Gene expression as a critical indicator of hippocampal function

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One of the greatest challenges facing neuroscience is to understand the cellular basis of cognition, which critically requires identifying neural activity patterns over widespread regions of the brain. Functional imaging methods (e.g., PET, fMRI) provide low spatiotemporal resolution across the brain; while microelectrode recordings provide precise resolution, but with limited sampling capabilities. What has been missing, until recently, is a method revealing functional activity during multiple epochs of behavior with cellular resolution - a problem recently solved by visualizing immediate-early genes (IEGs). When neurons engage in high frequency activity, they transcribe IEGs which are immediately visible within the nucleus. Subsequently (~30 min), the mRNA is translocated to the cytoplasm. Because mRNA can be resolved in two cellular compartments, it is possible to identify active neurons during two behavioral epochs in the same animal. Thus, like fMRI or PET, IEGs provides repeated activity measurements in the same subject, but with the cellular resolution to delineate neural networks engaged in specific behaviors. During spatial exploration, hippocampal cells fire in distinct physical locations, collectively creating an environment-specific "map" thought to establish the context of an episode to be remembered. These cells also reliably transcribe IEGs, permitting estimates of the size/consistency of place maps comparable to direct neuronal recording. Unlike direct recordings, however, IEG expression permits a limitless sample of precisely how many cells are engaged in an environment, and how the size/consistency of active populations change with the environment. Thus, the current grant capitalizes on the unique advantages of using IEG expression to (1) create estimates of how the number of active cells during (1) behavior and (2) subsequent memory-related processing change according to the physical characteristics of the environment (e.g., size/complexity of the environment) as well as (3) how these changes relate to learning. These studies provide critical data on the information that most reliably influences hippocampal activity and provide insight into the nature of the computations that define behavioral context.