Toward Personalized Cognitive Training in Older Adults: A Pilot Investigation of the Effects of Baseline Performance and Age on Cognitive Training Outcomes
Affiliations: [a] Computational Brain Research and Intervention (C-Brain) Laboratory, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| [b] Current affiliation: Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
Correspondence:
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Correspondence to: Jennifer Bruno, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA 94305-5795, USA. Tel.: +1 818 415 9119; E-mail: jenbruno@stanford.edu and Hadi Hosseini, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Rd., Stanford, CA 94305-5795, USA. Tel.: +1 650 724 2939; E-mail: hosseiny@stanford.edu.
Note: [1] These authors contributed equally to this work..
Abstract: Background:Cognitive training holds potential as a non-pharmacological intervention to decrease cognitive symptoms associated with Alzheimer’s disease (AD), but more research is needed to understand individual differences that may predict maximal training benefits. Objective:We conducted a pilot study using a six-month training regimen in healthy aging adults with no cognitive decline. We investigated the effects of baseline performance and age on training and transfer improvements. Methods:Out of 43 participants aged 65–84 years, 31 successfully completed cognitive training (BrainHQ) in one of three cognitive domains: processing speed (N = 13), inhibitory control (N = 9), or episodic memory (N = 9). We used standardized assessments to measure baseline performance and transfer effects. Results:All 31 participants improved on the cognitive training regimen and age was positively associated with training improvement (p = 0.039). The processing speed group improved significantly across many near- and far-transfer tasks. In the inhibitory control group, individuals with lower baseline performance improved more on inhibitory control and cognitive flexibility tasks. In the episodic memory group, older individuals improved most on a memory task while younger individuals improved most on an executive function far-transfer task. Conclusions:Individual differences are predictive of cognitive training gains, and the impact of individual differences on training improvements is specific to the domain of training. We provide initial insight regarding how non-pharmacological interventions can be optimized to combat the onset of cognitive decline in older adults. With future research this work can inform the design of effective cognitive interventions for delaying cognitive decline in preclinical AD.
