The long-term goal of our research is to elucidate the cellular and circuit mechanisms of decision making and its executive control. Flexible behavior in humans and animals relies on the brain's ability to accumulate information over time, deliberate about choice options, inhibit prepotent responses, and select purposeful actions. The frontal and parietal cortices are known to be critical to decision making, but the operation of this complex cognitive network is still poorly understood at the mechanistic level. We propose that accumulation of sensory information or planned action in decision making is instantiated by neural activity of strongly recurrent circuits that can be conceptualized as attractor networks. Moreover, the time integration process is not fixed, but can be readily adjusted to optimize behavior. We will test this hypothesis using neurophysiologically-based spiking network models, in close collaboration with experimentalists. Our models will be quantitatively tested against behavioral and physiological data (single-cell and local field potential) collected from behaving monkeys in oculomotor decision tasks. Model predictions will be checked experimentally. The structure of the oculomotor system is similar in humans and monkeys, therefore the knowledge gained in our work will be likely to contribute to our understanding of human decision making. This application has four Specific Aims.
In Aim 1 we will analyze stochastic, yet correlated, reverberatory neural dynamics in a cortical circuit that underlies the slow time integration of sensory evidence and the variability of reaction times in perceptual decisions.
Aim 2 will investigate the interplay between sensory and motor processes, and inhibitory control of action, in a parieto-frontal circuit.
In Aim 3, we will examine how decision making depends on the number of choice alternatives and their similarity, and how analog decision computation leads to the readout of a categorical choice, in a large-scale circuit model encompassing cortex, basal ganglia, and superior colliculus.
Aim 4 will be focused on optimality and flexibility of decision making instantiated by reward-dependent synaptic plasticity and the concerted action of several executive control mechanisms. Taken together, the proposed research will advance, for the first time, a detailed circuit model of sensory-motor decisions in the parieto-fronto-basal ganglia network.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH062349-10
Application #
8128508
Study Section
Cognitive Neuroscience Study Section (COG)
Program Officer
Glanzman, Dennis L
Project Start
2007-09-15
Project End
2012-11-30
Budget Start
2011-09-01
Budget End
2012-11-30
Support Year
10
Fiscal Year
2011
Total Cost
$368,651
Indirect Cost
Name
Yale University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
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Wei, Wei; Wang, Xiao-Jing (2016) Downstream Effect of Ramping Neuronal Activity through Synapses with Short-Term Plasticity. Neural Comput 28:652-66
Lo, Chung-Chuan; Wang, Xiao-Jing (2016) Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task. PLoS Comput Biol 12:e1005081

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