The basic operation of the cerebral cortex, a massively and dynamically interconnected sheet of cortical neurons and networks, depends critically on the rapid modulation of excitability of individual cells, allowing them to participate or not participate in currently active neural networks, in response to behavioral and contextual demands. This rapid gain modulation is reflected in the change in the number and timing of action potentials. Using the primary visual cortex as a model system, we will examine the synaptic and network mechanisms that control the responsiveness of cortical neurons on a moment-to-moment basis, with particular attention to naturalistic visual input (natural movies). To understand gain modulation thoroughly, we will first investigate the cellular mechanisms of the contrast response function curve, as a prototypical example of a cortical input-output relationship. These studies will examine the origins of threshold responsiveness, mid-range sensitivity, and saturation at high contrast. Once the cellular mechanisms of this prototypical relationship are understood, we will then manipulate the membrane potential, input conductance, and membrane variance of individual visual cortical neurons (as well as stimulate the non-classical receptive field) to determine how these factors affect the contrast response function curve. These gain modulation studies will be complemented with experiments designed to reveal the synaptic mechanisms that control response timing precision and variability. Visual cortical neurons respond to full field natural visual scenes (movies) with temporally precise, highly selective and unusually space action potential sequences. These responses are often not well predicted by the linear properties of cells' classical receptive fields. By recording the pattern of excitatory and inhibitory inputs arriving in visual cortical neurons during presentation of natural stimuli, we will identify the contributions of excitatory, inhibitory, and spike initiation properties to spike timing precision. By varying the size of visual stimuli (to include stimulation of the non-classical receptive field as well as the classical receptive field) while recording from V1 neurons at various membrane potentials, we will determine the relative contributions of excitatory and inhibitory events to increases in action potential selectivity and sparseness associated with responses to naturalistic stimulation. These studies will reveal fundamental mechanisms of cortical gain control, spike timing, and neuronal signaling and lead to a better and more thorough understanding of visual cortical network function and dysfunction. The cerebral cortex is the most important structure of the human brain, yet is only partially understood. We will examine the basic operating principles of the visual cortex and how it encodes information, allowing for proper behavioral function. Our studies will give fundamental information relevant to understanding not only vision, but also attention and memory. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
2R01EY012388-09
Application #
7516724
Study Section
Central Visual Processing Study Section (CVP)
Program Officer
Oberdorfer, Michael
Project Start
1999-01-01
Project End
2011-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
9
Fiscal Year
2008
Total Cost
$413,750
Indirect Cost
Name
Yale University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Casale, Amanda E; McCormick, David A (2011) Active action potential propagation but not initiation in thalamic interneuron dendrites. J Neurosci 31:18289-302
Haider, Bilal; Krause, Matthew R; Duque, Alvaro et al. (2010) Synaptic and network mechanisms of sparse and reliable visual cortical activity during nonclassical receptive field stimulation. Neuron 65:107-21
Brumberg, J C; Nowak, L G; McCormick, D A (2000) Ionic mechanisms underlying repetitive high-frequency burst firing in supragranular cortical neurons. J Neurosci 20:4829-43