Humans have a remarkable ability to flexibly interact with the environment. A compelling demonstration of this cognitive flexibility is our ability to perform complex, yet previously un-practiced tasks successfully on the first attempt. We refer to this ability as ‘ad hoc self-programming’: ‘ad hoc’ because these new behavioral repertoires are cobbled together on the fly, based on immediate demand, and then discarded when no longer necessary; ‘self-programming’ because the brain has to configure itself appropriately based on task demands and some combination of prior experience and/or instruction. This type of learning differs importantly from trial-and-error learning, in which responses are sculpted incrementally, based on feedback from previous attempts. In comparison to trial-and-error learning, much less is known about ad hoc self-programmed learning, but it clearly represents a fundamental feature of human intelligence. The overall goal of our research proposal is to understand the neurophysiological and computational basis for ad hoc self-programmed behavior. To do so, we leverage critical advances in neuroscience, neurosurgery, engineering, and computational modelling, including: 1) availability of a large-scale recording platform enabling simultaneous recordings of 100+ neurons from the cortical surface; 2) opportunities to record from lateral prefrontal cortex (lPFC) in human subjects engaged in a custom-designed behavioral task; 3) developments borrowed from the artificial intelligence community to create advanced neural network models of complex cognitive processes.
We expect that this innovative approach will revolutionize our understanding of this amazing capacity for immediate, configurable learning that characterizes our everyday lives. In doing so, we will develop new strategies to study mechanisms of rapid, flexible cognitive control in general. A better understanding of human cognitive control and its nuanced capacities will naturally translate into an appreciation of deficiencies in these processes, and how they manifest in the form of neuropsychiatric disorders. This appreciation can then lead to the development of rational, targeted therapies.
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Medical Laboratory Technician33%
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