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Decoding the brain state-dependent relationship between pupil dynamics and resting state fMRI signal fluctuation
Pupil dynamics serve as a physiological indicator of cognitive processes and arousal states of the brain across a diverse range of behavioral experiments. Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify...
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description | Pupil dynamics serve as a physiological indicator of cognitive processes and arousal states of the brain across a diverse range of behavioral experiments. Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil-fMRI relationships by optimizing the PCA component weighting via decoding methods. This work shows that pupil dynamics are tightly coupled with different neuromodulatory centers in different trials, presenting a novel PCA-based decoding method to study the brain state-dependent pupil-fMRI relationship. |
doi_str_mv | 10.7554/eLife.68980 |
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Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil-fMRI relationships by optimizing the PCA component weighting via decoding methods. This work shows that pupil dynamics are tightly coupled with different neuromodulatory centers in different trials, presenting a novel PCA-based decoding method to study the brain state-dependent pupil-fMRI relationship.</description><identifier>ISSN: 2050-084X</identifier><identifier>EISSN: 2050-084X</identifier><identifier>DOI: 10.7554/eLife.68980</identifier><identifier>PMID: 34463612</identifier><language>eng</language><publisher>England: eLife Science Publications, Ltd</publisher><subject>Activity patterns ; Analysis ; Anesthesia, General ; Animals ; Arousal ; Brain ; Brain - physiology ; Brain Mapping ; brain state ; Cognition ; Cognitive ability ; Correlation analysis ; decoding ; fMRI ; Functional magnetic resonance imaging ; Magnetic Resonance Imaging ; Male ; Neural Networks, Computer ; neuromodulation ; Neurons ; Neuroscience ; Pattern Recognition, Automated ; Physiological aspects ; Principal Component Analysis ; pupil ; Pupil - physiology ; Rats ; Rats, Sprague-Dawley ; Reproducibility ; Signal Processing, Computer-Assisted ; Standard deviation ; Time Factors</subject><ispartof>eLife, 2021-08, Vol.10</ispartof><rights>2021, Sobczak et al.</rights><rights>COPYRIGHT 2021 eLife Science Publications, Ltd.</rights><rights>2021, Sobczak et al. 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Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil-fMRI relationships by optimizing the PCA component weighting via decoding methods. 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Pupil diameter changes reflect brain state fluctuations driven by neuromodulatory systems. Resting-state fMRI (rs-fMRI) has been used to identify global patterns of neuronal correlation with pupil diameter changes; however, the linkage between distinct brain state-dependent activation patterns of neuromodulatory nuclei with pupil dynamics remains to be explored. Here, we identified four clusters of trials with unique activity patterns related to pupil diameter changes in anesthetized rat brains. Going beyond the typical rs-fMRI correlation analysis with pupil dynamics, we decomposed spatiotemporal patterns of rs-fMRI with principal component analysis (PCA) and characterized the cluster-specific pupil-fMRI relationships by optimizing the PCA component weighting via decoding methods. This work shows that pupil dynamics are tightly coupled with different neuromodulatory centers in different trials, presenting a novel PCA-based decoding method to study the brain state-dependent pupil-fMRI relationship.</abstract><cop>England</cop><pub>eLife Science Publications, Ltd</pub><pmid>34463612</pmid><doi>10.7554/eLife.68980</doi><orcidid>https://orcid.org/0000-0001-9169-0243</orcidid><orcidid>https://orcid.org/0000-0002-9381-3048</orcidid><orcidid>https://orcid.org/0000-0001-9890-5489</orcidid><orcidid>https://orcid.org/0000-0002-3532-1512</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Activity patterns Analysis Anesthesia, General Animals Arousal Brain Brain - physiology Brain Mapping brain state Cognition Cognitive ability Correlation analysis decoding fMRI Functional magnetic resonance imaging Magnetic Resonance Imaging Male Neural Networks, Computer neuromodulation Neurons Neuroscience Pattern Recognition, Automated Physiological aspects Principal Component Analysis pupil Pupil - physiology Rats Rats, Sprague-Dawley Reproducibility Signal Processing, Computer-Assisted Standard deviation Time Factors |
title | Decoding the brain state-dependent relationship between pupil dynamics and resting state fMRI signal fluctuation |
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