Evidence map›Paper›PMID 41808569›Full record

ArticleHuman brain mapping2026

Neural Architecture of Familiar Person Perception: Contributions of Unimodal and Multimodal Brain Regions.

Tianxing Zheng, Stefania Mattioni, Olivier Collignon, Xiaoqing Gao

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tianxing ZhengDepartment of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.
Stefania MattioniDepartment of Experimental Psychology (PP02) & Centre for Cognitive Neuroscience (CCN), University of Gent, Gent, Belgium.
Olivier CollignonCrossmodal Perception and Plasticity Lab, Institute of Neuroscience (IoNS) and Institute for Research in Psychology (IPSY), Louvain-la-Neuve, Belgium.
Xiaoqing GaoCenter for Psychological Sciences, Zhejiang University, Hangzhou, China.

Funding

Canadian Institute of Health Research Grant PJT-183761Zhejiang University
6 · The paper itself

Abstract

Faces and voices provide essential information for recognizing familiar people. The brain regions involved in processing person familiarity through these modalities have typically been studied independently, leaving unclear whether and where the auditory and visual networks overlap. In this study, we developed a novel frequency-tagging-based fMRI paradigm to examine the neural basis of familiarity processing from a multimodal perspective. Our findings indicate that the perception of person familiarity through faces and voices predominantly activates sensory-specific regions-the posterior superior temporal cortex (pSTC) for faces and the anterior superior temporal cortex (aSTC) for voices. Discrete regions in the temporal (posterior superior temporal sulcus, pSTS) and frontal (inferior frontal cortex, IFC) areas showed overlapping multisensory activity. pSTS sits as a spatial boundary between unimodal regions, whereas IFC shows connectivity-driven convergence without boundary constraints. These findings indicate shared neural processes for familiarity processing from faces and voices. All together, these results highlight the presence of distributed unisensory and multisensory networks engaging in recognizing familiar people.

Indexed as

Auditory PerceptionBrainBrain MappingFacial RecognitionRecognition, PsychologyVoice RecognitionAdultFemaleHumansMagnetic Resonance ImagingMalePhotic StimulationYoung Adultface perceptionfamiliaritymultisensoryvoice perception

Identifiers

PMID41808569
PMCPMC12976657

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.