Evidence map›Paper›PMID 41918584›Full record

ArticleFrontiers in psychiatry2026

Attenuated inferred-sensory mismatch during masked face recognition in schizophrenia.

Masakazu Sunaga, Yuichi Takei, Yutaka Kato, Reiko Oi, Kohei Imai, Keisuke Fukasawa, Yoshihito Shigihara, Kazuyuki Fujihara, Tatsuki Sekiya, Masato Fukuda and 1 more

Abstract read
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Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Masakazu SunagaDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Yuichi TakeiDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Yutaka KatoDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Reiko OiDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Kohei ImaiGunma Prefectural Psychiatric Medical Center, Gunma, Isesaki, Japan.
Keisuke FukasawaKumagaya General Hospital, Saitama, Japan.
Yoshihito ShigiharaKumagaya General Hospital, Saitama, Japan.
Kazuyuki FujiharaDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Tatsuki SekiyaDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Masato FukudaDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.
Seiichiro JindeDepartment of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Gunma, Maebashi, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Predictive-processing accounts have become increasingly influential in understanding the pathophysiology of schizophrenia (SZ). Within this framework, mismatch negativity (MMN) paradigms provide a well-established and widely replicated assay of mismatch processing. However, most MMN designs operationalize mismatch as violations of externally defined regularities. In this study, we aimed to use magnetoencephalography and a masked-face paradigm to probe a complementary form of mismatch that arises when an internally inferred representation of an occluded face is confronted with newly available sensory evidence after unmasking (an inferred-sensory mismatch). Methods: Participants first viewed the masked faces, followed by the same faces without masks. Two types of stimuli-individual and average-were used. Data from 18 individuals with SZ and 18 healthy controls (HCs) were analyzed using spatiotemporal cluster tests. Results: Among HCs, mask removal from individual faces elicited a significant cluster at the left temporal sensors (234-511 ms), with source estimates suggesting involvement of the left insular cortex. No significant clusters were observed for average faces. In the SZ group, no significant mismatch responses were observed in either condition. Discussion: Overall, HCs showed a reliable neural response to the unmasking of individual faces, consistent with a mismatch between an internally inferred representation and newly revealed sensory information. In contrast, no robust mismatch-related response was detected in the SZ group in the present dataset. This pattern is compatible with predictive-processing accounts that emphasize reduced precision of perceptual inference in SZ.

Indexed as

Bayesian brain hypothesisface recognitioninsular cortexmagnetoencephalographypredictive processingschizophrenia

Identifiers

PMID41918584
PMCPMC13034134

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.