Journal of neurophysiology最新文献

Constraining gait rhythm with a metronome has been shown to influence gait pattern in many different ways. Although rhythmic cues can improve several parameters in some clinical populations, they do alter the long-range autocorrelations naturally exhibited in series of stride durations. However, transitions between walking with and without a metronome (and vice versa) have not been measured; it is therefore unclear how people adapt to such a change in task. To address this gap, a total of 21 healthy volunteers were asked to walk overground under three conditions: one unconstrained control condition, followed by two conditions in which a metronome was activated during either the first or second half of the trial to test both transitions. The long-range autocorrelations were assessed over a sliding window on the stride series to measure their evolution. Our observations were reproduced with a computational model, allowing us to relate sudden changes in movement parameters to the long-range autocorrelations, which are typically measured over longer timescales. The results showed a clear transition in both conditions involving a metronome, with long-range autocorrelations of the series of stride durations gradually reduced when the metronome was turned on and recovered when it was turned off. In these two conditions, the change in long-range autocorrelations could be reproduced in the model by an instantaneous switching of the control policy associated with the presence or not of the metronome, suggesting that long-range autocorrelations emerge from a flexible control strategy that rapidly regulates timing and amplitude parameters according to task requirements.NEW & NOTEWORTHY Through an experiment involving transitions between walking with and without a metronome, we studied how people adapt to such a change of task by measuring the evolution of long-range autocorrelations (LRA) in the stride series. The results were reproduced in a model by an instantaneous change in the control policy, which validates the hypothesis that LRA emerge from a flexible control that rapidly regulates timing and amplitude parameters according to task requirements.

Vision is important for various tasks, from visually pursuing moving objects to maintaining balance. People obtain visual information through eye movements performed either alone or in combination with head movements. Even when isolated eye movements can accommodate the amplitude of the desired gaze shift, humans still perform head movements, as they provide sensory signals that can lead to improved gaze estimates. However, head movements also create mechanical torques that could disturb balance. We here examined whether head engagement is determined by postural challenges when performing a visual pursuit task. Young participants tracked a target moving horizontally along different amplitudes (15°, 42°, and 95°) while they were seated, standing on a firm, and standing on an unstable surface. Head engagement, which was the ratio of head rotation relative to the target's amplitude, was larger when standing than sitting, but no systematic differences were found between firm and unstable surfaces. To further explore the interplay between head engagement and postural challenges, we conducted a second experiment where young and older participants performed a similar task, but now they were either allowed to move their head or instructed to limit head movements. Both tracking accuracy and postural sway increased when engaging the head. When allowed to move their head naturally, young participants engaged their head more when standing than sitting, but older adults reduced their head movements with more demanding postures. We suggest that head movements in young adults facilitate visual tracking, whereas limited head movements in older adults are selected to preserve balance.NEW & NOTEWORTHY Head movements are important for gaze shifts. However, when keeping balance, mechanical torques from such movements can have detrimental effects. Here, we used a visual pursuit task and showed that, as postural challenge increases, young people engage their head more strongly, whereas older participants limit head engagement. Hence, we conclude that when performing visual tasks, the amount of head rotation is influenced by aging and postural challenge.

Copper, an essential trace element in the human body, plays a crucial role in various metabolic processes, and its homeostasis imbalance is increasingly recognized as being associated with the pathology of Alzheimer's disease (AD). Notably, elevated levels of serum-free copper are linked to cognitive decline in patients with AD and may actively contribute to the disease process by promoting Aβ aggregation, tau protein hyperphosphorylation, and oxidative stress. A recent groundbreaking discovery identified a novel, copper-dependent form of regulated cell death-"cuproptosis"-characterized by lipoylated protein aggregation and loss of iron-sulfur clusters. This finding provides a new and compelling mechanistic link between copper overload and neuronal loss in AD. This article reviews the pathogenesis of cuproptosis, its relationship with copper homeostasis in the body, and its role in the pathogenesis of AD, including the regulatory functions of cuproptosis-related genes (CRGs) in AD. In addition, it explores potential therapeutic strategies aimed at correcting copper imbalance in AD, including the use of copper chelators, lipid peroxidation inhibitors, and antioxidants. These treatments aim to restore copper homeostasis and prevent cuproptosis in Alzheimer's disease. However, the clinical application of these strategies remains challenging due to issues such as poor bioavailability, significant side effects, and insufficient targeting. Therefore, developing an ideal copper chelator for clinical use remains a distant goal. Elucidating the role of cuproptosis in AD not only deepens our understanding of its pathogenesis but also opens innovative avenues for therapeutic intervention, representing a significant frontier in future AD research.

Predictive control enables humans to anticipate future events by combining sensory feedback with internal models. In interception tasks, such mechanisms could allow the visual system to estimate future target positions, supporting timely and accurate motor responses. Here, we investigated predictive gaze behavior in a visuomotor task where participants used a joystick to intercept a moving target that rebounded within a circular arena. Eye movements were classified into fixations, smooth pursuit, and saccades using a velocity-based method. The arena's geometry constrained rebound angles and facilitated standardized trajectory analysis. Participants consistently deployed fixations aligned with the target's anticipated postrebound path, as confirmed by fixations that were closer to future than to current target positions. Moreover, saccade and fixation onsets were time-locked to the rebound event, reflecting anticipatory adjustments based on the statistical regularities of the task. Gaze alignment was modulated by the target's entry angle and velocity: steeper entries and higher speeds compressed fixation timing but increased spatial variability. Visual masking of the target disrupted predictive gaze, highlighting the critical role of target visibility in guiding anticipatory behavior. These findings demonstrate the crucial role of predictive fixations in visuomotor coordination, offering a broader understanding of anticipatory behaviors and their applications. Our task design offers a controlled platform to study anticipatory gaze strategies, with potential applications for clinical diagnostics, skill training, and human-computer interaction.NEW & NOTEWORTHY This study builds on previous research by demonstrating that predictive fixations align with future target trajectories during a dynamic interception task. Using a threshold-based classification of eye movements, it quantifies anticipatory gaze behavior before and after target rebounds. The findings show that entry and exit angles, target speed, and visual masking systematically influence predictive fixations. Together, these results underscore the critical role of predictive mechanisms in visuomotor control, particularly in adapting gaze behavior to dynamic and uncertain environments.

Explicit and implicit components of motor learning have been widely studied, but the extent to which movement information encoded and maintained in working memory (Motor Working Memory; MWM) contributes to motor learning remains unclear. Building on recent work pointing to separate effector-independent (abstract) and effector-specific (limb-bound) information formats in MWM, we conducted a correlational study in which human participants completed both a MWM task and a visuomotor rotation task. We observed that: 1) the fidelity of effector-independent MWM was selectively correlated with the degree of explicit visuomotor learning, and 2) the fidelity of inferred effector-specific MWM was selectively correlated with the degree of implicit visuomotor learning. Together, these results point to a possible relationship in which different formats of motor information stored in WM may contribute to distinct components of long-term motor learning, shedding light on a novel cognitive-motor interaction.NEW & NOTEWORTHY Working memory is important for motor learning, yet its role beyond visuospatial domains remains unclear. Here, we examine whether and how non-visual Motor Working Memory (MWM) is related to long-term motor learning. Specifically, we identified selective correlations between effector-independent MWM and explicit motor learning processes, and between effector-specific MWM and implicit motor learning processes. These findings extend prior research relating visuospatial working memory to motor learning and highlight distinct MWM mechanisms supporting different learning processes.

Previous studies have shown an association between interindividual variations in the frequency of α-band EEG oscillations such as estimates of peak alpha frequency (PAF) and pain sensitivity. Whether differences in PAF also influence the susceptibility to develop central sensitization (CS) is unknown. This study aimed to determine whether the PAF of vision- and sensorimotor-related alpha-band activity is associated with the magnitude and extent of secondary mechanical hyperalgesia induced by high-frequency stimulation (HFS) of the skin, a surrogate marker of CS. The EEG was recorded in 32 healthy participants at rest during eyes open and eyes closed conditions, and during bilateral finger movements. Then, HFS was applied to the right forearm. Pinprick sensitivity was assessed at both forearms, before and 40 min after HFS, to assess the magnitude and extent of HFS-induced secondary hyperalgesia. Two methods were used to isolate vision- and sensorimotor-related alpha-band activity based on sensitivity to eye closure and movement: one based on an independent component analysis, the other on spectral subtraction. PAF was characterized using a center-of-gravity approach and also using Gaussian fitting after removal of the aperiodic EEG component. Neither sensorimotor- nor vision-related PAF were significantly correlated with the magnitude or extent of HFS-induced secondary hyperalgesia. However, exploratory analyses revealed that participants with higher vision-related PAF showed greater pinprick habituation at the nonsensitized forearm, indicating a possible link between PAF and perceptual habituation. Interindividual variations of PAF at baseline were not significantly associated with the susceptibility to develop HFS-induced secondary hyperalgesia.NEW & NOTEWORTHY Using several methods to estimate vision- and sensorimotor-related peak alpha frequency (PAF) in the EEG frequency spectrum, we found no significant association between interindividual variations in PAF at baseline and the susceptibility to develop secondary hyperalgesia following high-frequency stimulation (HFS) of the skin in healthy participants.

Studying naturalistic hand behaviors is challenging due to the limitations of conventional marker-based motion capture, which can be costly, time-consuming, and encumber participants. Although markerless pose estimation exists-an accurate, off-the-shelf solution validated for hand-object manipulation is needed. We present Automatically Tracking Hands Expertly with No Annotations (ATHENA), an open-source, Python-based toolbox for three-dimensional (3-D) markerless hand tracking. To validate ATHENA, we concurrently recorded hand kinematics using ATHENA and an industry-standard optoelectronic marker-based system (OptiTrack). Participants performed unimanual, bimanual, and naturalistic object manipulation and we compared common kinematic variables like grip aperture, wrist velocity, index metacarpophalangeal flexion, and bimanual span. Our results demonstrated high spatiotemporal agreement between ATHENA and OptiTrack. This was evidenced by extremely high matches (R² > 0.90 across the majority of tasks) and low root mean square differences (<1 cm for grip aperture, <4 cm/s for wrist velocity, and <5°-10° for index metacarpophalangeal flexion). ATHENA reliably preserved trial-to-trial variability in kinematics, offering identical scientific conclusions to marker-based approaches, but with significantly reduced financial and time costs and no participant encumbrance. In conclusion, ATHENA is an accurate, automated, and easy-to-use platform for 3-D markerless hand tracking that enables more ecologically valid motor control and learning studies of naturalistic hand behaviors, enhancing our understanding of human dexterity.NEW & NOTEWORTHY An accurate, easy-to-use Python-based toolbox is shared to perform automated three-dimensional (3-D) tracking of the hands. When validated against an industry standard marker-based system, the toolbox demonstrated high spatiotemporal agreement and preserved trial-to-trial variability for tasks ranging from simple reaching to complex object manipulation behaviors. The toolbox offers reduced financial and time costs and does not require the use of markers that may encumber participant movements, thereby facilitating ecologically valid motor control studies of the hand.

Gluten is a protein that is present in a variety of grains and is added to many food products, such as pasta and bread. There are three disorders related to gluten consumption: celiac disease (CD), wheat allergy, and nonceliac gluten sensitivity (NCGS). CD and wheat allergies can be tested for and involve intestinal and extraintestinal symptoms, including a variety of neurological conditions. Individuals with NCGS are diagnosed if they have an adverse reaction to gluten, including intestinal and neurological effects such as "brain fog." To study the impact of gluten on brain function and test our hypothesis that diets with gluten would impair cognitive function in the presence of a high-fat diet, wild-type mice were fed 35% fat (kcal) in the absence or presence of gluten (3.4 g/100g diet). Body fat, food consumption, oral glucose tolerance tests, and various behavioral tests were evaluated after 2-3 mo of dietary intervention. Mice had similar body weights, body fat percentages, and oral glucose tolerance tests regardless of dietary gluten. Food consumption was also similar in both groups of mice. In behavioral studies, mice fed gluten stayed longer and traveled further in the open arm of an elevated platform maze, an indication of reduced anxiety, and had increased locomotor activity compared to mice not fed gluten, whereas mice fed diets with or without gluten had similar results from the Morris water maze and a restraint test, indications of similar memory and stress. Thus, dietary gluten impacts behavior in mice fed high-fat diets.NEW & NOTEWORTHY Recently, a growing number of individuals have associated dietary gluten with adverse neurological symptoms. In the current study, we examined the impact of gluten on the behaviors of mice, using behaviors to represent a culmination of various neurological processes. We discovered that behaviors did indeed differ in mice fed gluten versus not fed gluten in the presence of a high-fat diet.

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Despite advances in acute care and neurological intensive care units, predicting long-term outcomes for patients with TBI remains challenging. Aquaporin-4 (AQP4) has emerged as a potential biomarker for assessing TBI severity and prognosis. Our goal is to evaluate AQP4 as a novel agent in the accurate diagnosis and prognosis of patients with TBI. This study included patients with TBI classified into mild (n = 80), moderate (n = 139), and severe (n = 96) groups based on Glasgow Coma Scale (GCS) scores. Cerebrospinal fluid (CSF) samples were collected at 1-, 7-, 14-, and 28-days postadmission, and AQP4 concentrations were measured using ELISA. The prognosis was evaluated using the Glasgow Outcome Scale (GOS) at 3 mo postinjury. The relationship between AQP4 levels and TBI severity, and their predictive value for patient outcomes, was analyzed. AQP4 levels in CSF peaked at 14 days postadmission and significantly decreased by 28 days in patients with both moderate and severe TBI. Higher AQP4 levels were consistently associated with worse prognosis at all measured time points. receiver operating characteristic (ROC) analysis revealed that AQP4 levels had predictive values at 1-, 7-, 14-, and 28-days postadmission, and the highest was shown at 14 days postadmission, with an area under the curve (AUC) of 0.79, sensitivity of 67.82%, and specificity of 83.78%. AQP4 in CSF is a promising biomarker for assessing TBI severity and predicting prognosis. Monitoring AQP4 levels could be an effective way to enhance prognostic accuracy, guide therapeutic interventions, and improve clinical decision-making in TBI management.NEW & NOTEWORTHY Our study is the first to comprehensively track dynamic changes in cerebrospinal fluid (CSF) aquaporin-4 (AQP4) levels in patients with moderate to severe traumatic brain injury. We show that AQP4 peaks at 14 days, correlates with injury severity, and consistently predicts 3-mo outcomes, with the strongest prognostic accuracy at day 14. These findings identify CSF AQP4 as a promising biomarker for assessing severity and prognosis, offering potential to improve early prediction and guide clinical decision-making in TBI management.