Loading...
The computational foundations of dynamic coding in working memory
Title / Series / Name
Publication Volume
Publication Issue
Pages
Editors
Keywords
Neuropsychology and Physiological Psychology
Experimental and Cognitive Psychology
Cognitive Neuroscience
Experimental and Cognitive Psychology
Cognitive Neuroscience
URI
https://hdl.handle.net/20.500.14018/26808
Abstract
Working memory (WM) is a fundamental aspect of cognition. WM maintenance is classically thought to rely on stable patterns of neural activities. However, recent evidence shows that neural population activities during WM maintenance undergo dynamic variations before settling into a stable pattern. Although this has been difficult to explain theoretically, neural network models optimized for WM typically also exhibit such dynamics. Here, we examine stable versus dynamic coding in neural data, classical models, and task-optimized networks. We review principled mathematical reasons for why classical models do not, while task-optimized models naturally do exhibit dynamic coding. We suggest an update to our understanding of WM maintenance, in which dynamic coding is a fundamental computational feature rather than an epiphenomenon.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2024-07-01
Language
ISBN
Identifiers
10.1016/j.tics.2024.02.011