title: Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory.
abstract: Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM.
authors.affiliation: Department of Psychology - Cognition and Behavior, Université de Liège, 4000 Liège, Belgium Cyclotron Research Centre, Université de Liège, 4000 Liège, Belgium Fund for Scientific Research FNRS, 1000 Brussels, Belgium.
authors.forename: Steve
authors.initials: S
authors.lastname: Majerus
authors.affiliation: Department of Psychological Sciences, University of Missouri, Columbia, MO 65211-2500, USA.
authors.forename: Nelson
authors.initials: N
authors.lastname: Cowan
authors.affiliation: Department of Psychology - Cognition and Behavior, Université de Liège, 4000 Liège, Belgium.
authors.forename: Frédéric
authors.initials: F
authors.lastname: Péters
authors.affiliation: Department of Psychology - Cognition and Behavior, Université de Liège, 4000 Liège, Belgium.
authors.forename: Laurens
authors.initials: L
authors.lastname: Van Calster
authors.affiliation: Department of Psychology - Cognition and Behavior, Université de Liège, 4000 Liège, Belgium Fund for Scientific Research FNRS, 1000 Brussels, Belgium.
authors.forename: Christophe
authors.initials: C
authors.lastname: Phillips
authors.affiliation: Cyclotron Research Centre, Université de Liège, 4000 Liège, Belgium Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA.
authors.forename: Jessica
authors.initials: J
authors.lastname: Schrouff
mesh_terms: D000293:Adolescent; D000328:Adult; D001288:Attention / Q000502:physiology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology; D003071:Cognition / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*; D014706:Verbal Learning / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult
keywords: attention; fMRI; intraparietal sulcus; multivariate voxel pattern analysis; verbal; visual; working memory