Environmental effects on brain functional networks in a juvenile twin population.

The brain's intrinsic organization into large-scale functional networks, the resting state networks (RSN), shows complex inter-individual variability, consolidated during development. Nevertheless, the role of gene and environment on developmental brain functional connectivity (FC) remains largely unknown. Twin design represents an optimal platform to shed light on these effects acting on RSN characteristics. In this study, we applied statistical twin methods to resting-state functional magnetic resonance imaging (rs-fMRI) scans from 50 young twin pairs (aged 10-30 years) to preliminarily explore developmental determinants of brain FC. Multi-scale FC features were extracted and tested for applicability of classical ACE and ADE twin designs. Epistatic genetic effects were also assessed. In our sample, genetic and environmental effects on the brain functional connections largely varied between brain regions and FC features, showing good consistency at multiple spatial scales. Although we found selective contributions of common environment on temporo-occipital connections and of genetics on frontotemporal connections, the unique environment showed a predominant effect on FC link- and node-level features. Despite the lack of accurate genetic modeling, our preliminary results showed complex relationships between genes, environment, and functional brain connections during development. A predominant role of the unique environment on multi-scale RSN characteristics was suggested, which needs replications on independent samples. Future investigations should especially focus on nonadditive genetic effects, which remain largely unexplored.

Characterization of regional differences in resting-state fMRI with a data-driven network model of brain dynamics.

Model-based data analysis of whole-brain dynamics links the observed data to model parameters in a network of neural masses. Recently, studies focused on the role of regional variance of model parameters. Such analyses however necessarily depend on the properties of preselected neural mass model. We introduce a method to infer from the functional data both the neural mass model representing the regional dynamics and the region- and subject-specific parameters while respecting the known network structure. We apply the method to human resting-state fMRI. We find that the underlying dynamics can be described as noisy fluctuations around a single fixed point. The method reliably discovers three regional parameters with clear and distinct role in the dynamics, one of which is strongly correlated with the first principal component of the gene expression spatial map. The present approach opens a novel way to the analysis of resting-state fMRI with possible applications for understanding the brain dynamics during aging or neurodegeneration.

Region Anomaly Detection via Spatial and Semantic Attributed Graph in Human Monitoring.

This paper proposes a graph-based deep framework for detecting anomalous image regions in human monitoring. The most relevant previous methods, which adopt deep models to obtain salient regions with captions, focus on discovering anomalous single regions and anomalous region pairs. However, they cannot detect an anomaly involving more than two regions and have deficiencies in capturing interactions among humans and objects scattered in multiple regions. For instance, the region of a man making a phone call is normal when it is located close to a kitchen sink and a soap bottle, as they are in a resting area, but abnormal when close to a bookshelf and a notebook PC, as they are in a working area. To overcome this limitation, we propose a spatial and semantic attributed graph and develop a Spatial and Semantic Graph Auto-Encoder (SSGAE). Specifically, the proposed graph models the "context" of a region in an image by considering other regions with spatial relations, e.g., a man sitting on a chair is adjacent to a white desk, as well as other region captions with high semantic similarities, e.g., "a man in a kitchen" is semantically similar to "a white chair in the kitchen". In this way, a region and its context are represented by a node and its neighbors, respectively, in the spatial and semantic attributed graph. Subsequently, SSGAE is devised to reconstruct the proposed graph to detect abnormal nodes. Extensive experimental results indicate that the AUC scores of SSGAE improve from 0.79 to 0.83, 0.83 to 0.87, and 0.91 to 0.93 compared with the best baselines on three real-world datasets.

Determining Work-Rest Schedules for Visual Tasks That Use Optical Head-Mounted Displays Based on Visual Fatigue and Visually Induced Motion Sickness Recovery.

This study aimed to determine work-rest schedules for visual tasks of different lengths by evaluating visual fatigue and visually induced motion sickness (VIMS) using an optical head-mounted display (OHMD). Thirty participants were recruited to perform 15 and 30 min visual tasks using an OHMD. After completing each visual task, participants executed six levels of rest time. Critical flicker fusion frequency (CFF) values, relative electroencephalography indices, and Simulator Sickness Questionnaire (SSQ) scores were collected and analyzed. Results indicated that after completing the 15 and 30 min visual tasks, participants experienced visual fatigue and VIMS. There was no significant difference between baseline CFF values, four electroencephalography relative power index values, and SSQ scores when participants completed a 15 min visual task followed by a 20 min rest and a 30 min visual task followed by a 30 min rest. Based on our results, a 20 min rest for visual fatigue and VIMS recovery after a 15 min visual task on an OHMD and a 25 min rest for visual fatigue and VIMS recovery after a 30 min visual task on an OHMD are recommended. This study suggests a work-rest schedule for OHMDs that can be used as a reference for OHMD user guidelines to reduce visual fatigue and visually induced motion sickness.

Physiological demands and motion analysis of elite foil fencing.

The aim of this study was to determine the physiological demands and motion analysis of a simulated fencing competition. Eighteen fencers each completed 5 'poule' (5 touches) and 'direct elimination (DE)' (15 touches) fights. Expired gases were measured during 1 poule and DE fight. Heart rate (HR), ratings of perceived exertion (RPE) and movement data were recorded throughout all fights. Motion analysis was undertaken using the software LINCE PLUS. Differences between poule and DE fights were determined by either a paired t-test or a one-way repeated measures ANOVA. HR and RPE were significantly greater during DE compared to poule (170 ±10 vs 163 ±13 beats·min-1; P<0.05). A greater distance was covered during a DE fight compared to a poule fight (459.9 ± 117.7 m vs 162.6 ± 74.2 m; P<0.05). The average values of [Formula: see text] were 42.5 ±5.6 ml·kg-1·min-1 in men and 34.4 ±3.2 ml·kg-1·min-1 in women. Work-to-rest ratios reduced during the DE fights along with a lower average speed and increased max speed (11.7 ± 2.8 km∙h-1 vs 9.6 ± 1.6 km∙h-1; P<0.05). In conclusion, there is an increased physiological demand during a DE fight accompanied by a reduction in average speed and decreased work-to-rest ratio.

Paranormal believers show reduced resting EEG beta band oscillations and inhibitory control than skeptics.

Paranormal believers' thinking is frequently biased by intuitive beliefs. Lack of inhibition of these tempting beliefs is considered a key element in paranormal believers' thinking. However, the brain activity related to inhibitory control in paranormal believers is poorly understood. We examined EEG activities at resting state in alpha, beta, and gamma bands with inhibitory control in paranormal believers and skeptics. The present study shows that paranormal belief is related to the reduced power of the alpha, beta, and gamma frequency bands, and reduced inhibitory control. This study may contribute to understanding the differences between believers and skeptics in brain activity related to inhibitory control in paranormal believers.

Manipulating the Rapid Consolidation Periods in a Learning Task Affects General Skills More than Statistical Learning and Changes the Dynamics of Learning.

Memory consolidation processes have traditionally been investigated from the perspective of hours or days. However, recent developments in memory research have shown that memory consolidation processes could occur even within seconds, possibly because of the neural replay of just practiced memory traces during short breaks. Here, we investigate this rapid form of consolidation during statistical learning. We aim to answer (1) whether this rapid consolidation occurs in implicit statistical learning and general skill learning, and (2) whether the duration of rest periods affects these two learning types differently. Human participants performed a widely used statistical learning task-the alternating serial reaction time (ASRT) task-that enables us to measure implicit statistical and general skill learning separately. The ASRT task consisted of 25 learning blocks with a rest period between the blocks. In a between-subjects design, the length of the rest periods was fixed at 15 or 30 s, or the participants could control the length themselves. We found that the duration of rest periods does not affect the amount of statistical knowledge acquired but does change the dynamics of learning. Shorter rest periods led to better learning during the learning blocks, whereas longer rest periods promoted learning also in the between-block rest periods, possibly because of the higher amount of replay. Moreover, we found weaker general skill learning in the self-paced group than in the fixed rest period groups. These results suggest that distinct learning processes are differently affected by the duration of short rest periods.

Mood Status Response to Physical Activity and Its Influence on Performance: Are Chronotype and Exercise Timing Affect?

PURPOSE: It is well known that there is an obvious 24 h diurnal variation in the individual's mood state and physiological activity, and training at different times of the day may lead to different exercise performance and metabolic outcomes; however, the time-dependent effect of emotional state on physical activity and the influence of its circadian rhythm on exercise performance are still not comprehensively understood. Based on this, this study summarizes the rhythmic experimental research in the field of sport psychology, and it aims to provide the basis for coaches to optimize sports training scientifically and to improve the mental health of the related crowd to the greatest extent. METHODS: The systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched the PubMed, Web of Science, Medline, and CNKI databases for relevant literature; the search scope was research before September 2022. RESULTS: 13 studies comprising 382 subjects examined the effects of exercise timing on mood responses to exercise or the effects of circadian rhythms of mood on exercise performance, which included 3 RCTs and 10 Non-RCTs. The subjects included athletes (both training or retired), college students, and healthy adults. Two studies were designed for long-term exercise intervention (aerobic training and RISE) and the rest for acute intervention (CrossFit training, HIIT, aerobic combined with muscle conditioning training, constant power exhaustion training, and cycling) or physical function tests (RSA + BTV tests, 30 s Wingate test, muscle strength + CMJ + swimming performance test, RSSJA, shooting accuracy tests + 10 × 20 m dribbling sprint, 200 m time trials). All trials reported specific exercise timing; of these, 10 studies reported subjects' chronotypes, most commonly using the MEQ scale, while 1 recorded with the CSM. Mood responses were assessed with the POMS scale in 10 studies, while 3 other studies used the UMACL, PANAS, and GAS scales, respectively. CONCLUSION: There was much inconsistency between the results, with subjects likely to be exposed to more sunlight (the main timing factor of the circadian rhythm) during early morning exercise, resulting in feeling more positive emotions; however, following a night's rest, delayed responses and poor functioning of the various organ systems of the human body may also lead to higher feelings of fatigue and negative emotions indirectly. Conversely, for athletes, their physical function tests are also more susceptible to the circadian rhythm of emotions, suggesting the importance of synchronizing them. In addition, night owls' emotional state during physical activity seems to be more susceptible to exercise timing than that of early birds. In order to achieve the best emotional state, it is suggested that night owls arrange courses in the afternoon or evening in future training.

Pre- and post-task resting-state differs in clinical populations.

Resting-state functional connectivity has generated great hopes as a potential brain biomarker for improving prevention, diagnosis, and treatment in psychiatry. This neuroimaging protocol can routinely be performed by patients and does not depend on the specificities of a task. Thus, it seems ideal for big data approaches that require aggregating data across multiple studies and sites. However, technical variability, diverging data analysis approaches, and differences in data acquisition protocols introduce heterogeneity to the aggregated data. Besides these technical aspects, a prior task that changes the psychological state of participants might also contribute to heterogeneity. In healthy participants, studies have shown that behavioral tasks can influence resting-state measures, but such effects have not yet been reported in clinical populations. Here, we fill this knowledge gap by comparing resting-state functional connectivity before and after clinically relevant tasks in two clinical conditions, namely substance use disorders and phobias. The tasks consisted of viewing craving-inducing and spider anxiety provoking pictures that are frequently used in cue-reactivity studies and exposure therapy. We found distinct pre- vs post-task resting-state connectivity differences in each group, as well as decreased thalamo-cortical and increased intra-thalamic connectivity which might be associated with decreased vigilance in both groups. Our results confirm that resting-state measures can be strongly influenced by prior emotion-inducing tasks that need to be taken into account when pooling resting-state scans for clinical biomarker detection. This demands that resting-state datasets should include a complete description of the experimental design, especially when a task preceded data collection.

Sedentary behaviour and sleep quality.

High-quality sleep is an important factor in sustaining health and improving well-being. Previous evidence has demonstrated the positive associations between increased physical activity and reduced sedentary behaviour (SB) with sleep quality. The substitutional relationships between SB, light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) need to be considered when examining how a particular behaviour may impact sleep quality. No studies, to our knowledge, have explored these substitutional relationships in middle-aged adulthood. Using an isotemporal substitution approach, this study examined the associations of replacing sedentary time with physical activity on sleep quality measures in a sample of middle-aged adults in Japan. Data from 683 adults aged 40-64 living in Japan were used. The average daily time spent in SB, LPA, and MVPA was objectively assessed by accelerometers. Two self-reported sleep quality measures were obtained using questionnaires, including rest by sleep and sleep quality. Multivariable linear regression models were used to assess the associations of SB, LPA, and MVPA with the sleep quality measures stratified by gender. We found that each 60 min unit of SB or LPA replaced with MVPA was favourably associated with rest by sleep among women (ß = 0.16, 95% CI 0.07, 0.28, p < 0.001; ß = 0.18, 95% CI 0.07, 0.32, p < 0.05, respectively). There were no significant associations between SB, LPA, and MVPA with sleep measures in men across all three models. These findings indicate that higher MVPA has a positive association with sleep quality in middle-aged women.

Links between excessive daytime sleepiness and EEG power and activation in two subtypes of ADHD.

OBJECTIVES: This study aimed to replicate previously reported EEG characteristics between typically developing (TD) children and two subtypes of Attention Deficit Hyperactivity Disorder (ADHD) using a frontal, single-channel, dry-sensor portable EEG device, and explore whether differences are moderated by excessive daytime sleepiness (EDS). METHODS: Children with ADHD Inattentive (ADHD-I) and ADHD Combined presentation (ADHD-C) and typically-developing (TD) children (N = 34 in each group) had frontal EEG recorded during eyes-closed resting, eyes-open resting, and focus tasks. Participants also completed the Children's Self-Report Sleep Patterns - Sleepiness Scale as a measure of EDS. RESULTS: Consistent with previous literature, there were increases in frontal delta and theta power in the ADHD-C compared to ADHD-I and TD groups, in all conditions. Novel power and activation effects in ADHD subtypes, as well as significant group and EDS interactions for alpha and beta power were also found. CONCLUSIONS: These findings highlight the importance of considering ADHD subtypes and EDS when exploring EEG characteristics, and have important implications for the diagnosis and treatment of children with ADHD.

Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study.

The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time-resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time-resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U-shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State-based statistical summary measures presented robust and significant group differences that also showed significant age-related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time-resolved brain state trajectories.

Activity flow mapping over probabilistic functional connectivity.

Emerging evidence indicates that activity flow over resting-state network topology allows the prediction of task activations. However, previous studies have mainly adopted static, linear functional connectivity (FC) estimates as activity flow routes. It is unclear whether an intrinsic network topology that captures the dynamic nature of FC can be a better representation of activity flow routes. Moreover, the effects of between- versus within-network connections and tight versus loose (using rest baseline) task contrasts on the prediction of task-evoked activity across brain systems remain largely unknown. In this study, we first propose a probabilistic FC estimation derived from a dynamic framework as a new activity flow route. Subsequently, activity flow mapping was tested using between- and within-network connections separately for each region as well as using a set of tight task contrasts. Our results showed that probabilistic FC routes substantially improved individual-level activity flow prediction. Although it provided better group-level prediction, the multiple regression approach was more dependent on the length of data points at the individual-level prediction. Regardless of FC type, we consistently observed that between-network connections showed a relatively higher prediction performance in higher-order cognitive control than in primary sensorimotor systems. Furthermore, cognitive control systems exhibit a remarkable increase in prediction accuracy with tight task contrasts and a decrease in sensorimotor systems. This work demonstrates that probabilistic FC estimates are promising routes for activity flow mapping and also uncovers divergent influences of connectional topology and task contrasts on activity flow prediction across brain systems with different functional hierarchies.

Brain network integration, segregation and quasi-periodic activation and deactivation during tasks and rest.

Previous studies have shown that a re-organization of the brain's functional connectome expressed in terms of network integration and segregation may play a pivotal role for brain function. However, it has been proven difficult to fully capture both processes independently in a single methodological framework. In this study, by starting from pair-wise assessments of instantaneous phase synchronization and community membership, we assemble spatiotemporally flexible networks that reflect changes in integration/segregation that occur at a spectrum of spatial as well as temporal scales. This is achieved by iteratively assembling smaller networks into larger units under the constraint that the smaller units should be internally integrated, i.e. belong to the same community. The assembled subnetworks can be partly overlapping and differ in size across time. Our results show that subnetwork integration and segregation occur simultaneously in the brain. During task performance, global changes in synchronization between networks arise that are tied to the underlying temporal design of the experiment. We show that a hallmark property of the dynamics of the brain's functional connectome is a presence of quasi-periodic patterns of network activation and deactivation, which during task performance becomes intertwined with the underlying temporal structure of the experimental paradigm. Additionally, we show that the degree of network integration throughout a n-back working memory task is correlated to performance.

Rest is essential for effective therapies, and so it is for preparing a manuscript.

Numerous medical articles are commented upon. This suggests that their scientific quality is insufficient. This need not be the case, however: most comments regard the presentation of the data, the conclusions or lacking information in the discussion. Such flaws can commonly be attributed to either too much haste in writing the manuscript, or insufficient time between finishing the manuscript and submission; this last problem seems the most common cause, as it deprives the author from reading his own text critically and with an open mind. The solution for this problem is simple: after having finished a manuscript, it should be laid aside for at least a week, after which the author should read it with the eyes of a reader, not the eyes of an author. Critical, open-minded reading after rest helps increase the quality of the resulting manuscript, just like rest helps a patient during most therapies.

Altered functional connectivity of anterior cingulate cortex in chronic insomnia: A resting-state fMRI study.

The aim of our present study was to explore the connectivity pattern change between the anterior cingulate cortex (ACC) and the voxels from the whole brain in chronic insomnia (CI). With region of interest (ROI)-based functional connectivity, a two-sample t-test was performed on individual FC correlation maps from two groups based on the resting-state fMRI data acquired from 57 CI patients and 46 healthy controls (GRF correction, voxel-level P < 0.001 and cluster-level P < 0.001). A correlation analysis was performed to evaluate the relationship between the clinical features and the abnormal FC. Compared to the healthy controls, the CI patients show increased connectivity between the ACC and the right middle frontal gyrus, with decreased connectivity between the ACC and the bilateral precuneus gyrus. Correlation analysis indicated that the decreased connectivity showed positive correlations with Self-Rating Anxiety Scale (SAS) scores. Our study shows the alterations of CI patients in the level of functional integration and may indicate the dysfunction of communication within brain regions of the default mode network (DMN). These changes and their correlation with negative emotions may provide additional evidence to understand the possible neural mechanisms of CI.

Association of circadian rest-activity rhythms with cardiovascular disease and mortality in type 2 diabetes.

AIMS: To examine the associations of disrupted circadian rest-activity rhythm (CRAR) with cardiovascular diseases and mortality among people with type 2 diabetes. METHODS: A total of 3147 participants with baseline type 2 diabetes (mean age 65.21 years, 39.78% female; mean HbA1c 50.02 mmol/mol) from UK Biobank were included. The following CRAR parameters were derived from acceleration data: interdaily stability (IS), intradaily variability (IV), relative amplitude (RA), most active 10 h period onset (M10 onset), and least active 5 h period onset (L5 onset). We used Cox proportional hazards models to estimate the associations of CRAR with cardiovascular diseases and mortality, adjusting for sociodemographic, lifestyle, and health characteristics. RESULTS: Participants in the lowest quartile of IS and RA exhibited the greatest risk of developing cardiovascular disease (IS, hazard ratio [HR]Q1 vs. Q4 1.40 [95% confidence interval (CI) 1.04, 1.88]; RA, HRQ1 vs. Q4 2.45 [95% CI 1.73, 3.49]). However, the association between delayed L5 onset and cardiovascular disease risk did not reach statistical significance. Additionally, we found that high IV and low RA were associated with all-cause and cardiovascular mortality. CONCLUSION: Objectively determined CRAR disturbances may increase the risk of cardiovascular diseases and mortality among people with type 2 diabetes.

Single voxel autocorrelation uncovers gradients of temporal dynamics in the hippocampus and entorhinal cortex during rest and navigation.

During navigation, information at multiple scales needs to be integrated. Single-unit recordings in rodents suggest that gradients of temporal dynamics in the hippocampus and entorhinal cortex support this integration. In humans, gradients of representation are observed, such that granularity of information represented increases along the long axis of the hippocampus. The neural underpinnings of this gradient in humans, however, are still unknown. Current research is limited by coarse fMRI analysis techniques that obscure the activity of individual voxels, preventing investigation of how moment-to-moment changes in brain signal are organized and how they are related to behavior. Here, we measured the signal stability of single voxels over time to uncover previously unappreciated gradients of temporal dynamics in the hippocampus and entorhinal cortex. Using our novel, single voxel autocorrelation technique, we show a medial-lateral hippocampal gradient, as well as a continuous autocorrelation gradient along the anterolateral-posteromedial entorhinal extent. Importantly, we show that autocorrelation in the anterior-medial hippocampus was modulated by navigational difficulty, providing the first evidence that changes in signal stability in single voxels are relevant for behavior. This work opens the door for future research on how temporal gradients within these structures support the integration of information for goal-directed behavior.

A comparison of nomothetic and individualized alpha frequency approaches to measuring frontal EEG alpha asymmetry.

Frontal alpha asymmetry (FAA) is considered to be a reliable marker of affective processing and psychopathology. Traditionally, the magnitude of alpha is calculated by taking the average over a nomothetic fixed frequency window (e.g., 8 to 13 Hz). Alternatively, methods have been proposed to extract individualized alpha frequency (IAF) peaks and windows in hopes of improving the reliability and validity of signal detection. However, no study has compared the nomothetic to IAF approaches to examine the reliability and validity of resting FAA in a large well-characterized data set. In this study, we assessed the psychometric performance of the standard fixed window approach, a PZ-alpha based IAF approach and a global-alpha based IAF windows detection approach on a previously collected EEG data set (8 recordings per subject collected on four occasions across two weeks). Our results revealed that resting FAA calculated with these three different methods are highly correlated at all frontal regions (mean r = .98). The stability across the 8 recordings over the two weeks also showed no substantial difference between approaches as indicated by intraclass correlations. Moreover, internal-consistency reliability, validity with respect to measures of emotion and emotion-related psychopathology and state-trait Structure equation model (SEM) fitting were evaluated and yielded no significant differences across methods. Our results supported the overall reliability and validity of two different IAF approaches to assessing resting FAA but fail to find any incremental advantage over nomothetic approaches to defining alpha bands. Guidelines for methods selection for future research are provided.