title: Dynamic functional connectivity shapes individual differences in associative learning.
abstract: Current neuroscientific research has shown that the brain reconfigures its functional interactions at multiple timescales. Here, we sought to link transient changes in functional brain networks to individual differences in behavioral and cognitive performance by using an active learning paradigm. Participants learned associations between pairs of unrelated visual stimuli by using feedback. Interindividual behavioral variability was quantified with a learning rate measure. By using a multivariate statistical framework (partial least squares), we identified patterns of network organization across multiple temporal scales (within a trial, millisecond; across a learning session, minute) and linked these to the rate of change in behavioral performance (fast and slow). Results indicated that posterior network connectivity was present early in the trial for fast, and later in the trial for slow performers. In contrast, connectivity in an associative memory network (frontal, striatal, and medial temporal regions) occurred later in the trial for fast, and earlier for slow performers. Time-dependent changes in the posterior network were correlated with visual/spatial scores obtained from independent neuropsychological assessments, with fast learners performing better on visual/spatial subtests. No relationship was found between functional connectivity dynamics in the memory network and visual/spatial test scores indicative of cognitive skill. By using a comprehensive set of measures (behavioral, cognitive, and neurophysiological), we report that individual variations in learning-related performance change are supported by differences in cognitive ability and time-sensitive connectivity in functional neural networks. Hum Brain Mapp 37:3911-3928, 2016. © 2016 Wiley Periodicals, Inc.
authors.affiliation: Baycrest Centre, Rotman Research Institute, Toronto, Canada. zee.fatima1@gmail.com.
authors.forename: Zainab
authors.initials: Z
authors.lastname: Fatima
authors.affiliation: Baycrest Centre, Rotman Research Institute, Toronto, Canada.
authors.forename: Natasha
authors.initials: N
authors.lastname: Kovacevic
authors.affiliation: Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, Montreal, Canada.
authors.forename: Bratislav
authors.initials: B
authors.lastname: Misic
authors.affiliation: Baycrest Centre, Rotman Research Institute, Toronto, Canada.|Department of Psychology, University of Toronto, Toronto, Canada.
authors.forename: Anthony Randal
authors.initials: AR
authors.lastname: McIntosh
mesh_terms: D000328:Adult; D001245:Association Learning / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D002755:Choice Behavior / Q000502:physiology; D030141:Feedback, Psychological / Q000502:physiology; D005260:Female; D006801:Humans; D007206:Individuality; D059032:Learning Curve; D016018:Least-Squares Analysis; D015225:Magnetoencephalography; D008297:Male; D015999:Multivariate Analysis; D009434:Neural Pathways / Q000502:physiology; D009483:Neuropsychological Tests; D010364:Pattern Recognition, Visual / Q000502:physiology*; D025341:Principal Component Analysis; D011930:Reaction Time; D055815:Young Adult
keywords: conditional associative learning; human learning curve; magnetoencephalography; neuropsychological assessment; partial least squares; principal component analysis