小柯机器人

研究揭示防止感官和记忆之间干扰的机制
2021-04-07 13:40

美国普林斯顿大学Timothy J. Buschman研究团队在研究中取得进展。他们发现转换动力学减少了感官和记忆表达之间的干扰。2021年4月5日出版的《自然-神经科学》发表了这项成果。

在本研究中,研究人员发现大脑随着时间的推移将感觉表征转换为正交记忆表征从而减轻感觉与记忆之间的干扰。为了研究感官输入和记忆的表征方式,研究人员记录了小鼠听觉皮层中的神经元,因为它们完全记录了声音信息。

研究发现,神经亚群在两个正交维度上代表了感觉输入和最近的刺激记忆。感觉信息到记忆的转换是由“稳定的”神经元(随时间变化保持其选择性)和“转换”的神经元(随时间变化其选择性)组合形成。这些神经反应一起改变了细胞群表征,将感觉输入转化为记忆。

理论模型表明,这种转换动力学是一种用于生成正交表征的有效机制,从而保护内在记忆免受感觉干扰。

据介绍,感官知觉与最近的刺激记忆相结合决定了认知。但是,神经编码的分布式性质可能会干扰感觉和记忆。

附:英文原文

Title: Rotational dynamics reduce interference between sensory and memory representations

Author: Alexandra Libby, Timothy J. Buschman

Issue&Volume: 2021-04-05

Abstract: Cognition depends on integrating sensory percepts with the memory of recent stimuli. However, the distributed nature of neural coding can lead to interference between sensory and memory representations. Here, we show that the brain mitigates such interference by rotating sensory representations into orthogonal memory representations over time. To study how sensory inputs and memories are represented, we recorded neurons from the auditory cortex of mice as they implicitly learned sequences of sounds. We found that the neural population represented sensory inputs and the memory of recent stimuli in two orthogonal dimensions. The transformation of sensory information into a memory was facilitated by a combination of ‘stable’ neurons, which maintained their selectivity over time, and ‘switching’ neurons, which inverted their selectivity over time. Together, these neural responses rotated the population representation, transforming sensory inputs into memory. Theoretical modeling showed that this rotational dynamic is an efficient mechanism for generating orthogonal representations, thereby protecting memories from sensory interference.

DOI: 10.1038/s41593-021-00821-9

Source: https://www.nature.com/articles/s41593-021-00821-9

Nature Neuroscience:《自然—神经科学》,创刊于1998年。隶属于施普林格·自然出版集团,最新IF:28.771
官方网址:https://www.nature.com/neuro/
投稿链接:https://mts-nn.nature.com/cgi-bin/main.plex


本期文章:《自然—神经科学》:Online/在线发表

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