1. Department of Neurobiology and Anatomy, University of Texas-Houston Medical School, Houston, Texas 77030, USA

Correspondence to: Valentin Dragoi¹ Correspondence and requests for materials should be addressed to V.D. (Email: v.dragoi@uth.tmc.edu).

Abstract

Our perception of the environment relies on the capacity of neural networks to adapt rapidly to changes in incoming stimuli^{1, 2, 3, 4}. It is increasingly being realized that the neural code is adaptive⁵, that is, sensory neurons change their responses and selectivity in a dynamic manner to match the changes in input stimuli^{1, 2, 5}. Understanding how rapid exposure, or adaptation, to a stimulus of fixed structure changes information processing by cortical networks is essential for understanding the relationship between sensory coding and behaviour^{5, 6, 7, 8}. Physiological investigations of adaptation have contributed greatly to our understanding of how individual sensory neurons change their responses to influence stimulus coding^{2, 9, 10, 11, 12}, yet whether and how adaptation affects information coding in neural populations is unknown. Here we examine how brief adaptation (on the timescale of visual fixation)^{2, 9, 10} influences the structure of interneuronal correlations and the accuracy of population coding in the macaque (Macaca mulatta) primary visual cortex (V1). We find that brief adaptation to a stimulus of fixed structure reorganizes the distribution of correlations across the entire network by selectively reducing their mean and variability. The post-adaptation changes in neuronal correlations are associated with specific, stimulus-dependent changes in the efficiency of the population code, and are consistent with changes in perceptual performance after adaptation^{2, 13, 14}. Our results have implications beyond the predictions of current theories of sensory coding, suggesting that brief adaptation improves the accuracy of population coding to optimize neuronal performance during natural viewing.