Both contextual regularity and selective attention affect the reduction of precision-weighted prediction errors but in distinct manners

Yi Fang Hsu, Jarmo A. Hämäläinen

研究成果: 雜誌貢獻期刊論文同行評審

摘要

Predictive coding model of perception postulates that the primary objective of the brain is to infer the causes of sensory inputs by reducing prediction errors (i.e., the discrepancy between expected and actual information). Moreover, prediction errors are weighted by their precision (i.e., inverse variance), which quantifies the degree of certainty about the variables. There is accumulating evidence that the reduction of precision-weighted prediction errors can be affected by contextual regularity (as an external factor) and selective attention (as an internal factor). However, it is unclear whether the two factors function together or separately. Here we used electroencephalography (EEG) to examine the putative interaction of contextual regularity and selective attention on this reduction process. Participants were presented with pairs of regular and irregular quartets in attended and unattended conditions. We found that contextual regularity and selective attention independently modulated the N1/MMN where the repetition effect was absent. On the P2, the two factors respectively interacted with the repetition effect without interacting with each other. The results showed that contextual regularity and selective attention likely affect the reduction of precision-weighted prediction errors in distinct manners. While contextual regularity finetunes our efficiency at reducing precision-weighted prediction errors, selective attention seems to modulate the reduction process following the Matthew effect of accumulated advantage.

原文英語
文章編號e13753
期刊Psychophysiology
58
發行號3
DOIs
出版狀態已發佈 - 2021 三月
對外發佈

ASJC Scopus subject areas

  • 神經科學 (全部)
  • 神經心理學與生理心理學
  • 實驗與認知心理學
  • 神經內科
  • 內分泌和自主系統
  • 發展神經科學
  • 認知神經科學
  • 生物精神病學

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