The long-term objective of our research is to understand the computations performed by cerebral cortical circuit. Toward this end, we focus on understanding the circuitry of cat primary visual cortex (VI) and the manner in which it produces the functional response properties of cat VI neurons. We focus on can VI because it is by far the best-studied piece of cerebral cortex, and because it is part of the process of visual perception which is the sensory modality that is best understood at the cortical level. In particular, we aim to understand the functional connectivity of cat V1, that is, which neurons are connected to one another by excitatory or inhibitory synapses, as a function of the visual response properties, cortical layers of origin, and excitatory or inhibitory nature of the neurons. This will be accomplished by simultaneously recording from multiple nearby neurons using the tetrode method of recording, which allows the simultaneous isolation of multiple neurons at single recording sites. We will use cross-correlation analysis to infer which of the simultaneously recorded neurons make monosynaptic connections to one another and the sign of the connection when it exists. Evidence of an inhibitory connection simultaneously provides evidence of the excitatory of inhibitory nature, respectively, of the presynaptic neuron. We will functionally characterize the recorded neurons using a combination of traditional grating stimuli and noise stimuli. We will determine the cortical layers in which recorded neurons are located through histological analysis after the conclusion of the experiment. By studying large numbers of pairs, and determining who is connected to whom, vs. cell layers functional response properties, and excitatory or inhibitory nature of the connection, we will build up a statistical picture of the functional connectivity of cat V1. This information, in interaction with modeling of the cortical circuit, provides the basis for understanding how the function of cat V1 is created from its circuit structure. Understanding of cortical function in turn provides the basis for understanding visual disorders such as amblyopia and strabismus and neurological disorders due to stroke, and more generally for understanding normal function and its disorders such as learning disabilities.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY013595-03
Application #
6603733
Study Section
Integrative, Functional and Cognitive Neuroscience 8 (IFCN)
Program Officer
Oberdorfer, Michael
Project Start
2001-08-01
Project End
2005-06-30
Budget Start
2003-07-01
Budget End
2004-06-30
Support Year
3
Fiscal Year
2003
Total Cost
$368,750
Indirect Cost
Name
University of California San Francisco
Department
Physiology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Ziskind, Avi J; Emondi, Al A; Kurgansky, Andrei V et al. (2015) Neurons in cat V1 show significant clustering by degree of tuning. J Neurophysiol 113:2555-81
Sharpee, Tatyana O; Miller, Kenneth D; Stryker, Michael P (2008) On the importance of static nonlinearity in estimating spatiotemporal neural filters with natural stimuli. J Neurophysiol 99:2496-509
Sharpee, Tatyana O; Sugihara, Hiroki; Kurgansky, Andrei V et al. (2006) Adaptive filtering enhances information transmission in visual cortex. Nature 439:936-42
Emondi, A A; Rebrik, S P; Kurgansky, A V et al. (2004) Tracking neurons recorded from tetrodes across time. J Neurosci Methods 135:95-105
Sharpee, T; Sugihara, H; Kurgansky, A V et al. (2004) Probing feature selectivity of neurons in primary visual cortex with natural stimuli. Proc Soc Photo Opt Instrum Eng :212-222
Liu, R C; Tzonev, S; Rebrik, S et al. (2001) Variability and information in a neural code of the cat lateral geniculate nucleus. J Neurophysiol 86:2789-806