Open AccessA connectivity-constrained computational account of topographic organization in primate high-level visual cortex
Author(s) -
Nicholas M. Blauch,
Marlene Behrmann,
David C. Plaut
Publication year - 2022
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2112566119
Subject(s) - visual cortex , computer science , hierarchical organization , spatial organization , hierarchy , property (philosophy) , feed forward , domain (mathematical analysis) , representation (politics) , artificial intelligence , computational model , neuroscience , biology , evolutionary biology , mathematics , mathematical analysis , market economy , philosophy , management , epistemology , control engineering , politics , political science , law , engineering , economics
Significance We introduce the Interactive Topographic Network (ITN), a computational framework for modeling cortical organization of high-level vision. Through simulations of ITN models, we demonstrate that the topographic clustering of domains in primate inferotemporal cortex may arise from the demands of visual recognition under biological constraints on the wiring cost and modulatory sign of neuronal connections. The learned organization of the model is highly specialized but not fully modular, capturing many of the properties of organization in higher-order primates. Our work is significant for cognitive neuroscience, by providing a domain-general developmental account of topographic functional specialization, and for computational neuroscience, by demonstrating how well-known biological details can be incorporated into neural network models to account for empirical findings.