Evaluating Cognitive Function and Brain Activity Patterns via BolT in N-Back Working Memory Tasks

Working memory, which involves temporary storage, information processing, and regulating attention resources, is a fundamental cognitive process and constitutes a significant component of neuroscience research. In this study, we aimed to evaluate brain activation patterns by analyzing functional magnetic resonance imaging (fMRI) time-series data collected during a designed N-back working memory task with varying cognitive demands. We utilize a novel transformer model, blood-oxygen-level-dependent transformer (BolT), to extract the activation level features of brain regions in the cognitive process, thereby obtaining the influence weights of regions of interest (ROIs) on the corresponding tasks. Compared with previous studies, our work reaches similar conclusions in major brain region performance and provides a more precise analysis for identifying brain activation patterns. For each task, we select the top 5 percent of the most influential ROIs and conduct a systematic analysis and discussion. Additionally, we examined the impact of prior knowledge conditions on task performance and explored task classification at different time stages. The comparison results reflect the brain's adaptive strategies and dependencies in coping with different levels of cognitive demands and the stability optimization of the brain's cognitive processing. This study introduces innovative methodologies for understanding brain function and cognitive processes, highlighting the potential of transformer in cognitive neuroscience. Its findings offer new insights into brain activity patterns associated with working memory, contributing to the broader landscape of neuroscience research.