Movement Planning Research Articles

Investigation of the transcallosal ventral premotor cortex connection in humans using transcranial magnetic stimulation

Background: The premotor cortex plays a role in the planning of movement. Previous transcranial magnetic stimulation (TMS) studies have shown ipsilateral premotor-to-motor inhibition in healthy subjects at rest. Moreover, this premotor-to-motor inhibition has been found to be modulated during preparation for movement, such as precision grip and whole hand grasp. Cooperation between the bilateral ventral premotor cortices may play a functional role. We aimed to investigate the influence of the contralateral on the ipsilateral ventral premotor cortex.Methods: Fourteen right-handed healthy subjects (six women and eight men; mean age, 37 years; standard deviation, 14 years) completed the study. We used a three single-pulse TMS paradigm (preconditioning, conditioning and test pulse) to sequentially stimulate the right ventral premotor cortex, left ventral premotor cortex and left primary motor cortex.Results: We found that in healthy subjects at rest, stimulating the contralateral ventral premotor cortex resulted in reversal of the resting premotor-to-motor inhibition.Conclusions: Our results suggest that the contralateral ventral premotor cortex exerts an inhibitory influence on the ipsilateral ventral premotor cortex, which may be a component of bi-hemispheric control of manual tasks. This is the first study to evaluate the functional connectivity between the bilateral ventral premotor cortices.

Use of a hand-worn accelerometer to measure hand differences in Grooved Pegboard Test

Research on laterality, which pertains to the preference for using one hand over the other in daily activities, has recently been a growing topic of investigation. Studies demonstrate that performance differences between the right and left hands arise from distinct strategies in utilizing information for movement execution. To conduct a more comprehensive analysis of these differences, we aimed to investigate various measures using a wrist accelerometer during the execution of a traditional tool to assess manual performance. The proposed hypothesis suggested that tasks performed with the right hand would exhibit shorter movement times due to more efficient real-time information processing. In contrast, tasks performed with the left hand would show shorter reaction times due to movement planning proficiency. Furthermore, we hypothesized that increased task complexity would make these differences more pronounced. The study revealed that, in the less complex task, the right hand outperformed the left hand in execution speed, whereas the left hand demonstrated faster reaction times in the more complex task. The task complexity highlighted the differences, emphasizing the impact of task demands on hand specialization. Using an accelerometer provided valuable insights, indicating potential avenues for refining assessment tools and analyzing manual control. Keywords: motor control, hemispheric specialization, laterality, hand function, dexterity.

Passenger Flow Management in Front of Ticket Booths in Urban Railway Stations

In railway stations, queues often form in front of the ticketing booths that provide ticketing services. Proper design of service systems is key to effectively managing these queues, as waiting time is a critical factor affecting customer satisfaction. This research focuses on optimising the location and configuration of queues in front of ticket booths to minimise waiting times and increase service efficiency. Passenger flow management at the station can be understood as the planning and implementation of the orderly movement of the crowd through the infrastructure. Using operational Markov chain analysis, we evaluate different queue configurations and the number of service providers in urban railway stations. The study specifically focuses on the case of the Poprad-Tatry railway station in Slovakia, where we propose the introduction of a common queue for all ticket booths. We propose the distribution of lines and their schedule, based on mathematical analyses, by creating designated service zones with a common queue in front of the ticket booths. The results show that this approach significantly reduces waiting times and improves overall system efficiency. This research focusses on solving the shortcomings in the design of queues in railway stations, specifically on the use of a common queue, thereby contributing to the improvement of passenger movement management.

Mapping cognitive activity from electrocorticography field potentials in humans performing NBack task

Objective. Advancements in data science and assistive technologies have made invasive brain-computer interfaces (iBCIs) increasingly viable for enhancing the quality of life in physically disabled individuals. Intracortical microelectrode implants are a common choice for such a communication system due to their fine temporal and spatial resolution. The small size of these implants makes the implantation plan critical for the successful exfiltration of information, particularly when targeting representations of task goals that lack robust anatomical correlates. Approach. Working memory processes including encoding, retrieval, and maintenance are observed in many areas of the brain. Using human electrocorticography (ECoG) recordings during a working memory experiment, we provide proof that it is possible to localize cognitive activity associated with the task and to identify key locations involved with executive memory functions. Results. From the analysis, we could propose an optimal iBCI implant location with the desired features. The general approach is not limited to working memory but could also be used to map other goal-encoding factors such as movement intentions, decision-making, and visual-spatial attention. Significance. Deciphering the intended action of a BCI user is a complex challenge that involves the extraction and integration of cognitive factors such as movement planning, working memory, visual-spatial attention, and the decision state. Examining field potentials from ECoG electrodes while participants engaged in tailored cognitive tasks can pinpoint location with valuable information related to anticipated actions. This manuscript demonstrates the feasibility of identifying electrodes involved in cognitive activity related to working memory during user engagement in the NBack task. Devoting time in meticulous preparation to identify the optimal brain regions for BCI implant locations will increase the likelihood of rich signal outcomes, thereby improving the overall BCI user experience.

Future movement plans interact in sequential arm movements.

Real-world actions often comprise a series of movements that cannot be entirely planned before initiation. When these actions are executed rapidly, the planning of multiple future movements needs to occur simultaneously with the ongoing action. How the brain solves this task remains unknown. Here, we address this question with a new sequential arm reaching paradigm that manipulates how many future reaches are available for planning while controlling execution of the ongoing reach. We show that participants plan at least two future reaches simultaneously with an ongoing reach. Further, the planning processes of the two future reaches are not independent of one another. Evidence that the planning processes interact is twofold. First, correcting for a visual perturbation of the ongoing reach target is slower when more future reaches are planned. Second, the curvature of the current reach is modified based on the next reach only when their planning processes temporally overlap. These interactions between future planning processes may enable smooth production of sequential actions by linking individual segments of a long sequence at the level of motor planning.

Future movement plans interact in sequential arm movements

Real-world actions often comprise a series of movements that cannot be entirely planned before initiation. When these actions are executed rapidly, the planning of multiple future movements needs to occur simultaneously with the ongoing action. How the brain solves this task remains unknown. Here, we address this question with a new sequential arm reaching paradigm that manipulates how many future reaches are available for planning while controlling execution of the ongoing reach. We show that participants plan at least two future reaches simultaneously with an ongoing reach. Further, the planning processes of the two future reaches are not independent of one another. Evidence that the planning processes interact is twofold. First, correcting for a visual perturbation of the ongoing reach target is slower when more future reaches are planned. Second, the curvature of the current reach is modified based on the next reach only when their planning processes temporally overlap. These interactions between future planning processes may enable smooth production of sequential actions by linking individual segments of a long sequence at the level of motor planning.

Changes in brain functional connectivity and muscle strength independent of elbow flexor atrophy following upper limb immobilization in young females.

Muscle disuse induces a decline in muscle strength that exceeds the rate and magnitude of muscle atrophy, suggesting that factors beyond the muscle contribute to strength loss. The purpose of this study was to characterize changes in the brain and neuromuscular system in addition to muscle size following upper limb immobilization in young females. Using a within-participant, unilateral design, 12 females (age: 20.6±2.1years) underwent 14days of upper arm immobilization using an elbow brace and sling. Bilateral measures of muscle strength (isometric and isokinetic dynamometry), muscle size (magnetic resonance imaging), voluntary muscle activation capacity, corticospinal excitability, cortical thickness and resting-state functional connectivity were collected before and after immobilization. Immobilization induced a significant decline in isometric elbow flexion (-21.3±19.2%, interaction: P=0.0440) and extension (-19.9±15.7%, interaction: P=0.0317) strength in the immobilized arm only. There was no significant effect of immobilization on elbow flexor cross-sectional area (CSA) (-1.2±2.4%, interaction: P=0.466), whereas elbow extensor CSA decreased (-2.9±2.9%, interaction: P=0.0177) in the immobilized arm. Immobilization did not differentially alter voluntary activation capacity, corticospinal excitability, or cortical thickness (P>0.05); however, there were significant changes in the functional connectivity of brain regions related to movement planning and error detection (P<0.05). This study reveals that elbow flexor strength loss can occur in the absence of significant elbow flexor muscle atrophy, and that the brain represents a site of functional adaptation in response to upper limb immobilization in young females.

Effects of Virtual Rehabilitation Training on Post-Stroke Executive and Praxis Skills and Depression Symptoms: A Quasi-Randomised Clinical Trial.

Apraxia is a neurological disorder that is common after a stroke and impairs the planning and execution of movements. In the rehabilitation field, virtual reality (VR) presents new opportunities and offers advantages to both rehabilitation teams and individuals with neurological conditions. Indeed, VR can stimulate and improve cognitive reserve and abilities, including executive function, and enhance the patient's emotional status. The objective of this research is to determine the effectiveness of VR in improving praxis skills and behavioural functioning in individuals with severe stroke. A total of 20 stroke patients were enrolled from February 2022 to March 2023 and divided by the order of their recruitment into two groups: the experimental group (EG: n = 10) received training to improve their praxis skills using VR whereas the control one (CG: n = 10) received the same amount of standard training. All patients underwent an evaluation using a psychometric battery that consisted of the Hamilton Rating Scale for Depression (HRS-D), Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB), Spinnler and Tognoni test, and De Renzi and Faglioni test. Valuations were performed before rehabilitation (T0) and after its completion (T1). Both groups demonstrated significant improvements post-intervention. The EG showed a greater enhancement in their MMSE scores (p = 0.002), and reductions in both ideomotor and constructive apraxia (p = 0.002 for both), compared to the CG. The VR-based training also resulted in significant improvements in their depression symptoms (HRSD scores improved, p = 0.012 in EG vs. p = 0.021 in CG). This pilot study suggests that VR could help reduce cognitive, constructive apraxia and ideomotor apraxia symptoms caused by stroke injury.

Different sensory information is used for state estimation when stationary or moving.

The accurate estimation of limb state is necessary for movement planning and execution. While state estimation requires both feedforward and feedback information, we focus here on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improves estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. We formalized this hypothesis by modeling feedback-based state estimation using the longstanding maximum likelihood estimation model of multisensory integration, which we updated to account for sensory delays. Our model predicted that the benefit of multisensory integration was largely lost when the limb was passively moving. We tested this hypothesis in a series of experiments in human subjects that compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating limb position either statically at the end of the movement or dynamically at movement midpoint. In the static case, we observed significant interference: discrepant feedback in one modality systematically biased sensory estimates based on the other modality. However, no interference was seen in the dynamic case: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality.Significance statement The estimation of limb state involves feedforward and feedback information. While estimation based on feedback has been well studied when the limb is stationary, it is unknown if similar sensory processing supports limb position estimates when moving. Using a computational model and behavioral experiments, we show that feedback-based state estimation may involve multisensory integration in the static case, but it is likely based on a single modality when the limb is moving. We suggest that this difference may stem from visual and proprioceptive feedback delays.

Disentangling acute motor deficits and adaptive responses evoked by the loss of cerebellar output.

Our study examined the impact of cerebellar dysfunction on movement control by reversibly blocking the cerebellar output in monkeys. During a cerebellar block, reaching movements initially slowed due to an acute deficit in generating muscle torque. Beyond this primary deficit, there appeared to be a secondary, strategic slowing down of movements aimed at mitigating inter-joint interactions associated with rapid, ballistic movements. Finally, during the cerebellar block we observed movement variability increased independently of the reduced velocity, likely reflecting errors in movement planning. These findings highlight the role of the cerebellar in movement control and delineate the processes following cerebellar dysfunction that culminate in a broad range of motor impairments.

Neural-Targeted Rehabilitation Strategies to Restore Typical Activation after Joint Injury.

In patients with musculoskeletal injury, changes have been observed within the central nervous system that contribute to altered movement planning. This maladaptive neuroplasticity potentially explains the clinical disconnect where residual neuromuscular dysfunction and high rates of reinjury that are often observed even after individuals clear return-to-activity functional testing. An improved understanding of these neural changes could therefore serve as a guide for facilitating a more complete recovery and minimizing risk of re-injury. Therefore, we propose a paradigm of neural-targeted rehabilitation to augment commonly used therapeutic techniques targeting sensorimotor function in order to better address maladaptive plasticity. While most treatments have the capability to modify neural function, optimizing these treatments and combining them with integrative therapies (e.g. implementation of motor learning strategies, transcranial direct current stimulation) may enhance neural efficiency and facilitate return-to activity in patients with musculoskeletal injury. To complete this model, consideration of affective aspects of movement and associated interventions must also be considered to improve the durability of these changes.

Macroscopic brain dynamics beyond contralateral primary motor cortex for movement prediction

This study investigates the complex relationship between upper limb movement direction and macroscopic neural signals in the brain, which is critical for understanding brain-computer interfaces (BCI). Conventional BCI research has primarily focused on a local area, such as the contralateral primary motor cortex (M1), relying on the population-based decoding method with microelectrode arrays. In contrast, macroscopic approaches such as electroencephalography (EEG) and magnetoencephalography (MEG) utilize numerous electrodes to cover broader brain regions. This study probes the potential differences in the mechanisms of microscopic and macroscopic methods. It is important to determine which neural activities effectively predict movements. To investigate this, we analyzed MEG data from nine right-handed participants while performing arm-reaching tasks. We employed dynamic statistical parametric mapping (dSPM) to estimate source activity and built a decoding model composed of long short-term memory (LSTM) and a multilayer perceptron to predict movement trajectories. This model achieved a high correlation coefficient of 0.79 between actual and predicted trajectories. Subsequently, we identified brain regions sensitive to predicting movement direction using the integrated gradients (IG) method, which assesses the predictive contribution of each source activity. The resulting salience map demonstrated a distribution without significant differences across motor-related regions, including M1. Predictions based solely on M1 activity yielded a correlation coefficient of 0.42, nearly half as effective as predictions incorporating all source activities. This suggests that upper limb movements are influenced by various factors such as movement coordination, planning, body and target position recognition, and control, beyond simple muscle activity. All of the activities are needed in the decoding model using macroscopic signals. Our findings also revealed that contralateral and ipsilateral hemispheres contribute equally to movement prediction, implying that BCIs could potentially benefit patients with brain damage in the contralateral hemisphere by utilizing brain signals from the ipsilateral hemisphere. In conclusion, this study demonstrates that macroscopic activity from large brain regions significantly contributes to predicting upper limb movement. Non-invasive BCI systems would require a comprehensive collection of neural signals from multiple brain regions.

Microscopic simulation of bicycle traffic flow incorporating cyclists’ heterogeneous dynamics and non-lane-based movement strategies

Cycling as a mode of transport is on an upward trend as a low-emission alternative to driving in urbanized areas nowadays. With the increasing number of cyclists, it is of great importance to assess the capacity of cycling infrastructure in practice. Simulation models are useful tools to investigate bicycle flow performance considering cyclists’ distinct moving behaviors. However, existing bicycle simulation models are restricted by either space discretization, lane-based setup, adaptation from models for car traffic, or complicated calibration requirement in a force-based environment. In addition, cyclists’ decision-making ability in the operational-level cycling behavior are not well-captured in these models. This paper proposes a comprehensible microscopic bicycle simulation model which includes a detailed decision-making process and the ability to simulate continuous-space lateral movement. The model consists of three levels, maneuver decision, movement planning, and physical acceleration. It is able to simulate bicycle flow dynamics in undersaturated traffic conditions on an exclusive bike path. As we do not intend to show the empirical validity of the proposed model, the simulation experiment aims at verifying the model and exploring bicycle flow performance in various scenarios by estimating the fundamental diagrams (FDs). The effect of different path widths on bicycle flow capacity is first explored. Other behavioral factors, including desired speed heterogeneity, overtaking incentive, and safety region size perceived by cyclists, which can potentially influence the shape of the FD are also tested. The model can be further extended to simulate relatively complex cycling behavior with cooperative and anticipative strategies and investigate bicycle flow characteristics in congested traffic conditions.

Optimal time reuse strategy-based dynamic multi-AGV path planning method

The window strategy, known for its flexibility and efficiency, is extensively used in dynamic path planning. To further enhance the performance of the Automated Guided Vehicles (AGVs) sorting system, the two processes of AGV movement and path planning can be executed concurrently based on the window strategy. Nonetheless, difficulties in matching the computing time of the planning server with the moving time of AGVs may cause delays or reduced path optimality. To address the problem, this paper proposes an optimal time reuse strategy. The proposed solution controls computing time by managing path length for each planning instance, ensuring alignment with the moving time of AGVs to maximize path optimality and avoid delays. To achieve this, two aspects need to be considered. Firstly, on a systemic level, we control the entry rate of AGVs by adjusting the replanning period, thus avoiding congestion caused by excessive AGVs and maintaining high system efficiency. Secondly, we reversely control the computing time by adjusting the path length that needs to be planned for each single planning, so that it matches the moving time of AGVs. Simulation results show that our method outperforms existing top-performing methods, achieving task completion rates 1.64, 1.57, and 1.12 times faster across various map sizes. This indicates its effectiveness in synchronizing planning and movement times. The method contributes significantly to dynamic path planning methodologies, offering a novel approach to time management in AGV systems.

The Basal Ganglia Downstream Control of Action - An Evolutionarily Conserved Strategy.

The motor areas of the cortex and the basal ganglia both contribute to determining which motor actions will be recruited at any moment in time, and their functions are intertwined. Here, we review the basal ganglia mechanisms underlying the selection of behavior of the downstream control of motor centers in the midbrain and brainstem and show that the basic organization of the forebrain motor system is evolutionarily conserved throughout vertebrate phylogeny. The output level of the basal ganglia (e.g. substantia nigra pars reticulata) has GABAergic neurons that are spontaneously active at rest and inhibit a number of specific motor centers, each of which can be relieved from inhibition if the inhibitory output neurons themselves become inhibited. The motor areas of the cortex act partially via the dorsolateral striatum (putamen), which has specific modules for the forelimb, hindlimb, trunk, etc. Each module operates in turn through the two types of striatal projection neurons that control the output modules of the basal ganglia and thereby the downstream motor centers. The mechanisms for lateral inhibition in the striatum are reviewed as well as other striatal mechanisms contributing to action selection. The motor cortex also exerts a direct excitatory action on specific motor centers. An overview is given of the basal ganglia control exerted on the different midbrain/brainstem motor centers, and the efference copy information fed back via the thalamus to the striatum and cortex, which is of importance for the planning of future movements.

Implementation of Healthy Lifestyle Through Rhythmic Gymnastics for Village Communities

The purpose of community service activities is to provide the village community with guidance on maintaining bodily health by adopting a healthy lifestyle through rhythmic gymnastics. Based on data from the Directorate General of Public Health of the Ministry of Health of the Republic of Indonesia in 2022, the percentage of districts/cities promoting a healthy living movement in West Kalimantan province was 28.6%. This means that the figure has not yet reached the target of the community movement plan set at 40%. The methods provided include: (1) survey stages with partners, (2) coordination with the Village Chief and local tribal leaders, (3) implementation of healthy gymnastics socialization, (4) documentation and publication. The results of the community service (PKM) implementation are considered good and responsive, as conveyed by the PKM team that the enthusiasm of the villagers participating in the socialization of a healthy lifestyle through rhythmic gymnastics for the village community is high among both young and old age groups

Effects of Vergence Eye Movement Planning on Size Perception and Early Visual Processing

Effects of Vergence Eye Movement Planning on Size Perception and Early Visual Processing

Exploring Electrocortical Signatures of Gait Adaptation: Differential Neural Dynamics in Slow and Fast Gait Adapters.

Individuals exhibit significant variability in their ability to adapt locomotor skills, with some adapting quickly and others more slowly. Differences in brain activity likely contribute to this variability, but direct neural evidence is lacking. We investigated individual differences in electrocortical activity that led to faster locomotor adaptation rates. We recorded high-density electroencephalography while young, neurotypical adults adapted their walking on a split-belt treadmill and grouped them based on how quickly they restored their gait symmetry. Results revealed unique spectral signatures within the posterior parietal, bilateral sensorimotor, and right visual cortices that differ between fast and slow adapters. Specifically, fast adapters exhibited lower alpha power in the posterior parietal and right visual cortices during early adaptation, associated with quicker attainment of steady-state step length symmetry. Decreased posterior parietal alpha may reflect enhanced spatial attention, sensory integration, and movement planning to facilitate faster locomotor adaptation. Conversely, slow adapters displayed greater alpha and beta power in the right visual cortex during late adaptation, suggesting potential differences in visuospatial processing. Additionally, fast adapters demonstrated reduced spectral power in the bilateral sensorimotor cortices compared with slow adapters, particularly in the theta band, which may suggest variations in perception of the split-belt perturbation. These findings suggest that alpha and beta oscillations in the posterior parietal and visual cortices and theta oscillations in the sensorimotor cortex are related to the rate of gait adaptation.

Functional and Effective Connectivity Underlying Semantic Verbal Fluency.

Semantic verbal fluency (SVF) impairment is present in several neurological disorders. Although activation in SVF-related areas has been reported, how these regions are connected and their functional roles in the network remain divergent. We assessed SVF static and dynamic functional connectivity (FC) and effective connectivity in healthy participants using functional magnetic resonance imaging. We observed activation in the inferior frontal (IFG), middle temporal (pMTG) and angular gyri (AG), anterior cingulate (AC), insular cortex, and regions of the superior, middle, and medial frontal gyri (SFG, MFG, MidFG). Our static FC analysis showed a highly interconnected task and resting state network. Increased connectivity of AC with the pMTG and AG was observed for the task. The dynamic FC analysis provided circuits with connections similarly modulated across time and regions related to category identification, language comprehension, word selection and recovery, word generation, inhibition of speaking, speech planning, and articulatory planning of orofacial movements. Finally, the effective connectivity analysis provided a network that best explained our data, starting at the AG and going to the pMTG, from which there was a division between the ventral and dorsal streams. The SFG and MFG regions were connected and modulated by the MidFG, while the inferior regions formed the ventral stream. Therefore, we successfully assessed the SVF network, exploring regions associated with the entire processing, from category identification to word generation. The methodological approach can be helpful for further investigation of the SVF network in neurological disorders.

Artificial and biological supports are different for pea plants.

Previous studies on the kinematics of pea plants' ascent and attach behavior have demonstrated that the signature of their movement varies depending on the kind of support. So far, these studies have been confined to artificial supports (e.g. wooden sticks). Little is known regarding the conditions under which pea plants could rely on biological supports (e.g. neighboring plants) for climbing toward the light. In this study, we capitalize on the 3D kinematic analysis of movement to ascertain whether pea plants scale their kinematics differently depending on whether they aim for artificial or biological support. Results suggest that biological support determines a smoother and more accurate behavior than that elicited by the artificial one. These results shed light on pea plants' ability to detect and classify the properties of objects and implement a movement plan attuned to the very nature of the support. We contend that such differences depend on the augmented multisensory experience elicited by the biological support.