There is a need to develop tools that facilitate knowledge sharing and cooperation among researchers, institutions, and countries around the world, especially concerning global, transboundary, and long-term climate impacts. The IPCC report aims to achieve this goal, and emphasizes that digitization of global maps, centralization of multidisciplinary results, and further sorting and simplification of data products are necessary to make the immense amount of information accessible to broader communities. To this end, we build a new digital atlas useful for training the future generation of climate scientists, for academic collaboration, and as a first stop in intergovernmental conversations.

Climate change is a significant threat to humanity, and its impacts on natural and human systems have already been observed. Climate action requires both global and local cooperation and needs to be approached together with other world crises in a transformative, systemic, and holistic way, prioritizing long-term human and ecological well-being and short-term targeted action. Bridging the gap between climate scientists, educators, and decision-makers is crucial, which requires a multidisciplinary approach, meaningful collaboration tools, practical simplification, and visualization of research output data, and more effective communication. To address some of these challenges in communication for decision-making, as well as challenges in multidisciplinary climate teaching and research, we built a new digital atlas called the Perry World House Global Climate Security Atlas. Researchers, teachers, and policymakers are encouraged to use the Atlas to visualize global information on physical climate projections, environmental, and ecological data, as well as information on human, social, and political systems. In this paper, we motivate the need for the Atlas and summarize its potential uses, provide a summary description of the datasets, and offer suggestions on how to bridge the gap between science and policymaking.

A new interactive Atlas that brings together global, transboundary, multidisciplinary, and long-term climate impacts.

Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables.

Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants.

Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls.

Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.

Cognitive training is a non-pharmacological intervention aimed at improving cognitive function across a single or multiple domains. Although the underlying mechanisms of cognitive training and transfer effects are not well-characterized, cognitive training has been thought to facilitate neural plasticity to enhance cognitive performance. Indeed, the Scaffolding Theory of Aging and Cognition (STAC) proposes that cognitive training may enhance the ability to engage in compensatory scaffolding to meet task demands and maintain cognitive performance. We therefore evaluated the effects of cognitive training on working memory performance in older adults without dementia. This study will help begin to elucidate non-pharmacological intervention effects on compensatory scaffolding in older adults.

48 participants were recruited for a Phase III randomized clinical trial (Augmenting Cognitive Training in Older Adults [ACT]; NIH R01AG054077) conducted at the University of Florida and University of Arizona. Participants across sites were randomly assigned to complete cognitive training (n=25) or an education training control condition (n=23). Cognitive training and the education training control condition were each completed during 60 sessions over 12 weeks for 40 hours total. The education training control condition involved viewing educational videos produced by the National Geographic Channel. Cognitive training was completed using the Posit Science Brain HQ training program, which included 8 cognitive training paradigms targeting attention/processing speed and working memory. All participants also completed demographic questionnaires, cognitive testing, and an fMRI 2-back task at baseline and at 12-weeks following cognitive training.

Repeated measures analysis of covariance (ANCOVA), adjusted for training adherence, transcranial direct current stimulation (tDCS) condition, age, sex, years of education, and Wechsler Test of Adult Reading (WTAR) raw score, revealed a significant 2-back by training group interaction (F[1,40]=6.201, p=.017, η2=.134). Examination of simple main effects revealed baseline differences in 2-back performance (F[1,40]=.568, p=.455, η2=.014). After controlling for baseline performance, training group differences in 2-back performance was no longer statistically significant (F[1,40]=1.382, p=.247, η2=.034).

After adjusting for baseline performance differences, there were no significant training group differences in 2-back performance, suggesting that the randomization was not sufficient to ensure adequate distribution of participants across groups. Results may indicate that cognitive training alone is not sufficient for significant improvement in working memory performance on a near transfer task. Additional improvement may occur with the next phase of this clinical trial, such that tDCS augments the effects of cognitive training and results in enhanced compensatory scaffolding even within this high performing cohort. Limitations of the study include a highly educated sample with higher literacy levels and the small sample size was not powered for transfer effects analysis. Future analyses will include evaluation of the combined intervention effects of a cognitive training and tDCS on nback performance in a larger sample of older adults without dementia.

Traumatic brain injury is one of several recognized risk factors for cognitive decline and neurodegenerative disease. Currently, risk scores involving modifiable risk/protective factors for dementia have not incorporated head injury history as part of their overall weighted risk calculation. We investigated the association between the LIfestyle for BRAin Health (LIBRA) risk score with odds of mild cognitive impairment (MCI) diagnosis and cognitive function in older former National Football League (NFL) players, both with and without the influence of concussion history.

Former NFL players, ages ≥ 50 (N=1050; mean age=61.1±5.4-years), completed a general health survey including self-reported medical history and ratings of function across several domains. LIBRA factors (weighted value) included cardiovascular disease (+1.0), hypertension (+1.6), hyperlipidemia (+1.4), diabetes (+1.3), kidney disease (+1.1), cigarette use history (+1.5), obesity (+1.6), depression (+2.1), social/cognitive activity (-3.2), physical inactivity (+1.1), low/moderate alcohol use (-1.0), healthy diet (-1.7). Within Group 1 (n=761), logistic regression models assessed the association of LIBRA scores and independent contribution of concussion history with the odds of MCI diagnosis. A modified-LIBRA score incorporated concussion history at the level planned contrasts showed significant associations across concussion history groups (0, 1-2, 3-5, 6-9, 10+). The weighted value for concussion history (+1.9) within the modified-LIBRA score was based on its proportional contribution to dementia relative to other LIBRA risk factors, as proposed by the 2020 Lancet Commission Report on Dementia Prevention. Associations of the modified-LIBRA score with odds of MCI and cognitive function were assessed via logistic and linear regression, respectively, in a subset of the sample (Group 2; n=289) who also completed the Brief Test of Adult Cognition by Telephone (BTACT). Race was included as a covariate in all models.

The median LIBRA score in the Group 1 was 1.6(IQR= -1, 3.6). Standard and modified-LIBRA median scores were 1.1(IQR= -1.3, 3.3) and 2(IQR= -0.4, 4.6), respectively, within Group 2. In Group 1, LIBRA score was significantly associated with odds of MCI diagnosis (odds ratio[95% confidence interval]=1.27[1.19, 1.28], p <.001). Concussion history provided additional information beyond LIBRA scores and was independently associated with odds of MCI; specifically, odds of MCI were higher among those with 6-9 (Odds Ratio[95% confidence interval]; OR=2.54[1.21, 5.32], p<.001), and 10+ (OR=4.55;[2.21, 9.36], p<.001) concussions, compared with those with no prior concussions. Within Group 2, the modified-LIBRA score was associated with higher odds of MCI (OR=1.61[1.15, 2.25]), and incrementally improved model information (0.04 increase in Nagelkerke R2) above standard LIBRA scores in the same model. Modified-LIBRA scores were inversely associated with BTACT Executive Function (B=-0.53[0.08], p=.002) and Episodic Memory scores (B=-0.53[0.08], p=.002).

Numerous modifiable risk/protective factors for dementia are reported in former professional football players, but incorporating concussion history may aid the multifactorial appraisal of cognitive decline risk and identification of areas for prevention and intervention. Integration of multi-modal biomarkers will advance this person-centered, holistic approach toward dementia reduction, detection, and intervention.

It has been posited that alcohol use may confound the association between greater concussion history and poorer neurobehavioral functioning. However, while greater alcohol use is positively correlated with neurobehavioral difficulties, the association between alcohol use and concussion history is not well understood. Therefore, this study investigated the cross-sectional and longitudinal associations between cumulative concussion history, years of contact sport participation, and health-related/psychological factors with alcohol use in former professional football players across multiple decades.

Former professional American football players completed general health questionnaires in 2001 and 2019, including demographic information, football history, concussion/medical history, and health-related/psychological functioning. Alcohol use frequency and amount was reported for three timepoints: during professional career (collected retrospectively in 2001), 2001, and 2019. During professional career and 2001 alcohol use frequency included none, 1-2, 3-4, 5-7 days/week, while amount included none, 12, 3-5, 6-7, 8+ drinks/occasion. For 2019, frequency included never, monthly or less, 2-4 times/month, 2-3 times/week, >4 times/week, while amount included none, 1-2, 3-4, 5-6, 7-9, 10+ drinks/occasion. Scores on a screening measure for Alcohol Use Disorder (CAGE) were also available at during professional career and 2001 timepoints. Concussion history was recorded in 2001 and binned into five groups: 0, 1-2, 3-5, 6-9, 10+. Depression and pain interference were assessed via PROMIS measures at all timepoints. Sleep disturbance was assessed in 2001 via separate instrument and with PROMIS Sleep Disturbance in 2019. Spearman’s rho correlations tested associations between concussion history and years of sport participation with alcohol use across timepoints, and whether poor health functioning (depression, pain interference, sleep disturbance) in 2001 and 2019 were associated with alcohol use both within and between timepoints.

Among the 351 participants (Mage=47.86[SD=10.18] in 2001), there were no significant associations between concussion history or years of contact sport participation with CAGE scores or alcohol use frequency/amount during professional career, 2001, or 2019 (rhos=-.072-.067, ps>.05). In 2001, greater depressive symptomology and sleep disturbance were related to higher CAGE scores (rho=.209, p<.001; rho=.176, p<.001, respectively), while greater depressive symptomology, pain interference, and sleep disturbance were related to higher alcohol use frequency (rho=.176, p=.002; rho=.109, p=.045; rho=.132, p=.013, respectively) and amount/occasion (rho=.215, p<.001; rho=.127, p=.020; rho=.153, p=.004, respectively). In 2019, depressive symptomology, pain interference, and sleep disturbance were not related to alcohol use (rhos=-.047-.087, ps>.05). Between timepoints, more sleep disturbance in 2001 was associated with higher alcohol amount/occasion in 2019 (rho=.115, p=.036).

Increased alcohol intake has been theorized to be a consequence of greater concussion history, and as such, thought to confound associations between concussion history and neurobehavioral function later in life. Our findings indicate concussion history and years of contact sport participation were not significantly associated with alcohol use cross-sectionally or longitudinally, regardless of alcohol use characterization. While higher levels of depression, pain interference, and sleep disturbance in 2001 were related to greater alcohol use in 2001, they were not associated cross-sectionally in 2019. Results support the need to concurrently address health-related and psychological factors in the implementation of alcohol use interventions for former NFL players, particularly earlier in the sport discontinuation timeline.

Traumatic brain injury and cardiovascular disease (CVD) are modifiable risk factors for cognitive decline and dementia. Greater concussion history can potentially increase risk for cerebrovascular changes associated with cognitive decline and may compound effects of CVD. We investigated the independent and dynamic effects of CVD/risk factor burden and concussion history on cognitive function and odds of mild cognitive impairment (MCI) diagnoses in older former National Football League (NFL) players.

Former NFL players, ages 50-70 (N=289; mean age=61.02±5.33 years), reported medical history and completed the Brief Test of Adult Cognition by Telephone (BTACT). CVD/risk factor burden was characterized as ordinal (0-3+) based on the sum of the following conditions: coronary artery disease/myocardial infarction, chronic obstructive pulmonary disease, hypertension, hyperlipidemia, sleep apnea, type-I and II diabetes. Cognitive outcomes included BTACT Executive Function and Episodic Memory Composite Z-scores (standardized on age- and education-based normative data), and the presence of physician diagnosed (self-reported) MCI. Concussion history was discretized into five groups: 0, 1-2, 3-5, 6-9, 10+. Linear and logistic regression models were fit to test independent and joint effects of concussion history and CVD burden on cognitive outcomes and odds of MCI. Race (dichotomized as White and Non-white due to sample distribution) was included in models as a covariate.

Greater CVD burden (unstandardized beta [standard error]; B=-0.10[0.42], p=.013, and race (B=0.622[0.09], p<.001), were associated with lower executive functioning. Compared to those with 0 prior concussions, no significant differences were observed for those with 1-2, 3-5, 6-9, or 10+ prior concussions (ps >.05). Race (B=0.61[.13], p<.001), but not concussion history or CVD burden, was associated with episodic memory. There was a trend for lower episodic memory scores among those with 10+ prior concussion compared to those with no prior concussions (B=-0.49[.25], p=.052). There were no significant differences in episodic memory among those with 1-2, 3-5, or 6-9 prior concussions compared to those with 0 prior concussions (ps>.05). CVD burden (B=0.35[.13], p=.008), race (greater odds in Non-white group; B=0.82[.29], p=.005), and greater concussion history (higher odds of diagnosis in 10+ group compared to those with 0 prior concussions; B=2.19[0.78], p<.005) were associated with higher odds of MCI diagnosis. Significant interaction effects between concussion history and CVD burden were not observed for any outcome (ps >.05).

Lower executive functioning and higher odds of MCI diagnosis were associated with higher CVD burden and race. Very high concussion history (10+) was selectively associated with higher odds of MCI diagnosis. Reduction of these modifiable factors may mitigate adverse outcomes in older contact sport athletes. In former athletes, consideration of CVD burden is particularly pertinent when assessing executive dysfunction, considered to be a common cognitive feature of traumatic encephalopathy syndrome, as designated by the recent diagnostic criteria. Further research should investigate the social and structural determinants contributing to racial disparities in long-term health outcomes within former NFL players.

Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.

Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.

RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.

These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.

Interventions using a cognitive training paradigm called the Useful Field of View (UFOV) task have shown to be efficacious in slowing cognitive decline. However, no studies have looked at the engagement of functional networks during UFOV task completion. The current study aimed to (a) assess if regions activated during the UFOV fMRI task were functionally connected and related to task performance (henceforth called the UFOV network), (b) compare connectivity of the UFOV network to 7 resting-state functional connectivity networks in predicting proximal (UFOV) and near-transfer (Double Decision) performance, and (c) explore the impact of network segregation between higher-order networks and UFOV performance.

336 healthy older adults (mean age=71.6) completed the UFOV fMRI task in a Siemens 3T scanner. UFOV fMRI accuracy was calculated as the number of correct responses divided by 56 total trials. Double Decision performance was calculated as the average presentation time of correct responses in log ms, with lower scores equating to better processing speed. Structural and functional MRI images were processed using the default pre-processing pipeline within the CONN toolbox. The Artifact Rejection Toolbox was set at a motion threshold of 0.9mm and participants were excluded if more than 50% of volumes were flagged as outliers. To assess connectivity of regions associated with the UFOV task, we created 10 spherical regions of interest (ROIs) a priori using the WFU PickAtlas in SPM12. These include the bilateral pars triangularis, supplementary motor area, and inferior temporal gyri, as well as the left pars opercularis, left middle occipital gyrus, right precentral gyrus and right superior parietal lobule. We used a weighted ROI-to-ROI connectivity analysis to model task-based within-network functional connectivity of the UFOV network, and its relationship to UFOV accuracy. We then used weighted ROI-to-ROI connectivity analysis to compare the efficacy of the UFOV network versus 7 resting-state networks in predicting UFOV fMRI task performance and Double Decision performance. Finally, we calculated network segregation among higher order resting state networks to assess its relationship with UFOV accuracy. All functional connectivity analyses were corrected at a false discovery threshold (FDR) at p<0.05.

ROI-to-ROI analysis showed significant within-network functional connectivity among the 10 a priori ROIs (UFOV network) during task completion (all pFDR<.05). After controlling for covariates, greater within-network connectivity of the UFOV network associated with better UFOV fMRI performance (pFDR=.008). Regarding the 7 resting-state networks, greater within-network connectivity of the CON (pFDR<.001) and FPCN (pFDR=. 014) were associated with higher accuracy on the UFOV fMRI task. Furthermore, greater within-network connectivity of only the UFOV network associated with performance on the Double Decision task (pFDR=.034). Finally, we assessed the relationship between higher-order network segregation and UFOV accuracy. After controlling for covariates, no significant relationships between network segregation and UFOV performance remained (all p-uncorrected>0.05).

To date, this is the first study to assess task-based functional connectivity during completion of the UFOV task. We observed that coherence within 10 a priori ROIs significantly predicted UFOV performance. Additionally, enhanced within-network connectivity of the UFOV network predicted better performance on the Double Decision task, while conventional resting-state networks did not. These findings provide potential targets to optimize efficacy of UFOV interventions.

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 is variability in the level of cognitive gains after cognitive training across studies. One potential explanation for this variability could be moderating factors. Prior studies suggest variables moderating cognitive training gains share features of the training task. Learning trials of the Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R) recruit similar cognitive abilities and have overlapping neural correlates with the UFOV task and speed-ofprocessing/working memory tasks and therefore could serve as potential moderators. Exploring moderating factors of cognitive training gains may boost the efficacy of interventions, improve rigor in the cognitive training literature, and eventually help provide tailored treatment recommendations. This study explored the association between the HVLT-R and BVMT-R learning and the UFOV task, and assessed the moderation of HVLT-R and BVMT-R learning on UFOV improvement after a 3-month speed-ofprocessing/attention and working memory cognitive training intervention in cognitively healthy older adults.

75 healthy older adults (M age = 71.11, SD = 4.61) were recruited as part of a larger clinical trial through the Universities of Florida and Arizona. Participants were randomized into a cognitive training (n=36) or education control (n=39) group and underwent a 40-hour, 12-week intervention. Cognitive training intervention consisted of practicing 4 attention/speed-of-processing (including the UFOV task) and 4 working memory tasks. Education control intervention consisted of watching 40-minute educational videos. The HVLT-R and BVMT-R were administered at the pre-intervention timepoint as part of a larger neurocognitive battery. The learning ratio was calculated as: trial 3 total - trial 1 total/12 - trial 1 total. UFOV performance was measured at pre- and post-intervention time points via the POSIT Brain HQ Double Decision Assessment. Multiple linear regressions predicted baseline Double Decision performance from HVLT-R and BVMT-R learning ratios controlling for study site, age, sex, and education. A repeated measures moderation analysis assessed the moderation of HVLT-R and BVMT-R learning ratio on Double Decision change from pre- to post-intervention for cognitive training and education control groups.

Baseline Double Decision performance significantly associated with BVMT-R learning ratio (β=-.303, p=.008), but not HVLT-R learning ratio (β=-.142, p=.238). BVMT-R learning ratio moderated gains in Double Decision performance (p<.01); for each unit increase in BVMT-R learning ratio, there was a .6173 unit decrease in training gains. The HVLT-R learning ratio did not moderate gains in Double Decision performance (p>.05). There were no significant moderations in the education control group.

Better visuospatial learning was associated with faster Double Decision performance at baseline. Those with poorer visuospatial learning improved most on the Double Decision task after training, suggesting that healthy older adults who perform below expectations 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.

Aging is associated with disruptions in functional connectivity within the default mode (DMN), frontoparietal control (FPCN), and cingulo-opercular (CON) resting-state networks. Greater within-network connectivity predicts better cognitive performance in older adults. Therefore, strengthening network connectivity, through targeted intervention strategies, may help prevent age-related cognitive decline or progression to dementia. Small studies have demonstrated synergistic effects of combining transcranial direct current stimulation (tDCS) and cognitive training (CT) on strengthening network connectivity; however, this association has yet to be rigorously tested on a large scale. The current study leverages longitudinal data from the first-ever Phase III clinical trial for tDCS to examine the efficacy of an adjunctive tDCS and CT intervention on modulating network connectivity in older adults.

This sample included 209 older adults (mean age = 71.6) from the Augmenting Cognitive Training in Older Adults multisite trial. Participants completed 40 hours of CT over 12 weeks, which included 8 attention, processing speed, and working memory tasks. Participants were randomized into active or sham stimulation groups, and tDCS was administered during CT daily for two weeks then weekly for 10 weeks. For both stimulation groups, two electrodes in saline-soaked 5x7 cm2 sponges were placed at F3 (cathode) and F4 (anode) using the 10-20 measurement system. The active group received 2mA of current for 20 minutes. The sham group received 2mA for 30 seconds, then no current for the remaining 20 minutes.

Participants underwent resting-state fMRI at baseline and post-intervention. CONN toolbox was used to preprocess imaging data and conduct region of interest (ROI-ROI) connectivity analyses. The Artifact Detection Toolbox, using intermediate settings, identified outlier volumes. Two participants were excluded for having greater than 50% of volumes flagged as outliers. ROI-ROI analyses modeled the interaction between tDCS group (active versus sham) and occasion (baseline connectivity versus postintervention connectivity) for the DMN, FPCN, and CON controlling for age, sex, education, site, and adherence.

Compared to sham, the active group demonstrated ROI-ROI increases in functional connectivity within the DMN following intervention (left temporal to right temporal [T(202) = 2.78, pFDR < 0.05] and left temporal to right dorsal medial prefrontal cortex [T(202) = 2.74, pFDR < 0.05]. In contrast, compared to sham, the active group demonstrated ROI-ROI decreases in functional connectivity within the FPCN following intervention (left dorsal prefrontal cortex to left temporal [T(202) = -2.96, pFDR < 0.05] and left dorsal prefrontal cortex to left lateral prefrontal cortex [T(202) = -2.77, pFDR < 0.05]). There were no significant interactions detected for CON regions.

These findings (a) demonstrate the feasibility of modulating network connectivity using tDCS and CT and (b) provide important information regarding the pattern of connectivity changes occurring at these intervention parameters in older adults. Importantly, the active stimulation group showed increases in connectivity within the DMN (a network particularly vulnerable to aging and implicated in Alzheimer’s disease) but decreases in connectivity between left frontal and temporal FPCN regions. Future analyses from this trial will evaluate the association between these changes in connectivity and cognitive performance post-intervention and at a one-year timepoint.

The National Institutes of Health-Toolbox cognition battery (NIH-TCB) is widely used in cognitive aging studies and includes measures in cognitive domains evaluated for dimensional structure and psychometric properties in prior research. The present study addresses a current literature gap by demonstrating how NIH-TCB integrates into a battery of traditional clinical neuropsychological measures. The dimensional structure of NIH-TCB measures along with conventional neuropsychological tests is assessed in healthy older adults.

Baseline cognitive data were obtained from 327 older adults. The following measures were collected: NIH-Toolbox cognitive battery, Controlled Oral Word Association (COWA) letter and animals tests, Wechsler Test of Adult Reading (WTAR), Stroop Color-Word Interference Test, Paced Auditory Serial Addition Test (PASAT), Brief Visuospatial Memory Test (BVMT), Letter-Number Sequencing (LNS), Hopkins Verbal Learning Test (HVLT), Trail Making Test A&B, Digit Span. Hmisc, psych, and GPARotation packages for R were used to conduct exploratory factor analyses (EFA). A 5-factor solution was conducted followed by a 6-factor solution. Promax rotation was used for both EFA models.

The 6-factor EFA solution is reported here. Results indicated the following 6 factors: working memory (Digit Span forward, backward, and sequencing, PASAT trials 1 and 2, NIH-Toolbox List Sorting, LNS), speed/executive function (Stroop color naming, word reading, and color-word interference, NIH-Toolbox Flanker, Dimensional Change, and Pattern Comparison, Trail Making Test A&B), verbal fluency (COWA letters F-A-S), crystallized intelligence (WTAR, NIH-Toolbox Oral Recognition and Picture Vocabulary), visual memory (BVMT immediate and delayed), and verbal memory (HVLT immediate and delayed. COWA animals and NIH-Toolbox Picture Sequencing did not adequately load onto any EFA factor and were excluded from the subsequent CFA.

Findings indicate that in a sample of healthy older adults, these collected measures and those obtained through the NIH-Toolbox battery represent 6 domains of cognitive function. Results suggest that in this sample, picture sequencing and COWA animals did not load adequately onto the factors created from the rest of the measures collected. These findings should assist in interpreting future research using combined NIH-TCB and neuropsychological batteries to assess cognition in healthy older adults.

Nonpathological aging has been linked to decline in both verbal and visuospatial memory abilities in older adults. Disruptions in resting-state functional connectivity within well-characterized, higherorder cognitive brain networks have also been coupled with poorer memory functioning in healthy older adults and in older adults with dementia. However, there is a paucity of research on the association between higherorder functional connectivity and verbal and visuospatial memory performance in the older adult population. The current study examines the association between resting-state functional connectivity within the cingulo-opercular network (CON), frontoparietal control network (FPCN), and default mode network (DMN) and verbal and visuospatial learning and memory in a large sample of healthy older adults. We hypothesized that greater within-network CON and FPCN functional connectivity would be associated with better immediate verbal and visuospatial memory recall. Additionally, we predicted that within-network DMN functional connectivity would be associated with improvements in delayed verbal and visuospatial memory recall. This study helps to glean insight into whether within-network CON, FPCN, or DMN functional connectivity is associated with verbal and visuospatial memory abilities in later life.

330 healthy older adults between 65 and 89 years old (mean age = 71.6 ± 5.2) were recruited at the University of Florida (n = 222) and the University of Arizona (n = 108). Participants underwent resting-state fMRI and completed verbal memory (Hopkins Verbal Learning Test - Revised [HVLT-R]) and visuospatial memory (Brief Visuospatial Memory Test - Revised [BVMT-R]) measures. Immediate (total) and delayed recall scores on the HVLT-R and BVMT-R were calculated using each test manual’s scoring criteria. Learning ratios on the HVLT-R and BVMT-R were quantified by dividing the number of stimuli (verbal or visuospatial) learned between the first and third trials by the number of stimuli not recalled after the first learning trial. CONN Toolbox was used to extract average within-network connectivity values for CON, FPCN, and DMN. Hierarchical regressions were conducted, controlling for sex, race, ethnicity, years of education, number of invalid scans, and scanner site.

Greater CON connectivity was significantly associated with better HVLT-R immediate (total) recall (ß = 0.16, p = 0.01), HVLT-R learning ratio (ß = 0.16, p = 0.01), BVMT-R immediate (total) recall (ß = 0.14, p = 0.02), and BVMT-R delayed recall performance (ß = 0.15, p = 0.01). Greater FPCN connectivity was associated with better BVMT-R learning ratio (ß = 0.13, p = 0.04). HVLT-R delayed recall performance was not associated with connectivity in any network, and DMN connectivity was not significantly related to any measure.

Connectivity within CON demonstrated a robust relationship with different components of memory function as well across verbal and visuospatial domains. In contrast, FPCN only evidenced a relationship with visuospatial learning, and DMN was not significantly associated with memory measures. These data suggest that CON may be a valuable target in longitudinal studies of age-related memory changes, but also a possible target in future non-invasive interventions to attenuate memory decline in older adults.