The cerebral cortex is comprised of two competing types of brain cells: inhibitory neurons tend to suppress brain activity while excitatory neurons do the opposite. This project will illuminate principles governing the balance of inhibition versus excitation. Focusing on the role of inhibition, the project will test the hypothesis that a particular intermediate level of inhibition is optimal for sensory information processing, because it places the cortex network in a special operating regime called criticality.

When inhibition is too high, cortical neurons are suppressed and act largely independently. When inhibition is too low neurons are hyperactive and act largely in unison. Neither extreme is conducive to effective information processing. However, gradually decreasing inhibition from a high level can result in an abrupt onset of correlated, intense activity among the neurons. The tipping point of this onset is called criticality. Importantly, computer models and cortex slice investigations predict that at criticality certain types of information processing are optimized. However, the potentially pivotal role of criticality in processing real sensory input in an intact sensory system remains untested. Such tests will be undertaken here in an in vitro whole-brain preparation that allows the researchers to precisely manipulate levels of global inhibition, record cortical activity with microelectrode arrays for many hours, and stimulate the retina with naturalistic images. Employing novel, statistically rigorous, multifaceted, quantitative tests of criticality, the proposed research will determine the roles of inhibition and criticality in intact cortex during visual processing. Specifically, the experiments are designed to determine whether information transfer from visual stimulus to cortical response is maximized at an intermediate level of inhibition which manifests as criticality.

This project represents the first experimental test of the hypothesized functional benefits of criticality in real sensory processing. It builds on a strong conceptual foundation combining statistical physics and computational neuroscience, and may open a new paradigm for investigating cortical visual processing in large neural networks. This new paradigm is particularly relevant in light of emerging new technologies that enable the recording of activity from thousands of neurons. From the medical perspective this contribution is significant because it is expected to illuminate the etiology of numerous brain disorders with abnormal inhibition. Finally, the project brings the excitement of research into Missouri and Arkansas high schools with teacher training and classroom presentations. Newly fostered interest in STEM research will be assessed by longitudinal measures.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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Kenneth C. Whang
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Washington University
Saint Louis
United States
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