Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex
Name
Rikhye-2015-Spatial Correlations.pdf
Size
5.88 MB
Format
Adobe PDF
Checksum (MD5)
b7764f041cd5542c0a1722fb5648c316
Author(s)
Rikhye, Rajeev Vijay
Sur, Mriganka
Date Issued
October 2015
Journal
Journal of Neuroscience
Publisher
Society for Neuroscience
Citation
Rikhye, R. V., and M. Sur. “Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex.” Journal of Neuroscience 35, no. 43 (October 28, 2015): 14661–14680.
Version
Final published version
Abstract
Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). Certain stimuli can suppress this intertrial variability to increase the reliability of neuronal responses. In particular, responses to natural scenes, which have broadband spatiotemporal statistics, are more reliable than responses to stimuli such as gratings. However, very little is known about which stimulus statistics modulate reliable coding and how this occurs at the neural ensemble level. Here, we sought to elucidate the role that spatial correlations in natural scenes play in reliable coding. We developed a novel noise-masking method to systematically alter spatial correlations in natural movies, without altering their edge structure. Using high-speed two-photon calcium imaging in vivo, we found that responses in mouse V1 were much less reliable at both the single neuron and population level when spatial correlations were removed from the image. This change in reliability was due to a reorganization of between-neuron correlations. Strongly correlated neurons formed ensembles that reliably and accurately encoded visual stimuli, whereas reducing spatial correlations reduced the activation of these ensembles, leading to an unreliable code. Together with an ensemble-specific normalization model, these results suggest that the coordinated activation of specific subsets of neurons underlies the reliable coding of natural scenes.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Picower Institute for Learning and Memory
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.1523/jneurosci.1660-15.2015
