Dynamic shifts in brain network activation during supracapacity working memory task performance. Issue 4 (24th November 2014)

• Record Type: Journal Article
• Authors: Van Snellenberg, Jared X.; Slifstein, Mark; Read, Christina; Weber, Jochen; Thompson, Judy L.; Wager, Tor D.; Shohamy, Daphna; Abi‐Dargham, Anissa; Smith, Edward E.
• Is Part Of: Human brain mapping. Volume 36:Issue 4(2015:Apr.)
• Page Start: 1245
• Page End: 1264
• Publication Date: 2014-11-24
• Subjects: cognition -- memory, short‐term -- prefrontal cortex -- magnetic resonance imaging -- task performance and analysis; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.22699
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Despite significant advances in understanding how brain networks support working memory (WM) and cognitive control, relatively little is known about how these networks respond when cognitive capabilities are overtaxed. We used a fine‐grained manipulation of memory load within a single trial to exceed WM capacity during functional magnetic resonance imaging to investigate how these networks respond to support task performance when WM capacity is exceeded. Analyzing correct trials only, we observed a nonmonotonic (inverted‐U) response to WM load throughout the classic WM network (including bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and presupplementary motor areas) that peaked later in individuals with greater WM capacity. We also observed a relative increase in activity in medial anterior prefrontal cortex, posterior cingulate/precuneus, and lateral temporal and parietal regions at the highest WM loads, and a set of predominantly subcortical and prefrontal regions whose activation was greatest at the lowest WM loads. At the individual subject level, the inverted‐U pattern was associated with poorer performance while expression of the early and late activating patterns was predictive of better performance. In addition, greater activation in bilateral fusiform gyrus and right occipital lobe at the highest WM loads predicted better performance. These results demonstrate dynamic and behaviorally relevant changes in the level of activation of multiple brain networks in response to increasing WM load that are not well accounted for by present models of how the brain subserves the cognitive ability to hold and manipulate information on‐line. Hum Brain Mapp 36:1245–1264, 2015 . ©2014 Wiley Periodicals, Inc.