Movement Planning Research Articles

A control policy can be adapted to task demands during both motor execution and motor planning.

Movement planning consists of several processes related to the preparation of a movement such as decision making, target selection, application of task demands, action selection and specification of movement kinematics. These numerous processes are reflected in the reaction time, which is the time that it takes to start executing the movement. However, not all the processes that lead to motor planning increase reaction time. In this paper, we wanted to test whether tuning the control policy to task demands contributes to reaction time. Taking into account that the tuning of the control policy differs for narrow and wide targets, we used a timed response paradigm in order to track the amount of time needed to tune the control policy appropriately to task demands. We discovered that it does not take any time during motor planning and even that it can occur indistinguishably during motor planning or during motor execution. That is, the tuning the control policy was equally good when the narrow or wide target was displayed before than when it was displayed after the start of the movement. These results suggest that the frontier between motor planning and execution is not as clear cut as it is often depicted.

ADVANCES IN BONE REMODELING AND CLEAR ALIGNERS IN ORTHODONTICS

The use of clear aligners in orthodontics represents a significant advancement in dental treatment, allowing effective tooth movement with a less invasive approach compared to traditional fixed appliances. Clear aligners not only facilitate the alignment of teeth but also promote changes in the supporting alveolar bone. The success of these movements relies on the surrounding bone's response to mechanical stress during treatment, involving processes of bone resorption and deposition. Research has demonstrated that advancements in digital technology, such as 3D modeling and artificial intelligence, enhance the planning of tooth movements, making bone remodeling more predictable. Sophisticated algorithms simulate aligner forces on the alveolar bone, optimizing each treatment phase. However, limitations persist in complex cases where specific movements, like extrusion and rotation, require precise force control. Recent studies by Guo et al. (2023) and Abogabal et al. (2023) evaluated the effects of clear aligners on alveolar bone dimensions during orthodontic treatment, finding a greater occurrence of bone defects after treatment. They highlighted the differences in bone height changes between aligners and fixed appliances, indicating that clear aligners might have less impact on bone height. Innovative approaches such as low-intensity pulsed ultrasound (LIPUS) and high-frequency vibration (HFV) have also been investigated for their potential to enhance treatment outcomes. Research indicates that daily vibration may reduce the time required for dental correction while increasing levels of cytokines and markers for bone remodeling. Overall, the integration of digital tools and innovative techniques in orthodontics is crucial for improving treatment efficacy, addressing challenges in complex cases, and ultimately enhancing patient experience and satisfaction.

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

Cerebellar patients exhibit various motor impairments, but the sequence of primary and compensatory processes leading to these deficits remains unclear. To investigate this, we reversibly blocked cerebellar outflow in monkeys performing planar reaching. The block caused a spatially tuned reduction in hand velocity due to decreased muscle torque, especially in movements with high coupling torques. Examining repeated movements to the same target revealed that during multi-joint reaching movements, the reduced velocity was driven by an acute deficit superimposed on a gradually emergent strategic slowing aimed at minimizing passive inter-joint interactions. However, the reduced velocity did not explain the decomposed and variable trajectories observed during the cerebellar block. Our findings suggest that loss of cerebellar signals leads to motor impairments through insufficient muscle torques and an altered control strategy to compensate for the impaired control of limb dynamics. However, impaired feedforward control also increases motor noise, which cannot be strategically eliminated.

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

Our perception of objects depends on non-oculomotor depth cues, such as pictorial distance cues and binocular disparity, and oculomotor depth cues, such as vergence and accommodation. Although vergence eye movements are always involved in perceiving real distance, previous studies have mainly focused on the effect of oculomotor state via "proprioception" on distance and size perception. It remains unclear whether the oculomotor command of vergence eye movement would also influence visual processing. To address this question, we placed a light at 28.5 cm and a screen for stimulus presentation at 57 cm from the participants. In the NoDivergence condition, participants were asked to maintain fixation on the light regardless of stimulus presentation throughout the trial. In the WithDivergence condition, participants were instructed to initially maintain fixation on the near light and then turn their two eyes outward to look at the stimulus on the far screen. The stimulus was presented for 100 msec, entirely within the preparation stage of the divergence eye movement. We found that participants perceived the stimulus as larger but were less sensitive to stimulus sizes in the WithDivergence condition than in the NoDivergence condition. The earliest visual evoked component C1 (peak latency 80 msec), which varied with stimulus size in the NoDivergence condition, showed similar amplitudes for larger and smaller stimuli in the WithDivergence condition. These results show that vergence eye movement planning affects the earliest visual processing and size perception, and demonstrate an example of the effect of motor command on sensory processing.

Dynamic Routing and Scheduling Approach for Aircraft Taxi Automation with Adaptive Surface Situation

The emergence of surface trajectory-based operation (STBO) has promoted the development of taxi automation systems to plan conflict-free aircraft trajectories for efficient airport operations. Unlike traditional airport ground movement, aircraft guided by the taxi automation system possess a significant degree of freedom during taxiing, requiring the system to coordinate aircraft movement on the surface with timely responses to uncertainty. This study proposes a dynamic routing and scheduling approach with an adaptive surface situation characterization mechanism. A link-level unimpeded taxi time estimation method is designed to fine-grain characterize airport operation. A comprehensive evaluation system is then developed to identify similar situation patterns. Finally, a dynamic routing and scheduling approach is proposed to optimize airport ground movement with an adaptive and refined surface situation mechanism. The case study of actual operational data collected from a hub airport reveals that the proposed approach achieves efficient movement plans and collaborative control for all aircraft, as well as a more balanced utilization of the runway. The embedded adaptive situation mechanism also makes a better tradeoff between computational efficiency and optimal solutions. The study provides a promising approach to generating conflict-free four-dimensional trajectories for airport operations in future STBO scenarios.

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.

Biomechanics of tooth rotation in clear aligner therapy

Clear aligner therapy has become increasingly popular due to its esthetic and comfort advantages. However, its predictability in certain tooth movements, particularly rotations, is limited compared to fixed appliances. This article explains the biomechanical differences between fixed appliances and clear aligners, highlighting the influence of tooth geometry and aligner-tooth interface dynamics on treatment outcomes. It also explores the impact of unintended movements and the need for open contacts to facilitate rotations. By understanding these biomechanical details and considering innovative attachment designs and movement planning strategies, clinicians can enhance the predictability and effectiveness of clear aligner therapies.

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.

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.