%0 Generic %D 2015 %T Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM) %A Michael Buice %A Saskia de Vries %E Amy Bernard %E Brandon Rogeres %E Casey White %E Chinh Dang %E Pete Groblewski %E Chris Lau %E Cliff Slaughterbeck %E Colin Farrell %E Derric Williams %E Jack Waters %E Jed Perkins %E Kate Roll %E Leonard Kuan %E Lydia Ng %E Marina Garrett %E Natalia Orlova %E Shawn Olsen %E Sissy Cross %E Stefan Mihalas %E Thomas Keenan %E Wayne Wakeman %E John Phillips %E Christof Koch %E Clay Reid %X

The Cortical Activity Map will provide neural responses from large sets of simultaneously recorded cells to a diverse set of visual stimuli from awake, behaving mice in multiple layers, regions, and cell types. This data set allows for unprecedented access to population responses and provides a unique opportunity to explore the collective characteristics of neural dynamics. The visual stimuli for CAM include gratings, sparse noise, spatio-temporal noise, simple objects, natural images, and natural movies. We demonstrate the power of this data set by exploring the nature of population coding in the visual system. To assess information processing across visual areas we develop decoders. We analyze and compare the performance of these decoders for each stimulus type. In particular, we compare the performance of correlation based decoders and those with functional connectivity to independent decoders. For more complex stimuli, we use these models as the basis for reconstruction of the visual stimulus. This set of analyses demonstrates that the Cortical Activity Map will be a powerful tool for exploring the joint activity of large populations of neurons.

%B Society for Neuroscience 2015 %8 09/19/2015 %9 Poster