Background: Working memory, a fundamental short-term cognitive process, is known to decline with advanced age even in healthy older adults. Normal agerelated declines in working memory can cause loss of independence and decreased quality of life. Cognitive training has shown some potential at enhancing certain cognitive processes, although, enhancements are variable. Transcranial direct current stimulation (tDCS), a form of non-invasive brain stimulation, has shown promise at enhancing working memory abilities, and may further the benefits from cognitive training interventions. However, the neural mechanisms underlying tDCS brain-based enhancements remain unknown. Objective/Hypothesis: Assess the effects of a 2-week intervention of active-tDCS vs. sham paired with cognitive training on functional connectivity of the working memory network during an N-Back working memory task. Methods: Healthy older adults (N = 28; mean age = 74 ± 7.3) completed 10-sessions of cognitive training paired with active or sham-tDCS. Functional connectivity was evaluated at baseline and post-intervention during an N-Back task (2-Back vs. 0-Back). Results: Active-tDCS vs. sham demonstrated a significant increase in connectivity between the left dorsolateral prefrontal cortex and right inferior parietal lobule at postintervention during 2-Back. Target accuracy on 2-Back was significantly improved for active vs. sham at post-intervention. Conclusion: These results suggest pairing tDCS with cognitive training enhances functional connectivity and working memory performance in older adults, and thus may hold promise as a method for remediating age-related cognitive decline. Future studies evaluating optimal dose and long-term effects of tDCS on brain function will help to maximize potential clinical impacts of tDCS paired with cognitive training in older adults.

Background: Varying treatment outcomes in transcranial electrical stimulation (tES) recipients may depend on the amount of current reaching the brain. Brain atrophy associated with normal aging may affect tES current delivery to the brain. Computational models have been employed to compute predicted tES current inside the brain. This study is the largest study that uses computational models to investigate tES field distribution in healthy older adults. Methods: Individualized head models from 587 healthy older adults (mean ¼ 73.9years, 51e95 years) were constructed to create field maps. Two electrode montages (F3-F4, M1-SO) with 2 mA input current were modeled using ROAST with modified codes. A customized template of healthy older adults, the UFAB-587, was created from the same dataset and used to warp individual brains into the same space. Warped models were analyzed to determine the relationship between computed field measures, brain atrophy and age. Main results: Computed field measures were inversely correlated with brain atrophy (R 2 ¼ 0.0829, p ¼ 1.14e-12). Field pattern showed negative correlation with age in brain sub-regions including part of DLPFC and precentral gyrus. Mediation analysis revealed that the negative correlation between age and current density is partially mediated by brain-to-CSF ratio. Conclusions: Computed field measures showed decreasing amount of tES current reaching the brain with increasing atrophy. Therefore, adjusting current dose by modifying tES stimulation parameters in older adults based on degree of atrophy may be necessary to achieve desired stimulation benefits. Results from this study may inform future tES application in healthy older adults.

Aging is associated with disruptions in the resting-state functional architecture of the brain. Previous studies have primarily focused on age-related declines in the default mode network (DMN) and its implications in Alzheimer's disease. However, due to mixed findings, it is unclear if changes in resting-state network functional connectivity are linked to cognitive decline in healthy older adults. In the present study, we evaluated the influence of intra-network coherence for four higher-order cognitive resting-state networks on a sensitive measure of cognitive aging (i.e., NIH Toolbox Fluid Cognition Battery) in 154 healthy older adults with a mean age of 71 and education ranging between 12 years and 21 years (mean = 16). Only coherence within the cinguloopercular network (CON) was significantly related to Fluid Cognition Composite scores, explaining more variance in scores than age and education. Furthermore, we mapped CON connectivity onto fluid cognitive subdomains that typically decline in advanced age. Greater CON connectivity was associated with better performance on episodic memory, attention, and executive function tasks. Overall, the present study provides evidence to propose CON coherence as a potential novel neural marker for nonpathological cognitive aging.

Background: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delivery to the brain can vary significantly across individuals. Quantification of this variability could enable person-specific optimization of tDCS outcomes. This pilot study used machine learning and MRI-derived electric field models to predict working memory improvements as a proof of concept for precision cognitive intervention. Methods: Fourteen healthy older adults received 20 minutes of 2 mA tDCS stimulation (F3/F4) during a two-week cognitive training intervention. Participants performed an N-back working memory task pre-/ post-intervention. MRI-derived current models were passed through a linear Support Vector Machine (SVM) learning algorithm to characterize crucial tDCS current components (intensity and direction) that induced working memory improvements in tDCS responders versus non-responders. Main results: SVM models of tDCS current components had 86% overall accuracy in classifying treatment responders vs. non-responders, with current intensity producing the best overall model differentiating changes in working memory performance. Median current intensity and direction in brain regions near the electrodes were positively related to intervention responses (r ¼ 0:811; p < 0:001 and r ¼ 0:774; p ¼ 0:001). Conclusions: This study provides the first evidence that pattern recognition analyses of MRI-derived tDCS current models can provide individual prognostic classification of tDCS treatment response with 86% accuracy. Individual differences in current intensity and direction play important roles in determining treatment response to tDCS. These findings provide important insights into mechanisms of tDCS response as well as proof of concept for future precision dosing models of tDCS intervention.

Background: Transcranial direct current stimulation (tDCS) has been proposed as a possible method for remediating age-associated cognitive decline in the older adult population. While tDCS has shown potential for improving cognitive functions in healthy older adults, stimulation outcomes on various cognitive domains have been mixed. Methods: A systematic search was performed in four databases: PubMed, EMBASE, Web of Science, and PsychInfo. Search results were then screened for eligibility based on inclusion/exclusion criteria to only include studies where tDCS was applied to improve cognition in healthy older adults 65 years and above. Eligible studies were reviewed and demographic characteristics, tDCS dose parameters, study procedures, and cognitive outcomes were extracted. Reported effect sizes for active compared to sham group in representative cognitive domain were converted to Hedges' g. Main Results: A total of thirteen studies involving healthy older adults (n=532, mean age=71.2+5.3 years) were included in the meta-analysis. The majority of included studies (94%) targeted the prefrontal cortex with stimulation intensity 1-2 mA using various electrode placements with anodes near the frontal region. Across all studies, we found Hedges' g values ranged from −0.31 to 1.85 as reported group effect sizes of active stimulation compared to sham. Conclusion: While observed outcomes varied, overall findings indicated promising effects of tDCS to remediate cognitive aging and thus deserves further exploration. Future characterization of inter-individual variability in tDCS dose response and applications in larger cohorts are warranted to further validate benefits of tDCS for cognition in healthy older adults.