Activity Patterns Research Articles

Physical Activity and Pregnancy Norms Among Daasanach Semi-Nomadic Pastoralist Women in Northern Kenya.

In subsistence populations, high physical activity is typically maintained throughout pregnancy. Market integration shifts activity patterns to resemble industrialized populations, with more time allocated to sedentary behavior. Daasanach semi-nomadic pastoralists living in northern Kenya face lifestyle heterogeneity due to the emergence of a market center. We investigate how Daasanach women manage the energetic demands of pregnancy with subsistence labor tasks and how market integration relates to variation in energetic demands, physical activity, and coping strategies. We conducted nine focus group discussions with 72 pregnant women. We also deployed wrist-worn fitness trackers with 21 pregnant women in two community types: central or peripheral to the market center to capture variation in market integration. Data from focus group discussions were analyzed using thematic analysis. We used multiple linear regression to examine the relationship between gestational age and physical activity. We identified themes of increased fatigue, diet restrictions, and assistance with labor tasks during pregnancy. Gestational age negatively predicted mean daily steps, with a decrease of 1160 ± 437 steps per day with each consecutive pregnancy month. Stratified by community type, gestational age only negatively predicted mean daily steps for peripheral communities, with a decrease of 1443 ± 629 steps per day with each consecutive pregnancy month. Results suggest that physical activity differs with market integration early, but not late, in pregnancy. Daasanach women cope with the energetic demands of pregnancy by reducing physical activity late in pregnancy and receiving assistance with labor tasks from family and neighbors.

Inter-Individual Variability in Muscle Fiber-Type Distribution Affects Running Economy but Not Running Gait at Submaximal Running Speeds.

Running economy is an important determinant of endurance running performance, yet insights into characteristics contributing to its inter-individual variability remain limited. Although slow-twitch muscle fibers are more energy-efficient than fast-twitch fibers during the (near-)isometric contractions common during submaximal running, current literature lacks a consensus on whether a relationship between muscle fiber-type distribution and running economy exists. This study aims to resolve the ongoing debate by addressing potential confounding factors often overlooked in prior research, such as the effect of different running speeds, the homogeneity of investigated groups, and the potential impact of the adopted running gait. We selected two groups with predetermined distinct muscle fiber-type distribution in their triceps surae muscle by measurement of carnosine via 1H-MRS, one predominantly slow (ST; n = 11; carnosine z-score = -1.31) and the other predominantly fast (FT; n = 10; z-score = 0.83). Across a range of running speeds (2-4 m/s), we measured running economy (W/kg) through indirect calorimetry, along with running kinematics, kinetics and muscle activity of the lower limb. The ST-group exhibited, on average, 7.8% better running economy than the FT-group (p = 0.01) and this difference was consistent across speeds. Both groups demonstrated almost identical kinematics, kinetics, and muscle activity patterns across submaximal running speeds. Overall, our findings indicate that distinct muscle fiber-type distribution explains some of the observed variability in running economy, for which a predominance of energy-efficient slow-twitch fibers appear beneficial. In contrast, muscle fiber-type distribution does not affect running gait substantially.

Spatiotemporal mapping of auditory onsets during speech production.

The human auditory cortex is organized according to the timing and spectral characteristics of speech sounds during speech perception. During listening, the posterior superior temporal gyrus is organized according to onset responses, which segment acoustic boundaries in speech, and sustained responses, which further process phonological content. When we speak, the auditory system is actively processing the sound of our own voice to detect and correct speech errors in real time. This manifests in neural recordings as suppression of auditory responses during speech production compared to perception, but whether this differentially affects onset and sustained temporal profiles is not known. Here we investigated this question using intracranial EEG recorded from seventeen pediatric, adolescent, and adult patients with medication-resistant epilepsy while they performed a reading/listening task. We identified onset and sustained responses to speech in bilateral auditory cortex and observed a selective suppression of onset responses during speech production. We conclude that onset responses provide a temporal landmark during speech perception that is redundant with forward prediction during speech production and are therefore suppressed. Phonological feature tuning in these "onset suppression" electrodes remained stable between perception and production. Notably, auditory onset responses and phonological feature tuning were present in the posterior insula during both speech perception and production, suggesting an anatomically and functionally separate auditory processing zone that we believe to be involved in multisensory integration during speech perception and feedback control.Significance Statement Specific neural populations in the auditory cortex preferentially respond to the onset of speech sounds. These "onset responses" aid in perceiving boundaries in continuous speech. We recorded neural responses from patients with intracranial electrodes during a speaking and listening task to investigate the role of onset responses in speech production. Onset responses were present in the auditory cortex during listening, but absent during speaking. On the other hand, onset responses were observed in the insula during both conditions, suggesting a different functional role for the insula in auditory feedback processing. These findings extend our knowledge of how different parts of the brain involved in feedback control operate during speech production by identifying two functionally and anatomically distinct patterns of activity.

Exploring bike-commuter habits through data physicalisation engagement

ABSTRACT Engagement with real-time GPS data presents an obvious avenue towards behaviour change for sustainable mobility choices, as tracking human activity patterns becomes more ubiquitous. However, tracking data in visual form does not invite the quality of engagement that data physicalisations afford. In this blended method experiment, we study bike-commuter habits by combining data tracking, ethnographic studies and data physicalisation. We invited 12 everyday bicycle commuters to track their mobility patterns through an app, to be video shadowed on their daily commute and finally to engage in workshops with different data physicalisations based on the personal mobility data collected. We employ an analytic framework to indicate how the participant engagements match the theories of Flow State, Play Moods and Small Beginnings. The results of the study show that there is a potential for engaging local communities in reflecting on their day-to-day mobility choices through active engagement with data physicalisations. We also suggest that the framework can be used to develop facilitation practices to further enhance data physicalisation engagement and deepen insights.

Utilizing graph neural networks for adverse health detection and personalized decision making in sensor-based remote monitoring for dementia care

Background:Sensor-based remote health monitoring is increasingly used to detect adverse health in people living with dementia (PLwD) at home, aiming to prevent hospitalizations and reduce caregiver burden. However, home sensor data is often noisy, overly granular, and suffers from unreliable labeling, data drift and high variability between households. Current anomaly detection methods lack generalizability and personalization, often requiring anomaly-free training data and frequent model updates. Objective:To develop a lightweight, explainable, self-supervised approach with personalized alert thresholds to detect adverse health events in PLwD, using changes in home activity. Methods:We hypothesized that health downturns manifest as detectable shifts in household movement patterns. Our approach leverages a Graph Barlow Twins contrastive model, which uses granular activity data and a macroscopic view to extract noise-robust, high-level and low-level discriminative features that represent daily activity patterns. Household-personalized alert thresholds are calculated based on clinician-set target alert rates, and daily anomaly scores are compared against these thresholds, triggering alerts for the clinical monitoring team. Model attention weights support explainability. Data were collected from a real-world dataset by the UK Dementia Research Institute (August 2019-April 2022). Results:Our model outperformed state-of-the-art temporal graph algorithms in detecting agitation and fall events across three patient cohorts, achieving 81% average recall and 88% generalizability at a target alert rate of 7%. Conclusion:We developed a novel, lightweight, explainable, and personalized Graph Barlow Twins model for real-world remote health monitoring in dementia care, with potential for broader applications in healthcare and sensor-based environments.

The influence of domestic dogs on the spatial and temporal distribution of tayra

The domestic dog Canis familiaris is an exotic species known to have impacts on native fauna and it may induce spatial and temporal segregation in other species as a mechanism to reduce agonistic interactions. The tayra Eira barbara, a medium‐sized, widely distributed mustelid, is one of the species that can be affected. To test this hypothesis, between 2020 and 2022, we installed camera traps in an agricultural landscape composed of a protected area, agro‐livestock areas, an urban area, and several rural households. We calculated the activity patterns, their overlapping coefficients and generated models to explain the species's occupancy and verify possible interferences. We obtained 32 records of tayras and 100 of domestic dogs. In only 8 of 73 sampling points, the two species occurred concomitantly. Activity overlap was 68%; however, at the points where both species occurred, the overlap was 43%. Tayra showed to be positively associated with forest areas, and negatively with agricultural exploitation areas. Dogs predominantly occupied agricultural areas and were negatively related to forest areas. In addition to dog interference, which seems to affect tayra's use of the landscape, environmental conditions are also essential in describing the occupancy of the subordinate species. It is possible that their scansorial habit is important to avoid agonistic events.

Influence of physical activity and screen time on sleep quality in primary school students

In a society where, sedentary lifestyles and the use of technological screens are on the rise, students' lifestyle is being significantly affected. In fact, nowadays many students experience various sleep problems, and two of its main factors may be physical activity and the use of technological screens. In this sense, this research aimed to analyze the influence of students' physical activity and the screen time on sleep quality of students. The participants were 28 students in 5th and 6th grade of primary school. They wore ActiGraph WGT3X-BT accelerometers for one week to collect data related to physical activity and sleep patterns. Additionally, a survey was conducted to assess their use of technological screens. The collected data were analyzed, with a focus on differences by sex. Correlations between these parameters were also analyzed. The analysis revealed no significant correlation between physical activity and sleep quality. However, a significant correlation was observed between screen time and sleep quality. This finding highlights the importance of continued research in these areas to enhance the wellbeing and sleep quality of students.

Creation of an Anomaly Detection System for Blockchain-based Cloud Deployments that Consider Privacy and Delay.

Cloud-based deployments are increasingly vulnerable to many kinds of assaults; hence powerful anomaly detection systems are needed to prevent security breaches. While effective to some degree, current methods like RSSI, GTM, and APG have drawbacks in terms of scalability, precision, and accuracy. In order to improve the forecast accuracy of cloud assaults and optimize blockchain-based cloud installations, this study suggests a novel anomaly detection system that combines multimodal feature analysis, deep learning models, and QoS-aware sidechains. The suggested strategy considerably surpasses traditional approaches in terms of precision, accuracy, recall, and AUC performance by optimizing feature variance across various sample types and utilizing cutting-edge deep learning algorithms. Additionally, the framework shows increased efficiency in terms of throughput, energy usage, and block mining latency, makingcombining Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), the system analyses system logs to find anomalous patterns of activity linked to various threats. The architecture guarantees the transparency and integrity of system records through the use of Blockchain technology, while Deep Learning models offer accurate and quick anomaly detection. The advantages of both Deep Learning and Blockchain technology support the choice to merge them. Blockchain technology ensures the accuracy of anomaly detection and prevents tampering with system records by providing a distributed, immutable ledger. On the other hand, deep learning models produce high precision, accuracy, recall, and AUC measures because of their remarkable pattern recognition skills and ability to adjust to shifting attack strategies. Experimental data analyses show the effectiveness of the suggested framework.

Circadian fruit phenology: An overlooked crucial aspect of plant‐frugivore interactions

Abstract The intrinsic ability of plants to face environmental diel changes is paramount for flowering and interactions with pollinators and herbivores. Surprisingly, despite the commendable research efforts on the ecology and evolution of fruit‐frugivore interactions, very little is known about how fruit ripening and dropping vary throughout 24‐h cycle. Even less is known about the potential consequences of circadian fruit phenology on plant interactions with mutualistic and antagonistic frugivores. We illustrate for the first time how the circadian pattern of fleshy fruit dropping and its matching/mismatching with the diel activity of functionally diverse frugivores (fruit/seed predators, seed dispersers, pulp feeders) can drive the outcome of complex multispecies plant‐frugivore interactions. To that end, we used camera trapping to quantify the circadian fruit dropping of a mammal‐dispersed tree, Pyrus bourgaeana, and the diel activity patterns of its functionally diverse vertebrate frugivores during two fruiting seasons in two tree populations of Mediterranean Spain. Using a large data set (20,878 frugivore visits and 701 fruit‐dropping records), we evaluate the adaptive hypothesis that the circadian pattern of fruit dropping will match the diel activity of seed dispersers rather than that of fruit/seed predators. Fruit dropping during daytime doubled that at night‐time, being considerably consistent across and within seasons, study sites and individual trees. Specifically, overlaps between circadian patterns of fruit dropping across and within seasons (0.83 and 0.84 ± 0.02, respectively), study sites (0.95) and individual trees (0.68 ± 0.01) were always high. Whereas seed dispersers (mammalian carnivores) were mostly nocturnal, the most frequent fruit/seed predators (cervids) were mostly diurnal. Consequently, and contrary to our expectations, circadian fruit dropping was more aligned with the diel activity of overabundant fruit/seed predators than with that of carnivore seed dispersers. Our study illustrates how quantifying the circadian patterns of fruit dropping, the diel activity of functionally diverse frugivores, and the matching/mismatching between both patterns can contribute to a better understanding of multispecies plant‐frugivore interactions. Circadian fruiting phenology is an overlooked key attribute for most tropical and temperate fruiting plants, which patterns, mechanisms and outcomes must be fully investigated. Read the free Plain Language Summary for this article on the Journal blog.

Nasal obstruction during development leads to defective synapse elimination, hypersynchrony, and impaired cerebellar function

Nasal respiratory disorders are linked to craniofacial anomalies and systemic dysfunctions. However, the implications of nasal respiratory disorders on brain development and their subsequent impact on brain functionalization remain largely unknown. Here, we describe that nasal obstruction from postnatal developmental stages in mice precipitates deficits in cerebellum-associated behaviors and compromised refinement and maturation of neural circuits in the cerebellum. We show that mice with nasal obstruction during developmental phases exhibit marked impairments in motor function and exhibit increased immobility time in forced swimming test. Additionally, we identified critical periods during which nasal respiration is essential for optimizing motor function and preserving mental health. Our study also reveals that nasal obstruction in mice disrupts the typical developmental process of synapse elimination in the cerebellum and hinders the normal transition of activity patterns in cerebellar Purkinje cell populations during development. Through comparing activity patterns in mouse models subjected to nasal obstruction at various stages, we suggest that the maturation of specific activity pattern among Purkinje cell populations is fundamental to the functional integrity of the cerebellum. Our findings highlight the indispensable role of adequate nasal respiration during development for the establishment and functional integrity of neural circuits, thereby significantly affecting brain function.

Repulsion of CA3 / dentate gyrus representations is driven by distinct internal beliefs in the face of ambiguous sensory input.

Recent human neuroimaging studies of episodic memory have revealed a counterintuitive phenomenon in the hippocampus: when events are highly similar, corresponding hippocampal activity patterns are sometimes less correlated than activity patterns associated with unrelated events. This phenomenon- repulsion- is not accounted for by most theories of the hippocampus, and the conditions that trigger repulsion remain poorly understood. Here, we used a spatial route-learning task and high-resolution fMRI in humans to test whether hippocampal repulsion is fundamentally driven by internal beliefs about the environment. By precisely measuring participants' internal beliefs and actively manipulating them, we show that repulsion selectively occurred in hippocampal subfields CA3 and dentate gyrus when visual input was ambiguous-or even identical -but internal beliefs were distinct. These findings firmly establish conditions that elicit repulsion and have broad relevance to theories of hippocampal function and to the fields of human episodic memory and rodent spatial navigation.

Functional quantile principal component analysis.

This paper introduces functional quantile principal component analysis (FQPCA), a dimensionality reduction technique that extends the concept of functional principal components analysis (FPCA) to the examination of participant-specific quantiles curves. Our approach borrows strength across participants to estimate patterns in quantiles, and uses participant-level data to estimate loadings on those patterns. As a result, FQPCA is able to capture shifts in the scale and distribution of data that affect participant-level quantile curves, and is also a robust methodology suitable for dealing with outliers, heteroscedastic data or skewed data. The need for such methodology is exemplified by physical activity data collected using wearable devices. Participants often differ in the timing and intensity of physical activity behaviors, and capturing information beyond the participant-level expected value curves produced by FPCA is necessary for a robust quantification of diurnal patterns of activity. We illustrate our methods using accelerometer data from the National Health and Nutrition Examination Survey, and produce participant-level 10%, 50%, and 90% quantile curves over 24 h of activity. The proposed methodology is supported by simulation results, and is available as an R package.

Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements.

The diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (CFS) is based on a constellation of symptoms which center around fatigue. However, fatigue is commonly reported in the general population by people without CFS. Does the biology underlying fatigue in patients with CFS also drive fatigue experienced by individuals without CFS? We used UK Biobank actigraphy data to characterize differences in physical activity patterns and daily temperature rhythms between participants diagnosed with CFS compared to controls. We then tested if single nucleotide variants (SNVs) previously associated with CFS are also associated with the variation of these actigraphic CFS correlates and/or subjective fatigue symptoms in the general population. Participants diagnosed with CFS (n = 295) had significantly decreased overall movement (Cohen's d = 0.220, 95% CI of -0.335 to -0.106, p-value = 2.42x10-15), lower activity amplitudes (Cohen's d = -0.377, 95% CI of -0.492 to -0.262, p-value = 1.74x10-6), and lower wrist temperature amplitudes (Cohen's d = -0.173, 95% CI of -0.288 -0.059, p-value = 0.002) compared to controls (n = 63,133). Of 30 tested SNVs associated in the literature with CFS, one was associated in the control population with subjective fatigue and one with actigraphic measurements (FDR < 0.05). The genetic overlap of CFS risk with actigraphy and subjective fatigue phenotypes suggests that some biological mechanisms underlying pathologic fatigue in CFS patients also underlie fatigue symptoms at a broader population level. Therefore, understanding the biology of fatigue in general may inform our understanding of CFS pathophysiology.

40 Hz sensory stimulation enhances CA3-CA1 coordination and prospective coding during navigation in a mouse model of Alzheimer's disease.

Brain stimulation has emerged as a new potential therapeutic approach to potentially correct or improve altered neural activity in Alzheimer's disease. One such approach, 40 Hz sensory stimulation, or flicker, has been shown to improve cognition in disease models. However, it is not clear how 40 Hz flicker affects neural activity underlying memory processes. Here, we investigate how 40 Hz flicker exposure affects neural activity patterns that are crucial for memory. We find 40Hz flicker increases neural coordination in memory circuits, indicating better communication. Furthermore, 40Hz flicker increased neural representations of future positions, patterns theorized to support memory-based planning. These results indicate that 40 Hz flicker increases key neural activity that is important for memory.

Impairment of Neuronal Activity in the Dorsolateral Prefrontal Cortex Occurs Early in Parkinsonism.

Parkinson's disease (PD) is often characterized by altered rates and patterns of neuronal activity in the sensorimotor regions of the basal ganglia thalamocortical network. Little is known, however, regarding how neuronal activity in the executive control network of the brain changes in the parkinsonian condition. Investigate the impact of parkinsonism on neuronal activity in the dorsolateral prefrontal cortex (DLPFC), a key region in executive control, during a go/nogo reaching task. Using a within-subject design, single and multi-unit neuronal activity was recorded in the DLPFC of a nonhuman primate before and after the induction of mild parkinsonism using the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Coincident with development of mild parkinsonian motor signs, there was a marked reduction in the percentage of DLPFC cells with significant task-related firing rate modulation during go and nogo conditions. These results suggest that DLPFC dysfunction may occur early in parkinsonism and contribute to cognitive impairments and disrupted executive function often observed in PD patients.

Theoretical framework for learning through structural plasticity

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework of learning through this kind of plasticity, capable of taking into account several features of the connectivity and pattern of activity of biological neural networks, including probability distributions of neuron firing rates, selectivity of the responses of single neurons to multiple stimuli, probabilistic connection rules, and noisy stimuli. More importantly, it describes the effects of stabilization, pruning, and reorganization of synaptic connections. This framework is used to compute the values of some relevant quantities used to characterize the learning and memory capabilities of the neuronal network in training and testing procedures as the number of training patterns and other model parameters vary. The results are then compared with those obtained through simulations with firing-rate-based neuronal network models. Published by the American Physical Society 2024

Spatiotemporal responses of ungulates to hunting in a fenced multi-use area

Context Human activities, such as tourism and hunting, affect the spatiotemporal behaviour of wildlife. For example, it is well documented that ungulates change their spatiotemporal behaviour as a response to hunting pressure, but less is known about ungulate responses to hunting in areas where human activity is common throughout the year and ungulates are constrained by fences. Aims In this camera-trap study, we analysed the change in spatiotemporal behaviour of wild ungulates (elk, Cervus canadensis (3519 events), moose, Alces alces (1153 events), and white-tailed deer, Odocoileus virginianus (2708 events)) in response to the hunting period in a recreational and fenced park, the Cooking Lake–Blackfoot Provincial Area, Canada. Methods We used general linear models to compare species-specific patterns of intensity of use, calculated as events per week, in response to changes in the nature of human disturbance, namely a shift from recreation to hunting activity. In particular, we compared intensity of use in and out of the hunting season to determine whether species engaged in spatial patterns of avoidance with respect to hunting. We used daily and seasonal patterns of activity to determine how ungulates shifted their temporal use in response to hunting activity and whether they became more nocturnal as a result. Key results We found that ungulates responded temporally to the hunting period by generally shifting their activity to more nocturnal hours, with white-tailed deer showing the biggest temporal shift, suggesting that the ungulates distinguish between consumptive and non-consumptive human activities. Nevertheless, temporal overlap between humans and all ungulate species increased during the hunting period as humans targeted times of increased ungulate activity. Spatially, the response was less distinctive and was species-specific. Elk showed little change in spatial behaviour in response to the hunting period. In contrast, moose decreased the use of trail areas and other areas frequented by humans, whereas deer, counterintuitively, increased the use of trail areas, albeit their use became much more nocturnal. Conclusions We have shown that responses of ungulates to hunting exceed those to non-consumptive recreational use, and whereas temporal responses (increased nocturnality) were consistent across ungulate species, spatial responses were species-specific. Implications Management in small fenced multi-use areas needs to account for shifts in the intensity of disturbance resulting from a change in human disturbance from recreational activity to hunting. Providing spatial opportunities for avoidance of humans is key for most species if hours of operation in these areas already limit the timing of human activity.

Development of an Electromyography Signal Acquisition Prototype and Statistical Validation Against a Commercial Device

Electromyography (EMG) stands out as an accessible and inexpensive method for identifying muscle contractions on the surface and within deeper muscle tissues. Using specialized electronic circuits for amplification and filtering can help develop simple but effective systems for detecting and analyzing these signals. However, EMG devices developed by research teams frequently lack rigorous methodologies for validating the quality of the signals they record compared to those obtained by commercial systems that have undergone extensive testing and regulatory approval for market release. This underscores the critical need for standardized validation techniques to reliably assess the performance of experimental devices relative to established commercial equipment. Hence, this study introduces a methodology for the development and statistical validation of a laboratory EMG circuit compared with a professional device available on the market. The experiment simultaneously recorded the muscle electrical activity of 18 volunteers using two biosignal acquisition devices—a prototype EMG and a commercial system—both applied in parallel at the same recording site. Volunteers performed a series of finger and wrist extension movements to elicit myoelectric activity in these forearm muscles. To achieve this, it was necessary to develop not only the EMG signal conditioning board, but also two additional interface boards: one for enabling parallel recording on both devices and another for synchronizing the devices with the task programmatically controlled in Python that the volunteers were required to perform. The EMG signals generated during these tasks were recorded simultaneously by both devices. Subsequently, 22 feature indices commonly used for classifying muscular activity patterns were calculated from two-second temporal windows of the recordings to extract detailed temporal and spatial characteristics. Finally, the Mean Absolute Percentage Error (MAPE) was computed to compare the indices from the prototype with those from the commercial device, using this method as a validation system to assess the quality of the signals recorded by the prototype relative to the commercial equipment. A concordance of 87.6% was observed between the feature indices calculated from the recordings of both devices, suggesting high effectiveness and reliability of the EMG signals recorded by the prototype compared to the commercial device. These results validate the efficacy of our EMG prototype device and provide a solid foundation for the future evaluation of similar devices, ensuring their reliability, accuracy, and suitability for research or clinical applications.

Brain-movement relationship during upper-limb functional movements in chronic post-stroke patients

BackgroundFollowing a stroke, brain activation reorganisation, movement compensatory strategies, motor performance and their evolution through rehabilitation are matters of importance for clinicians. Two non-invasive neuroimaging methods allow for recording task-related brain activation: functional near-infrared spectroscopy (fNIRS) and electroencephalography (fEEG), respectively based on hemodynamic response and neuronal electrical activity. Their simultaneous measurement during movements could allow a better spatiotemporal mapping of brain activation, and when associated to kinematic parameters could unveil underlying mechanisms of functional upper limb (UL) recovery. This study aims to depict the motor cortical activity patterns using combined fNIRS-fEEG and their relationship to motor performance and strategies during UL functional tasks in chronic post-stroke patients.MethodsTwenty-one healthy old adults and 21 chronic post-stroke patients were recruited and completed two standardised functional tasks of the UL: a paced-reaching task where they had to reach a target in front of them and a circular steering task where they had to displace a target using a hand-held stylus, as fast as possible inside a circular track projected on a computer screen. The activity of the bilateral motor cortices and motor performance were recorded simultaneously utilizing a fNIRS-fEEG and kinematics platform.Results and conclusionsKinematic analysis revealed that post-stroke patients performed worse in the circular steering task and used more trunk compensation in both tasks. Brain analysis of bilateral motor cortices revealed that stroke individuals over-activated during the paretic UL reaching task, which was associated with more trunk usage and a higher level of impairment (clinical scores). This work opens up avenues for using such combined methods to better track and understand brain-movement evolution through stroke rehabilitation.

Revisiting the epidemiological role of a native vector in Northern California vineyards

Abstract Effective disease management hinges on an accurate understanding of the ecological and epidemiological underpinnings of the pathosystem. New epidemics may prompt consideration of whether knowledge gaps or changes to the pathosystem warrant revision of management strategies. Pierce’s disease of grapevines is highly episodic in coastal Northern California vineyards, with modest incidence in most years punctuated by occasionally severe epidemics. To better understand what was driving a developing epidemic in the region, we revaluated what is known about the ecology and epidemiological role of the dominant vector, the blue-green sharpshooter Graphocephala atropunctata. We monitored vector spatiotemporal dynamics at 32 vineyards over three years, surveyed plant community composition in the adjacent habitat to understand its link to vector recruitment, and quantified patterns of natural infectivity for the pathogen Xylella fastidiosa. Overall, the results were consistent with past studies of G. atropunctata ecology. For example, the scale of dispersal from source habitat and seasonal patterns in activity were generally similar to those documented in prior studies. The results also confirmed the influence of adjacent plant community composition on G. atropunctata activity in vineyards, and the role of riparian habitat and select plant taxa as vector sources. Nonetheless, further consideration of the epidemiological significance of certain features of the pathosystem may be warranted, especially those related to seasonality in X. fastidiosa infection in vectors. A marked increase in infected G. atropunctata late in the season likely reflects pathogen acquisition from infected grapevines, which may have implications for disease management strategies.