School of Cognitive Sciences, Institute for Research in Fundamental Sciences, P.O. Box 19395-5746, Tehran, Iran.
Cognitive Systems Lab, Control and Intelligent Processing Centre of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, P.O. Box 14395-515, Tehran, Iran.
Sci Rep. 2017 May 10;7(1):1709. doi: 10.1038/s41598-017-01864-4.
Neuronal networks of the brain adapt their information processing according to the history of stimuli. Whereas most studies have linked adaptation to repetition suppression, recurrent connections within a network and disinhibition due to adaptation predict more complex response patterns. The main questions of this study are as follows: what is the effect of the selectivity of neurons on suppression/enhancement of neural responses? What are the consequences of adaptation on information representation in neural population and the temporal structure of response patterns? We studied rapid face adaptation using spiking activities of neurons in the inferior-temporal (IT) cortex. Investigating the responses of neurons, within a wide range from negative to positive face selectivity, showed that despite the peak amplitude suppression in highly positive selective neurons, responses were enhanced in most other neurons. This enhancement can be attributed to disinhibition due to adaptation. Delayed and distributed responses were observed for positive selective neurons. Principal component analysis of the IT population responses over time revealed that repetition of face stimuli resulted in temporal decorrelation of the network activity. The contributions of the main and higher neuronal dimensions were changed under an adaptation condition, where more neuronal dimensions were used to encode repeated face stimuli.
大脑中的神经网络会根据刺激的历史来调整其信息处理方式。虽然大多数研究都将适应与重复抑制联系起来，但网络内的递归连接和适应引起的去抑制预测了更复杂的反应模式。本研究的主要问题如下：神经元的选择性对神经反应的抑制/增强有什么影响？适应对神经元群体中的信息表示和反应模式的时间结构有什么影响？我们使用下颞（IT）皮层神经元的尖峰活动研究了快速面部适应。对从负性到正性面部选择性范围很宽的神经元的反应进行研究表明，尽管高度正性选择性神经元的峰值幅度受到抑制，但大多数其他神经元的反应得到了增强。这种增强可归因于适应引起的去抑制。对于正性选择性神经元，观察到延迟和分布式反应。随着时间的推移，对 IT 群体反应进行主成分分析表明，面部刺激的重复导致网络活动的时间去相关。在适应条件下，主要和更高的神经元维度的贡献发生了变化，更多的神经元维度被用于编码重复的面部刺激。
