Exact linear theory of perturbation response in a space- and feature-dependent cortical circuit model

• 成果类型: Article
• 署名作者: Chau, Ho Yin; Miller, Kenneth D.; Palmigiano, Agostina
• 署名单位: Columbia University; Columbia University; Columbia University; Columbia University; University of London; University College London
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-10317
• DOI: 10.1073/pnas.2426758122
• 发表日期: 2025-07-29
• 关键词: integration; network; noise

摘要

What are the principles that govern the responses of cortical networks to their inputs and the emergence of these responses from recurrent connectivity? Recent experiments have probed these questions by measuring cortical responses to two-photon optogenetic perturbations of single cells in the mouse primary visual cortex. A robust theoretical framework is needed to determine the implications of these responses for cortical recurrence. Here, we propose a formulation of the dependence of cell-type-specific connectivity on spatial distance that yields an exact analytic solution for the linear perturbation response of a model with multiple cell types and space- and featuredependent connectivity. Importantly and unlike previous approaches, the solution is valid in regimes of strong as well as weak intracortical coupling. Analysis reveals the structure of connectivity implied by various features of single-cell perturbation responses, such as the surprisingly narrow spatial radius of nearby excitation beyond which inhibition dominates, the number of transitions between mean excitation and inhibition thereafter, and the dependence of these responses on feature preferences. Comparison of these results to existing optogenetic perturbation data yields constraints provide experimental predictions regarding the response of inhibitory neurons to singlecell perturbations and the modulation of perturbation response by neuronal gain.