Does temporal irregularity drive prediction failure in schizophrenia? Temporal modelling of ERPs

Schizophrenia is associated with failures to predict sensory consequences of one’s own actions, but the neural mechanisms remain unclear. This study tests whether aberrant predictive processing in schizophrenia is reflected in temporal irregularity of neuronal signals. Using an ERP study with EEG modeled via an event-related time-domain equation and its Laplace-domain Transfer Function (TF), the authors derived temporal parameters of auditory ERPs in 49 patients with schizophrenia (SZ) and 32 healthy controls (HC) during a predictive auditory paradigm (self-generated tones vs passive playback). SZ showed significantly greater temporal irregularity across single trials, indexed by altered latency (notably shorter P200), lower similarity across time courses using dynamic time warping (DTW), and longer, more variable intertrial settling times to steady state. Machine learning classifiers using TF model poles distinguished SZ from HC with high accuracy (~92%). Findings suggest increased temporal imprecision in SZ that may impair precise prediction of sensory consequences of actions.