Given the same sensory information, we generate different responses in different situations, depending on our goal, task rule, etc. This flexibilit is a hallmark of cognition and involves gated routing of information flow in the brain circuitry, the underlying mechanism remains largely mysterious. The overarching objective of the proposed research is to elucidate computational principles and circuit basis of gated computation and flexible sensori-motor mapping in decision-making. I propose that gating is accomplished by four complementary mechanisms: (a) tunable dendritic inhibition by a subclass of GABAergic neurons for input gating, (b) """"""""pathway-specific excitation-inhibition balance"""""""" for processing in discrete stages, (c) top-down signaling from rule representation for network selection, (d) a """"""""STOP"""""""" process for inhibitory control of automatic response. I will rigorously investigate these mechanisms in biologically based circuit models, in collaboration with experimentalists who are carrying out single-neuron physiological experiments in which monkeys perform flexible visuo-motor tasks. In a paradigmatic task of controlled action, the appropriate response to a sensory target is to either shift the gaze toward it (pro-saccade) or away from it (anti-saccade) depending on task context. In """"""""colored-target"""""""" tasks, a perceptual decision about an ambiguous stimulus or a probabilistic inference based on sensory cues must be made, before the subject knows when and how the decision will be used to guide action selection. Our model will be tested by quantitatively reproducing single-neuron activity data as well as behavioral performance, and uncovering the underlying circuit mechanisms that will be testable in new experiments.
In Aim 1, I will examine circuit mechanisms for gating, including input-specific dendritic inhibition and the idea of """"""""pathway-specific excitation-inhibition balance.
Aim 2 will be devoted to rule-based action selection, by developing a detailed circuit model of the pro-/anti-saccade task.
In Aim 3, I will examine gated neural dynamics when perceptual decision and action selection are temporally separated. We will build spiking network models for versions of the random dot motion direction discrimination task and weather prediction task. The pro-/anti-saccade and colored-target visuo-motor tasks all depend on flexible routing of information from a sensory decision circuit to an action selection circuit, which confers a strong cohesiveness to this application. This research program will shed insights into complex dynamics of neurons endowed with mixed selectivity that underlie adaptive coding in flexible behavior.

Public Health Relevance

Impaired behavioral flexibility and executive control are robust characteristics of schizophrenic and ADHD patients. The parieto-frontal circuitry has been demonstrated to be critical for decision-making and inhibitory control of action, both in human imaging studies and animal physiological experiments. However, we still do not understand core computations and their underlying mechanisms. Brain circuit modeling proposed in this application, with a focus on the parieto-frontal system, will elucidate gating mechanisms that underlie flexible visuo-motor behavior. It will be capable of accounting for single-neuron data and performance data from behaving animals, and provide a platform to elucidate the brain circuit mechanisms of different types of behavioral errors observed in humans. By uncovering the required biological mechanisms for flexible behavior, our work has a high potential for understanding molecular and circuit abnormalities that cause these cognitive deficits associated with mental illness like Schizophrenia and ADHD.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Sensorimotor Integration Study Section (SMI)
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Glanzman, Dennis L
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New York University
Schools of Arts and Sciences
New York
United States
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Chaisangmongkon, Warasinee; Swaminathan, Sruthi K; Freedman, David J et al. (2017) Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions. Neuron 93:1504-1517.e4
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