Neural and behavioral signatures of resource limitations in visual speed perception

Bayesian inference is an elegant theoretical framework for understanding the characteristic biases and discrimination thresholds in visual speed perception. However, the framework is difficult to validate due to its flexibility and the fact that suitable constraints on the structure of thessensory uncertainty have been missing. In this talk, I will discuss how assumptions of efficient coding, as the consequence of resource limitations, help to formulate a well constrained Bayesian observer model that not only well explains human visual speed perception but also provides an accurate quantitative account of the tuning characteristics of neurons known for representing visual motion.

Zoom details:

• Zoom Link
• Meeting ID: 889 1427 4367
• Passcode: 550611