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Posttraumatic stress disorder (PTSD) has been associated with advanced epigenetic age cross-sectionally, but the association between these variables over time is unclear. This study conducted meta-analyses to test whether new-onset PTSD diagnosis and changes in PTSD symptom severity over time were associated with changes in two metrics of epigenetic aging over two time points.
Methods
We conducted meta-analyses of the association between change in PTSD diagnosis and symptom severity and change in epigenetic age acceleration/deceleration (age-adjusted DNA methylation age residuals as per the Horvath and GrimAge metrics) using data from 7 military and civilian cohorts participating in the Psychiatric Genomics Consortium PTSD Epigenetics Workgroup (total N = 1,367).
Results
Meta-analysis revealed that the interaction between Time 1 (T1) Horvath age residuals and new-onset PTSD over time was significantly associated with Horvath age residuals at T2 (meta β = 0.16, meta p = 0.02, p-adj = 0.03). The interaction between T1 Horvath age residuals and changes in PTSD symptom severity over time was significantly related to Horvath age residuals at T2 (meta β = 0.24, meta p = 0.05). No associations were observed for GrimAge residuals.
Conclusions
Results indicated that individuals who developed new-onset PTSD or showed increased PTSD symptom severity over time evidenced greater epigenetic age acceleration at follow-up than would be expected based on baseline age acceleration. This suggests that PTSD may accelerate biological aging over time and highlights the need for intervention studies to determine if PTSD treatment has a beneficial effect on the aging methylome.
Objectives/Goals: Early childhood obesity is a major concern for Latin American children in the U.S., with gut barrier dysfunction as a key risk factor. Diet plays a role in gut development, but few studies have focused on Latin American infants. Our objective is to identify culturally relevant introductory foods that promote in vitro gut barrier development and function. Methods/Study Population: Pooled human milk (2.5 mL) from 6-month postpartum Hispanic mothers was combined with fruit and vegetable baby food products (2.5 g) and subjected to a 3-phase in vitro digestion system that simulates oral, gastric, and intestinal digestion. Digesta products were then anaerobically fermented for 24-hours using human stool inoculum, centrifuged, and filter sterilized. Intestinal epithelial cells (Caco-2, ATCC) were grown to confluence on 0.4 μm polystyrene transwell inserts using a DMEM + 10% FBS medium and allowed to differentiate for 21-days. Highly differentiated monolayers were treated with a 1:4 dilution of fermenta with medium in triplicate. The cell experiment was conducted twice. Cell layer integrity was measured using transepithelial electrical resistance (TEER) 24- and 48-hours after treatment. Results/Anticipated Results: Dietary intake data from the What We Eat in America database indicated that the top 3 fruit and vegetable exposures for infants with Mexican or Hispanic ethnicity were banana, apple, and carrot. Commercial baby food purees of these fruits and vegetables, in addition to baby foods with blueberry and spinach (Natural for Baby, Gerber Products Company) were acquired for digestion and fermentation experiments. Caco-2 cell experiments with these foods are ongoing. We expect Caco-2 monolayer incubated with fermenta from human milk and fruit or vegetables will have greater TEER values due to increased integrity of the cell layer as compared to those with breast milk alone. We also expect that exposure to fruit and vegetable fermenta will increase gene expression of tight junctions compared to exposure to media and human milk. Discussion/Significance of Impact: Using an in vitro digestion and fermentation system coupled with cell culture studies, we are identifying cellular mechanisms that link individual fruits and vegetables to gut barrier function. This will support translational work focused on mitigating obesity development in vulnerable populations.
A prominent paradigm demonstrates many White Americans respond negatively to information on their declining population share. But this paradigm considers this “racial shift” in a single hierarchy-challenging context that produces similar status threat responses across conceptually distinct outcomes, undercutting the ability to both explain the causes of Whites’ social and political responses and advance theorizing about native majorities’ responses to demographic change. We test whether evidence for Whites’ responses to demographic change varies across three distinct hierarchy-challenging contexts: society at large, culture, and politics. We find little evidence any racial shift information instills status threat or otherwise changes attitudes or behavioral intentions, and do not replicate evidence for reactions diverging by left- versus right-wing political attachments. We conclude with what our well-powered (n = 2100) results suggest about a paradigm and intervention used prominently, with results cited frequently, to understand native majorities’ responses to demographic change and potential challenges to multiracial democracy.
We present the Sydney Radio Star Catalogue, a new catalogue of stars detected at megahertz to gigahertz radio frequencies. It consists of 839 unique stars with 3 405 radio detections, more than doubling the previously known number of radio stars. We have included stars from large area searches for radio stars found using circular polarisation searches, cross-matching, variability searches, and proper motion searches as well as presenting hundreds of newly detected stars from our search of Australian SKA Pathfinder observations. The focus of this first version of the catalogue is on objects detected in surveys using SKA precursor and pathfinder instruments; however, we will expand this scope in future versions. The 839 objects in the Sydney Radio Star Catalogue are distributed across the whole sky and range from ultracool dwarfs to Wolf-Rayet stars. We demonstrate that the radio luminosities of cool dwarfs are lower than the radio luminosities of more evolved sub-giant and giant stars. We use X-ray detections of 530 radio stars by the eROSITA soft X-ray instrument onboard the Spectrum Roentgen Gamma spacecraft to show that almost all of the radio stars in the catalogue are over-luminous in the radio, indicating that the majority of stars at these radio frequencies are coherent radio emitters. The Sydney Radio Star Catalogue can be found in Vizier or at https://radiostars.org.
At high elevations on the Greenland ice sheet meltwater percolates and refreezes in place, and hence does not contribute to mass loss. However, meltwater generation and associated surface runoff is occurring from increasingly higher altitudes, causing changes in firn stratigraphy that have led to the presence of near-surface ice slabs. These ice slabs force meltwater to flow laterally instead of percolating downwards. Here we present a simple, physics-based quasi-2-D model to simulate lateral meltwater runoff and superimposed ice (SI) formation on top of ice slabs. Using an Eulerian Darcy flow scheme, the model calculates how far meltwater can travel within a melt season and when it appears at the snow surface. Results show that lateral flow is a highly efficient runoff mechanism, as lateral outflow exceeds locally generated meltwater in all model gridcells, with total meltwater discharge sometimes reaching more than 30 times the average amount of in situ generated melt. SI formation, an important process in the formation and thickening of the ice slabs, can retain up to 40% of the available meltwater, and generally delays the appearance of visible runoff. Validating the model against field- or remote-sensing data remains challenging, but the results presented here are a first step towards a more comprehensive understanding and description of the hydrological system in the accumulation zone of the southwestern Greenland ice sheet.
Operationalization guidance is needed to support health technology assessment (HTA) bodies considering implementing lifecycle HTA (LC-HTA) approaches. The 2022 Health Technology Assessment International (HTAi) Global Policy Forum (GPF) established a Task Force to develop a position paper on LC-HTA. In its first paper, the Task Force established a definition and framework for LC-HTA in order to tailor it to specific decision problems. This second paper focused on the provision of practical operational guidance to implement LC-HTA. Detailed descriptions of the three LC-HTA operational steps are provided (defining the decision problem, sequencing of HTA activities, and developing optimization criteria) and accompanied by worked examples and an operationalization checklist with 20 different questions for HTA bodies to consider when developing an LC-HTA approach. The questions were designed to be applicable across different types of HTA and scenarios, and require adaptation to local jurisdictions, remits, and context.
The 2022 Health Technology Assessment International (HTAi) Global Policy Forum (GPF) established the goal of developing a position statement and framework for lifecycle HTA (LC-HTA), through a Task Force leveraging multi-stakeholder monthly discussions and GPF member input. The Task Force developed a working definition: LC-HTA is a systematic process utilizing sequential HTA activities to inform decision making where the evidence base, the health technology itself, or the context in which it is applied, has a potential to meaningfully change at different points in its LC. Four key scenarios were identified where it was considered that an LC-HTA approach would add sufficient value to HTA bodies and their key stakeholders to justify the additional resource burden. Based on the four scenarios, a high-level LC-HTA framework was developed consisting of (i) defining the decision problem, (ii) sequencing of HTA activities, and (iii) developing optimization criteria. Subsequently, the Task Force developed operationalization guidance for LC-HTA in a companion paper.
Following an outbreak of Salmonella Typhimurium in Wales in July 2021 associated with sheep meat and offal, further genetically related cases were detected across the UK. Cases were UK residents with laboratory-confirmed Salmonella Typhimurium in the same 5-single-nucleotide polymorphism (SNP) single-linkage cluster with specimen date between 01/08/2021–2031/12/2022. We described cases using routine (UK) and enhanced (Wales only) surveillance data. Exposures in cases in Wales were compared with non-Typhimurium Salmonella case–controls. Environmental Health Practitioners and the Food Standards Agency investigated supply chains of food premises reported by ≥2 cases. Animal, carcass, and environmental samples taken for diagnostic or monitoring purposes for gastrointestinal pathogens were included in microbiological investigations. We identified 142 cases: 75% in England, 23% in Wales and 3% in Scotland. Median age was 32 years, and 59% were male. Direct contact with sheep was associated with becoming a case (aOR: 14, 95%CI: 1.4–145) but reported by few (6/32 cases). No single food item, premises, or supplier linked all cases. Multi-agency collaboration enabled the identification of isolates in the same 5-SNP single-linkage cluster from a sheep carcass at an English abattoir and in ruminant, wildlife, poultry, and environmental samples, suggesting multiple vehicles and pathways of infection.
In this paper, we consider random dynamical systems formed by concatenating maps acting on the unit interval $[0,1]$ in an independent and identically distributed (i.i.d.) fashion. Considered as a stationary Markov process, the random dynamical system possesses a unique stationary measure $\nu $. We consider a class of non-square-integrable observables $\phi $, mostly of form $\phi (x)=d(x,x_0)^{-{1}/{\alpha }}$, where $x_0$ is a non-recurrent point (in particular a non-periodic point) satisfying some other genericity conditions and, more generally, regularly varying observables with index $\alpha \in (0,2)$. The two types of maps we concatenate are a class of piecewise $C^2$ expanding maps and a class of intermittent maps possessing an indifferent fixed point at the origin. Under conditions on the dynamics and $\alpha $, we establish Poisson limit laws, convergence of scaled Birkhoff sums to a stable limit law, and functional stable limit laws in both the annealed and quenched case. The scaling constants for the limit laws for almost every quenched realization are the same as those of the annealed case and determined by $\nu $. This is in contrast to the scalings in quenched central limit theorems where the centering constants depend in a critical way upon the realization and are not the same for almost every realization.
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.
Participants and Methods:
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.
Results:
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).
Conclusions:
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.
Transcranial magnetic stimulation (TMS) is an effective treatment for individuals with pharmacoresistant major depressive disorder (MDD), yet identifying which patients best respond remains an important area of inquiry. The Brief Symptom Inventory (BSI-18) serves as a screen for psychological distress, providing measures across three separate domains (e.g., somatization, depression, and anxiety) and one composite score (i.e., global severity index). The psychometric properties of the BSI-18 have been validated across multiple studies; however, it has sparsely been used to track changes in patient symptoms in response to intervention. Assessing patient symptom severity across these domains is imperative since these symptoms can negatively influence cognitive functioning. Accordingly, the current study utilized the BSI-18 to measure psychological distress across these different domains in patients receiving TMS treatment. We hypothesized that all domains of the BSI-18 would see a significant decrease after treatment, that elevated scores in specific domains would predict a less favorable response to treatment, and that measurement of depressive symptoms will be consistent across measures of similar scope.
Participants and Methods:
Veterans (n=94) with MDD and met standard clinical TMS criteria were administered the BSI-18 before and after receiving an adequate dose of treatment (e.g., 30 sessions). Paired Samples T-test were used to compare the pre-treatment and post-treatment scores across domains.
Results:
The results of paired sample t-tests indicated a statistically significant reduction in measures of global psychological distress (t(93) = 7.99, p < .001, Cohen's d =.82), as well as depressive (t(93) = 8.34, p < .001, d = .86), anxious (t(93) = 7.64, p < .001, d = .79), and somatic symptoms (t(92) = 5.29, p < .001, d = .55) after receiving treatment. Individuals with elevated levels of anxiety (e.g., BSI-A>63) saw a significant reduction in depressive (t(62) = 8.15, p < .001, d = 1.03), anxious (t(62) = 8.34, p < .001, d = 1.05) and somatic (t(61) = 4.94, p < .001, d = .63) symptoms. Lastly, two measures of depressive symptoms, the BSI-D and PHQ-9, had a statistically significant strong, positive relationship before (r=.66) and after (r=.88) treatment (all n=65 and p<.001).
Conclusions:
The BSI-18 can detect changes in different domains of psychological distress as a function of TMS treatment. Unexpectedly, TMS patients with elevated levels of anxiety responded well to treatment despite comorbid anxiety often being associated with less favorable outcomes in treatment trials. The positive relationship of the BSI-D and PHQ-9 before and after treatment suggests the use of the BSI as a valid, additional measure of depressive symptoms.
This study builds on the work by Rehman et al (2022) who argued that transcranial magnetic stimulation (TMS) treatment not only helps treat depression but also decreases sleep problems such as difficulty falling asleep,staying asleep, and waking too early. The present study further explores differences in sleep onset latency, meaning the time it takes to fall asleep, and duration of sleep per night in the pre and post treatment phases of rTMS. The information regarding major attributes of sleep is critical because recent research shows that about 90% of patients with major depressive disorder (MDD) also struggle with sleep disorders (Li et al., 2022), and sleeping for less than seven hours may eventually lead to sleep deprivation (Hirshkowitz et al., 2015), with increased risk of physical and mental health problems (Sheehan et al, 2019). Sleep onset latency estimates vary from individual to individual but typical sleep latency is considered between 10 to 20 minutes (Jung et al, 2013). As it has been shown that overall sleep problems improve with rTMS, we hypothesized that self-reported sleep onset latency will decrease, and sleep duration will increase.
Participants and Methods:
All participants met inclusion criteria for MDD diagnosis and completed a full course of TMS treatment (N=470; Mean age=53.45, SD=13.73). The sample was mostly male (81%) and ethnically diverse: 77.7% non-Hispanic White, 13.3% Black Americans, 1.9% Asian, 0.2 % Asian Indian, and 1.9% other ethnicities. Sleep problems were assessed using the following questions at the pre and post treatment stages: the number of minutes it takes to fall asleep and duration of sleep each night.
Results:
A Wilcoxon matched-pairs signed-rank test was conducted to determine whether there was a difference in sleep onset latency and hours of sleep per night between pre and post intervention. The results indicated a significant difference in time to fall asleep between pre and post treatment (pre-treatment M = 1.19, SD = 0.99, post-treatment M = 0.93, SD = 0.91; z = -5.01, p < .001. In addition, there was a significant increase in the minutes of sleep per night in pre (M = 6.11, SD = 2.07) compared to the post treatment (M = 6.32, SD = 1.77), z = -2.56, p = .010.
Conclusions:
Reduced sleep is known to negatively impact mood, cognitive ability, work performance, and immune function (Besedovsky et al., 2012; Killgore, 2010; Massar et al, 2019; Vandekerckhove & Wang, 2018). Similarly, longer sleep onset latency can cause an individual to enter the first sleep stage later than expected and complete fewer sleep cycles. The results of the present study show the effectiveness of rTMS in decreasing sleep onset latency and increasing the duration of sleep. Given the comorbidity and bidirectionality between sleep disturbances and mood disorders (Fang et al., 2019; Palagini et al., 2019), further researching treatments such as rTMS to improve sleep as a means to also improve mood is crucial. We propose acquiring knowledge about sleep attributes as an essential part of clinicians’ work early on in the rTMS treatment in order to monitor an individual’s global functioning level in light of improved sleep.
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.
Participants and Methods:
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.
Results:
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.
Conclusions:
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.
Participants and Methods:
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.
Results:
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).
Conclusions:
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.
Participants and Methods:
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.
Results:
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.
Conclusions:
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.
Participants and Methods:
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.
Results:
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.
Conclusions:
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.
Participants and Methods:
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.
Results:
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.
Conclusions:
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.
Participants and Methods:
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.
Results:
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.
Conclusions:
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.
Repetitive transcranial magnetic stimulation (TMS) is an evidenced based treatment for adults with treatment resistant depression (TRD). The standard clinical protocol for TMS is to stimulate the left dorsolateral prefrontal cortex (DLPFC). Although the DLPFC is a defining region in the cognitive control network of the brain and implicated in executive functions such as attention and working memory, we lack knowledge about whether TMS improves cognitive function independent of depression symptoms. This exploratory analysis sought to address this gap in knowledge by assessing changes in attention before and after completion of a standard treatment with TMS in Veterans with TRD.
Participants and Methods:
Participants consisted of 7 Veterans (14.3% female; age M = 46.14, SD = 7.15; years education M = 16.86, SD = 3.02) who completed a full 30-session course of TMS treatment and had significant depressive symptoms at baseline (Patient Health Questionnaire-9; PHQ-9 score >5). Participants were given neurocognitive assessments measuring aspects of attention [Wechsler Adult Intelligence Scale 4th Edition (WAIS-IV) subtests: Digits Forward, Digits Backward, and Number Sequencing) at baseline and again after completion of TMS treatment. The relationship between pre and post scores were examined using paired-samples t-test for continuous variables and a linear regression to covary for depression and posttraumatic stress disorder (PTSD), which is often comorbid with depression in Veteran populations.
Results:
There was a significant improvement in Digit Span Forward (p=.01, d=-.53), but not Digit Span Backward (p=.06) and Number Sequencing (p=.54) post-TMS treatment. Depression severity was not a significant predictor of performance on Digit Span Forward (f(1,5)=.29, p=.61) after TMS treatment. PTSD severity was also not a significant predictor of performance on Digit Span Forward (f(1,5)=1.31, p=.32).
Conclusions:
Findings suggested that a standard course of TMS improves less demanding measures of working memory after a full course of TMS, but possibly not the more demanding aspects of working memory. This improvement in cognitive function was independent of improvements in depression and PTSD symptoms. Further investigation in a larger sample and with direct neuroimaging measures of cognitive function is warranted.