BackgroundAs the global population ages, it is crucial to understand sensorimotor compensation mechanisms. These mechanisms are thought to enable older adults to remain in good physical health, but despite important research efforts, their precise nature remains elusive and has not been definitively demonstrated. A major problem with their identification is the ambiguous interpretation of age-related alterations. Whether a change reflects deterioration or compensation is difficult to determine.MethodsTo address this challenge, we examined movement efficiency in younger and older adults using two complementary approaches. In Experiment 1 (Younger, n = 20; mean age = 23.6 years, and older adults, n = 24; mean age = 72 years), we quantified energetic efficiency through the negativity of phasic EMG activity—an established marker of how the nervous system exploits gravity to minimize muscular effort—during both single-joint arm movements and whole-body actions (sit-to-stand/back-to-sit and whole-body reaching). In Experiment 2 (younger adults, n = 20; mean age = 22.9 years; older adults, n = 20; mean age = 70.6 years), we directly measured energetic cost using exhaled-gas analysis during treadmill walking under varying balance constraints.ResultsIn Experiment 1, older adults preserved efficient planning during arm movements, but they showed reduced gravity-related efficiency during whole-body tasks. Complementary center-of-mass analyses and optimal control simulations indicated that this reduced efficiency aligned with movement strategies favoring stability over energy minimization. In Experiment 2, older adults exhibited a disproportionately larger increase in metabolic cost and perceived effort when equilibrium demands were elevated, despite performing the same tasks as younger adults.DiscussionThis supports a causal role of equilibrium constraints in decreasing walking efficiency in older adults. Overall, these results suggest that reduced movement efficiency in healthy older adults does not reflect a deterioration but rather a compensation process that adapts movement strategy to the task specificities. When balance is at stake, healthy older adults prefer stability to energy efficiency.

Interval timing is essential for adapting behaviour in dynamic environments. While previous research has shown that time perception is influenced by movement, the role of movement type in this interaction remains poorly understood. The present study aimed to further investigate this interaction, by comparing temporal performance (i.e., temporal accuracy and precision) across two movement types: whole-body reaching (WBR) movements and finger movements. Fourteen participants reproduced time intervals while performing both movement types using five target durations centred around the natural duration of the WBR movement. We observed lower temporal variability with WBR movements compared to finger movements. This can be explained by a Bayesian cue combination framework or an increase of the pacemaker rate within the Scalar Expectancy Theory. Regarding temporal accuracy, intervals were over-reproduced with finger movements compared to WBR movements, possibly due to fluctuations in attentional allocation during finger movements or an increase of the pacemaker rate during WBR movements. Additionally, within the WBR condition, shorter intervals were over-reproduced, which may reflect either subjective time compression induced by faster movements, or the influence of biomechanical constraints. These findings extend current models by suggesting that motor execution actively shapes temporal performance, serving as more than just a final output mechanism. This could hold implications for training and rehabilitation strategies, where engaging whole-body movements may help reduce temporal variability.

Arm movements in our daily lives have to be adjusted for several factors in response to the demands of the environment, for example, speed, direction or distance. Previous research has shown that arm movement kinematics is optimally tuned to take advantage of gravity effects and minimize muscle effort in various pointing directions and gravity contexts. Here we build upon these results and focus on muscular adjustments. We used Machine Learning to analyze the ensemble activities of multiple muscles recorded during pointing in various directions. The advantage of such a technique would be the observation of patterns in collective muscular activity that may not be noticed using univariate statistics. By providing an index of multimuscle activity, the Machine Learning (ML) analysis brought to light several features of tuning for pointing direction. In attempting to trace tuning curves, all comparisons were done with respects to pointing in the horizontal, gravity free plane. We demonstrated that tuning for direction does not take place in a uniform fashion but in a modular manner in which some muscle groups play a primary role. The antigravity muscles were more finely tuned to pointing direction than the gravity muscles. Of note, was their tuning during the first half of downward pointing. As the antigravity muscles were deactivated during this phase, it supported the idea that deactivation is not an on-off function but is tuned to pointing direction. Further support for the tuning of the negative portions of the phasic EMG was provided by the observation of progressively improving classification accuracies with increasing angular distance from the horizontal. We also demonstrated that the durations of these negative phases, without information on their amplitudes, is tuned to pointing directions. Overall, these results show that the motor system tunes muscle commands to exploit gravity effects and reduce muscular effort. It quantitatively demonstrates that phasic EMG negativity is an essential feature of muscle control. The ML analysis was done using Linear Discriminant analysis (LDA) and Support Vector Machines (SVM). The two led to the same conclusions concerning the movements being investigated, hence showing that the former, computationally inexpensive technique is a viable tool for regular investigation of motor control.

There is experimental evidence of varying correlation among the elements of the neuromuscular system over the course of the reach-and-grasp task. The aim of this study was to investigate if modifications in correlations and clustering can be detected in the local field potential (LFP) recordings of the motor cortex during the task. To this end, we analyzed the LFP recordings from a previously published study on monkeys that performed a reach-and-grasp task for targets with a vertical or horizontal orientation. LFP signals were recorded from the motor and premotor cortex of macaque monkeys as they performed the task. We found very robust changes in the correlations of the multielectrode LFP recordings that corresponded to task epochs. Mean LFP correlation increased significantly during reach and then decreased during grasp. This pattern was very robust for both left and right arm reaches irrespective of target orientation. A hierarchical cluster analysis also demonstrated similar changes. In focusing on correlations, our study has contributed new insights to the understanding of LFP signals and their relationship to movement. A sliding window computation of the number of clusters was performed to probe the capacities of the LFP clusters for detecting upcoming task events. For a very high percentage of trials (97.89%), there was a downturn in cluster number following the Pellet Drop (GO signal) that reached a minimum preceding the Start of grasp, hence indicating that cluster analyses of LFPs could contribute to signaling an increased probability of the Start of grasp.

A bstract As the global population ages, it is crucial to understand sensorimotor compensation mechanisms. These mechanisms are thought to enable older adults to remain in good physical health, but despite important research efforts, they remain essentially chimeras. A major problem with their identification is the ambiguous interpretation of age-related alterations. Whether a change reflects deterioration or compensation is difficult to determine. Here we compared the electromyographic and kinematic patterns of different motor tasks in younger (n = 20; mean age = 23.6 years) and older adults (n = 24; mean age = 72 years). Building on the knowledge that humans take advantage of gravity effects to minimize their muscle effort, we probed the ability of younger and older adults to plan energetically efficient movement during arm-only and whole-body movements. In line with previous studies and compared to younger adults, muscle activation patterns revealed that older adults used a less efficient movement strategy during whole-body movement tasks. We found that this age-related alteration was task-specific. It did not affect arm movements, thereby supporting the hypothesis that healthy older adults maintain the ability to plan energetically efficient movements. More importantly, we found that the reduced whole-body movement efficiency was correlated with kinematic measures of balance control (i.e., the center-of-mass movement amplitude and speed). The more efficient the movement strategy, the more challenging the balance. Overall, these results suggest that reduced movement efficiency in healthy older adults does not reflect a deterioration but rather a compensation process that adapts movement strategy to the task specificities. When balance is at stake, healthy older adults prefer stability to energy efficiency.

The cerebellum plays an important role in diverse brain functions, ranging from motor learning to cognition. Recent studies have suggested that molecular and cellular heterogeneity within cerebellar lobules contributes to functional differences across the cerebellum. However, the specific relationship between molecular and cellular heterogeneity and diverse functional outputs of different regions of the cerebellum remains unclear. Here, we describe a previously unappreciated form of synaptic heterogeneity at parallel fiber synapses to Purkinje cells in the mouse cerebellum (both sexes). In contrast to uniform fast synaptic transmission, we found that the properties of slow synaptic transmission varied by up to threefold across different lobules of the mouse cerebellum, resulting in surprising heterogeneity. Depending on the location of a Purkinje cell, the time of peak of slow synaptic currents varied by hundreds of milliseconds. The duration and decay time of these currents also spanned hundreds of milliseconds, based on lobule. We found that, as a consequence of the heterogeneous synaptic dynamics, the same brief input stimulus was transformed into prolonged firing patterns over a range of timescales that depended on Purkinje cell location.

The aim of this study was to develop the use of Machine Learning techniques as a means of multivariate analysis in studies of motor control. These studies generate a huge amount of data, the analysis of which continues to be largely univariate. We propose the use of machine learning classification and feature selection as a means of uncovering feature combinations that are altered between conditions. High dimensional electromyogram (EMG) vectors were generated as several arm and trunk muscles were recorded while subjects pointed at various angles above and below the gravity neutral horizontal plane. We used Linear Discriminant Analysis (LDA) to carry out binary classifications between the EMG vectors for pointing at a particular angle, vs. pointing at the gravity neutral direction. Classification success provided a composite index of muscular adjustments for various task constraints-in this case, pointing angles. In order to find the combination of features that were significantly altered between task conditions, we conducted a post classification feature selection i.e., investigated which combination of features had allowed for the classification. Feature selection was done by comparing the representations of each category created by LDA for the classification. In other words computing the difference between the representations of each class. We propose that this approach will help with comparing high dimensional EMG patterns in two ways; (i) quantifying the effects of the entire pattern rather than using single arbitrarily defined variables and (ii) identifying the parts of the patterns that convey the most information regarding the investigated effects.

Attachment to the intestinal epithelium is critical to the lifestyle of the ubiquitous parasite Giardia lamblia . The ventrolateral flange is a sheet-like membrane protrusion at the interface between parasites and attached surfaces. This structure has been implicated in attachment, but its role has been poorly defined. Here, we identified a novel actin associated protein with putative WH2-like actin binding domains we named Flangin. Flangin complexes with Giardia actin ( Gl Actin) and is enriched in the ventrolateral flange making it a valuable marker for studying the flanges’ role in Giardia biology. Live imaging revealed that the flange grows to around 1 μm in width after cytokinesis, then remains uniform in size during interphase, grows in mitosis, and is resorbed during cytokinesis. A flangin truncation mutant stabilizes the flange and blocks cytokinesis, indicating that flange disassembly is necessary for rapid myosin-independent cytokinesis in Giardia . Rho family GTPases are important regulators of membrane protrusions and Gl Rac, the sole Rho family GTPase in Giardia , was localized to the flange. Knockdown of Flangin, Gl Actin, and Gl Rac result in flange formation defects. This indicates a conserved role for Gl Rac and Gl Actin in forming membrane protrusions, despite the absence of canonical actin binding proteins that link Rho GTPase signaling to lamellipodia formation. Flangin-depleted parasites had reduced surface contact and when challenged with fluid shear force in flow chambers they had a reduced ability to remain attached, confirming a role for the flange in attachment. This secondary attachment mechanism complements the microtubule based adhesive ventral disc, a feature that may be particularly important during mitosis when the parental ventral disc disassembles in preparation for cytokinesis. This work supports the emerging view that Giardia’s unconventional actin cytoskeleton has an important role in supporting parasite attachment.

Recent studies have demonstrated that selective activation of mammalian target of rapamycin complex 1 (mTORC1) in the cerebellum by deletion of the mTORC1 upstream repressors TSC1 or phosphatase and tensin homolog (PTEN) in Purkinje cells (PCs) causes autism-like features and cognitive deficits. However, the molecular mechanisms by which overactivated mTORC1 in the cerebellum engenders these behaviors remain unknown. The eukaryotic translation initiation factor 4E-binding protein 2 (4E-BP2) is a central translational repressor downstream of mTORC1. Here, we show that mice with selective ablation of 4E-BP2 in PCs display a reduced number of PCs, increased regularity of PC action potential firing, and deficits in motor learning. Surprisingly, although spatial memory is impaired in these mice, they exhibit normal social interaction and show no deficits in repetitive behavior. Our data suggest that, downstream of mTORC1/4E-BP2, there are distinct cerebellar mechanisms independently controlling social behavior and memory formation.

Attachment to the intestinal epithelium is critical to the lifestyle of the ubiquitous parasite Giardia lamblia. The microtubule cytoskeleton plays a well characterized role in attachment via the ventral adhesive disc, whereas the role of the unconventional actin cytoskeleton is controversial. We identified a novel actin associated protein with putative WH2-like actin binding domains we named Flangin. Flangin complexes with Giardia actin and is enriched in the ventrolateral flange (VLF), a lamellipodium-like membrane protrusion at the interface between parasites and attached surfaces. Live imaging revealed that the VLF grows to ~1 μm in width after cytokinesis, then remains size-uniform in interphase, grows during mitosis, and is resorbed during cytokinesis. A Flangin truncation mutant stabilizes the VLF and blocks cytokinesis, indicating that the VLF is a membrane reservoir supporting rapid myosin-independent cytokinesis in Giardia. Rho family GTPases are important regulators of membrane protrusions, GlRac, the sole Rho family GTPase in Giardia, was localized to the VLF. Knockdown of Flangin, actin, and GlRac result in VLF formation defects indicating a conserved role for GlRac and actin in forming membrane protrusions, despite the absence of canonical actin binding proteins that link Rho GTPase signaling to lamellipodia formation. Flangin-depleted parasites challenged with fluid shear force in flow chambers had a reduced ability to remain attached, indicating a role for the VLF in attachment. This secondary attachment mechanism complements the microtubule based adhesive ventral disc, a feature that is particularly important during mitosis when the parental ventral disc begins disassembly in preparation for cytokinesis. Importance The ventrolateral flange (VLF) is a lamellipodium-like structure found at the host-parasite interface that has long been thought to be involved in parasite attachment. The proteins responsible for building the VLF have remained unidentified precluding manipulation of the VLF to determine its role in Giardia biology. We identified Flangin, a novel actin associated protein that localizes to the VLF, implicating Giardia actin in VLF formation. We demonstrate that: 1.) Flangin, actin, and GlRac are required for VLF formation, 2.) the VLF serves as a membrane reservoir to support Giardia’s incredibly fast cytokinesis, and 3) the VLF augments attachment, which is critical to parasitism. The microtubule-based adhesive ventral disc and the actin-based ventrolateral flange represent redundant means of maintaining attachment, the presence of redundant systems illustrate the importance of attachment to the lifestyle of this ubiquitous parasite.

Differentiation into environmentally resistant cysts is required for transmission of the ubiquitous intestinal parasite Giardia lamblia . Encystation in Giardia requires the production, processing and transport of Cyst Wall Proteins (CWPs) in developmentally induced, Golgi-like, Encystation Specific Vesicles (ESVs). Progress through this trafficking pathway can be followed by tracking CWP localization over time. However, there is no recognized system to distinguish the advancing stages of this process which can complete at variable rates depending on how encystation is induced. Here, we propose a staging system for encysting Giardia based on the morphology of CWP1-stained ESVs. We demonstrate the molecular distinctiveness of maturing ESVs at these stages by following Gl Rab GTPases through encystation. Previously, we established that Giardia ’s sole Rho family GTPase, Gl Rac, associates with ESVs and has a role in regulating their maturation and the secretion of their cargo. As a proof of principle, we delineate the relationship between Gl Rac and ESV stages. Through proteomic studies, we identify putative interactors of Gl Rac that could be used as additional ESV stage markers. This staging system provides a common descriptor of ESV maturation regardless of the source of encysting cells. Furthermore, the identified set of molecular markers for ESV stages will be a powerful tool for characterizing trafficking mutants that impair ESV maturation and morphology.

Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published between 1 January 2000 to 31 July 2020. This systematic review is reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and is registered on Prospero (CRD42020149352). Study characteristics, sensors and algorithms used, accuracy and robustness were also summarized. In total, 1343 records were identified and 58 studies were included in this review. The experimental condition which was most often investigated was level ground walking along with stair and ramp ascent/descent activities. The machine learning algorithms implemented in the included studies reached global mean accuracies of around 90%. However, the robustness of those algorithms seems to be more broadly evaluated, notably, in everyday life. We also propose some guidelines for homogenizing future reports.

We examined how motor responses to a stimulus evolve as individuals learn to predict when a stimulus will appear, by comparing responses to a regular versus irregular stimulus train. The study was conducted with two groups of adults — one responded to the regular appearance of a visual stimulus every 3 s (R group) and the second responded to the irregular presentation of the same stimulus (IR group) at intervals varying between 2 and 4 s. Participants responded to the appearance of the stimulus by bending over to press a button that was slightly out of reach. This whole body reach requires muscular activation at the ankles. Over the course of 50 consecutive responses, the response times in the R group were found to decrease more than those for participants in the IR group. The electromyographs (EMGs) of two ankle antagonist muscles, the anterior tibialis and soleus were also modified as participants progressively learnt the temporal regularity of a sequence. Tibialis onset times for the R group were found to decrease faster. A less predictable observation was the faster reduction in post stimulus activation of the tibialis muscle for the R group. Soleus muscle deactivation is an indicator of movement preparation. EMG integrals for this muscle a little before stimulus onset showed a trend for greater decrease in the R group. In summary, our study shows that temporal expectations over repeated stimulus presentation permit the dynamic optimization of motor activity with progressively faster response times, muscle activation onset times and lower muscle activation amplitudes.

In this study, we compared key temporal points in the whole body pointing movement of healthy aging and young subjects. During this movement, subject leans forward from a standing position to reach a target. As it involves forward inclination of the trunk, the movement creates a risk for falling. We examined two strategic time points during the task—first, the crossover point where the velocity of the center of mass (CoM) in the vertical dimension outstripped the velocity in the anteroposterior dimension and secondly, the time to peak of the CoM velocity profile. Transitions to stabilizing postures occur at these time points. They both occurred earlier in aging subjects. The crossover point also showed adjustments with target distance in aging subjects, while this was not observed in younger subjects. The shifts in these key time points could not be attributed to differences in movement duration between the two groups. Investigation with an optimal control model showed that the temporal adjustment as a function of target distance in the healthy aging subjects fits into a strategy that emphasized equilibrium maintenance rather than absolute work as a control strategy.

Our goal was to apply a statistical approach to allow the identification of atypical language patterns and to differentiate patients with epilepsy from healthy subjects, based on their cerebral activity, as assessed by functional MRI (fMRI). Patients with focal epilepsy show reorganization or plasticity of brain networks involved in cognitive functions, inducing ‘atypical’ (compared to ‘typical’ in healthy people) brain profiles. Moreover, some of these patients suffer from drug-resistant epilepsy, and they undergo surgery to stop seizures. The neurosurgeon should only remove the zone generating seizures and must preserve cognitive functions to avoid deficits. To preserve functions, one should know how they are represented in the patient’s brain, which is in general different from that of healthy subjects. For this purpose, in the pre-surgical stage, robust and efficient methods are required to identify atypical from typical representations. Given the frequent location of regions generating seizures in the vicinity of language networks, one important function to be considered is language. The risk of language impairment after surgery is determined pre-surgically by mapping language networks. In clinical settings, cognitive mapping is classically performed with fMRI. The fMRI analyses allowing the identification of atypical patterns of language networks in patients are not sufficiently robust and require additional statistic approaches. In this study, we report the use of a statistical nonlinear machine learning classification, the Extreme Gradient Boosting (XGBoost) algorithm, to identify atypical patterns and classify 55 participants as healthy subjects or patients with epilepsy. XGBoost analyses were based on neurophysiological features in five language regions (three frontal and two temporal) in both hemispheres and activated with fMRI for a phonological (PHONO) and a semantic (SEM) language task. These features were combined into 135 cognitively plausible subsets and further submitted to selection and binary classification. Classification performance was scored with the Area Under the receiver operating characteristic curve (AUC). Our results showed that the subset SEM_LH BA_47-21 (left fronto-temporal activation induced by the SEM task) provided the best discrimination between the two groups (AUC of 91 ± 5%). The results are discussed in the framework of the current debates of language reorganization in focal epilepsy.

Recent evidence suggests that interval timing (the judgment of durations lasting from approximately 500 ms. to a few minutes) is closely coupled to the action control system. We used surface electromyography (EMG) and motion capture technology to explore the emergence of this coupling in 4-, 6-, and 8-month-olds. We engaged infants in an active and socially relevant arm-raising task with seven cycles and response period. In one condition, cycles were slow (every 4 s); in another, they were fast (every 2 s). In the slow condition, we found evidence of time-locked sub-threshold EMG activity even in the absence of any observed overt motor responses at all three ages. This study shows that EMGs can be a more sensitive measure of interval timing in early development than overt behavior.

We do not dispute the possibility of the existence in the brain of grandmother cells, which are very finely tuned neurons that fire only in the presence of specific objects or categories. However, we question the causal efficacy of such neurons at the functional or behaviour level. We claim that, even though very familiar items, such as my grandmother, may well have associated grandmother neurons, these neurons have very little, or no impact on the actual recognition of my grandmother. A study by Thomas, Van Hulle, and Vogels [(2002). Encoding of categories by noncategory-specific neurons in the inferior temporal cortex. Journal of Cognitive Neuroscience, 13, 190-200. doi:10.1162/089892901564252] found finely tuned, category-specific neurons in the inferior temporal cortex of monkeys, but also found that when these neurons were removed from their analysis, this had no effect on categorisation performance. Further, we have found no reported cases of the loss of recognition of single, highly familiar objects, which also argues for a lack of causal efficacy of grandmother-cell neurons.

OBJECTIVE:While previous studies have demonstrated that depressive elderly subjects (DES) experience difficulties in the processing of simultaneous cognitive tasks, few have examined the coupling of cognitive tasks with seemingly 'automatic' tasks, such as standing upright. Current patient management focuses on pharmacological treatments and cognitive-behavioral therapies. METHODS:Healthy elderly (HES) and non-treated DES were included. Postural sway in DES was compared with that in HES while in single-task and dual-task conditions. The single-task consisted of standing upright. For the dual-task, the subjects recalled various items from memory or counted while standing upright. Postural sway was evaluated by computing the center of pressure (CoP) area and path length. RESULTS:DES showed greater postural sway than HES in all conditions. The HES showed a greater CoP area in the dual-task than in the single-task conditions. In DES, the CoP area in the single-task condition was similar to that in the dual-task condition. CONCLUSIONS:The greater postural sway observed in DES may be a cause of a greater risk of falls. We showed that even seemingly automatic tasks, such as maintaining an upright posture, are affected by depression. SIGNIFICANCE:These results are important for the management of DES.

In recent years great progress has been made in the computational modeling of interval timing. A wide range of models capturing different aspects of interval timing now exist. These models can be seen as constituting four, sometimes overlapping, general classes of models: pacemaker-accumulator models, multiple-oscillator models, memory-trace models, and drift-diffusion (or random-process) models. We suggest that computational models should be judged based on their performance on a number of criteria-namely, the scalar property, their ability to reproduce retrospective and prospective timing effects, and their sensitivity to attentional and neurochemical manipulations. Future challenges will involve building integrated models and sharing model code to allow direct comparisons against a battery of empirical data.

Handheld video game consoles have evolved much like their desktop counterparts over the years. The most recent eighth generation of game consoles are now defined not by their ability to interact online using a web browser, but by the social media facilities they now provide. This chapter describes a forensic methodology for analyzing Nintendo 3DS handheld video game consoles, demonstrating their potential for misuse and highlighting areas where evidence may reside. Empirical research has led to the formulation of a detailed methodology that can assist forensic examiners in maximizing evidence extraction while minimizing, if not preventing, the destruction of information.