Serial dependence in face-gender classification revealed in low-beta frequency EEG
Abstract Background Perception 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. Results We measured discrimination of face-gender in participants to...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12915-025-02289-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849331654160547840 |
|---|---|
| author | Giacomo Ranieri David C. Burr Jason Bell Maria Concetta Morrone |
| author_facet | Giacomo Ranieri David C. Burr Jason Bell Maria Concetta Morrone |
| author_sort | Giacomo Ranieri |
| collection | DOAJ |
| description | Abstract Background Perception 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. Results We 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. Conclusions Overall, 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. |
| format | Article |
| id | doaj-art-aa051745f0f64d6caa9a012a6867c4d8 |
| institution | Kabale University |
| issn | 1741-7007 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Biology |
| spelling | doaj-art-aa051745f0f64d6caa9a012a6867c4d82025-08-20T03:46:27ZengBMCBMC Biology1741-70072025-07-0123111310.1186/s12915-025-02289-6Serial dependence in face-gender classification revealed in low-beta frequency EEGGiacomo Ranieri0David C. Burr1Jason Bell2Maria Concetta Morrone3Department of Neuroscience, Psychology, Pharmacology, and Child Health, University of FlorenceDepartment of Neuroscience, Psychology, Pharmacology, and Child Health, University of FlorenceSchool of Psychology, University of Western AustraliaDepartment of Translational Research On New Technologies in Medicine and Surgery, University of PisaAbstract Background Perception 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. Results We 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. Conclusions Overall, 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.https://doi.org/10.1186/s12915-025-02289-6Face-gender discriminationSerial dependenceEEG decodingVisionBeta oscillations |
| spellingShingle | Giacomo Ranieri David C. Burr Jason Bell Maria Concetta Morrone Serial dependence in face-gender classification revealed in low-beta frequency EEG BMC Biology Face-gender discrimination Serial dependence EEG decoding Vision Beta oscillations |
| title | Serial dependence in face-gender classification revealed in low-beta frequency EEG |
| title_full | Serial dependence in face-gender classification revealed in low-beta frequency EEG |
| title_fullStr | Serial dependence in face-gender classification revealed in low-beta frequency EEG |
| title_full_unstemmed | Serial dependence in face-gender classification revealed in low-beta frequency EEG |
| title_short | Serial dependence in face-gender classification revealed in low-beta frequency EEG |
| title_sort | serial dependence in face gender classification revealed in low beta frequency eeg |
| topic | Face-gender discrimination Serial dependence EEG decoding Vision Beta oscillations |
| url | https://doi.org/10.1186/s12915-025-02289-6 |
| work_keys_str_mv | AT giacomoranieri serialdependenceinfacegenderclassificationrevealedinlowbetafrequencyeeg AT davidcburr serialdependenceinfacegenderclassificationrevealedinlowbetafrequencyeeg AT jasonbell serialdependenceinfacegenderclassificationrevealedinlowbetafrequencyeeg AT mariaconcettamorrone serialdependenceinfacegenderclassificationrevealedinlowbetafrequencyeeg |