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Spatially informed voxelwise modeling for naturalistic fMRI experiments

Çelik, Emin and Hassan Dar, Salman Ul and Yılmaz, Özgür and Keleş, Ümit and Çukura, Tolga (2019) Spatially informed voxelwise modeling for naturalistic fMRI experiments. NeuroImage, 186 . pp. 741-757. ISSN 1053-8119. http://resolver.caltech.edu/CaltechAUTHORS:20181128-140625360

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Abstract

Voxelwise modeling (VM) is a powerful framework to predict single voxel responses evoked by a rich set of stimulus features present in complex natural stimuli. However, because VM disregards correlations across neighboring voxels, its sensitivity in detecting functional selectivity can be diminished in the presence of high levels of measurement noise. Here, we introduce spatially-informed voxelwise modeling (SPIN-VM) to take advantage of response correlations in spatial neighborhoods of voxels. To optimally utilize shared information, SPIN-VM performs regularization across spatial neighborhoods in addition to model features, while still generating single-voxel response predictions. We demonstrated the performance of SPIN-VM on a rich dataset from a natural vision experiment. Compared to VM, SPIN-VM yields higher prediction accuracies and better capture locally congruent information representations across cortex. These results suggest that SPIN-VM offers improved performance in predicting single-voxel responses and recovering coherent information representations.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.neuroimage.2018.11.044DOIArticle
Additional Information:© 2018 Elsevier. Received 23 October 2018, Accepted 25 November 2018, Available online 28 November 2018. The authors declare no competing financial interests. We thank A. Vu, N. Bilenko, J. Gao, A. Huth, S. Nishimoto, and J.L. Gallant for assistance in various aspects of this research. The work was supported in part by a National Eye Institute Grant (EY019684), by a Marie Curie Actions Career Integration Grant (PCIG13-GA-2013-618101), by a European Molecular Biology Organization Installation Grant (IG 3028), by a TUBA GEBIP 2015 fellowship, and by a Science Academy BAGEP 2017 award.
Funders:
Funding AgencyGrant Number
NIHEY019684
Marie Curie FellowshipPCIG13-GA-2013-618101
European Molecular Biology Organization (EMBO)IG 3028
Türkiye Bilimser AkademisiUNSPECIFIED
Subject Keywords:fMRI; Voxelwise modeling; Response correlations; Coherent representation; Spatial regularization; Computational neuroscience
Record Number:CaltechAUTHORS:20181128-140625360
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181128-140625360
Official Citation:Emin Çelik, Salman Ul Hassan Dar, Özgür Yılmaz, Ümit Keleş, Tolga Çukur, Spatially informed voxelwise modeling for naturalistic fMRI experiments, NeuroImage, Volume 186, 2019, Pages 741-757, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2018.11.044. (http://www.sciencedirect.com/science/article/pii/S1053811918321256)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:91306
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:28 Nov 2018 22:38
Last Modified:10 Dec 2018 18:49

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