title: Perceptual training continuously refines neuronal population codes in primary visual cortex.
abstract: Perceptual learning substantially improves visual discrimination and detection ability, which has been associated with visual cortical plasticity. However, little is known about the dynamic changes in neuronal response properties over the course of training. Using chronically implanted multielectrode arrays, we were able to capture day-by-day spatiotemporal dynamics of neurons in the primary visual cortex (V1) of monkeys trained to detect camouflaged visual contours. We found progressive strengthening and accelerating in both facilitation of neurons encoding the contour elements and suppression of neurons responding to the background components. The enhancement of this figure-ground contrast in V1 was closely correlated with improved behavioral performance on a daily basis. Decoding accuracy of a simple linear classifier based on V1 population responses also paralleled the animal's behavioral changes. Our results indicate that perceptual learning shapes the V1 population code to allow a more efficient readout of task-relevant information.
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Yin
authors.initials: Y
authors.lastname: Yan
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Malte J
authors.initials: MJ
authors.lastname: Rasch
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Minggui
authors.initials: M
authors.lastname: Chen
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Xiang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Min
authors.initials: M
authors.lastname: Huang
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Si
authors.initials: S
authors.lastname: Wu
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
authors.forename: Wu
authors.initials: W
authors.lastname: Li
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001931:Brain Mapping; D003216:Conditioning, Operant / Q000502:physiology*; D008253:Macaca mulatta; D009474:Neurons / Q000502:physiology*; D010775:Photic Stimulation; D013997:Time Factors; D014793:Visual Cortex / Q000166:cytology*; D014796:Visual Perception / Q000502:physiology*; D014851:Wakefulness