OBJECTIVE:Functional connectivity (FC) coordinates brain activity during cognitive tasks, yet the influence of demographic variables and health factors on task-related dynamic FC remains underexplored. We examined FC within and between seven core brain networks: Default Mode (DMN), Ventral Attention (VAN), Somatomotor (SMN), Dorsal Attention (DAN), Frontoparietal (FPN), Visual (VIN), and Limbic (LIN) during a modified Eriksen flanker task. We aimed to identify distinct network configurations linked to varying cognitive control demands and assess the influence of demographic and health factors. METHODS:Secondary analyses of source-localized EEG data from 255 adults (mean age 38.97 ± 11.65 years; BMI 30.21 ± 9.29 kg/m2) were conducted. A hidden Markov model extracted spatiotemporal dynamics, quantifying within- and between-network correlations. Extreme Gradient Boosting with recursive feature elimination identified connectivity metrics predicting reaction time (RT) of high performers (>80% accuracy). Regression models assessed effects of age, sex, BMI, and income on task-related FC. RESULTS:Classification accurately predicted RT in both congruent (AUC = 0.81) and incongruent (AUC = 0.86) trials. Key FC features included VAN-LIN, VIN-VAN, and SMN-DAN for congruent trials; SMN-DMN, LIN-FPN, and VIN-DAN for incongruent trials. Age was linked to reduced FC, while higher BMI showed modest positive FC associations in LIN-FPN and VIN-DAN. Sex and income were not significant predictors of RT or FC. CONCLUSIONS:These findings reveal the relevance of specific dynamic network interactions in cognitive control and highlight the need to consider age and BMI as contributors to brain connectivity during task performance.

Anxiety disorders are prevalent worldwide and can negatively impact physical and mental health. Thus, the timely detection of changes in anxiety levels is crucial for mental health management. This study used multimodal physiological features from wearable devices to classify anxiety levels across various conditions, normalized by individual baseline responses for personalized analysis. Gaussian Mixture Models clustered data into binary or ternary anxiety levels, interpreted by statistics of self-reported scores and physiological features. Clus ters showed modest alignment with State and Trait Inventory scores and physiological markers and demonstrated task-specific variability. Silhouette scores indicated moderate separation (0.40 for two clusters, 0.14 for three clusters). Binary and three-class classifications using unsupervised learning and leave-one-participant-out validation demonstrated effectiveness, with Support Vector Machine achieving highest accuracies (90.9% and 73.3%). This approach enables objective, personalized anxiety monitoring without relying on subjective labeling.

This study quantitatively evaluated whether and how machine learning (ML) models built by data from controlled conditions can fit real-world conditions. This study focused on feature-based models using wearable technology from real-world data collected from young adults, so as to provide insights into the models’ robustness and the specific challenges posed by diverse environmental noise. Feature-based models, particularly XGBoost and Decision Trees, demonstrated considerable resilience, maintaining higher accuracy and reliability across different noise levels. This investigation included an in-depth analysis of transfer learning, highlighting its potential and limitations in adapting models developed from standard datasets, like WESAD, to complex real-world scenarios. Moreover, this study analyzed the distributed feature importance across various physiological signals, such as electrodermal activity (EDA) and electrocardiography (ECG), considering their vulnerability to environmental factors. It was found that integrating multiple physiological data types could significantly enhance model robustness. The results underscored the need for a nuanced understanding of signal contributions to model efficacy, suggesting that feature-based models showed much promise in practical applications.

Tai Chi is a Chinese martial art that provides an adaptive and accessible exercise for older adults with varying functional capacity. While Tai Chi is widely recommended for its physical benefits, wider adoption in at-home practice presents challenges for practitioners, as limited feedback may hamper learning. This study examined the feasibility of using a wearable sensor, combined with machine learning (ML) approaches, to automatically and objectively classify Tai Chi expertise. We hypothesized that the combination of wrist acceleration profiles with ML approaches would be able to accurately classify practitioners' Tai Chi expertise levels. Twelve older active Tai Chi practitioners were recruited for this study. The self-reported lifetime practice hours were used to identify subjects in low, medium, or highly experienced groups. Using 15 acceleration-derived features from a wearable sensor during a self-guided Tai Chi movement and 8 ML architectures, we found multiclass classification performance to range from 0.73 to 0.97 in accuracy and F1-score. Based on feature importance analysis, the top three features were found to each result in a 16-19% performance drop in accuracy. These findings suggest that wrist-wearable-based ML models may accurately classify practice-related changes in movement patterns, which may be helpful in quantifying progress in at-home exercises.

Anxiety is a prevalent and detrimental mental health condition affecting young adults, particularly in college students who face a range of stressors including academic pressures, interpersonal relationships, and financial concerns. The ability to predict anxiety would help create individualized treatment. There is a need for objective and non-invasive continuous monitoring tools that allow for the prediction of anxiety. However, the generalizability of physiological changes across various stressors and participants must first be examined. The aim of this work is to examine the relationship of different stressors on heart rate variability in combination with machine learning models to assess binary and multi-class classification performance using electrocardiography derived features from a wearable device. Twenty-six college students performed a series of non-stressful and stressful conditions while wearing a Hexoskin smartshirt. The performance of binary and multi-class ML classifiers of stressor type was evaluated. Condition-wise binary classification accuracy of 76.2% and multi-class classification accuracy of 79.1% were achieved using a support vector machine (SVM) architecture. These results contribute to our understanding of individual anxiety symptom detection using ML and offer implications for applying similar monitoring tools to predict anxiety using wearable devices.

Tai Chi (TC) practice has been shown to improve both cognitive and physical function in older adults. However, the neural mechanisms underlying the benefits of TC remain unclear. Our primary aims are to explore whether distinct age-related and TC-practice-related relationships can be identified with respect to either temporal or spatial (within/between-network connectivity) differences. This cross-sectional study examined recurrent neural network dynamics, employing an adaptive, data-driven thresholding approach to source-localized resting-state EEG data in order to identify meaningful connections across time-varying graphs, using both temporal and spatial features derived from a hidden Markov model (HMM). Mann–Whitney U tests assessed between-group differences in temporal and spatial features by age and TC practice using either healthy younger adult controls (YACs, n = 15), healthy older adult controls (OACs, n = 15), or Tai Chi older adult practitioners (TCOAs, n = 15). Our results showed that aging is associated with decreased within-network and between-network functional connectivity (FC) across most brain networks. Conversely, TC practice appears to mitigate these age-related declines, showing increased FC within and between networks in older adults who practice TC compared to non-practicing older adults. These findings suggest that TC practice may abate age-related declines in neural network efficiency and stability, highlighting its potential as a non-pharmacological intervention for promoting healthy brain aging. This study furthers the triple-network model, showing that a balancing and reorientation of attention might be engaged not only through higher-order and top-down mechanisms (i.e., FPN/DAN) but also via the coupling of bottom-up, sensory–motor (i.e., SMN/VIN) networks.

While protein intake augments resistance training–induced changes in muscular strength and body composition, the benefits of higher protein intake and resistance training on cognitive outcomes and myokines with neurocognitive implications are unclear. The objective of this study is to compare the efficacy of moderate (0.8–1.0 g·kg −1 ·day −1 ) and high (1.6–1.8 g·kg −1 ·day −1 ) protein intake during a 10-week resistance training intervention, combined with blood and muscle sampling, on neurocognitive function and circulating myokines (e.g., cathepsin B [CTSB] and brain-derived neurotrophic factor [BDNF]) in 40 adults (age = 50.0 ± 7.3 years). A muscle biopsy was collected from the vastus lateralis to measure CTSB mRNA. Performance during the spatial reconstruction and Flanker tasks were utilized to assess relational memory and executive function. N2 and P3 event-related potentials (ERPs) were assessed during the Flanker task to index neuroelectric function. While differing protein intake did not impact outcomes, there were increases in muscle CTSB mRNA expression and plasma BDNF concentrations from resistance training, independent of protein intake. Increased BDNF was associated with decreased reaction time (congruent: β = − 0.38, p = 0.026; incongruent: β = − 0.38, p = 0.024) and congruent N2 fractional peak latency (FPL) ( β = − 0.52, p = 0.016) during the Flanker task, while increased plasma CTSB was associated with faster incongruent P3 FPL ( β = − 0.42, p = 0.036). Although there was no significant effect of protein group, increases in circulating myokines showed improvement in executive function and information processing speed. (NCT03029975; January 1, 2017).

Objective: This study aims at comparing the energy expenditure (EE) and heart rate (HR) data from Ring Fit Adventure (RFA) with those from indirect calorimetry (COSMED) and a heart rate monitor (Polar FT7). A secondary goal is to evaluate self-reported enjoyment and perceived effort levels.Materials and Methods: Thirty participants (age = 21.8 +/- 2.2; body mass index = 31.8 +/- 4.4) were recruited for two laboratory visits. The first visit involved baseline measurements. In the second visit, participants performed a 55-minute ad libitum exercise session with the RFA in adventure mode with moderate difficulty. During this session, EE, HR, perceived effort, and enjoyment of physical activity were recorded.Results: Although no statistically significant overestimation of EE was found between the RFA and the metabolic cart, two-way analysis of variance results show a main effect of condition (RFA vs. Polar FT7) on HR (122.8 +/- 20.1 bpm and 129.0 +/- 18.6 bpm; P = 0.007; f;(2)(P) = 0.235). Based on comprehensive statistical evaluations, including the mean absolute percent error, intraclass correlations, typical error of measurement, and limits of agreement, the data suggest that the RFA provides reliable estimates for EE and HR. Overall, participants enjoyed the game considerably (71.3 +/- 5.9/80 arbitrary units), and their reported perceived exertion was low.Conclusion: This study underscores that the RFA values are relatively accurate and precise, and thus it can be safely suggested for individuals with overweight and obesity to adopt an active lifestyle.

To determine if 3-year changes in serum insulin resistance (IR) were related to changes in brain volume and glucose uptake, cognition, and CSF biomarkers in cognitively unimpaired and impaired older adults. Alzheimer’s Disease Neuroimaging Initiative data was downloaded for 275 aged adults (55-89 years). Participants had longitudinal T1- and T2-weighted volume scans, fluorodeoxyglucose (FDG) scans, CSF β-amyloid (Aβ) and tau species, and cognitive performance over baseline and months 6, 12, 18, 24, and 36. Growth curve modeling in R regressed IR against these outcomes, by itself and with clinical diagnosis as a moderator. Cognitively unimpaired (CU) adults were used as a reference group to determine potential effects in pathological aging. In AD and/or Mild Cognitive Impairment progressors to AD (MCI-P), higher IR over time was related to progressive atrophy in medial temporal frontoinsular areas. Similarly, decline was seen in global cognition and both memory and executive function. HOMA1-IR associations were partially mediated by p-tau-181. Among clinical diagnosis groups, higher IR was significantly related to amyloid, p-tau-181, and total tau 181 among AD patients but not MCI or unimpaired groups. These findings suggest that in older adults who develop AD or had AD at baseline, higher IR over time is related to brain atrophy and consequent cognitive decline, perhaps as a function of amyloid or tau deposition.

Background: No studies to date have examined if macular xanthophyll accumulation and retinal integrity are independently associated with cognitive function in individuals with multiple sclerosis (MS). This study explored whether macular xanthophyll accumulation and structural morphometry in the retina were associated with behavioral performance and neuroelectric function during a computerized cognitive task among persons with MS and healthy controls (HCs).Methods: 42 HCs and 42 individuals with MS aged 18-64 years were enrolled. Macular pigment optical density (MPOD) was measured using heterochromatic flicker photometry. Optic disc retinal nerve fiber layer (odRNFL), macular retinal nerve fiber layer, and total macular volume were assessed via optical coherence tomography. Attentional inhibition was assessed using an Eriksen flanker task while underlying neuroelectric function was recorded using event-related potentials.Results: Persons with MS had a slower reaction time, lower accuracy, and delayed P3 peak latency time during both congruent and incongruent trials compared with HCs. Within the MS group, MPOD explained variance in incongruent P3 peak latency, and odRNFL explained variance in congruent reaction time and congruent P3 peak latency.Conclusions: Persons with MS exhibited poorer attentional inhibition and slower processing speed, yet higher MPOD and odRNFL levels were independently associated with greater attentional inhibition and faster pro-cessing speed among persons with MS. Future interventions are necessary to determine if improvements in these metrics may promote cognitive function among persons with MS.

PURPOSE: Previous studies reported muscular strength may protect against cognitive decline in aging adults. However, the specific aspects of cognitive function that may be sensitive to muscular strength are unclear. Thus, this study sought to explore the cross-sectional relationship between muscular strength, cathepsin B (CTSB), and the N2 and P3 event related potentials (ERPs), neurophysiological markers of inhibition and attention. METHODS: Adults (N = 37; 45-64 yrs) underwent strength testing measured via isokinetic knee extensions at 60, 120, and 180 deg·s-1. Inhibitory control and attentional resource allocation was assessed through neuroelectrical indices of the N2 and P3 during the Eriksen Flanker task. Lean body mass was measured through dual X-ray absorptiometry. CTSB was measured in plasma samples after an overnight fast and analyzed via enzyme-linked immunosorbent assay (ELISA). RESULTS: Isokinetic strength was determined by summing the respective z-scores of the peak torque at each velocity. Upon adjusting for covariates, isokinetic strength was inversely associated with congruent (β = -0.664, P = 0.005) and incongruent (β = -0.655, P = 0.005) reaction time, but not accuracy. Similarly, isokinetic strength was inversely associated with congruent (β = -0.619, P = 0.014) and incongruent (β = -0.532, P = 0 .026) mean amplitude, as well as incongruent fractional peak latency (β = -0.736, P = 0.003) of the N2. However, isokinetic strength was not associated with the P3. Similar to isokinetic strength, CTSB was inversely associated with congruent (β = -0.479, P = 0.002) and incongruent (β = -0.437, P = 0.004) reaction time, but not accuracy. However, CTSB was not associated with the N2. Finally, CTSB was inversely associated with incongruent fractional peak latency of the P3 (β = -0.356, P = 0.042). CONCLUSION: These findings suggest that greater muscular strength and CTSB may support cognitive control through different neuroelectrical pathways, particularly when upregulation of cognitive control is required. Specifically, individuals with greater isokinetic strength exhibit greater ability to allocate resources to inhibitory control while exhibiting faster information processing speed, and individuals with greater CTSB exhibit faster stimulus processing. This work was funded by The Beef Checkoff.

Yoga, a physical and contemplative practice, offers the practitioner a unique mind-body exercise experience demonstrating preliminary efficacy in improving cognitive health. We examine the evidence for underlying mechanisms that explain the yoga-cognition relationship in healthy older adults. The cognitive benefits of yoga may be the result of improved stress regulation and neurocognitive resource efficiency that facilitate bidirectional brain-body communication.

BACKGROUND:Moderate-to-vigorous physical activity (MVPA) may confer benefits for axonal and/or neuronal integrity in adults with multiple sclerosis (MS).PURPOSE:Examine the association between device-measured MVPA with optical coherence tomography (OCT) metrics of retinal nerve fiber layer (RNFL) thickness and total macular volume (TMV) in persons with and without MS.METHODS:Adults with MS (N = 41), along with sex-matched healthy control (HC) participants (N = 79), underwent measurements of retinal morphology via OCT and wore an accelerometer for a period of 7 days as a measure of MVPA.RESULTS:Persons with MS had significantly lower MVPA, RNFL thickness, and TMV compared with HCs. MVPA was correlated with RNFL (r = .38, P < .01) thickness and TMV (r = .49, P < .01). Hierarchical linear regression analyses indicated that addition of MVPA attenuated the Group effect on RNFL and TMV. MVPA accounted for 8% and 3% of the variance in TMV (β = .343, P < .01) and RNFL thickness (β = .217, P = .03), respectively.CONCLUSION:MVPA was positively associated with axonal and neuronal integrity assessed by OCT and partially explained group differences in those metrics. These results present possible future targets for MS management by increasing MVPA.

Although muscular strength has been linked to greater cognitive function across different cognitive domains, the mechanism(s) through which this occurs remain(s) poorly understood. Indeed, while an emerging body of literature suggests peripheral myokines released from muscular contractions may play a role in this relationship, additional research is needed to understand this link. Accordingly, this study sought to compare the influences of a particular myokine, Cathepsin B (CTSB), and muscular strength on hippocampal-dependent relational memory and cognitive control in 40 adults (age = 50.0±7.3 yrs). Overnight fasted venous blood draws were taken to assess plasma CTSB and muscular strength was assessed as maximal isokinetic strength testing using a Biodex dynamometer. Cognitive performance was assessed using a Spatial Reconstruction Task to assess relational memory and a modified Flanker task to assess cognitive control. Neuroelectric function for cognitive control was assessed using event-related potentials (ERPs) recorded during the Flanker task. Initial bivariate correlational analyses revealed that neither sex, age, lean body mass, or muscular strength was associated with CTSB. However, CTSB was inversely associated with reaction time and fractional peak latency of the P3 component of the Flanker task. Muscular strength was also inversely associated with reaction time and positively associated with relational memory performance. However, the influence of muscular strength on relational memory did not persist following adjustment for covariates. Greater circulating CTSB was selectively associated with greater cognitive control as well as faster information processing speed. These findings are the first to link circulating CTSB to both cognitive control and neuroelectric function. Future intervention studies are needed to examine the effects of changes in muscular strength, circulating myokines, and different domains of cognitive function.

BACKGROUNDMultiple sclerosis (MS) can cause retinal thinning among persons with MS with optic neuritis (MS-ON). Macular xanthophylls are carotenoids that comprise the macular pigment, filtering blue light and countering photo-oxidation. However, macular xanthophyll status and its implications for markers of neuroaxonal degeneration have not been examined in MS.OBJECTIVESThis study characterized differences in macular and serum xanthophylls, and retinal morphometry [retinal nerve fiber layer thickness at the macular (mRNFL) and optic disc (odRNFL) and total macular volume (TMV)] in individuals with MS and healthy controls (HC). Associations between macular pigment optical density (MPOD) and retinal morphometry were also examined.METHODSAdults aged 45-64 y (HC, n = 42; MS, n = 40) participated in a cross-sectional study. MPOD was measured via heterochromatic flicker photometry. Retinal morphometry was measured via optical coherence tomography (OCT). Serum carotenoids were quantified using HPLC. Dietary carotenoids were collected using 7-d records. One-factor ANOVA was conducted to determine group effects on macular, serum, and dietary carotenoids. Partial correlations examined the relations between MPOD, retinal morphometry, diet, and serum carotenoids.RESULTSRelative to HC, persons with MS-ON had lower MPOD (Cohen's d = 0.84, P = 0.014), lower odRNFL (Cohen's d = 2.16, P <0.001), lower mRNFL (Cohen's d = 0.57, P = 0.028), and lower TMV (Cohen's d = 0.95, P = 0.011). MS without ON (MS) had lower odRNFL (Cohen's d = 0.93, P = 0.001) than HC and lower serum lutein than MS-ON subjects (Cohen's d = 0.65, P = 0.014). Among MS, MPOD was positively correlated with odRNFL thickness (ρ = 0.43, P = 0.049) and TMV (ρ = 0.45, P = 0.039), whereas odRNFL was negatively correlated with serum lutein (ρ = -0.68, P = 0.016) and zeaxanthin (ρ = -0.62, P = 0.028).CONCLUSIONSPersons with MS-ON exhibited poorer xanthophyll status in the macula and serum. MPOD was associated with beneficial anatomical features in the MS group. These findings warrant confirmation with larger cohorts and prospective trials to evaluate xanthophyll effects on the anterior visual pathway in MS.