How Fast Is a Neural "Winner-Take-All" When Deciding Between Many Noisy Options?

Explore the neural mechanisms behind rapid decision-making in a lecture that delves into the speed of "Winner-Take-All" processes when faced with multiple noisy options. Examine the importance of this question in neuroscience and learn about the intrinsic complexity of decision-making circuits. Discover parallel strategies and the canonical circuit used in neural networks. Investigate stochastic winner-take-all processes and the sparsity of maximum representation. Compare alternative models and analyze the results of efficient networks. Gain insights into Hicks Law and neural responses as they relate to decision-making speed. Conclude with a comprehensive summary of the findings presented by Ila Fiete from the University of Texas at Austin in this 38-minute talk at the Simons Institute, part of the "Representation, Coding and Computation in Neural Circuits" series.

Introduction
Decisionmaking
Why is this question important
How to answer this question
Intrinsic complexity
Parallel strategy
The canonical circuit
How do things behave
Stochastic winnertakeall
Sparsity of maximum representation
Alternative model
Results
Efficient Networks
Hicks Law
Neural Responses
Summary