Evidence map›Paper›PMID 40629393›Full record

ArticleBMC biology2025

Serial dependence in face-gender classification revealed in low-beta frequency EEG.

Giacomo Ranieri, David C Burr, Jason Bell, Maria Concetta Morrone

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Article in BMC biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Giacomo RanieriDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, Florence, 50135, Italy.
David C BurrDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of Florence, Florence, 50135, Italy.
Jason BellSchool of Psychology, University of Western Australia, Crawley, 6009, Australia.
Maria Concetta MorroneDepartment of Translational Research On New Technologies in Medicine and Surgery, University of Pisa, Pisa, 56123, Italy. concetta.morrone@unipi.it.

Funding

European Research Council 832813European Union Next Generation grant PNRR MUR M4 C1 TNE 00034
6 · The paper itself

Abstract

backgroundPerception depends not only on current sensory input but is also heavily influenced by the immediate past perceptual experience, a phenomenon known as "serial dependence," particularly robust in face perception.

resultsWe measured discrimination of face-gender in participants to a sequence of intermingled male, female, and androgynous images, while recording EEG responses. The discriminations showed strong serial dependence (androgynous images biased towards male when preceded by male and female when preceded by female). The strength of the bias oscillated over time in the beta range, at 14 Hz for female prior stimuli, 18 Hz for male. Using classification techniques, we were able to successfully classify the previous stimulus from current EEG activity. Classification accuracy correlated well with the strength of serial dependence across individual participants, confirming that the neural signal from the past trial biased face perception. Bandpass filtering of the signal within the beta range showed that the most useful information to classify gender was around 14 Hz when the previous response was "female," and around 18 Hz when it was "male," reinforcing the psychophysical results showing serial dependence to be carried at those frequencies.

conclusionsOverall, the results suggest that recent experience of face-gender is selectively represented in beta-frequency (14-20 Hz) spectral components of intrinsic neural oscillations. SIGNIFICANCE STATEMENT: The neurophysiological mechanisms of how past perceptual experience affects current perception are poorly understood. Using classification techniques, we demonstrate that the response to gender of the previous face image of a sequence can be decoded from the neural activity of the current EEG response, showing that relevant neural signals are maintained over trials. Classification accuracy was higher for participants with strong serial dependence, strongly implicating these signals as the neural substrate for serial dependence. The best information to classify gender was around 14 Hz for "female" faces, and around 18 Hz for "male,", reinforcing the psychophysical results showing serial dependence to be carried at those beta -frequencies.

Indexed as

Beta RhythmElectroencephalographyFaceFacial RecognitionAdultFemaleHumansMalePhotic StimulationYoung AdultBeta oscillationsEEG decodingFace-gender discriminationSerial dependenceVision

Identifiers

PMID40629393
PMCPMC12239500

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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.