Topological insights into the neural basis of flexible behavior
Year: 2023
Type: article
Abstract: It is widely accepted that there is an inextricable link between neural computations, biological mechanisms, and behavior, but it is challenging to simultaneously relate all three. Here, we show that topological data analysis (TDA) provides an important bridge between these approaches to studying how brains mediate behavior. We demonstrate that cognitive processes change the topological description of the shared activity of populations of visual neurons. These topological changes constrain and distinguish between competing mechanistic models, are connected to subjects' performance on a visual change detection task, and, via a link with network control theory, reveal a tradeoff between improving sensitivity to subtle visual stimulus changes and increasing the chance that the subject will stray off task. These connections provide a blueprint for using TDA to uncover the biological and computational mechanisms by which cognition affects behavior in health and disease.
Institutions: University of Chicago, University of Pittsburgh
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Awards: CRCNS: Heterogeneous effects of cognition on perception: unique leverage on circuit mechanisms, Neuronal Population Coding: From Vision to Decision, Topological bridges between circuits, models, and behavior, G5624695289, Using multiple species, stimuli, and tasks to study the neural basis of visually guided behavior
OpenAlex ID: W4379536882