Perceptual inference, accuracy, and precision in temporal reproduction in schizophrenia

Natsuki Ueda*, Kanji Tanaka, Kazushi Maruo, Neil Roach, Tomiki Sumiyoshi, Katsumi Watanabe, Takashi Hanakawa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Accumulating evidence suggests that deficits in perceptual inference account for symptoms of schizophrenia. One manifestation of perceptual inference is the central bias, i.e., the tendency to put emphasis on prior experiences over actual events in perceiving incoming sensory stimuli. Using an interval reproduction task, this study aimed to determine whether patients with schizophrenia show a stronger central bias than participants without schizophrenia. In the interval reproduction task, participants were shown a cross on a screen. The cross was replaced with a Gaussian patch for a predetermined time interval, and participants were required to reproduce the interval duration by pressing and releasing the space key. We manipulated the uncertainty of prior information using different interval distributions. We found no difference in the influence of prior information on interval reproduction between patients and controls. However, patients with SZ showed a stronger central bias than healthy participants in the intermediate interval range (approximately 450 ms to 900 ms). It is possible that the patients in SZ have non-uniform deficits associated with interval range or uncertainty of prior information in perceptual inference. Further, the severity of avolition and alogia was correlated with the strength of central bias in SZ. This study provides some insights into the mechanisms underlying the association between schizophrenic symptoms and perceptual inference.

Original languageEnglish
Article number100229
JournalSchizophrenia Research: Cognition
Publication statusPublished - 2022 Jun


  • Central bias
  • Perceptual inference
  • Schizophrenia
  • Time perception
  • Uncertainty adjustment

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Psychiatry and Mental health


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