School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.
PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
PLoS Biol. 2023 Mar 24;21(3):e3002056. doi: 10.1371/journal.pbio.3002056. eCollection 2023 Mar.
The regularities of the world render an intricate interplay between past and present. Even across independent trials, current-trial perception can be automatically shifted by preceding trials, namely the "serial bias." Meanwhile, the neural implementation of the spontaneous shift of present by past that operates on multiple features remains unknown. In two auditory categorization experiments with human electrophysiological recordings, we demonstrate that serial bias arises from the co-occurrence of past-trial neural reactivation and the neural encoding of current-trial features. The meeting of past and present shifts the neural representation of current-trial features and modulates serial bias behavior. Critically, past-trial features (i.e., pitch, category choice, motor response) keep their respective identities in memory and are only reactivated by the corresponding features in the current trial, giving rise to dissociated feature-specific serial biases. The feature-specific automatic reactivation might constitute a fundamental mechanism for adaptive past-to-present generalizations over multiple features.
世界的规律呈现出过去和现在之间错综复杂的相互作用。即使在独立的试验中,当前试验的感知也可以被前一个试验自动转移,即“序列偏差”。同时,目前对过去的自发转变的神经实现,其在多个特征上的运作机制仍然未知。在两个具有人类电生理记录的听觉分类实验中,我们证明了序列偏差是由过去试验神经再激活和当前试验特征的神经编码共同引起的。过去和现在的交汇改变了当前试验特征的神经表示,并调节了序列偏差行为。关键是,过去试验的特征(即音高、类别选择、运动反应)在记忆中保持各自的身份,并且仅被当前试验中相应的特征重新激活,从而产生分离的特征特异性序列偏差。特征特异性的自动再激活可能构成了过去到现在在多个特征上自适应概括的基本机制。