Age differences in functional network reconfiguration with working memory training
dc.contributor.author | Iordan, Alexandru D. | |
dc.contributor.author | Moored, Kyle D. | |
dc.contributor.author | Katz, Benjamin | |
dc.contributor.author | Cooke, Katherine A. | |
dc.contributor.author | Buschkuehl, Martin | |
dc.contributor.author | Jaeggi, Susanne M. | |
dc.contributor.author | Polk, Thad A. | |
dc.contributor.author | Peltier, Scott J. | |
dc.contributor.author | Jonides, John | |
dc.contributor.author | Reuter‐lorenz, Patricia A. | |
dc.date.accessioned | 2021-04-06T02:10:09Z | |
dc.date.available | 2022-05-05 22:10:06 | en |
dc.date.available | 2021-04-06T02:10:09Z | |
dc.date.issued | 2021-04-15 | |
dc.identifier.citation | Iordan, Alexandru D.; Moored, Kyle D.; Katz, Benjamin; Cooke, Katherine A.; Buschkuehl, Martin; Jaeggi, Susanne M.; Polk, Thad A.; Peltier, Scott J.; Jonides, John; Reuter‐lorenz, Patricia A. (2021). "Age differences in functional network reconfiguration with working memory training." Human Brain Mapping 42(6): 1888-1909. | |
dc.identifier.issn | 1065-9471 | |
dc.identifier.issn | 1097-0193 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/167029 | |
dc.description.abstract | Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10- days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task- related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default- mode network for younger adults, it enhanced efficiency within a task- specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default- mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between- network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age- related trajectories in functional network reorganization with WM training.We examined how working memory (WM) training affects the integration and modularity of functional networks in older and younger adults. Younger adults increase network segregation with training, suggesting more automated processing. Older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age- related trajectories in functional network reorganization with WM training. | |
dc.publisher | John Wiley & Sons, Inc. | |
dc.subject.other | graph theory | |
dc.subject.other | intrinsic activity | |
dc.subject.other | participation coefficient | |
dc.subject.other | Sternberg task | |
dc.subject.other | task- related connectivity | |
dc.subject.other | cingulo- opercular network | |
dc.subject.other | global efficiency | |
dc.title | Age differences in functional network reconfiguration with working memory training | |
dc.type | Article | |
dc.rights.robots | IndexNoFollow | |
dc.subject.hlbsecondlevel | Neurosciences | |
dc.subject.hlbsecondlevel | Kinesiology and Sports | |
dc.subject.hlbtoplevel | Health Sciences | |
dc.description.peerreviewed | Peer Reviewed | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/167029/1/hbm25337.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/167029/2/hbm25337-sup-0001-supinfo.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/167029/3/hbm25337_am.pdf | |
dc.identifier.doi | 10.1002/hbm.25337 | |
dc.identifier.source | Human Brain Mapping | |
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