Literature DB >> 30004603

Multimodal cortical and hippocampal prediction of episodic-memory plasticity in young and older adults.

Anne Cecilie Sjøli Bråthen1, Ann-Marie Glasø de Lange1, Darius A Rohani1, Markus H Sneve1, Anders M Fjell1,2, Kristine B Walhovd1,2.   

Abstract

Episodic memory can be trained in both early and late adulthood, but there is considerable variation in cognitive improvement across individuals. Which brain characteristics make some individuals benefit more than others? We used a multimodal approach to investigate whether volumetric magnetic resonance imaging (MRI) and resting-state functional MRI characteristics of the cortex and hippocampus, brain regions involved in episodic-memory function, were predictive of cognitive improvement after memory training. We hypothesized that these brain characteristics would differentially predict memory improvement in young and older adults, given the vulnerability of cortical regions as well as the hippocampus to healthy aging. Following structural and resting-state activity magnetic resonance scans, 50 young and 76 older participants completed 10 weeks of strategic episodic-memory training. Both age groups improved their memory performance, but the young adults more so than the older. Vertex-wise analyses of cortical volume showed no significant relation to memory benefit. When analyzing the two age groups separately, hippocampal volume was predictive of memory improvement in the group of older participants only. In this age group, the lower resting-state activity of the hippocampus was also predictive of memory improvement. Both volumetric and resting-state characteristics of the hippocampus explained unique variance of the improvement in the older participants suggesting that a multimodal imaging approach is valuable for the understanding of mechanisms underlying memory plasticity in aging.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  cognitive plasticity; cortex; episodic memory; hippocampus; memory training; multimodal

Mesh:

Year:  2018        PMID: 30004603      PMCID: PMC6866451          DOI: 10.1002/hbm.24287

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


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