A large-scale, standardized physiological survey reveals higher order coding throughout the mouse visual cortex
Saskia E. J. de VriesiD, Jérôme A. LecoqiD, Michael A. BuiceiD, Peter A. GroblewskiiD, Gabriel Koch OckeriD, Michael Oliver, David H. FengiD, Nicholas CainiD, Peter LedochowitschiD, Daniel J. MillmaniD, Kate RolliD, Marina GarrettiD, Tom Keenan, Leonard Kuan, Ştefan MihalaşiD, Shawn R. OlseniD, Carol L. ThompsoniD, Wayne WakemaniD, Jack WatersiD, Derric Williams, Chris Barber, Nathan Berbesque, Brandon Blanchard, Nicholas Bowles, Shiella CaldejoniD, , Christof Koch AiD
Abstract
To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of neural activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes cortical activity from nearly 60,000 neurons collected from 6 visual areas, 4 layers, and 12 transgenic mouse lines from 221 adult mice, in response to a systematic set of visual stimuli. Using this dataset, we reveal functional differences across these dimensions and show that visual cortical responses are sparse but correlated. Surprisingly, responses to different stimuli are largely independent, e.g. whether a neuron responds to natural scenes provides no information about whether it responds to natural movies or to gratings. We show that these phenomena cannot be explained by standard local filter-based models, but are consistent with multi-layer hierarchical computation, as found in deeper layers of standard convolutional neural networks.
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