{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Letzen JE"],"funding":["NIDA NIH HHS","NHLBI NIH HHS","NINR NIH HHS","National Institutes of Health","NIH HHS"],"pagination":["581-593"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6981017"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["41(3)"],"pubmed_abstract":["Previous work suggests that sleep disruption can contribute to poor pain modulation. Here, we used experimental sleep disruption to examine the relationship between sleep disruption-induced pain sensitivity and functional connectivity (FC) of cognitive networks contributing to pain modulation. Nineteen healthy individuals underwent two counterbalanced experimental sleep conditions for one night each: uninterrupted sleep versus sleep disruption. Following each condition, participants completed functional MRI including a simple motor task and a noxious thermal stimulation task. Pain ratings and stimulus temperatures from the latter task were combined to calculate a pain sensitivity change score following sleep disruption. This change score was used as a predictor of simple motor task FC changes using bilateral executive control networks (RECN, LECN) and the default mode network (DMN) masks as seed regions of interest (ROIs). Increased pain sensitivity after sleep disruption was positively associated with increased RECN FC to ROIs within the DMN and LECN (F<sub>(4,14)</sub> = 25.28, pFDR = 0.05). However, this pain sensitivity change score did not predict FC changes using LECN and DMN masks as seeds (pFDR > 0.05). Given that only RECN FC was associated with sleep loss-induced hyperalgesia, findings suggest that cognitive networks only partially contribute to the sleep-pain dyad."],"journal":["Human brain mapping"],"pubmed_title":["Individual differences in pain sensitivity are associated with cognitive network functional connectivity following one night of experimental sleep disruption."],"pmcid":["PMC6981017"],"funding_grant_id":["NIH K23 DA035915","NIH T32 NS7020110","NIH F32 HL143941","K23 DA035915","P30 NR014131","NIH R01 DA0329922","F32 HL143941","NIH P30 NR014131"],"pubmed_authors":["Remeniuk B","Irwin MR","Letzen JE","Smith MT","Seminowicz DA","Finan PH"],"additional_accession":[]},"is_claimable":false,"name":"Individual differences in pain sensitivity are associated with cognitive network functional connectivity following one night of experimental sleep disruption.","description":"Previous work suggests that sleep disruption can contribute to poor pain modulation. Here, we used experimental sleep disruption to examine the relationship between sleep disruption-induced pain sensitivity and functional connectivity (FC) of cognitive networks contributing to pain modulation. Nineteen healthy individuals underwent two counterbalanced experimental sleep conditions for one night each: uninterrupted sleep versus sleep disruption. Following each condition, participants completed functional MRI including a simple motor task and a noxious thermal stimulation task. Pain ratings and stimulus temperatures from the latter task were combined to calculate a pain sensitivity change score following sleep disruption. This change score was used as a predictor of simple motor task FC changes using bilateral executive control networks (RECN, LECN) and the default mode network (DMN) masks as seed regions of interest (ROIs). Increased pain sensitivity after sleep disruption was positively associated with increased RECN FC to ROIs within the DMN and LECN (F<sub>(4,14)</sub> = 25.28, pFDR = 0.05). However, this pain sensitivity change score did not predict FC changes using LECN and DMN masks as seeds (pFDR > 0.05). Given that only RECN FC was associated with sleep loss-induced hyperalgesia, findings suggest that cognitive networks only partially contribute to the sleep-pain dyad.","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Feb","modification":"2024-12-03T16:33:37.334Z","creation":"2020-05-22T10:30:25Z"},"accession":"S-EPMC6981017","cross_references":{"pubmed":["31617662"],"doi":["10.1002/hbm.24824"]}}