“Age differences in functional network reconfiguration with working memory training”

Professor Susanne Jaeggi (right) published an article in Human Brain Mapping exploring the associations between cognitive training and aging. 
 
The title of the article is “Age differences in functional network reconfiguration with working memory training.”
 
Co-authors are Alexandru Jordan (lead author, University of Michigan), Kyle Moored (University of Pittsburgh), Benjamin Katz (University of Michigan), Katherine A. Cooke (University of Michigan), Martin Buschkuehl (MIND Research Institute), Thad A. Polk (University of Michigan), Scott J. Peltier (University of Michigan), John Jonides (University of Pennsylvania), and Patricia Reuter-Lorenz (University of Michigan)
 
Jaeggi researches training and transfer, individual differences in working memory capacity and executive control, as well as the nature of working memory limitations across the lifespan. She directs UCI's Working Memory and Plasticity Lab (WMP) at UCI. Jaeggi is a fellow of the Center for the Neurobiology of Learning and Memory and holds a courtesy appointment in the Department of Cognitive Sciences in UCI's School of Social Sciences.

​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.