Author: Quanjing Chen, Haichuan Yang, Brian Rooks, Mia Anthony, Zhengwu Zhang, Duje Tadin, Kathi L Heffner, Feng V Lin
1 Elaine C. Hubbard Center for Nursing Research on Aging, School of Nursing, University of Rochester Medical Center, Rochester, New York, USA.
2 Department of Psychiatry, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, New York, USA.
3 Department of Computer Science, University of Rochester, Rochester, New York, USA.
4 Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, New York, USA.
5 Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, USA.
6 Department of Neuroscience, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, New York, USA.
7 Department of Neurology, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, New York, USA.
Conference/Journal: Hum Brain Mapp
Date published: 2020 Jun 8 2020
Other: Special Notes: doi: 10.1002/hbm.25034. , Word Count: 280
Effective learning in old age, particularly in those at risk for dementia, is essential for prolonging independent living. Individual variability in learning, however, is remarkable; that is, months of cognitive training to improve learning may be beneficial for some individuals but not others. So far, little is known about which neurophysiological mechanisms account for the observed variability in learning induced by cognitive training in older adults. By combining Lövdén et al.'s (2010, A theoretical framework for the study of adult cognitive plasticity. Psychological Bulletin, 136, 659-676) framework proposing the role of adaptation capacity in neuroplasticity and a neurovisceral integration model of the relationship between autonomic nervous system (ANS) and brain with a novel shapelet analytical approach that allows for accurate and interpretable analysis of time series data, we discovered an acute, ECG-derived ANS segment in response to cognitive training tasks at baseline that predicted learning outcomes from a 6-week cognitive training intervention. The relationship between the ANS segment and learning was robust in both cross-participant and cross-task analyses among a group of older adults with amnestic mild cognitive impairment. Furthermore, the revealed ANS shapelet significantly predicted training-induced neuroplasticity in the dorsal anterior cingulate cortex and select frontal regions during task fMRI. Across outcome measures, individuals were less likely to prospectively benefit from the cognitive training if their ECG data were more similar to this particular ANS segment at baseline. Our findings are among the first empirical evidence to confirm that adaptation capacity, indexed by ANS flexibility, predicts individual differences in learning and associated neuroplasticity beyond individual characteristics (e.g., age, education, neurodegeneration, total training).
Keywords: adaptation capacity; amnestic mild cognitive impairment; anterior cingulate cortex; autonomic nervous system; learning.