Title: On k-Winners-Take-All as a Model of Neuron Communication

Date: Monday, November 24, 2025

Time: 9:00AM- 11:00 AM ET

Location: Hybrid, Klaus Advanced Computing Building 1120A

Zoom: https://gatech.zoom.us/j/92075978467

Mirabel Reid

Ph.D. Candidate

School of Computer Science

College of Computing

Georgia Institute of Technology

Committee:

Dr. Santosh Vempala (advisor) -  School of Computer Science, Georgia Institute of Technology

Dr. Debankur Mukherjee - School of Industrial and Systems Engineering, Georgia Institute of Technology

Dr. Will Perkins - School of Computer Science, Georgia Institute of Technology

Dr. Dana Randall, School of Computer Science, Georgia Institute of Technology

Dr. Angela Yu, Department of Human Sciences, Technische Universität Darmstadt

Abstract: Understanding how local interactions between neurons give rise to high-level structures in the brain is one of the key open questions in neuroscience. This thesis investigates discrete-time, weighted digraph models of the connectome, which not only provide insight into biological neural networks, but also form the backbone of modern artificial neural networks. The primary model of interest is the k-cap process, a recurrent neural network employing k-winners-take-all (k-WTA) as a nonlinear gating function; this mechanism models firing rate regulation via global lateral inhibition. By exploring the computational properties arising from this model, this work aims to offer insights into the emergence of structures in the connectome.