Study on individual differences in visual working memory tasks based on spatiotemporal brain functional metrics and biological perspectives

Abstract

Visual working memory (VWM) is a critical area of study in cognitive neuroscience, yet the neural and genetic foundations of individual differences in VWM remain unclear. This study investigates individual differences in VWM performance across four types of visual stimuli (Body, Face, Place, Tool) under 0-back and 2-back conditions by integrating gene expression data and spatiotemporal brain function metrics. First, multiple spatiotemporal brain function metrics were extracted, and Sequential Backward Selection (SBS) and Leave-One-Subject-Out Cross-Validation (LOSO-CV) linear regression were applied to predict behavioral performance under VWM conditions. Model performance was evaluated using RMSE. Next, the Working Memory Individual Differences Map (WMIDM) was constructed based on Pearson correlation coefficients between actual and predicted behavioral performance. Finally, WMIDM was integrated with Allen Human Brain Atlas (AHBA) gene expression data to explore its genetic underpinnings. Notably, the gene analysis is exploratory, providing a preliminary framework for future investigations into the molecular basis of working memory. The results demonstrated that under the 2 vs. 0-back condition, spatiotemporal metrics outperformed static metrics ($r_{\text{spa}}=0.40,q=8.9\times 10^{-28},\text{RMSE}=0.928$ vs. $r_{\text{sta}}=0.28,q=2.7\times 10^{-14},\text{RMSE}=0.966$). Brain regions contributing to the WMIDM were primarily located in the frontal lobe. Furthermore, genes associated with WMIDM were significantly enriched in pathways linked to intellectual disability and mental disorders, as well as related biological processes and cell types. This study highlights the neural and potential genetic foundations of individual differences in working memory through the lens of spatiotemporal multidimensional brain function and gene expression. These findings provide valuable insights for future neuroscience research and pave the way for personalized cognitive interventions.