From physiological complexity to data interactions-A case study of recordings from exercise monitoring.

The popularity of nonlinear analysis has been growing simultaneously with the technology of effort monitoring. Therefore, considering the simple methods of physiological data collection and the approaches from the information domain, we proposed integrating univariate and bivariate analysis for the rest and effort comparison. Two sessions separated by an intensive training program were studied. Nine subjects participated in the first session (S1) and seven in the second session (S2). The protocol included baseline (BAS), exercise, and recovery phase. During all phases, electrocardiogram (ECG) was recorded. For the analysis, we selected corresponding data lengths of BAS and exercise usually lasting less than 5 min. We found the utility of the differences between original data and their surrogates for sample entropy Sdiff and Kullback-Leibler divergence KLDdiff. Sdiff of heart rate variability was negative in BAS and exercise but its sensitivity for phases discrimination was not satisfactory. We studied the bivariate analysis of RR intervals and corresponding QT peaks by Interlayer Mutual Information (IMI) and average edge overlap (AVO) markers. While the IMI parameter decreases in exercise conditions, AVO increased in effort compared to BAS. These findings conclude that researchers should consider a bivariate analysis of extracted RR intervals and corresponding QT datasets, when only ECG is recorded during tests.

Developmental relationship between junctional epithelium and epithelial rests of Malassez.

Keratin 17 (K17) is thought to be a candidate target gene for regulation by Lymphoid Enhancer Factor-1 (Lef-1). K17 is a marker that distinguishes junctional epithelium (JE) from epithelial rests of Malassez (ERM). However, the relationship of Lef-1 to K17 is not clear in this context. Moreover, the expression of other keratins such as K5, K6, K7 and K16 is not reported. Therefore, the aim of our study was to assay the expression of K5, K6, K7, K14, K16, K17 and Lef-1 in postnatal developing teeth, and clarify the corresponding immunophenotypes of the JE and ERM. Upper jaws of Wistar rats aged from postnatal (PN) day 3.5 to PN21 were used and processed for immunohistochemistry. K5 and K14 were intensely expressed in inner enamel epithelium (IEE), reduced enamel epithelium (REE), ERM and JE. There was no staining for K16 in the tissue, except for strong staining in the oral epithelium. Specifically, at PN3.5 and PN7, K17 was initially strongly expressed and then negative in the IEE. At PN16 and PN21, both REE and ERM were strongly stained for K17, whereas K17 was negative in the JE. In addition, K6, K7 and Lef-1 were not detected in any tissue investigated. REE and ERM have an identical keratin expression pattern before eruption, while JE differs from ERM in the expression of K17 after eruption. The expression of K17 does not coincide with that of Lef-1. These data indicate that JE has a unique phenotype different from ERM, which is of odontogenic origin.

STELA: a community-centred approach to norm elicitation for AI alignment.

Value alignment, the process of ensuring that artificial intelligence (AI) systems are aligned with human values and goals, is a critical issue in AI research. Existing scholarship has mainly studied how to encode moral values into agents to guide their behaviour. Less attention has been given to the normative questions of whose values and norms AI systems should be aligned with, and how these choices should be made. To tackle these questions, this paper presents the STELA process (SocioTEchnical Language agent Alignment), a methodology resting on sociotechnical traditions of participatory, inclusive, and community-centred processes. For STELA, we conduct a series of deliberative discussions with four historically underrepresented groups in the United States in order to understand their diverse priorities and concerns when interacting with AI systems. The results of our research suggest that community-centred deliberation on the outputs of large language models is a valuable tool for eliciting latent normative perspectives directly from differently situated groups. In addition to having the potential to engender an inclusive process that is robust to the needs of communities, this methodology can provide rich contextual insights for AI alignment.

Functional connectivity between the habenula and posterior default mode network contributes to the response of the duloxetine effect in major depressive disorder.

This study aims to investigate the functional connectivity (FC) changes of the habenula (Hb) among patients with major depressive disorder (MDD) after 12 weeks of duloxetine treatment (MDD12). Patients who were diagnosed with MDD for the first time and were drug-naïve were recruited at baseline as cases. Healthy controls (HCs) matched for sex, age, and education level were also recruited at the same time. At baseline, all participants underwent resting-state functional MRI. FC analyses were performed using the Hb seed region of interest, and three groups including HCs, MDD group and MDD12 group were compared using whole-brain voxel-wise comparisons. Compared to the HCs, the MDD group had decreased FC between the Hb and the right anterior cingulate cortex at baseline. Compared to the HCs, the FC between the Hb and the left medial superior frontal gyrus decreased in the MDD12 group. Additionally, the FC between the left precuneus, bilateral cuneus and Hb increased in the MDD12 group than that in the MDD group. No significant correlation was found between HDRS-17 and the FC between the Hb, bilateral cuneus, and the left precuneus in the MDD12 group. Our study suggests that the FC between the post-default mode network and Hb may be the treatment mechanism of duloxetine and the treatment mechanisms and the pathogenesis of depression may be independent of each other.

On the interplay between state-dependent reconfigurations of global signal correlation and BOLD fluctuations: An fMRI study.

BACKGROUND: The dynamics of global, state-dependent reconfigurations in brain connectivity are yet unclear. We aimed at assessing reconfigurations of the global signal correlation coefficient (GSCORR), a measure of the connectivity between each voxel timeseries and the global signal, from resting-state to a stop-signal task. The secondary aim was to assess the relationship between GSCORR and blood-oxygen-level-dependent (BOLD) activations or deactivation across three different trial-conditions (GO, STOP-correct, and STOP-incorrect). METHODS: As primary analysis we computed whole-brain, voxel-wise GSCORR during resting-state (GSCORR-rest) and stop-signal task (GSCORR-task) in 107 healthy subjects aged 21-50, deriving GSCORR-shift as GSCORR-task minus GSCORR-rest. GSCORR-tr and trGSCORR-shift were also computed on the task residual time series to quantify the impact of the task-related activity during the trials. To test the secondary aim, brain regions were firstly divided in one cluster showing significant task-related activation and one showing significant deactivation across the three trial conditions. Then, correlations between GSCORR-rest/task/shift and activation/deactivation in the two clusters were computed. As sensitivity analysis, GSCORR-shift was computed on the same sample after performing a global signal regression and GSCORR-rest/task/shift were correlated with the task performance. RESULTS: Sensory and temporo-parietal regions exhibited a negative GSCORR-shift. Conversely, associative regions (ie. left lingual gyrus, bilateral dorsal posterior cingulate gyrus, cerebellum areas, thalamus, posterolateral parietal cortex) displayed a positive GSCORR-shift (FDR-corrected p < 0.05). GSCORR-shift showed similar patterns to trGSCORR-shift (magnitude increased) and after global signal regression (magnitude decreased). Concerning BOLD changes, Brodmann area 6 and inferior parietal lobule showed activation, while posterior parietal lobule, cuneus, precuneus, middle frontal gyrus showed deactivation (FDR-corrected p < 0.05). No correlations were found between GSCORR-rest/task/shift and beta-coefficients in the activation cluster, although negative correlations were observed between GSCORR-task and GO/STOP-correct deactivation (Pearson rho=-0.299/-0.273; Bonferroni-p < 0.05). Weak associations between GSCORR and task performance were observed (uncorrected p < 0.05). CONCLUSION: GSCORR state-dependent reconfiguration indicates a reallocation of functional resources to associative areas during stop-signal task. GSCORR, activation and deactivation may represent distinct proxies of brain states with specific neurofunctional relevance.

Sleep Inertia in Aviation.

INTRODUCTION: Sleep inertia is the transition state during which alertness and cognitive performance are temporarily impaired after awakening. Magnitude and time course of sleep inertia are characterized by high individual variability with large differences between the cognitive functions affected. This period of impairment is of concern to pilots, who take sleep or nap periods during on-call work hours or in-flight rest, then need to perform safety-critical tasks soon after waking. This review analyzes literature related to sleep inertia and countermeasures applicable for aviation.METHODS: The large part of scientific literature that focuses on sleep inertia is based on studies in patients with chronic sleep inertia. We analyzed 8 narrative reviews and 64 papers related to acute sleep inertia in healthy subjects.DISCUSSION: Sleep inertia is a multifactorial, complex process, and many different protocols have been conducted, with a low number of subjects, in noncontrolled laboratory designs, with questionnaires or cognitive tests that have not been replicated. Evidence suggests that waking after sleep loss, or from deeper stages of sleep, can exacerbate sleep inertia through complex interactions between awakening and sleep-promoting brain structures. Nevertheless, no meta-analyses are possible and extrapolation to pilots' performances is hypothetical. Studies in real life or simulated operational situations must be conducted to improve the description of the impact of sleep inertia and kinetics on pilots' performances. Taking rest or sleep time remains the main method for pilots to fight against fatigue and related decreases in performance. We propose proactive strategies to mitigate sleep inertia and improve alertness.Sauvet F, Beauchamps V, Cabon P. Sleep inertia in aviation. Aerosp Med Hum Perform. 2024; 95(4):206-213.

No Frequency-Specific Effect of Transcranial Random Noise Stimulation on Resting EEG.

BACKGROUND: Transcranial random noise stimulation (tRNS) is a form of noninvasive transcranial electrical stimulation that applies alternating current in various randomized frequencies to the cortex, thereby improving cognitive functioning in multiple domains. However, the precise mechanism of tRNS, as well as its impact on human electroencephalography (EEG), remains unclear. This is partly because most studies have used tRNS in conjunction with a cognitive task, making it difficult to tease apart whether the observed changes in EEG are a result of tRNS, the cognitive task, or their interaction. METHODS: Forty-nine healthy individuals participated in this study and were randomly assigned to active tRNS (n = 24) and sham (n = 25) groups. tRNS was delivered for 20 minutes over Fp1/Fp2 and Oz. Resting-state EEG data were collected before and after either tRNS or sham stimulation. RESULTS: Cluster-based permutation tests using FieldTrip revealed no frequency-specific effect of tRNS on resting-state EEG data across four frequency bands (theta, alpha, beta, gamma). CONCLUSIONS: These observations suggest that tRNS itself does not target or alter specific EEG frequencies. Rather, tRNS most likely interacts with the cognitive task/activity at hand to produce an observable difference in post-tRNS EEG. Positive tRNS-EEG findings from previous studies are also likely to have resulted from the interactive and cognitive activity-dependent nature of tRNS.

The dorsomedial prefrontal cortex prioritizes social learning during rest.

Sociality is a defining feature of the human experience: We rely on others to ensure survival and cooperate in complex social networks to thrive. Are there brain mechanisms that help ensure we quickly learn about our social world to optimally navigate it? We tested whether portions of the brain's default network engage "by default" to quickly prioritize social learning during the memory consolidation process. To test this possibility, participants underwent functional MRI (fMRI) while viewing scenes from the documentary film, Samsara. This film shows footage of real people and places from around the world. We normed the footage to select scenes that differed along the dimension of sociality, while matched on valence, arousal, interestingness, and familiarity. During fMRI, participants watched the "social" and "nonsocial" scenes, completed a rest scan, and a surprise recognition memory test. Participants showed superior social (vs. nonsocial) memory performance, and the social memory advantage was associated with neural pattern reinstatement during rest in the dorsomedial prefrontal cortex (DMPFC), a key node of the default network. Moreover, it was during early rest that DMPFC social pattern reinstatement was greatest and predicted subsequent social memory performance most strongly, consistent with the "prioritization" account. Results simultaneously update 1) theories of memory consolidation, which have not addressed how social information may be prioritized in the learning process, and 2) understanding of default network function, which remains to be fully characterized. More broadly, the results underscore the inherent human drive to understand our vastly social world.

Weights, resistance bands, and rest days are best for tendinopathy.

The studyPavlova AV, Shim JSC, Moss R, et al. Effect of resistance exercise dose components for tendinopathy management: a systematic review with meta-analysis. Br J Sports Med 2023;57:1327-34.To read the full NIHR Alert, go to: https://evidence.nihr.ac.uk/alert/weights-resistance-bands-rest-days-best-tendinopathy/.

Does rest interval between unilateral exercise protocols influences on contralateral neuromuscular responses in untrained individuals?

INTRODUCTION: Effects on strength performance and muscle activation in the contralateral limb have been observed after training with the ipsilateral limb (IL). Cross fatigue effects in the contralateral limb (CL) can occur at intervals of up to 48 h after a training session performed with the ipsilateral limb. The objective of this study was to verify the effect of a training session in the ipsilateral limb, on the strength and activation of the muscles in the contralateral limb also submitted to the training protocol. METHODS: 10 untrained men (mean ± SD: age = 23.7 ± 4.9 years) performed unilateral knee extension with both limbs in equated protocols, in two conditions with different intervals between limbs - 20 min and 24 h. RESULTS: There were no differences in the comparison of the force produced between the pre x post interventions with the CL limb, as well as in the activation of the quadriceps during its performance. These results were similar for the two different intervals between the protocols. CONCLUSION: It was concluded that when the CL member performs the protocol after the IL, the responses in the CL depend mainly on the requirement imposed on the protocol performed by this member, without influence of the training protocol performed previously with the IL member.

Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis.

BACKGROUND: Individuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD. METHODS: Neuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global 'variability score'. Pairwise correlational distance was calculated as 1 - the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability. RESULTS: Group comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01). CONCLUSIONS: Diagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.

Functional connectivity and complexity analyses of resting-state fMRI in pre-adolescents demonstrating the behavioral symptoms of ADHD.

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), reward and motivation-related circuits (RMN), and salience network (SAL). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with the behavioral symptoms of ADHD, for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children demonstrating the behavioral features of ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in the relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents demonstrating the behavior symptoms of ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in the FPN and RMN in the healthy controls however the association was absent in the participants demonstrating the behavior symptoms of ADHD. The current findings of complexity and FC in ADHD pathology support hypotheses of altered function of inhibitory control networks in ADHD.

Cortical timescales and the modular organization of structural and functional brain networks.

Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the "timescale" over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.

Age Is Associated With Dampened Circadian Patterns of Rest and Activity: The Study of Muscle, Mobility, and Aging (SOMMA).

BACKGROUND: The effects of aging on circadian patterns of behavior are insufficiently described. To address this, we characterized age-specific features of rest-activity rhythms (RAR) in community-dwelling older adults both overall, and in relation, to sociodemographic characteristics. METHODS: We examined cross-sectional associations between RAR and age, sex, race, education, multimorbidity burden, financial, work, martial, health, and smoking status using assessments of older adults with wrist-worn free-living actigraphy data (N = 820, age = 76.4 years, 58.2% women) participating in the Study of Muscle, Mobility, and Aging (SOMMA). RAR parameters were determined by mapping an extension to the traditional cosine curve to activity data. Functional principal component analysis determined variables accounting for variance. RESULTS: Age was associated with several metrics of dampened RAR; women had stronger and more robust RAR versus men (all p < .05). Total activity (56%) and time of activity (20%) accounted for most of the RAR variance. Compared to the latest decile of acrophase, those in the earliest decile had higher average amplitude (p < .001). Compared to the latest decile of acrophase, those in the earliest and midrange categories had more total activity (p = .02). Being in a married-like relationship and a more stable financial situation were associated with stronger rhythms; higher education was associated with less rhythm strength (all p < .05). CONCLUSIONS: Older age was associated with dampened circadian behavior; behaviors were sexually dimorphic. Some sociodemographic characteristics were associated with circadian behavior. We identified a behavioral phenotype characterized by early time of day of peak activity, high rhythmic amplitude, and more total activity.

High-skilled first-person shooting game players have specific frontal lobe activity: Power spectrum analysis in an electroencephalogram study.

First-person shooting (FPS) games are among the most famous video games worldwide. However, cortical activities in environments related to real FPS games have not been studied. This study aimed to determine differences in cortical activity between low- and high-skilled FPS game players using 160-channel electroencephalography. Nine high-skilled FPS game players (official ranks: above the top 10%) and eight low-skilled FPS game players (official ranks: lower than the top 20%) were recruited for the experiment. The task was set for five different conditions using the AimLab program, which was used for the FPS game players' training. Additionally, we recorded the brain activity in the resting condition before and after the task, in which the participants closed their eyes and relaxed. The reaction time and accuracy (the number of hit-and-miss targets) were calculated to evaluate the task performance. The results showed that high-skilled FPS game players have fast reaction times and high accuracy during tasks. High-skilled FPS game players had higher cortical activity in the frontal cortex than low-skilled FPS game players during each task. In low-skilled players, cortical activity level and performance level were associated. These results suggest that high cortical activity levels were critical to achieving high performance in FPS games.

Resting state electroencephalographic alpha rhythms are sensitive to Alzheimer's disease mild cognitive impairment progression at a 6-month follow-up.

Are posterior resting-state electroencephalographic (rsEEG) alpha rhythms sensitive to the Alzheimer's disease mild cognitive impairment (ADMCI) progression at a 6-month follow-up? Clinical, cerebrospinal, neuroimaging, and rsEEG datasets in 52 ADMCI and 60 Healthy old seniors (equivalent groups for demographic features) were available from an international archive (www.pdwaves.eu). The ADMCI patients were arbitrarily divided into two groups: REACTIVE and UNREACTIVE, based on the reduction (reactivity) in the posterior rsEEG alpha eLORETA source activities from the eyes-closed to eyes-open condition at ≥ -10% and -10%, respectively. 75% of the ADMCI patients were REACTIVE. Compared to the UNREACTIVE group, the REACTIVE group showed (1) less abnormal posterior rsEEG source activity during the eyes-closed condition and (2) a decrease in that activity at the 6-month follow-up. These effects could not be explained by neuroimaging and neuropsychological biomarkers of AD. Such a biomarker might reflect abnormalities in cortical arousal in quiet wakefulness to be used for clinical studies in ADMCI patients using 6-month follow-ups.

Circadian rhythm and whole gut transit in mice.

BACKGROUND: In preclinical studies whole gut transit (WGT) in mice is a gold-standard "leading-edge" approach that measures the time between orogastric gavage of carmine red and defecation of the first carmine red pellet. Transit studies in humans are performed during the active day because GI motility and transit are suppressed during the night. Since mice are nocturnal, WGT studies traditionally done during the day occur during their rest phase. How circadian rhythm affects WGT in mice is not known. METHODS: We used an automated approach for high temporal resolution uninterrupted testing of mouse WGT and activity. We housed wild-type Bl6/C57 mice under the standard 12 h light-dark cycles. At 8 weeks, we performed carmine red orogastric gavage and assessed WGT during Light (rest) conditions. Then, we exposed mice to a reverse 12 h light-dark cycle for 2 weeks and tested them in the Dark (active) under red light conditions. Timelapse videos were analyzed to quantify activity and to timestamp all pellets, and multiple parameters were analyzed. KEY RESULT: When complementary light cycle reversal experiments were performed, we found a significant increase in mouse activity when mice were tested during their Dark (active) phase, compared to their Light (rest) phase. In mice tested in the Active phase compared to the Rest phase, we found a significant acceleration in WGT, increased rate and total number of pellets produced, and more pellet clustering. These data show that the mice tested in the Active phase have important differences in activity that correlate with multiple alterations in gastrointestinal transit. CONCLUSION & INFERENCES: During the Active phase mice have faster WGT, produce more pellets, and cluster their output compared to testing in the Rest phase. Like in humans, circadian rhythm is an important consideration for transit studies in mice, and a simple reverse light cycle approach facilitates further studies on the role of circadian rhythm in GI motility.

Current State of EEG/ERP Microstate Research.

The analysis of EEG microstates for investigating rapid whole-brain network dynamics during rest and tasks has become a standard practice in the EEG research community, leading to a substantial increase in publications across various affective, cognitive, social and clinical neuroscience domains. Recognizing the growing significance of this analytical method, the authors aim to provide the microstate research community with a comprehensive discussion on methodological standards, unresolved questions, and the functional relevance of EEG microstates. In August 2022, a conference was hosted in Bern, Switzerland, which brought together many researchers from 19 countries. During the conference, researchers gave scientific presentations and engaged in roundtable discussions aiming at establishing steps toward standardizing EEG microstate analysis methods. Encouraged by the conference's success, a special issue was launched in Brain Topography to compile the current state-of-the-art in EEG microstate research, encompassing methodological advancements, experimental findings, and clinical applications. The call for submissions for the special issue garnered 48 contributions from researchers worldwide, spanning reviews, meta-analyses, tutorials, and experimental studies. Following a rigorous peer-review process, 33 papers were accepted whose findings we will comprehensively discuss in this Editorial.