4.5 Article

LEARNING-STAGE-DEPENDENT, FIELD-SPECIFIC, MAP PLASTICITY IN THE RAT AUDITORY CORTEX DURING APPETITIVE OPERANT CONDITIONING

Journal

NEUROSCIENCE
Volume 199, Issue -, Pages 243-258

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neuroscience.2011.09.046

Keywords

auditory cortex; learning; homeostasis; plasticity; disinhibition; operant conditioning

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Cortical reorganizations during acquisition of motor skills and experience-dependent recovery after deafferentation consist of several distinct phases, in which expansion of receptive fields is followed by the shrinkage and use-dependent refinement. In perceptual learning, however, such non-monotonic, stage-dependent plasticity remains elusive in the sensory cortex. In the present study, microelectrode mapping characterized plasticity in the rat auditory cortex, including primary, anterior, and ventral/suprarhinal auditory fields (A1, AAF, and VAF/SRAF), at the early and late stages of appetitive operant conditioning. We first demonstrate that most plasticity at the early stage was tentative, and that long-lasting plasticity after extended training was able to be categorized into either early- or late-stage-dominant plasticity. Second, training-induced plasticity occurred both locally and globally with a specific temporal order. Conditioned-stimulus (CS) frequency used in the task tended to be locally over-represented in AAF at the early stage and in VAF/SRAF at the late stage. The behavioral relevance of neural responses suggests that the local plasticity also occurred in A1 at the early stage. In parallel, the tone-responsive area globally shrank at the late stage independently of CS frequency, and this shrinkage was also correlated with the behavioral improvements. Thus, the stage-dependent plasticity may commonly underlie cortical reorganization in the perceptual learning, yet the interactions of local and global plasticity have led to more complicated reorganization than previously thought. Field-specific plasticity has important implications for how each field subserves in the learning; for example, consistent with recent notions, A1 should construct filters to better identify auditory objects at the early stage, while VAF/SRAF contribute to hierarchical computation and storage at the late stage. (C) 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

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