Top-down control: A unified principle of cortical learning. (April 2019)

• Record Type: Journal Article
• Authors: Makino, Hiroshi
• Is Part Of: Neuroscience research. Volume 141(2019)
• Page Start: 23
• Page End: 28
• Publication Date: 2019-04
• Subjects: Top-down control -- Perceptual learning -- Motor learning -- Offline learning; Neurosciences -- Research -- Periodicals; Neurosciences -- Research -- Japan -- Periodicals; Neurology -- Periodicals; Neurosciences -- Periodicals; Neurosciences -- Recherche -- Périodiques; Neurosciences -- Recherche -- Japon -- Périodiques; Neurosciences -- Research; Japan; Periodicals; 612.8
• DOI: 10.1016/j.neures.2018.08.004
• Languages: English
• ISSNs: 0168-0102

Abstract

Highlights: Recruitment of top-down control is proposed as a unified principle of cortical learning. Microscopic circuit dissection revealed dynamic recruitment of top-down activity during sensory learning. Macroscopic activity analysis uncovered top-down-mediated orchestration of cortical activity during motor learning. Abstract: Cognitive control of the brain flexibly maps incoming sensory information onto execution of actions appropriate for the current goal. Learning is a process that enables the brain to estimate current states of the world by extracting its spatiotemporal structure and generate goal-directed motor outputs through selective association of events or movement refinement. Accumulating evidence suggests that top-down control from higher-order brain areas modulates downstream neural activity and changes local computations that are critical for the execution of learned behavior. Recent technological advances in multi-site recordings and optogenetic approaches are beginning to reveal more direct evidence of top-down cognitive control by monitoring and perturbing activity of top-down inputs and observing its causal consequences on behavior and downstream neural dynamics. Here I highlight that learning-related changes in neural circuits in distinct domains of learning converge onto a unified principle; namely recruitment of top-down control whether it involves sensory, motor or offline learning. Recruitment of top-down control may reflect experience-dependent adaptation and integration of internal models for refined state estimation and goal-directed optimal behavior.