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Why the brain appears to be noisy: rapid waking state variations and the optimal state for task performance - David McCormick
Stanford Neurosciences Institute Seminar Series Presents
Why the brain appears to be noisy: rapid waking state variations and the optimal state for task performance
David McCormick, Ph.D
Presidential Chair, Director, Institute of Neuroscience,Co-Director, Neurons to Mind Cluster of Excellence University of Oregon, Eugene, Oregon
Host: John Huguenard
What are the cellular and network mechanisms of optimal neural and behavioral performance? Through what mechanisms do spontaneous and evoked changes in the waking state influence sensory processing and behavior? The goal of my laboratory is to answer these broad and important questions at levels extending from cellular and synaptic properties, to local circuits, to thalamocortical networks, modulation, and behavior.
More than a hundred years ago, two investigators, Yerkes and Dodson, noted that optimal performance on difficult detection tasks was related to arousal level in an “inverted-U” shaped fashion. Increases from low arousal to intermediate arousal would enhance performance on difficult tasks, while further increases in arousal from intermediate to high would decrease performance. This result suggests that there is an “optimal state” for both the brain and behavior Surprisingly, the cortical activity or circuit representation of optimal state has not been thoroughly investigated. Our studies have revealed that the optimal state for performance of a difficult auditory sensory detection task occurred at intermediate levels of arousal and was associated with the suppression of slow corticocortical and thalamocortical activity, a hyperpolarized and low variability of pyramidal cell membrane potential, and large amplitude and highly reliable evoked auditory cortical synaptic responses. In an indication of the broad nature of these effects, we observed that we could predict more than half of the variance in cortical neuronal membrane potential, action potential, and even behavioral performance simply by measuring the pupil diameter – an easily obtained measure of rapid (second to second) fluctuations in behavioral state. We are now working to reveal the detailed cellular, modulatory, and network mechanisms that account for these prominent effects of state variation on neural and behavioral performance. Through a combination of state-of-the-art imaging, whole cell recording, optogenetic manipulation, and high quality behavioral monitoring, we will be able to detail the contribution of multiple neuronal and modulatory pathways to the determination of optimal state for neural/behavioral responses.