Large-scale calcium imaging reveals a systematic V4 map for encoding natural scenes.

Autor: Wang T; Peking University School of Life Sciences, Beijing, 100871, China.; Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China.; IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China., Lee TS; Computer Science Department and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA., Yao H; Peking University School of Life Sciences, Beijing, 100871, China.; Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China.; IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China., Hong J; Peking University School of Life Sciences, Beijing, 100871, China., Li Y; Peking University School of Life Sciences, Beijing, 100871, China.; Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China.; IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China., Jiang H; Peking University School of Life Sciences, Beijing, 100871, China.; Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China.; IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China., Andolina IM; The Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China., Tang S; Peking University School of Life Sciences, Beijing, 100871, China. tangshm@pku.edu.cn.; Peking-Tsinghua Center for Life Sciences, Beijing, 100871, China. tangshm@pku.edu.cn.; IDG/McGovern Institute for Brain Research at Peking University, Beijing, 100871, China. tangshm@pku.edu.cn.; Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China. tangshm@pku.edu.cn.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2024 Jul 30; Vol. 15 (1), pp. 6401. Date of Electronic Publication: 2024 Jul 30.
DOI: 10.1038/s41467-024-50821-z
Abstrakt: Biological visual systems have evolved to process natural scenes. A full understanding of visual cortical functions requires a comprehensive characterization of how neuronal populations in each visual area encode natural scenes. Here, we utilized widefield calcium imaging to record V4 cortical response to tens of thousands of natural images in male macaques. Using this large dataset, we developed a deep-learning digital twin of V4 that allowed us to map the natural image preferences of the neural population at 100-µm scale. This detailed map revealed a diverse set of functional domains in V4, each encoding distinct natural image features. We validated these model predictions using additional widefield imaging and single-cell resolution two-photon imaging. Feature attribution analysis revealed that these domains lie along a continuum from preferring spatially localized shape features to preferring spatially dispersed surface features. These results provide insights into the organizing principles that govern natural scene encoding in V4.
(© 2024. The Author(s).)
Databáze: MEDLINE
Externí odkaz: