UC Davis

Phenomenological models of neural computations have achieved considerable success within modern visual neuroscience; however, the biological details of how neurons and neural circuits might perform these computations remains considerably less well understood. One of the key components in uncovering the biological basis of particular computations is a detailed knowledge of how the response properties of pre-synaptic populations differ from their post-synaptic targets. Armed with a precise understanding of such input-output relations, candidate circuit architectures and cellular or synaptic attributes that could mediate such transformations can then be explored within computational models to generate specific predictions that can then be experimentally tested. The research projects outlined in this work aim to apply this framework to two micro-circuits within the mammalian visual system, the retinogeniculate circuit in carnivores, and the thalamo-cortical circuit in primates. Ultimately, beyond primary sensory receptors, neurons do not respond directly to external stimuli but to patterns of input from their pre-synaptic network. Thus, understanding how information is integrated and transformed across synapses is a critical step in the broader endeavor to understand how organisms sense and respond to the world around them.