TY - JOUR T1 - Robust representation of natural images by sparse and variable population of active neurons in visual cortex JF - bioRxiv DO - 10.1101/300863 SP - 300863 AU - Takashi Yoshida AU - Kenichi Ohki Y1 - 2018/01/01 UR - http://biorxiv.org/content/early/2018/07/30/300863.abstract N2 - Natural scenes sparsely activate neurons in the primary visual cortex (V1). However, whether and how sparsely active neurons sufficiently and robustly represent natural image contents has not been revealed. We reconstructed the natural images from neuronal activities of mouse V1. Single natural images were linearly decodable from surprisingly small number (~20) of highly responsive neurons. This was achieved by diverse receptive fields (RFs) of the small number of responsive neurons. Furthermore, these neurons robustly represented the image against trial-to-trial response variability. Synchronous neurons with partially overlapping RFs formed functional clusters and were active at the same trials. Importantly, multiple clusters represented similar patterns of local images but were active at different trials. Thus, integration of activities among the clusters led to robust representation against the variability. Our results suggest that the diverse, partially overlapping RFs ensure the sparse and robust representation, and propose a new representation scheme in which information is reliably represented, while representing neuronal patterns change across trials. ER -