonical functional subsystems exhibited increased fractional occupancy and limiting probability in schizophrenia. Furthermore, state-to-state transition probabilities were altered in schizophrenia. This revealed a reduced probability of remaining in a global integrative state, increased probability of switching from this state to functionally meaningful networks and reduced probability of remaining in a state related to the Default Mode network. These results revealed medium to large effect sizes. Finally, this study showed that using K-medoids clustering did not influence the observed intergroup differences - highlighting the utility of dynamical systems theory to better understand brain activity. Combined, these findings expose pronounced differences between schizophrenia patients and healthy controls - supporting and extending current knowledge regarding disrupted brain dynamics in schizophrenia.

Metastability as a neuromechanistic biomarker of schizophrenia pathology

“…Effect sizes were negligible to small ( d =-0.16 to d =0.36) for early disorder subjects (NAP group) and moderate to large ( d =-0.58 to d =-0.82) for subjects with established schizophrenia (SCHZ group). Previous discrimination analysis on the same Cobre dataset using a distance measure between patterns of instantaneous phase synchrony reported a moderate effect size ( d =0.67) [28], as did another study using the mean probability of dwell time in a global state (Hedge’s g =0.73) [60]. In contrast, one study reported significantly lower effect sizes ( d =0.06 to d =0.31) using measures of metastability in its original form, and using measures of between-network FC ( d =0.04 to d =0.52) [61].…”

Psilocybin modulation of dynamic functional connectivity is associated with plasma psilocin and subjective effects

“…Previous studies applying LEiDA have reported alterations in a "fully connected" brain state, characterized by all elements having the same sign 31,32,39,[42][43][44][45][46] . Here we also observed this fully connected state and report an increase in fractional occurrence significantly associated with SDI, but not PPL.…”

“…Previous studies applying LEiDA have reported alterations in a “fully connected” brain state, characterized by all elements having the same sign (Cabral et al, 2017; Escrichs et al, 2021; Farinha et al, 2021; Figueroa et al, 2019; Larabi et al, 2020; Lord et al, 2019; Stark et al, 2021; Vohryzek et al, 2020). Here we also observed this fully connected state and report an increase in fractional occurrence significantly associated with SDI, but not PPL.…”

“…Especially in the case of an eigenvector with similar numbers of positive and negative loadings, slight variations can result in sign flips that place otherwise similar eigenvectors in different areas of this region space, which can affect clustering results when antipodal symmetry is not considered (see Supplementary Figure S1). More recent approaches to address this include estimating the cosine distance metric and the use of “k-medoids”, which labels specific observed data points as centroids (Farinha et al, 2021). However, this leaves unresolved the limitation of the sign-flip procedure.…”

Using in silico perturbational approach to identify critical areas in schizophrenia

“…Several studies have found alterations in GS, although the results are not always consistent. For instance, Farinha et al described decreased GS and increased recruitment of functional networks in schizophrenia (Farinha et al 2022). On the other hand, increased cortical power and variance were observed in two independent samples of patients affected by schizophrenia compared to healthy controls when global signal was not regressed out of the data (Yang et al 2014(Yang et al , 2017.…”