EEG-fMRI fusion analysis of attention and visual working memory
Salmela, V., Guo, L., Alho, K., & Ye, C. (2023). EEG-fMRI fusion analysis of attention and visual working memory. In CCN 2023 : 2023 Conference on Cognitive Computational Neuroscience (pp. 678-680). Conference Management Services, Inc.. https://doi.org/10.32470/ccn.2023.1293-0
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2023Copyright
© Authors 2023
While the previous fMRI studies suggest that the contents of the visual working memory (VWM) are represented in a spatially widely distributed brain network and the previous EEG studies have revealed some temporal properties of the memory processes, the exact spatio-temporal dynamics of working memory processes are not yet understood. Here we used multivariate EEG-fMRI fusion analysis to combine spatially (fMRI) and temporally (EEG) precise information, separately measured (n = 29) during a cued and delayed orientation change detection. Representational dissimilarity matrices (RDMs) from EEG responses in 10 ms time bins and fMRI responses from 360 different brain regions were correlated with each other as well as with model RDMs. Both EEG and fMRI response patterns were almost fully explained by attention (left/right cue) and only minimally by memory (set size and change magnitude). EEG-fMRI fusion showed distinct temporal profiles in different regions containing sustained information and transient peaks. The results highlight the role of attentional processes during working memory tasks
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Conference on Cognitive Computational NeuroscienceIs part of publication
CCN 2023 : 2023 Conference on Cognitive Computational NeuroscienceKeywords
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https://converis.jyu.fi/converis/portal/detail/Publication/184774553
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Research Council of FinlandFunding program(s)
Postdoctoral Researcher, AoFAdditional information about funding
This work was supported by grants from the National Natural Science Foundation of China (No. 31700948), and the Academy of Finland (No. 333649 to C.Y.).License
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