Tracing Visual Computations from the Retina to Behavior

Introduction

Every second, millions of bits of information enter our eyes. How does the brain identify task-relevant information from this gigantic input stream? This key challenge of the visual system is tackled by substantially processing the sensory input for behavioral relevance.

Retinal Processing

Already in the retina, the front-end of the visual system, neuronal circuits extract multiple features from the environment and form up to 40 channels to the brain. So far, however, one of the basic principles underlying vision, namely how the brain processes these multiple channels from the eye, remains fundamentally unclear.

Research Focus

In this proposal, I will focus on the superior colliculus, an evolutionarily conserved retino-recipient brain area critically involved in visuomotor transformations, and solve the following problem:

1. How do neuronal circuits in mouse superior colliculus integrate retinal signals to drive behavior?

Methodology

I will implement an interdisciplinary approach that combines:

• Population imaging of neuronal activity in behaving mice
• Optogenetic manipulations
• Deep neural network modeling
• Quantitative behavioral analysis

By modeling a defined brain area all the way from the retinal input to its role in behavior in an ecological setting, I will mechanistically dissect the behavioral relevance of retinal circuits.

Expected Outcomes

My work will uncover general principles of how diverse retinal channels are represented in downstream targets, identify elemental convergence rules of feedforward retinal signals in postsynaptic neurons, and causally link retinal function to distinct behaviors.

If successful, my proposal will reveal fundamental neuronal and computational mechanisms used by the visual system to convert a complex visual input into action.

Broader Implications

My approach can be adapted to other sensory modalities, guiding the design of innovative experiments and analyses. The identified mechanisms of efficient information processing will also contribute to the development of robust neuro-inspired artificial intelligence.