Kevin Briggman

Computational Neuroethology
The goal of the Department of Computational Neuroethology (CNE) is to develop computational models which can predict goal-directed animal behaviors.

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To acquire the data needed to build biologically plausible models, we develop and utilize a multidisciplinary range of experimental techniques. We record cellular resolution images of neuronal populations from behaving animals. In addition, we use fluorescence microscopy to identify the expression patterns of specific proteins. Finally, we reconstruct synaptic connectivity using 3D electron microscopy.

By combining these methods within individual brains, we aim to discover the relationships between the structure and function of neuronal networks driving behavior. Firstly, we want to understand how sensory stimuli are transformed in the brain to ultimately generate motor decisions. Building on this understanding, we aim to identify the sources of variability during goal-directed behaviors. To address these questions, we compare and analyze neural circuits across mammals, fish and amphibians to determine which aspects of a computation are species-specific and which generalize across species.

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