Different timescales of neural activities introduce different representations of task-relevant information

Recent findings indicate significant variations in neuronal activity timescales across and within cortical areas, yet their impact on cognitive processing remains inadequately understood. This study explores the role of neurons with different timescales in information processing within the neural system, particularly during the execution of context-dependent working memory tasks. Especially, we hypothesized that neurons with varying timescales contribute distinctively to task performance by forming diverse representations of task-relevant information. To test this, the model was trained to perform a context-dependent working memory task with a machine-learning technique. Results revealed that slow timescale neurons maintained stable representations of contextual information throughout the trial, whereas fast timescale neurons responded transiently to immediate stimuli. This differentiation in neuronal function suggests a fundamental role for timescale diversity in supporting the neural systems ability to integrate and process information dynamically. Our findings contribute to understanding how neural timescale diversity underpins cognitive flexibility and task-specific information processing, highlighting implications for both theoretical neuroscience and practical applications in designing artificial neural networks.