Topological insights into the neural basis of flexible behavior

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 120; no. 24; p. e2219557120
• Main Authors: Rouse, Tevin C., Ni, Amy M., Huang, Chengcheng, Cohen, Marlene R.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 13.06.2023
• Subjects: Biological computing; Biological Sciences; Brain - physiology; Change detection; Cognition; Cognition - physiology; Cognitive ability; Control theory; Data analysis; Humans; Network control; Neurons - physiology; Topology; Visual stimuli; Visual tasks; visual attention; computational neuroscience; neurophysiology; topological data analysis
• ISSN: 0027-8424; 1091-6490; 1091-6490
• DOI: 10.1073/pnas.2219557120

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.