Abnormal trial-to-trial variability in P300 time-varying directed eeg network of schizophrenia

Cognitive disturbance in identifying, processing, and responding to salient or novel stimuli are typical attributes of schizophrenia (SCH), and P300 has been proven to serve as a reliable psychosis endophenotype. The instability of neural processing across trials, i.e., trial-to-trial variability (TTV), is getting increasing attention in uncovering how the SCH “noisy” brain organizes during cognition processes. Nevertheless, the TTV in the brain network remains unrevealed, notably how it varies in different task stages. In this study, resorting to the time-varying directed electroencephalogram (EEG) network, we investigated the time-resolved TTV of the functional organizations subserving the evoking of P300. Results revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. The TTV of cross-band time-varying network properties can efficiently recognize SCH (accuracy: 83.39%, sensitivity: 89.22%, and specificity: 74.55%) and evaluate the psychiatric symptoms (i.e., Hamilton’s depression scale-24, r = 0.430, p = 0.022, RMSE = 4.891; Hamilton’s anxiety scale-14, r = 0.377, p = 0.048, RMSE = 4.575). Our study brings new insights into probing the time-resolved functional organization of the brain, and TTV in time-varying networks may provide a powerful tool for mining the substrates accounting for SCH and diagnostic evaluation of SCH.

Schematic view of the TTV in time-varying networks, as well as the patient’s recognition and psychiatric symptoms prediction based on the anomalous TTV of SCH. The TTV is getting increasing attention in understanding the “noise” brain of SCH, whereas a perspective in a time-varying directed network still lacking. We proposed to focus on the TTV in a time-varying directed EEG electroencephalogram (EEG) network to uncover how the brain unstably organizes during cognition processes and probe the instability of neural processing across trials during the P300 task process to find the potential mechanisms that account for the cognitive disturbance of SCH. Based on the P300 task EEG of SCHs and HCs, we revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. And the TTV of cross-band time-varying network properties can efficiently recognize SCH and evaluate the psychiatric symptoms.