This project aims to achieve a fundamental advance in our understanding of how neural populations process and represent information within visual cortex. By combining pioneering recording technology with new analytical tools and theoretical frameworks, this research effort will provide the first glimpse at how large numbers of neurons interact within the cortex during the processing of dynamic natural scenes. Silicon polytrodes will be used to record simultaneously from populations of lOO-i- neurons in primary visual cortex. The activity of these populations will be characterized in terms of response precision, sparsity, correlation, and LFP coherence. In order to elucidate the causal factors that contribute to stimulus-evoked responses in the cortex, the joint activity and stimuli will be fit with predictive models that attempt to capture the stimulus-response relationships of large neuronal ensembles. Finally, we will attempt to account for these relationships by building functional models that achieve theoretically-motivated information processing objectives for perception and cognition. The project is highly interdisciplinary in nature, combining the expertise of neurophyslologists, theoreticians, and engineers to answer questions that are beyond the scope of any one discipline.

Public Health Relevance

The data obtained and models developed in this work will open a new window into the operation of cortical circuits, providing a first glimpse of the simultaneous activity of large numbers of neurons responding to dynamic natural scenes. These new insights will pave the way for the development of neural prosthetic devices (cortical implants) and new forms of treatment for visual disorders.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY019965-05
Application #
8531943
Study Section
Special Emphasis Panel (ZRG1-IFCN-B (50))
Program Officer
Steinmetz, Michael A
Project Start
2009-08-01
Project End
2014-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
5
Fiscal Year
2013
Total Cost
$299,263
Indirect Cost
$28,448
Name
University of California Berkeley
Department
None
Type
Schools of Optometry/Ophthalmol
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Köster, Urs; Sohl-Dickstein, Jascha; Gray, Charles M et al. (2014) Modeling higher-order correlations within cortical microcolumns. PLoS Comput Biol 10:e1003684
Shapero, Samuel; Zhu, Mengchen; Hasler, Jennifer et al. (2014) Optimal sparse approximation with integrate and fire neurons. Int J Neural Syst 24:1440001
Zhu, Mengchen; Rozell, Christopher J (2013) Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system. PLoS Comput Biol 9:e1003191
Herikstad, Roger; Baker, Jonathan; Lachaux, Jean-Philippe et al. (2011) Natural movies evoke spike trains with low spike time variability in cat primary visual cortex. J Neurosci 31:15844-60