Longitudinal development of frontoparietal activity during feedback learning: Contributions of age, performance, working memory and cortical thickness

• Published in: Developmental cognitive neuroscience Vol. 19; no. C; pp. 211 - 222
• Main Authors: Peters, Sabine, Van Duijvenvoorde, Anna C.K., Koolschijn, P. Cédric M.P., Crone, Eveline A.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.06.2016; Elsevier
• Subjects: Adolescence; Adolescent; Adult; Age Factors; Biofeedback, Psychology - physiology; Brain Mapping - trends; Child; Cognitive control; Development; Feedback learning; Female; Frontal cortex; Frontal Lobe - growth & development; Frontal Lobe - physiology; Humans; Learning - physiology; Longitudinal Studies; Magnetic Resonance Imaging - trends; Male; Memory, Short-Term - physiology; Nerve Net - growth & development; Nerve Net - physiology; Organ Size; Original Research; Parietal cortex; Parietal Lobe - growth & development; Parietal Lobe - physiology; Photic Stimulation - methods; Psychomotor Performance - physiology; Young Adult; Development; Adolescence; Feedback learning; Frontal cortex; Cognitive control; Parietal cortex
• ISSN: 1878-9293; 1878-9307
• DOI: 10.1016/j.dcn.2016.04.004

•We performed a longitudinal study on feedback learning (N=208, age 8–27 years).•We tested linear and nonlinear patterns in frontoparietal activity during learning.•DLPFC and parietal cortex showed a late-adolescent peak in activity.•SMA showed a linear increase, and ACC a linear decrease in brain activity with age.•Performance predicted DLPFC and parietal activity, thickness predicted SMA activity. Feedback learning is a crucial skill for cognitive flexibility that continues to develop into adolescence, and is linked to neural activity within a frontoparietal network. Although it is well conceptualized that activity in the frontoparietal network changes during development, there is surprisingly little consensus about the direction of change. Using a longitudinal design (N=208, 8–27 years, two measurements in two years), we investigated developmental trajectories in frontoparietal activity during feedback learning. Our first aim was to test for linear and nonlinear developmental trajectories in dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), supplementary motor area (SMA) and anterior cingulate cortex (ACC). Second, we tested which factors (task performance, working memory, cortical thickness) explained additional variance in time-related changes in activity besides age. Developmental patterns for activity in DLPFC and SPC were best characterized by a quadratic age function leveling off/peaking in late adolescence. There was a linear increase in SMA and a linear decrease with age in ACC activity. In addition to age, task performance explained variance in DLPFC and SPC activity, whereas cortical thickness explained variance in SMA activity. Together, these findings provide a novel perspective of linear and nonlinear developmental changes in the frontoparietal network during feedback learning.