Network and dendritic mechanisms of context-dependent cortical computation

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Many disorders including schizophrenia, Parkinson's disease, and Alzheimer's disease are being studied in-depth on the cellular and molecular level, and considerable progress has been made on how they change synaptic transmission and single neuron function. However, how cellular-level neuronal function translates to disruptions in larger-scale network function and cognition is not well understood. A key link between cellular function and behavior is the integration of synaptic inputs in the dendrites of neurons, which can give each individual neuron its own computational mechanisms that in turn shape the computations performed by networks of neurons. Efforts to study how sub-cellular dendritic function contributes to brain function and behavior, especially via the associative cortices involved in higher-level cognition, have been challenging, due to two major barriers. First, in rodents, the behaviors that engage associative cortices are incompatible with head fixation, limiting our ability to measure dendritic signals during complex behavior. Second, interpreting data from natural behaviors is computationally and conceptually hard: sensory encoding can be understood by averaging hundreds of trial repetitions, but studying decision-making in this manner makes animals memorize simple and stable stimulus-response associations, which do not require associative cortices in the same manner. This proposal will use new approaches that overcome these issues to examine the contributions of dendritic and network computation in a complex associative behavior. This project exploits a novel approach for cellular-level imaging in free behavior, and a task that requires animals to perform associative computations but is easy to train. The candidate has expertise in systems neuroscience, electrophysiology, calcium imaging, and engineering, providing a strong foundation for this program. The K99 will provide training in dendritic physiology, and the computational methods required for linking complex tasks to the activity of individual neurons and networks of neurons despite variability in behavior. The primary mentor Dr. Mark Harnett will provide mentorship in dendritic function and methods for studying subcellular computation. The co- mentor Dr. Ila Fiete will provide training in computational methods relevant to the task. Additional advice from Dr. Mehrdad Jazayeri on modeling population dynamics and Dr. Cengiz Pehlevan on the mathematical properties of the underlying computations will ensure high-level training in all relevant scientific approaches. This training will enable the candidate to complete these aims and to develop an independent research program focused on neural computations underlying complex natural behaviors. The results of this research will provide new insight into how cellular computations contribute to complex behaviors, which will be important for understanding disorders with non-trivial behavioral phenotypes that are not easily studied in classical rodent behavior, such as dementia and schizophrenia.