tDCS reduces depression and state anxiety symptoms in older adults from the augmenting cognitive training in older adults study (ACT).

BACKGROUND: Pharmacological interventions for depression and anxiety in older adults often have significant side effects, presenting the need for more tolerable alternatives. Transcranial direct current stimulation (tDCS) is a promising non-pharmacological intervention for depression in clinical populations. However, its effects on depression and anxiety symptoms, particularly in older adults from the general public, are understudied. OBJECTIVE: We conducted a secondary analysis of the Augmenting Cognitive Training in Older Adults (ACT) trial to assess tDCS efficacy in reducing psychological symptoms in older adults. We hypothesized that active stimulation would yield greater reductions in depression and state anxiety compared to sham post-intervention and at the one-year follow-up. We also explored tDCS effects in subgroups characterized by baseline symptom severity. METHODS: A sample of 378 older adults recruited from the community completed a 12-week tDCS intervention with cognitive or education training. Electrodes were placed at F3/F4, and participants received active or sham tDCS during training sessions. We assessed the association between tDCS group and changes in depression, state anxiety, and trait anxiety from baseline to post-intervention and one-year controlling for covariates. RESULTS: The active tDCS group demonstrated greater reductions in depression and state anxiety compared to sham post-intervention, particularly in individuals with mild depression and moderate/severe state anxiety at baseline. Furthermore, the active tDCS group with moderate/severe state anxiety maintained greater symptom reductions at one-year. CONCLUSIONS: tDCS effectively reduced depression and state anxiety symptoms in a large sample of older adults. These findings highlight the importance of considering symptom severity when identifying those who may benefit most from this intervention.

Precise and Rapid Whole-Head Segmentation from Magnetic Resonance Images of Older Adults using Deep Learning.

Whole-head segmentation from Magnetic Resonance Images (MRI) establishes the foundation for individualized computational models using finite element method (FEM). This foundation paves the path for computer-aided solutions in fields, particularly in non-invasive brain stimulation. Most current automatic head segmentation tools are developed using healthy young adults. Thus, they may neglect the older population that is more prone to age-related structural decline such as brain atrophy. In this work, we present a new deep learning method called GRACE, which stands for General, Rapid, And Comprehensive whole-hEad tissue segmentation. GRACE is trained and validated on a novel dataset that consists of 177 manually corrected MR-derived reference segmentations that have undergone meticulous manual review. Each T1-weighted MRI volume is segmented into 11 tissue types, including white matter, grey matter, eyes, cerebrospinal fluid, air, blood vessel, cancellous bone, cortical bone, skin, fat, and muscle. To the best of our knowledge, this work contains the largest manually corrected dataset to date in terms of number of MRIs and segmented tissues. GRACE outperforms five freely available software tools and a traditional 3D U-Net on a five-tissue segmentation task. On this task, GRACE achieves an average Hausdorff Distance of 0.21, which exceeds the runner-up at an average Hausdorff Distance of 0.36. GRACE can segment a whole-head MRI in about 3 seconds, while the fastest software tool takes about 3 minutes. In summary, GRACE segments a spectrum of tissue types from older adults T1-MRI scans at favorable accuracy and speed. The trained GRACE model is optimized on older adult heads to enable high-precision modeling in age-related brain disorders. To support open science, the GRACE code and trained weights are made available online and open to the research community at https://github.com/lab-smile/GRACE.

Learning ratio performance on a brief visual learning and memory test moderates cognitive training gains in Double Decision task in healthy older adults.

Cognitive training using a visual speed-of-processing task, called the Useful Field of View (UFOV) task, reduced dementia risk and reduced decline in activities of daily living at a 10-year follow-up in older adults. However, there was variability in the achievement of cognitive gains after cognitive training across studies, suggesting moderating factors. Learning trials of visual and verbal learning tasks recruit similar cognitive abilities and have overlapping neural correlates with speed-of-processing/working memory tasks and therefore could serve as potential moderators of cognitive training gains. This study explored the association between the Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R) learning with a commercial UFOV task called Double Decision. Through a secondary analysis of a clinical trial, we assessed the moderation of HVLT-R and BVMT-R learning on Double Decision improvement after a 3-month speed-of-processing/attention and working memory cognitive training intervention in a sample of 75 cognitively healthy older adults. Multiple linear regressions showed that better baseline Double Decision performance was significantly associated with better BVMT-R learning (ß = - .303). This association was not significant for HVLT-R learning (ß = - .142). Moderation analysis showed that those with poorer BVMT-R learning improved the most on the Double Decision task after cognitive training. This suggests that healthy older adults who perform below expectations on cognitive tasks related to the training task may show the greatest training gains. Future cognitive training research studying visual speed-of-processing interventions should account for differing levels of visuospatial learning at baseline, as this could impact the magnitude of training outcomes and efficacy of the intervention.

Frontal-temporal regional differences in brain energy metabolism and mitochondrial function using 31P MRS in older adults.

Aging is a major risk for cognitive decline and transition to dementia. One well-known age-related change involves decreased brain efficiency and energy production, mediated in part by changes in mitochondrial function. Damaged or dysfunctional mitochondria have been implicated in the pathogenesis of age-related neurodegenerative conditions like Alzheimer's disease (AD). The aim of the current study was to investigate mitochondrial function over frontal and temporal regions in a sample of 70 cognitively normal older adults with subjective memory complaints and a first-degree family history of AD. We hypothesized cerebral mitochondrial function and energy metabolism would be greater in temporal as compared to frontal regions based on the high energy consumption in the temporal lobes (i.e., hippocampus). To test this hypothesis, we used phosphorous (31P) magnetic resonance spectroscopy (MRS) which is a non-invasive and powerful method for investigating in vivo mitochondrial function via high energy phosphates and phospholipid metabolism ratios. We used a single voxel method (left temporal and bilateral prefrontal) to achieve optimal sensitivity. Results of separate repeated measures analyses of variance showed 31P MRS ratios of static energy, energy reserve, energy consumption, energy demand, and phospholipid membrane metabolism were greater in the left temporal than bilateral prefrontal voxels. Our findings that all 31P MRS ratios were greater in temporal than bifrontal regions support our hypothesis. Future studies are needed to determine whether findings are related to cognition in older adults.

The impact of a tDCS and cognitive training intervention on task-based functional connectivity.

Declines in several cognitive domains, most notably processing speed, occur in non-pathological aging. Given the exponential growth of the older adult population, declines in cognition serve as a significant public health issue that must be addressed. Promising studies have shown that cognitive training in older adults, particularly using the useful field of view (UFOV) paradigm, can improve cognition with moderate to large effect sizes. Additionally, meta-analyses have found that transcranial direct current stimulation (tDCS), a non-invasive form of brain stimulation, can improve cognition in attention/processing speed and working memory. However, only a handful of studies have looked at concomitant tDCS and cognitive training, usually with short interventions and small sample sizes. The current study assessed the effect of a tDCS (active versus sham) and a 3-month cognitive training intervention on task-based functional connectivity during completion of the UFOV task in a large older adult sample (N = 153). We found significant increased functional connectivity between the left and right pars triangularis (the ROIs closest to the electrodes) following active, but not sham tDCS. Additionally, we see trending behavioral improvements associated with these functional connectivity changes in the active tDCS group, but not sham. Collectively, these findings suggest that tDCS and cognitive training can be an effective modulator of task-based functional connectivity above and beyond a cognitive training intervention alone.

Associations between physical exercise type, fluid intelligence, executive function, and processing speed in the oldest-old (85 +).

BACKGROUND: While much is known about the effects of physical exercise in adult humans, literature on the oldest-old (≥ 85 years old) is sparse. The present study explored the relationship between self-reported engagement in physical exercise and cognition in the oldest-old. METHODS: The sample included 184 cognitively healthy participants (98 females, MoCA mean score = 24.81) aged 85 to 99 years old (mean = 88.49 years). Participants completed the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire and a cognitive battery including NIH-TB, Coding, Symbol Search, Letter Fluency, and Stroop task. Three groups of participants - sedentary (n = 58; MoCA mean score = 24; 36 females; mean age = 89.03), cardio (n = 60; MoCA mean score = 25.08; 29 females; mean age = 88.62), and cardio + strength training (n = 66; MoCA mean score = 25.28; 33 females; mean age = 87.91) - were derived from responses on CHAMPS. RESULTS: Analyses controlled for years of education, NIH-TB Crystallized Composite, and metabolic equivalent of tasks. The cardio + strength training group had the highest cognitive performances overall and scored significantly better on Coding (p < 0.001) and Symbol Search (p < 0.05) compared to the sedentary group. The cardio + strength training group scored significantly better on Symbol Search, Letter Fluency, and Stroop Color-Word compared to the cardio group (p < 0.05). CONCLUSIONS: Our findings suggest self-reported exercise in the oldest-old is linked to better performance on cognitive measures of processing speed and executive functioning, and that there may be a synergistic effect of combining aerobic and resistance training on cognition.

Impact of electrode selection on modeling tDCS in the aging brain.

Background: Person-specific computational models can estimate transcranial direct current stimulation (tDCS) current dose delivered to the brain and predict treatment response. Artificially created electrode models derived from virtual 10-20 EEG measurements are typically included in these models as current injection and removal sites. The present study directly compares current flow models generated via artificially placed electrodes ("artificial" electrode models) against those generated using real electrodes acquired from structural MRI scans ("real" electrode models) of older adults. Methods: A total of 16 individualized head models were derived from cognitively healthy older adults (mean age = 71.8 years) who participated in an in-scanner tDCS study with an F3-F4 montage. Visible tDCS electrodes captured within the MRI scans were segmented to create the "real" electrode model. In contrast, the "artificial" electrodes were generated in ROAST. Percentage differences in current density were computed in selected regions of interest (ROIs) as examples of stimulation targets within an F3-F4 montage. Main results: We found significant inverse correlations (p < 0.001) between median current density values and brain atrophy in both electrode pipelines with slightly larger correlations found in the artificial pipeline. The percent difference (PD) of the electrode distances between the two models predicted the median current density values computed in the ROIs, gray, and white matter, with significant correlation between electrode distance PDs and current density. The correlation between PD of the contact areas and the computed median current densities in the brain was found to be non-significant. Conclusions: This study demonstrates potential discrepancies in generated current density models using real versus artificial electrode placement when applying tDCS to an older adult cohort. Our findings strongly suggest that future tDCS clinical work should consider closely monitoring and rigorously documenting electrode location during stimulation to model tDCS montages as closely as possible to actual placement. Detailed physical electrode location data may provide more precise information and thus produce more robust tDCS modeling results.

Connecting memory and functional brain networks in older adults: a resting-state fMRI study.

Limited research exists on the association between resting-state functional network connectivity in the brain and learning and memory processes in advanced age. This study examined within-network connectivity of cingulo-opercular (CON), frontoparietal control (FPCN), and default mode (DMN) networks, and verbal and visuospatial learning and memory in older adults. Across domains, we hypothesized that greater CON and FPCN connectivity would associate with better learning, and greater DMN connectivity would associate with better memory. A total of 330 healthy older adults (age range = 65-89) underwent resting-state fMRI and completed the Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R) in a randomized clinical trial. Total and delayed recall scores were assessed from baseline data, and a learning ratio calculation was applied to participants' scores. Average CON, FPCN, and DMN connectivity values were obtained with CONN Toolbox. Hierarchical regressions controlled for sex, race, ethnicity, years of education, and scanner site, as this was a multi-site study. Greater within-network CON connectivity was associated with better verbal learning (HVLT-R Total Recall, Learning Ratio), visuospatial learning (BVMT-R Total Recall), and visuospatial memory (BVMT-R Delayed Recall). Greater FPCN connectivity was associated with better visuospatial learning (BVMT-R Learning Ratio) but did not survive multiple comparison correction. DMN connectivity was not associated with these measures of learning and memory. CON may make small but unique contributions to learning and memory across domains, making it a valuable target in future longitudinal studies and interventions to attenuate memory decline. Further research is necessary to understand the role of FPCN in learning and memory.

Frontal adenosine triphosphate markers from 31P MRS are associated with cognitive performance in healthy older adults: preliminary findings.

Aging is associated with declines in mitochondrial efficiency and energy production which directly impacts the availability of adenosine triphosphate (ATP), which contains high energy phosphates critical for a variety of cellular functions. Previous phosphorous magnetic resonance spectroscopy (31P MRS) studies demonstrate cerebral ATP declines with age. The purpose of this study was to explore the functional relationships of frontal and posterior ATP levels with cognition in healthy aging. Here, we measured frontal and posterior ATP levels using 31P MRS at 3 Tesla (3 T) and assessed cognition using the Montreal Cognitive Assessment (MoCA) in 30 healthy older adults. We found that greater frontal, but not posterior, ATP levels were significantly associated with better MoCA performance. This relationship remained significant after controlling for age, sex, years of education, and brain atrophy. In conclusion, our findings indicate that cognition is related to ATP in the frontal cortex. These preliminary findings may have important implications in the search for non-invasive markers of in vivo mitochondrial function and the impact of ATP availability on cognition. Future studies are needed to confirm the functional significance of regional ATP and cognition across the lifespan.

Machine-learning defined precision tDCS for improving cognitive function.

BACKGROUND: Transcranial direct current stimulation (tDCS) paired with cognitive training (CT) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that the level of benefit from tDCS paired with CT varies from person to person, likely due to individual differences in neuroanatomical structure. OBJECTIVE: The current study aims to develop a method to objectively optimize and personalize current dosage to maximize the functional gains of non-invasive brain stimulation. METHODS: A support vector machine (SVM) model was trained to predict treatment response based on computational models of current density in a sample dataset (n = 14). Feature weights of the deployed SVM were used in a weighted Gaussian Mixture Model (GMM) to maximize the likelihood of converting tDCS non-responders to responders by finding the most optimum electrode montage and applied current intensity (optimized models). RESULTS: Current distributions optimized by the proposed SVM-GMM model demonstrated 93% voxel-wise coherence within target brain regions between the originally non-responders and responders. The optimized current distribution in original non-responders was 3.38 standard deviations closer to the current dose of responders compared to the pre-optimized models. Optimized models also achieved an average treatment response likelihood and normalized mutual information of 99.993% and 91.21%, respectively. Following tDCS dose optimization, the SVM model successfully predicted all tDCS non-responders with optimized doses as responders. CONCLUSIONS: The results of this study serve as a foundation for a custom dose optimization strategy towards precision medicine in tDCS to improve outcomes in cognitive decline remediation for older adults.

Primary outcome from the augmenting cognitive training in older adults study (ACT): A tDCS and cognitive training randomized clinical trial.

BACKGROUND: There is a need for effective interventions to stave off cognitive decline in older adults. Cognitive training has variably produced gains in untrained tasks and daily functioning. Combining cognitive training with transcranial direct current stimulation (tDCS) may augment cognitive training effects; however, this approach has yet to be tested on a large-scale. OBJECTIVE: This paper will present the primary findings of the Augmenting Cognitive Training in Older Adults (ACT) clinical trial. We hypothesize that receiving active stimulation with cognitive training will result in greater improvements on an untrained fluid cognition composite compared to sham following intervention. METHODS: 379 older adults were randomized, and 334 were included in intent-to-treat analyses for a 12-week multidomain cognitive training and tDCS intervention. Active or sham tDCS was administered at F3/F4 during cognitive training daily for two weeks then weekly for 10 weeks. To assess the tDCS effect, we fitted regression models for changes in NIH Toolbox Fluid Cognition Composite scores immediately following intervention and one year from baseline controlling for covariates and baseline scores. RESULTS: Across the entire sample, there were improvements in NIH Toolbox Fluid Cognition Composite scores immediately post-intervention and one year following baseline; however, there were no significant tDCS group effects at either timepoint. CONCLUSIONS: The ACT study models rigorous, safe administration of a combined tDCS and cognitive training intervention in a large sample of older adults. Despite potential evidence of near-transfer effects, we failed to demonstrate an additive benefit of active stimulation. Future analyses will continue to assess the intervention's efficacy by examining additional measures of cognition, functioning, mood, and neural markers.

DOMINO: Domain-aware loss for deep learning calibration.

Deep learning has achieved the state-of-the-art performance across medical imaging tasks; however, model calibration is often not considered. Uncalibrated models are potentially dangerous in high-risk applications since the user does not know when they will fail. Therefore, this paper proposes a novel domain-aware loss function to calibrate deep learning models. The proposed loss function applies a class-wise penalty based on the similarity between classes within a given target domain. Thus, the approach improves the calibration while also ensuring that the model makes less risky errors even when incorrect. The code for this software is available at https://github.com/lab-smile/DOMINO.

Change in medial frontal cerebral metabolite concentrations following bariatric surgery.

Obesity is associated with adverse effects on brain health, including an increased risk of neurodegenerative diseases. Changes in cerebral metabolism may underlie or precede structural and functional brain changes. While bariatric surgery is known to be effective in inducing weight loss and improving obesity-related medical comorbidities, few studies have examined whether it may be able to improve brain metabolism. In the present study, we examined changes in cerebral metabolite concentrations in participants with obesity who underwent bariatric surgery. Thirty-five patients with obesity (body mass index ≥ 35 kg/m2 ) were recruited from a bariatric surgery candidate nutrition class. They completed single voxel proton magnetic resonance spectroscopy at baseline (presurgery) and within 1 year postsurgery. Spectra were obtained from a large medial frontal brain region using a PRESS sequence on a 3-T Siemens Verio scanner. The acquisition parameters were TR = 3000 ms and TE = 37 ms. Tissue-corrected metabolite concentrations were determined using Osprey. Paired t-tests were used to examine within-subject change in metabolite concentrations, and correlations were used to relate these changes to other health-related outcomes, including weight loss and glycated hemoglobin (HbA1c ), a measure of blood sugar levels. Bariatric surgery was associated with a reduction in cerebral choline-containing compounds (Cho; t [34] = - 3.79, p < 0.001, d = -0.64) and myo-inositol (mI; t [34] = - 2.81, p < 0.01, d = -0.47) concentrations. There were no significant changes in N-acetyl-aspartate, creatine, or glutamate and glutamine concentrations. Reductions in Cho were associated with greater weight loss (r = 0.40, p < 0.05), and reductions in mI were associated with greater reductions in HbA1c (r = 0.44, p < 0.05). In conclusion, participants who underwent bariatric surgery exhibited reductions in cerebral Cho and mI concentrations, which were associated with improvements in weight loss and glycemic control. Given that elevated levels of Cho and mI have been implicated in neuroinflammation, reduction in these metabolites after bariatric surgery may reflect amelioration of obesity-related neuroinflammatory processes. As such, our results provide evidence that bariatric surgery may improve brain health and metabolism in individuals with obesity.

Resting-state network functional connectivity before and after bariatric surgery.

BACKGROUND: Bariatric surgery is an increasingly popular treatment for patients with severe obesity and related health issues (e.g., diabetes, cardiovascular disease). Studies have identified alterations in functional connectivity both in obesity and following surgical treatment for severe obesity. OBJECTIVE: This study aimed to assess brain function via resting-state within-network connectivity in bariatric surgery patients with severe obesity. SETTING: University hospital. METHODS: Thirty-four bariatric surgery patients completed functional neuroimaging at baseline and postoperatively (goal, 12 weeks; actual, 16 weeks, on average). They also self-reported health information. Baseline resting-state functional connectivity (RSFC) was predicted by baseline age, body mass index (BMI), continuous positive airway pressure use, and reported history of rheumatoid arthritis and type 2 diabetes. Change in RSFC was assessed using the same predictors. This model was run with and without controlling for baseline RSFC. RESULTS: Higher baseline BMI predicted lower baseline RSFC in 3 networks. Lower baseline RSFC also was related to rheumatoid arthritis and type 2 diabetes. Difference between baseline and follow-up RSFC was strongly negatively associated with baseline RSFC. Controlling for baseline RSFC, type 2 diabetes negatively predicted RSFC difference. CONCLUSIONS: RSFC may reflect brain dysfunction in patients with obesity and related diseases. That less connectivity at baseline predicted greater positive change suggests that RSFC may be a biomarker of neurocognitive improvement following bariatric surgery. Diseases more prevalent in patients with obesity (e.g., rheumatoid arthritis and type 2 diabetes) along with elevated BMI negatively affect RSFC likely through inflammatory pathways.

Validity of the NIH toolbox cognitive battery in a healthy oldest-old 85+ sample.

OBJECTIVE: To evaluate the construct validity of the NIH Toolbox Cognitive Battery (NIH TB-CB) in the healthy oldest-old (85+ years old). METHOD: Our sample from the McKnight Brain Aging Registry consists of 179 individuals, 85 to 99 years of age, screened for memory, neurological, and psychiatric disorders. Using previous research methods on a sample of 85 + y/o adults, we conducted confirmatory factor analyses on models of NIH TB-CB and same domain standard neuropsychological measures. We hypothesized the five-factor model (Reading, Vocabulary, Memory, Working Memory, and Executive/Speed) would have the best fit, consistent with younger populations. We assessed confirmatory and discriminant validity. We also evaluated demographic and computer use predictors of NIH TB-CB composite scores. RESULTS: Findings suggest the six-factor model (Vocabulary, Reading, Memory, Working Memory, Executive, and Speed) had a better fit than alternative models. NIH TB-CB tests had good convergent and discriminant validity, though tests in the executive functioning domain had high inter-correlations with other cognitive domains. Computer use was strongly associated with higher NIH TB-CB overall and fluid cognition composite scores. CONCLUSION: The NIH TB-CB is a valid assessment for the oldest-old samples, with relatively weak validity in the domain of executive functioning. Computer use's impact on composite scores could be due to the executive demands of learning to use a tablet. Strong relationships of executive function with other cognitive domains could be due to cognitive dedifferentiation. Overall, the NIH TB-CB could be useful for testing cognition in the oldest-old and the impact of aging on cognition in older populations.

Task-based functional connectivity of the Useful Field of View (UFOV) fMRI task.

Declines in processing speed performance occur in aging and are a critical marker of functional independence in older adults. Numerous studies suggest that Useful Field of View (UFOV) training may ameliorate cognitive decline in older adults. Despite its efficacy, little is known about the neural correlates of this task. The current study is the first to investigate the coherence of functional connectivity during UFOV task completion. A total of 336 participants completed the UFOV task while undergoing task-based functional magnetic resonance imaging (fMRI). Ten spherical regions of interest (ROIs), selected a priori, were created based on regions with the greatest peak BOLD activation patterns in the UFOV fMRI task and regions that have been shown to significantly relate to UFOV fMRI task performance. We used a weighted ROI-to-ROI connectivity analysis to model task-specific functional connectivity strength between these a priori selected ROIs. We found that our UFOV fMRI network was functionally connected during task performance and was significantly associated to UFOV fMRI task performance. Within-network connectivity of the UFOV fMRI network showed comparable or better predictive power in accounting for UFOV accuracy compared to 7 resting state networks, delineated by Yeo and colleagues. Finally, we demonstrate that the within-network connectivity of UFOV fMRI task accounted for scores on a measure of "near transfer", the Double Decision task, better than the aforementioned resting state networks. Our data elucidate functional connectivity patterns of the UFOV fMRI task. This may assist in future targeted interventions that aim to improve synchronicity within the UFOV fMRI network.

Effects of Prefrontal Transcranial Direct Current Stimulation on Retention of Performance Gains on an Obstacle Negotiation Task in Older Adults.

OBJECTIVES: Complex walking in older adults can be improved with task practice and might be further enhanced by pairing transcranial direct current stimulation (tDCS) to the dorsolateral prefrontal cortex. We tested the hypothesis that a single session of practice of a complex obstacle negotiation task paired with active tDCS in older adults would produce greater within-session improvements in walking performance and retention of gains, compared to sham tDCS and no tDCS conditions. MATERIALS AND METHODS: A total of 50 older adults (mean age = 74.46 years ± 6.49) with self-reported walking difficulty were randomized to receive either active tDCS (active-tDCS group) or sham tDCS (sham-tDCS group) bilaterally to the dorsolateral prefrontal cortex or no tDCS (no-tDCS group). Each group performed ten practice trials of an obstacle negotiation task at their fastest safe speed. Retention of gains in walking performance was assessed with three trials conducted one week later. Within-session effects of practice and between-session retention effects on obstacle negotiation speed were examined. RESULTS: At the practice session, all three groups exhibited significant within-session gains in walking speed (p ≤ 0.005). However, the gains were significantly greater in the sham-tDCS group than in the active-tDCS and no-tDCS groups (p ≤ 0.03) and were comparable between the active-tDCS and no-tDCS groups (p = 0.89). At one-week follow-up, the active-tDCS group exhibited significant between-session retention of gains and continued "offline" improvement in walking speed (p = 0.005). The active-tDCS group showed significantly greater retention of gains than the no-tDCS (p = 0.02) but not the sham-tDCS group (p = 0.24). CONCLUSIONS: Pairing prefrontal active tDCS with a single session of obstacle negotiation practice may enhance one-week retention of gains in walking performance compared to no tDCS. However, the evidence is insufficient to suggest a benefit of active tDCS over sham tDCS for enhancing the gains in walking performance. Additional studies with a multisession intervention design and larger sample size are needed to further investigate these findings. CLINICAL TRIAL REGISTRATION: The Clinicaltrials.gov registration number for the study is NCT03122236.

The longitudinal impact of the COVID-19 pandemic on health behaviors, psychosocial factors, and cognitive functioning in older adults.

Background: Older adults are at a greater risk for contracting and experiencing severe illness from COVID-19 and may be further affected by pandemic-related precautions (e.g., social distancing and isolation in quarantine). However, the longitudinal impact of the COVID-19 pandemic on older adults is unclear. The current study examines changes in health behaviors, psychosocial factors, and cognitive functioning in a large sample of older adults using a pre-pandemic baseline and longitudinal follow-up throughout 9 months of the COVID-19 pandemic. Methods: One hundred and eighty-nine older adults (ages 65-89) were recruited from a multisite clinical trial to complete additional virtual assessments during the COVID-19 pandemic. Mixed effects models evaluated changes in health behaviors, psychosocial factors, and cognitive functioning during the pandemic compared to a pre-pandemic baseline and over the course of the pandemic (i.e., comparing the first and last COVID-19 timepoints). Results: Compared to their pre-pandemic baseline, during the pandemic, older adults reported worsened sleep quality, perceived physical health and functioning, mental health, slight increases in depression and apathy symptoms, reduced social engagement/perceived social support, but demonstrated better performance on objective cognitive tasks of attention and working memory. Throughout the course of the pandemic, these older adults reported continued worsening of perceived physical health and function, fewer depression symptoms, and they demonstrated improved cognitive performance. It is important to note that changes on self-report mood measures and cognitive performance were relatively small regarding clinical significance. Education largely served as a protective factor, such that greater years of education was generally associated with better outcomes across domains. Conclusions: The present study provides insights into the longitudinal impact of the COVID-19 pandemic on health behaviors, psychosocial factors, and cognitive functioning in a population disproportionately affected by the virus. Replicating this study design in a demographically representative older adult sample is warranted to further inform intervention strategies targeting older adults negatively impacted by the COVID-19 pandemic.

The Preventing Alzheimer's with Cognitive Training (PACT) randomized clinical trial.

BACKGROUND: To address the rising prevalence of Alzheimer's disease and related dementias, effective interventions that can be widely disseminated are warranted. The Preventing Alzheimer's with Cognitive Training study (PACT) investigates a commercially available computerized cognitive training program targeting improved Useful Field of View Training (UFOVT) performance. The primary goal is to test the effectiveness of UFOVT to reduce incidence of clinically defined mild cognitive impairment (MCI) or dementia with a secondary objective to examine if effects are moderated by plasma ß-amyloid level or apolipoprotein E e4 (APOE e4) allele status. METHODS/DESIGN: This multisite study utilizes a randomized, controlled experimental design with blinded assessors and investigators. Individuals who are 65 years of age and older are recruited from the community. Eligible participants who demonstrate intact cognitive status (Montreal Cognitive Assessment score > 25) are randomized and asked to complete 45 sessions of either a commercially available computerized-cognitive training program (UFOVT) or computerized games across 2.5 years. After three years, participants are screened for cognitive decline. For those demonstrating decline or who are part of a random subsample, a comprehensive neuropsychological assessment is completed. Those who perform below a pre-specified level are asked to complete a clinical evaluation, including an MRI, to ascertain clinical diagnosis of normal cognition, MCI, or dementia. Participants are asked to provide blood samples for analyses of Alzheimer's disease related biomarkers. DISCUSSION: The PACT study addresses the rapidly increasing prevalence of dementia. Computerized cognitive training may provide a non-pharmaceutical option for reducing incidence of MCI or dementia to improve public health. REGISTRATION: The PACT study is registered at http://Clinicaltrials.govNCT03848312.