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

IF 4.4 1区 生物学 Q1 BIOLOGY
Giacomo Ranieri, David C Burr, Jason Bell, Maria Concetta Morrone
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引用次数: 0

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.

低频脑电图显示人脸性别分类的序列依赖性。
背景:感知不仅依赖于当前的感官输入,而且还严重受到刚刚过去的感知经验的影响,这种现象被称为“序列依赖”,尤其是在面部感知中。结果:我们测量了参与者对一系列混杂的男性、女性和雌雄同体图像的面部性别歧视,同时记录了脑电图反应。识别表现出强烈的序列依赖性(雌雄同体图像前有男性倾向,前有女性倾向)。偏见的强度随时间在beta范围内振荡,女性先前刺激为14赫兹,男性为18赫兹。使用分类技术,我们能够成功地从当前的脑电图活动中分类以前的刺激。分类准确性与个体参与者的序列依赖强度密切相关,证实了来自过去试验的神经信号偏向于面部感知。对beta范围内的信号进行带通滤波,结果显示,当之前的反应是“女性”时,最有用的性别分类信息约为14赫兹,当之前的反应是“男性”时,约为18赫兹,这加强了心理物理结果,表明在这些频率上携带了一系列依赖性。结论:总的来说,研究结果表明,最近的面部性别经验被选择性地反映在内在神经振荡的β频率(14-20 Hz)频谱成分中。意义说明:过去知觉经验如何影响当前知觉的神经生理机制尚不清楚。利用分类技术,我们证明了序列的前一个人脸图像的性别反应可以从当前脑电图反应的神经活动中解码出来,表明相关的神经信号在试验中保持不变。序列依赖性强的被试分类准确率较高,强烈暗示这些信号是序列依赖性的神经基质。分类性别的最佳信息是“女性”面孔的14赫兹左右,“男性”面孔的18赫兹左右,这加强了心理物理结果,表明在这些β频率上进行了一系列依赖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Biology
BMC Biology 生物-生物学
CiteScore
7.80
自引率
1.90%
发文量
260
审稿时长
3 months
期刊介绍: BMC Biology is a broad scope journal covering all areas of biology. Our content includes research articles, new methods and tools. BMC Biology also publishes reviews, Q&A, and commentaries.
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