Journal
NEUROIMAGE
Volume 83, Issue -, Pages 809-816Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2013.07.033
Keywords
Transcranial magnetic stimulation; Resting motor threshold; Paired associative stimulation; Diffusion tensor imaging; Cortical thickness
Funding
- Deutsche Forschungsgemeinschaft [FI-379-8/1
- 379-10/1, DFG-Exc-257]
- Bundesministerium fur Bildung und Forschung [FKZ0315673A, 01EO0801, 01GY1144]
- Else-Kroner Fresenius Stiftung [2009-141, 2011-119]
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The relationship between brain structure, cortical physiology, and learning ability in older adults is of particular interest in understanding mechanisms of age-related cognitive decline. Only a few studies addressed this issue so far, yielding mixed results. Here, we used comprehensive multiple regression analyses to investigate associations between brain structure on the one hand, i.e., cortical thickness (CT), fractional anisotropy (FA) of the pyramidal tract and individual coil-to-cortex distance, and cortical physiology on the other hand, i.e. motor cortex excitability and long-term potentiation (LTP)-like cortical plasticity, in healthy older adults (mean age 64 years, 14 women). Additional exploratory analyses assessed correlations between cortical physiology and learning ability in the verbal domain. In the regression models, we found that cortical excitability could be best predicted by Cl of the hand knob of the primary motor cortex (CT-M1(HAND)) and individual coil-to-cortex distance, while LTP-like cortical plasticity was predicted by CT-M1(HAND) and FA of the pyramidal tract. Exploratory analyses revealed a significant inverse correlation between cortical excitability and learning ability. In conclusion, higher cortical excitability was associated with lower CT and lower learning ability in a cohort of healthy older adults, in line with previous reports of increased cortical excitability in patients with cortical atrophy and cognitive deficits due to Alzheimer's Disease. Cortical excitability may thus be a parameter to identify individuals at risk for cognitive decline and gray matter atrophy, a hypothesis to be explored in future longitudinal studies. (C) 2013 Elsevier Inc. All rights reserved.
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