The effects of the post-delay epochs on working memory error reduction

• Published in: PLoS computational biology Vol. 21; no. 5; p. e1013083
• Main Authors: Ye, Zeyuan, Li, Haoran, Tian, Liang, Zhou, Changsong
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 13.05.2025; Public Library of Science (PLoS)
• Subjects: Biology and Life Sciences; Computational Biology; Computer and Information Sciences; Humans; Male; Memory, Short-Term - physiology; Models, Neurological; Neural circuitry; Neural Networks, Computer; Neurological research; Physical Sciences; Research and Analysis Methods; Short-term memory; Social Sciences; Hong Kong, China
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1013083

Accurate retrieval of the maintained information is crucial for working memory. This process primarily occurs during post-delay epochs, when subjects receive cues and generate responses. However, the computational and neural mechanisms that underlie these post-delay epochs to support robust memory remain poorly understood. To address this, we trained recurrent neural networks (RNNs) on a color delayed-response task, where certain colors (referred to as common colors) were more frequently presented for memorization. We found that the trained RNNs reduced memory errors for common colors by decoding a broader range of neural states into these colors through the post-delay epochs. This decoding process was driven by convergent neural dynamics and a non-dynamic, biased readout process during the post-delay epochs. Our findings highlight the importance of post-delay epochs in working memory and suggest that neural systems adapt to environmental statistics by using multiple mechanisms across task epochs.