Grant: Discovery Grants Program - Individual

One of the greatest challenges facing neuroscience remains the description of how lasting memory is implemented within the brain. The search for a tractable description of episodic memory (the memory for experiences that unfold over space and time) has, for many reasons, focused on the hippocampal formation and surrounding medial temporal lobe cortices. Part of the body of evidence that makes the hippocampal formation an attractive seat for the ultimate ""indexing"" of memories is the fact that this structure receives a huge array of convergent input in every sensory modality from across the entire brain. This very convergence, however, creates unique challenges, since it is becoming increasingly clear that these various inputs are not processed equally robustly. Input from different structures arrive to the hippocampal formation at different parts of the memory system and in different gradients, creating the potential for dramatic differences in how these inputs impact the information representations of large-scale ensembles of hippocampal neurons. The multitude of functional gradients across the hippocampal memory system and how they impact information processing is only beginning to be understood. The current proposal aims to further this understanding by assessing the pattern of activity of large-scale neuronal populations using activity-related gene expression. These data will be collected across several known functional gradients (e.g., from the septal to temporal poles of the hippocampal formation as well as the perpendicular proximodistal gradient). This information will be gathered as animals react to changes in qualitatively different types of stimuli (e.g., reward magnitude, aversive stimuli, outcome probabilities, changes in spatial surroundings). Collectively, these studies will provide critical data for understanding, in general, how internal representations of experiences are dynamically maintained, processed and stored, and how they interact with sensory input.