Intrinsic functional networks for distinct sources of error in visual working memory

• Published in: Cerebral cortex (New York, N.Y. 1991) N.Y. 1991), 2024-10, Vol.34 (10)
• Main Authors: Li, Xuqian, Oestreich, Lena K L, Rangelov, Dragan, Lévy-Bencheton, Delphine, O’Sullivan, Michael J
• Format: Article
• Language: English
• Subjects: Adult; Brain - diagnostic imaging; Brain - physiology; Brain Mapping - methods; Female; Humans; Magnetic Resonance Imaging; Male; Memory, Short-Term - physiology; Nerve Net - diagnostic imaging; Nerve Net - physiology; Neural Pathways - physiology; Original; Visual Perception - physiology; Young Adult
• ISSN: 1047-3211; 1460-2199; 1460-2199
• DOI: 10.1093/cercor/bhae401

Abstract Visual working memory (VWM) is a core cognitive function wherein visual information is stored and manipulated over short periods. Response errors in VWM tasks arise from the imprecise memory of target items, swaps between targets and nontargets, and random guesses. However, it remains unclear whether these types of errors are underpinned by distinct neural networks. To answer this question, we recruited 80 healthy adults to perform delayed estimation tasks and acquired their resting-state functional magnetic resonance imaging scans. The tasks required participants to reproduce the memorized visual feature along continuous scales, which, combined with mixture distribution modeling, allowed us to estimate the measures of memory precision, swap errors, and random guesses. Intrinsic functional connectivity within and between different networks, identified using a hierarchical clustering approach, was estimated for each participant. Our analyses revealed that higher memory precision was associated with increased connectivity within a frontal-opercular network, as well as between the dorsal attention network and an angular-gyrus-cerebellar network. We also found that coupling between the frontoparietal control network and the cingulo-opercular network contributes to both memory precision and random guesses. Our findings demonstrate that distinct sources of variability in VWM performance are underpinned by different yet partially overlapping intrinsic functional networks.