dc.contributor.author | Kim, Insub | |
dc.contributor.author | Kupers, Eline R. | |
dc.contributor.author | Lerma-Usabiaga, Garikoitz | |
dc.contributor.author | Grill-Spector, Kalanit | |
dc.date.accessioned | 2024-05-27T14:40:59Z | |
dc.date.available | 2024-05-27T14:40:59Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Insub Kim, Eline R. Kupers, Garikoitz Lerma-Usabiaga, Kalanit Grill-Spector Journal of Neuroscience 10 January 2024, 44 (2) e0803232023; DOI: 10.1523/JNEUROSCI.0803-23.2023 | es_ES |
dc.identifier.citation | Journal of Neuroscience | |
dc.identifier.issn | 0270-6474 | |
dc.identifier.uri | http://hdl.handle.net/10810/68188 | |
dc.description | Published on 10 January 2024 | es_ES |
dc.description.abstract | The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time-varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRIandanovelstimulusparadigm,wemappedspatiotemporalpRFsinindividual voxelsacrosshumanvisual cortexin 10 participants (both females and males). We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (1) from early to later areas within a visual stream, spatial and temporal windows of pRFs progressively increase in size and show greater compressive nonlinearities, (2) later visual areas show diverging spatial and temporal windows across streams, and (3) within early visual areas (V1–V3), both spatial and temporal windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses using fMRI. | es_ES |
dc.description.sponsorship | Author contributions: I.K. and K.G.-S. designed research; I.K. and E.R.K. performed research; I.K., E.R.K., and G.L.-U. contributed to the development of simulation tools; I.K. and K.G.-S. analyzed data; I.K., E.R.K., and K.G.-S. wrote the paper. All authors provided input on the manuscript. This work was supported by NIH grant R01 EY023915 to K.G.-S. G.L.-U. was supported by grants from the Spanish Ministry of Science and Innovation (IJC2020-042887-I; PID2021-123577NA-I00) and Basque Government (PIBA-2022-1-0014). We thank Won Mok Shim for providing resources for pilot data collection. We extend our thanks to Justin Gardner and Brian Wandell for fruitful discussions. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Jneurosci | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/IJC2020-042887-I | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/PID2021-123577NA-I00 | es_ES |
dc.relation | info:eu-repo/grantAgreement/GV/PIBA-2022-1-0014 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | fMRI | es_ES |
dc.subject | human visual cortex | es_ES |
dc.subject | pRF | es_ES |
dc.subject | Spatiotemporal | es_ES |
dc.title | Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | Copyright © 2023 Kim et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. | es_ES |
dc.relation.publisherversion | https://www.jneurosci.org/ | es_ES |
dc.identifier.doi | 10.1523/JNEUROSCI.0803-23.2023 | |