Independent Component and Graph Theory Analyses Reveal Normalized Brain Networks on Resting-State Functional MRI After Working Memory Training in People With HIV

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dc.contributor.authorJia, Chunying
dc.contributor.authorLong, Qunfang
dc.contributor.authorErnst, Thomas
dc.contributor.authorShang, Yuanqi
dc.contributor.authorChang, Linda
dc.contributor.authorAdali, Tulay
dc.date.accessioned2022-11-28T18:49:22Z
dc.date.available2022-11-28T18:49:22Z
dc.date.issued2022-09-27
dc.description.abstractBackground Cognitive training may partially reverse cognitive deficits in people with HIV (PWH). Previous functional MRI (fMRI) studies demonstrate that working memory training (WMT) alters brain activity during working memory tasks, but its effects on resting brain network organization remain unknown. Purpose To test whether WMT affects PWH brain functional connectivity in resting-state fMRI (rsfMRI). Study Type Prospective. Population A total of 53 PWH (ages 50.7 ± 1.5 years, two women) and 53 HIV-seronegative controls (SN, ages 49.5 ± 1.6 years, six women). Field Strength/Sequence Axial single-shot gradient-echo echo-planar imaging at 3.0 T was performed at baseline (TL1), at 1-month (TL2), and at 6-months (TL3), after WMT. Assessment All participants had rsfMRI and clinical assessments (including neuropsychological tests) at TL1 before randomization to Cogmed WMT (adaptive training, n = 58: 28 PWH, 30 SN; nonadaptive training, n = 48: 25 PWH, 23 SN), 25 sessions over 5–8 weeks. All assessments were repeated at TL2 and at TL3. The functional connectivity estimated by independent component analysis (ICA) or graph theory (GT) metrics (eigenvector centrality, etc.) for different link densities (LDs) were compared between PWH and SN groups at TL1 and TL2. Statistical Tests Two-way analyses of variance (ANOVA) on GT metrics and two-sample t-tests on FC or GT metrics were performed. Cognitive (eg memory) measures were correlated with eigenvector centrality (eCent) using Pearson's correlations. The significance level was set at P < 0.05 after false discovery rate correction. Results The ventral default mode network (vDMN) eCent differed between PWH and SN groups at TL1 but not at TL2 (P = 0.28). In PWH, vDMN eCent changes significantly correlated with changes in the memory ability in PWH (r = −0.62 at LD = 50%) and vDMN eCent before training significantly correlated with memory performance changes (r = 0.53 at LD = 50%). Data Conclusion ICA and GT analyses showed that adaptive WMT normalized graph properties of the vDMN in PWH.en_US
dc.description.sponsorshipThis work was supported in parts by these NIH grants (R01-DA035659, R01-MH118695, and R01-EB020407) and these NSF grants (CCF 1618551 and NCS 1631838). The authors would like to thank the numerous research staff members at the University of Hawaii who contributed to the data collection for the MRI and clinical data, and the staff at the University of Maryland Baltimore for organizing and preprocessing the data. The authors also appreciate the valuable feedback from the members of Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, and Jingfeng Zhou at the National Institute on Drug Abuse Intramural Research Program.en_US
dc.description.urihttps://onlinelibrary.wiley.com/doi/10.1002/jmri.28439en_US
dc.format.extent19 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2ytah-2slb
dc.identifier.citationJia, C., Long, Q., Ernst, T., Shang, Y., Chang, L. and Adali, T. (2022), Independent Component and Graph Theory Analyses Reveal Normalized Brain Networks on Resting-State Functional MRI After Working Memory Training in People With HIV. J Magn Reson Imaging. https://doi.org/10.1002/jmri.28439en_US
dc.identifier.urihttps://doi.org/10.1002/jmri.28439
dc.identifier.urihttp://hdl.handle.net/11603/26377
dc.language.isoen_USen_US
dc.publisherWileyen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis is the peer reviewed version of the following article: Jia, C., Long, Q., Ernst, T., Shang, Y., Chang, L. and Adali, T. (2022), Independent Component and Graph Theory Analyses Reveal Normalized Brain Networks on Resting-State Functional MRI After Working Memory Training in People With HIV. J Magn Reson Imaging. https://doi.org/10.1002/jmri.28439, which has been published in final form at https://doi.org/10.1002/jmri.28439 . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.en_US
dc.rightsAccess to this item will begin on 09-27-2023
dc.titleIndependent Component and Graph Theory Analyses Reveal Normalized Brain Networks on Resting-State Functional MRI After Working Memory Training in People With HIVen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-7941-0605en_US
dcterms.creatorhttps://orcid.org/0000-0002-6323-6366en_US
dcterms.creatorhttps://orcid.org/0000-0003-0594-2796en_US

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