Ranieri, G., Burr, D. C., Bell, J., & Morrone, M. C.
Serial Dependence in face-gender classification revealed in low-beta frequency EEG
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”. It is particularly robust in face perception. We measured face-gender classification for a sequence of intermingled male, female and androgynous images. The classification showed strong serial dependence (androgynous images biased 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, 17 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 in 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 best information to classify gender was around 14 Hz when the previous response was “female”, and around 17 Hz when it was “male”, reinforcing the psychophysical results showing serial dependence to be carried at those frequencies. 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 gender of face images can be decoded from the neural activity of the EEG response to the successive face stimulus, 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 17 Hz for “male”, reinforcing the psychophysical results showing serial dependence to be carried at those beta-frequencies.