From the motor cortex to the movement and back again

A follow up investigation of placental pathology, responsive parenting, and preschool children's executive functioning and language development

Despite documented effects linking underlying placental diseases and neurological impairments in children, little is known about the long-term effects of placental pathology on children's neurocognitive outcomes. In addition, maternal responsivity, known to positively influence early postnatal cognitive development, may act to protect children from putative adverse effects of placental pathology. The current study is a follow up of medically healthy, term born, preschool age children, born with placental pathology. A sample of 118 children (45 comparison children with normal placental findings, 73 born with placental pathology) were followed when children were 3-4 years old. In comparison to children born to mothers with normal placentas, placental pathology was associated with poorer performance in the executive function involving cognitive flexibility, but not inhibitory control or receptive language. Maternal responsivity was observed to be marginally protective on the impact of placental pathology risk on cognitive flexibility, but this was not seen for either inhibitory control or receptive language.

An Acellular, Self-Healed Trilayer Cryogel for Osteochondral Regeneration in Rabbits

Osteochondral regeneration remains formidable challenges despite significant advances in microsurgery. Herein, an acellular trilayer cryogel (TC) with injectability, tunable pore sizes (80-200 µm), and appropriate compressive modulus (10.8 kPa) is manufactured from self-healable hydrogel under different gelling times through Schiff reaction between chitosan and difunctionalized polyurethane (DFPU). Bioactive molecules (Y27632 and dexamethasone) are respectively loaded in the top and bottom layers to form the Y27632/dexamethasone-loaded trilayer cryogel (Y/DEX-TC). Mesenchymal stem cells (MSCs) seeded in Y/DEX-TC proliferated ≈350% in vitro and underwent chondrogenesis or osteogenesis in response to the respective release of Y or DEX in 14 days. Acupuncture is administered to animals in an attempt to modulate the innate regulatory system and mobilize endogenous MSCs for osteochondral defect regeneration. In vivo rabbit experiments using Y/DEX-TC combined with acupuncture successfully regulate SDF-1 and TGF-β1 levels, which possibly cause MSC migration toward Y/DEX-TC. The synergistic effect of cryogel and acupuncture on immunomodulation is verified with a ≈7.3-fold enhancement of the M2-/M1-macrophage population ratio by treatment of Y/DEX-TC combining acupuncture, significantly greater than ≈1.5-fold increase by acupuncture or ≈2.2-fold increase by Y/DEX-TC alone. This novel strategy using acellular drug-loaded cryogel and accessible acupuncture shows promise in treating osteochondral defects of joint damage.

Emotion in action: When emotions meet motor circuits

The brain is a remarkably complex organ responsible for a wide range of functions, including the modulation of emotional states and movement. Neuronal circuits are believed to play a crucial role in integrating sensory, cognitive, and emotional information to ultimately guide motor behavior. Over the years, numerous studies employing diverse techniques such as electrophysiology, imaging, and optogenetics have revealed a complex network of neural circuits involved in the regulation of emotional or motor processes. Emotions can exert a substantial influence on motor performance, encompassing both everyday activities and pathological conditions. The aim of this review is to explore how emotional states can shape movements by connecting the neural circuits for emotional processing to motor neural circuits. We first provide a comprehensive overview of the impact of different emotional states on motor control in humans and rodents. In line with behavioral studies, we set out to identify emotion-related structures capable of modulating motor output, behaviorally and anatomically. Neuronal circuits involved in emotional processing are extensively connected to the motor system. These circuits can drive emotional behavior, essential for survival, but can also continuously shape ongoing movement. In summary, the investigation of the intricate relationship between emotion and movement offers valuable insights into human behavior, including opportunities to enhance performance, and holds promise for improving mental and physical health. This review integrates findings from multiple scientific approaches, including anatomical tracing, circuit-based dissection, and behavioral studies, conducted in both animal and human subjects. By incorporating these different methodologies, we aim to present a comprehensive overview of the current understanding of the emotional modulation of movement in both physiological and pathological conditions.

Biomechanical modeling for the estimation of muscle forces: toward a common language in biomechanics, medical engineering, and neurosciences

Different research fields, such as biomechanics, medical engineering or neurosciences take part in the development of biomechanical models allowing for the estimation of individual muscle forces involved in motor action. The heterogeneity of the terminology used to describe these models according to the research field is a source of confusion and can hamper collaboration between the different fields. This paper proposes a common language based on lexical disambiguation and a synthesis of the terms used in the literature in order to facilitate the understanding of the different elements of biomechanical modeling for force estimation, without questioning the relevance of the terms used in each field or the different model components or their interest. We suggest that the description should start with an indication of whether the muscle force estimation problem is solved following the physiological movement control (from the nervous drive to the muscle force production) or in the opposite direction. Next, the suitability of the model for force production estimation at a given time or for monitoring over time should be specified. Authors should pay particular attention to the method description used to find solutions, specifying whether this is done during or after data collection, with possible method adaptations during processing. Finally, the presence of additional data must be specified by indicating whether they are used to drive, assist, or calibrate the model. Describing and classifying models in this way will facilitate the use and application in all fields where the estimation of muscle forces is of real, direct, and concrete interest.

Transcranial direct current stimulation to facilitate neurofunctional rehabilitation in children with autism spectrum disorder: a protocol for a randomized, sham-controlled, double-blind clinical trial

Background

Anodal transcranial direct current stimulation (tDCS) over the primary motor cortex and cerebellum is gaining prominence in the literature due to its potential to favor learning and motor performance. If administered during motor training, tDCS is capable of increasing the effect of training. Considering the motor impairment presented by children with Autism Spectrum Disorders (ASD), atDCS applied during motor training may contribute to the rehabilitation of these children. However, it is necessary to examine and compare the effects of atDCS over the motor cortex and the cerebellum on the motor skills of children with ASD. This information may benefit future clinical indications of tDCS for rehabilitation of children with ASD. The aim of the proposed study is to determine whether anodal tDCS over the primary motor cortex and cerebellum can enhance the effects of gait training and postural control on motor skills, mobility, functional balance, cortical excitability, cognitive aspects and behavioral aspects in children with ASD. Our hypothesis is the active tDCS combined with motor training will enhance the performance of the participants in comparison to sham tDCS.

Methods and design

A randomized, sham-controlled, double-blind clinical trial will be conducted involving 30 children with ASD that will be recruited to receive ten sessions of sham or ten sessions of active anodal tDCS (1 mA, 20 min) over the primary motor cortex or cerebellun combined with motor training. The participants will be assessed before as well as one, four and eight weeks after the interventions. The primary outcome will be gross and fine motor skills. The secondary outcomes will be mobility, functional balance, motor cortical excitability, cognitive aspects and behavioral aspects.

Discussion

Although abnormalities in gait and balance are not primary characteristics of ASD, such abnormalities compromise independence and global functioning during the execution of routine activities of childhood. If demonstrated that anodal tDCS administered over areas of the brain involved in motor control, such as the primary motor cortex and cerebellum, can enhance the effects of gait and balance training in only ten sessions in two consecutive weeks, the clinical applicability of this stimulation modality will be expanded as well as more scientifically founded.Clinical trial registration February 16, 2023 (https://ensaiosclinicos.gov.br/rg/RBR-3bskhwf).

Linking cortex and contraction-Integrating models along the corticomuscular pathway

Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons  and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.

The connectome from the cerebral cortex to skeletal muscle using viral transneuronal tracers: a review

Connectomics has developed from an initial observation under an electron microscope to the present well-known medical imaging research approach. The emergence of the most popular transneuronal tracers has further advanced connectomics research. Researchers use the virus trans-nerve tracing method to trace the whole brain, mark the brain nerve circuit and nerve connection structure, and construct a complete nerve conduction pathway. This review assesses current methods of studying cortical to muscle connections using viral neuronal tracers and demonstrates their application in disease diagnosis and prognosis.

In vivo neural spike detection with adaptive noise estimation

The ability to reliably detect neural spikes from a relatively large population of neurons contaminated with noise is imperative for reliable decoding of recorded neural information. This article first analyzes the accuracy and feasibility of various potential spike detection techniques for in vivo realizations. Then an accurate and computationally-efficient spike detection module that can autonomously adapt to variations in recording channels' statistics is presented. The accuracy of the chosen candidate spike detection technique is evaluated using both synthetic and real neural recordings. The designed detector also offers the highest decoding performance over two animal behavioral datasets among alternative detection methods. The implementation results of the designed 128-channel spike detection module in a standard 180-nm CMOS process is among the most area and power-efficient spike detection ASICs and operates within the tissue-safe constraints for brain implants, while offering adaptive noise estimation.

In-silico neuro musculoskeletal model reproduces the movement types obtained by spinal micro stimulation

BACKGROUND AND OBJECTIVES

Virtual patients and physiologies allow experimentation, design, and early-stage clinical trials in-silico. Virtual patient technology for human movement systems that encompasses musculoskeleton and its neural control are few and far in between. Our major goal is to create a neuro- musculoskeletal upper limb in-silico model, which is modular in architecture and generates movement as an emergent phenomenon out of a multiscale co-simulation of spinal cord neural control and musculoskeletal dynamics.

METHODS

The model is developed on the NEUROiD movement simulation platform that enables a co-simulation of popular neural simulator NEURON and the musculoskeletal simulator OpenSim. We further characterized and demonstrated the use of this model in generating a range of commonly observed upper limb movements by means of a spatio-temporal stimulation pattern delivered to the cervical spinal cord.

RESULTS

We were able to characterize the model based on proprioception (Ia, Ib and II fibers), afferent conduction delay and inital postures of the musculoskeletal system. A smooth movement was achieved in all the considered experiments. The generated movements in all degrees of freedom were reproduced in accordance with the previous experimental studies.

CONCLUSION

In this work, design and development of the upper limb model was described in a modular fashion, while reusing existing models and modules. We believe this work enables a first and small step towards an in-silico paradigms for understanding upper limb movement, disease pathology, medication, and rehabilitation.

Locomotor Pattern and Force Generation Modulated by Ionic Channels: A Computational Study of Spinal Networks Underlying Locomotion

Locomotion is a fundamental movement in vertebrates produced by spinal networks known as central pattern generators (CPG). During fictive locomotion cat lumbar motoneurons (MNs) exhibit changes in membrane properties, including hyperpolarization of voltage threshold, reduction of afterhyperpolarization and input resistance, and amplification of nonlinear membrane properties. Both modeling and electrophysiological studies suggest that these changes can be produced by upregulating voltage-gated sodium channel (VGSC), persistent sodium (NaP), or L-type calcium channel (LTCC) or downregulating delayed-rectifier potassium (K(DR)) or calcium-dependent potassium channel (KCa) in spinal MNs. Further studies implicate that these channel modulations increase motor output and facilitate MN recruitment. However, it remains unknown how the channel modulation of CPG networks or MN pools affects the rhythmic generation of locomotion and force production of skeletal muscle during locomotion. In order to investigate this issue, we built a two-level CPG model composed of excitatory interneuron pools (Exc-INs), coupled reciprocally with inhibitory interneuron pools (Inh-INs), and projected to the flexor-extensor MN pools innervating skeletal muscles. Each pool consisted of 100 neurons with membrane properties based on cat spinal neurons. VGSC, K(DR), NaP, KCa, LTCC, and H-current channels were included in the model. Simulation results showed that (1) upregulating VGSC, NaP, or LTCC or downregulating KCa in MNs increased discharge rate and recruitment of MNs, thus facilitating locomotor pattern formation, increased amplitude of electroneurogram (ENG) bursting, and enhanced force generation of skeletal muscles. (2) The same channel modulation in Exc-INs increased the firing frequency of the Exc-INs, facilitated rhythmic generation, and increased flexor-extensor durations of step cycles. (3) Contrarily, downregulation of NaP or LTCC in MNs or Exc-INs or both CPG (Exc-INs and Inh-INs) and MNs disrupted locomotor pattern and reduced or even blocked the ENG bursting of MNs and force generation of skeletal muscles. (4) Pharmacological experiments showed that bath application of 25 μM nimodipine or 2 μM riluzole completely blocked fictive locomotion in isolated rat spinal cord, consistent with simulation results. We concluded that upregulation of VGSC, NaP, or LTCC or downregulation of KCa facilitated rhythmic generation and force production during walking, with NaP and LTCC playing an essential role.

Additional Effects of Xbox Kinect Training on Upper Limb Function in Chronic Stroke Patients: A Randomized Control Trial

Background: Xbox Kinect-based virtual reality, being a novel approach, has therapeutic benefits in rehabilitation and its use is encouraged in stroke rehabilitation of upper extremities. Objective: Primary aim of the current study is to investigate the additional effects of Xbox Kinect training in combination with routine physiotherapy exercises based on each component of Fugl-Meyer Assessment Scale for Upper Extremity (FMA-UE). Moreover, effect of upper limb rehabilitation on cognitive functions was also assessed. Methods: This study was a parallel arm randomized control trial. Fifty-six participants were recruited and randomly allocated to either an Xbox Kinect training group (XKGT) or exercise training group (ETG). Measures of concern were recorded using FMA-UE, Box and Block Test (BBT), and Montreal Cognitive Assessment (MOCA). Evaluation was conducted at baseline and after completion of intervention at the sixth week. Results: There were significant differences from pre- to post-intervention scores of FMA-UE and BBT (p < 0.001) in both groups, whereas no difference was observed for MOCA (XKTG p value 0.417, ETG p value 0.113). At six-week follow-up there were significant differences between both groups in FMA-UE total score (p < 0.001), volitional movement within synergies (p < 0.001), wrist (p = 0.021), hand (p = 0.047), grasp (p = 0.006) and coordination/speed (p = 0.004), favoring the Xbox Kinect training group. Conclusion: To conclude, results indicate repetitive use of the hemiparetic upper extremity by Xbox Kinect-based upper limb rehabilitation training in addition to conventional therapy has a promising potential to enhance upper limb motor function for stroke patients.

Anodal transcranial direct current stimulation enhances strength training volume but not the force-velocity profile

PURPOSE

This study aimed to explore the acute effect of transcranial direct current stimulation (tDCS) on the force-velocity relationship, strength training volume, movement velocity, and ratings of perceived exertion.

METHODS

Fourteen healthy men (age 22.8 ± 3.0 years) were randomly stimulated over the dorsolateral prefrontal cortex with either ANODAL, CATHODAL or SHAM tDCS for 15 min at 2 mA. The one-repetition maximum (1RM) and force-velocity relationship parameters were evaluated during the bench press exercise before and after receiving the tDCS. Subsequently, participants completed a resistance training session consisting of sets of five repetitions with 1 min of inter-set rest against the 75%1RM until failure.

RESULTS

No significant changes were observed in the 1RM or in the force-velocity relationship parameters (p ≥ 0.377). The number of repetitions was higher for the ANODAL compared to the CATHODAL (p = 0.025; ES = 0.37) and SHAM (p = 0.009; ES = 0.47) conditions. The reductions of movement velocity across sets were lower for the ANODAL than for the CATHODAL and SHAM condition (p = 0.014). RPE values were lower for the ANODAL compared to the CATHODAL (p = 0.119; ES = 0.33) and SHAM (p = 0.150; ES = 0.44) conditions. No significant differences between the CATHODAL and SHAM conditions were observed for any variable.

CONCLUSION

The application of ANODAL tDCS before a resistance training session increased training volume, enabled the maintenance of higher movement velocities, and reduced RPE values. These results suggest that tDCS could be an effective method to enhance resistance-training performance.

Predicting Perturbed Human Arm Movements in a Neuro-Musculoskeletal Model to Investigate the Muscular Force Response

Human movement is generated by a dynamic interplay between the nervous system, the biomechanical structures, and the environment. To investigate this interaction, we propose a neuro-musculoskeletal model of human goal-directed arm movements. Using this model, we simulated static perturbations of the inertia and damping properties of the arm, as well as dynamic torque perturbations for one-degree-of freedom movements around the elbow joint. The controller consists of a feed-forward motor command and feedback based on muscle fiber length and contraction velocity representing short-latency (25 ms) or long-latency (50 ms) stretch reflexes as the first neuronal responses elicited by an external perturbation. To determine the open-loop control signal, we parameterized the control signal resulting in a piecewise constant stimulation over time for each muscle. Interestingly, such an intermittent open-loop signal results in a smooth movement that is close to experimental observations. So, our model can generate the unperturbed point-to-point movement solely by the feed-forward command. The feedback only contributed to the stimulation in perturbed movements. We found that the relative contribution of this feedback is small compared to the feed-forward control and that the characteristics of the musculoskeletal system create an immediate and beneficial reaction to the investigated perturbations. The novelty of these findings is (1) the reproduction of static as well as dynamic perturbation experiments in one neuro-musculoskeletal model with only one set of basic parameters. This allows to investigate the model's neuro-muscular response to the perturbations that-at least to some degree-represent stereotypical interactions with the environment; (2) the demonstration that in feed-forward driven movements the muscle characteristics generate a mechanical response with zero-time delay which helps to compensate for the perturbations; (3) that this model provides enough biomechanical detail to allow for the prediction of internal forces, including joint loads and muscle-bone contact forces which are relevant in ergonomics and for the development of assistive devices but cannot be observed in experiments.

How does the CNS control arm reaching movements? Introducing a hierarchical nonlinear predictive control organization based on the idea of muscle synergies

In this study, we introduce a hierarchical and modular computational model to explain how the CNS (Central Nervous System) controls arm reaching movement (ARM) in the frontal plane and under different conditions. The proposed hierarchical organization was established at three levels: 1) motor planning, 2) command production, and 3) motor execution. Since in this work we are not discussing motion learning, no learning procedure was considered in the model. Previous models mainly assume that the motor planning level produces the desired trajectories of the joints and feeds it to the next level to be tracked. In the proposed model, the motion control is described based on a regulatory control policy, that is, the output of the motor planning level is a step function defining the initial and final desired position of the hand. For the command production level, a nonlinear predictive model was developed to explain how the time-invariant muscle synergies (MSs) are recruited. We used the same computational model to explain the arm reaching motion for a combined ARM task. The combined ARM is defined as two successive ARM such that it starts from point A and reaches to point C via point B. To develop the model, kinematic and kinetic data from six subjects were recorded and analyzed during ARM task performance. The subjects used a robotic manipulator while moving their hand in the frontal plane. The EMG data of 15 muscles were also recorded. The MSs used in the model were extracted from the recorded EMG data. The proposed model explains two aspects of the motor control system by a novel computational approach: 1) the CNS reduces the dimension of the control space using the notion of MSs and thereby, avoids immense computational loads; 2) at the level of motor planning, the CNS generates the desired position of the hand at the starting, via and the final points, and this amounts to a regulatory and non-tracking structure.

Bilateral Transcranial Direct Stimulation Over the Primary Motor Cortex Alters Motor Modularity of Multiple Muscles

Transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) has been demonstrated to modulate the motor performance of both healthy individuals and patients with neuromuscular disorders. However, the effect of tDCS on motor control of multiple muscles, which is a prerequisite to change in motor performance, is currently unknown. Using dimensionality reduction analysis, we investigated whether bilateral tDCS over M1 modulates the coordinated activity of 12 muscles. Fifteen healthy men participated in this randomized, double-blind crossover study. Each participant received a 20-min sham and 2-mA stimulation bilaterally over M1 (anode on the right M1 and cathode on the left M1), with a minimum washout period of 4 days. Muscle activation and end-point kinematics were evaluated during a task where participants reached out to a marked target with non-dominant hand as fast as possible, before and immediately after tDCS application. We found decreased similarity in motor modularity and significant changes in muscle activation in a specific motor module, particularly when reaching out to a target placed within arm's length and improved smoothness index of movement only following 2-mA stimulation. These findings indicate that clinicians and researchers need to consider the simultaneous effect of bilateral tDCS over M1 on multiple muscles when they establish tDCS protocol to change in motor performance of patients with neuromuscular deficits.

Encoding of kinetic and kinematic movement parameters in the sensorimotor cortex: A Brain-Computer Interface perspective

For severely paralyzed people, Brain-Computer Interfaces (BCIs) can potentially replace lost motor output and provide a brain-based control signal for augmentative and alternative communication devices or neuroprosthetics. Many BCIs focus on neuronal signals acquired from the hand area of the sensorimotor cortex, employing changes in the patterns of neuronal firing or spectral power associated with one or more types of hand movement. Hand and finger movement can be described by two groups of movement features, namely kinematics (spatial and motion aspects) and kinetics (muscles and forces). Despite extensive primate and human research, it is not fully understood how these features are represented in the SMC and how they lead to the appropriate movement. Yet, the available information may provide insight into which features are most suitable for BCI control. To that purpose, the current paper provides an in-depth review on the movement features encoded in the SMC. Even though there is no consensus on how exactly the SMC generates movement, we conclude that some parameters are well represented in the SMC and can be accurately used for BCI control with discrete as well as continuous feedback. However, the vast evidence also suggests that movement should be interpreted as a combination of multiple parameters rather than isolated ones, pleading for further exploration of sensorimotor control models for accurate BCI control.

The interplay between cerebellum and basal ganglia in motor adaptation: A modeling study

Motor adaptation to perturbations is provided by learning mechanisms operating in the cerebellum and basal ganglia. The cerebellum normally performs motor adaptation through supervised learning using information about movement error provided by visual feedback. However, if visual feedback is critically distorted, the system may disengage cerebellar error-based learning and switch to reinforcement learning mechanisms mediated by basal ganglia. Yet, the exact conditions and mechanisms of cerebellum and basal ganglia involvement in motor adaptation remain unknown. We use mathematical modeling to simulate control of planar reaching movements that relies on both error-based and non-error-based learning mechanisms. We show that for learning to be efficient only one of these mechanisms should be active at a time. We suggest that switching between the mechanisms is provided by a special circuit that effectively suppresses the learning process in one structure and enables it in the other. To do so, this circuit modulates learning rate in the cerebellum and dopamine release in basal ganglia depending on error-based learning efficiency. We use the model to explain and interpret experimental data on error- and non-error-based motor adaptation under different conditions.

The Functional Role of Striatal Cholinergic Interneurons in Reinforcement Learning From Computational Perspective

In this study, we explore the functional role of striatal cholinergic interneurons, hereinafter referred to as tonically active neurons (TANs), via computational modeling; specifically, we investigate the mechanistic relationship between TAN activity and dopamine variations and how changes in this relationship affect reinforcement learning in the striatum. TANs pause their tonic firing activity after excitatory stimuli from thalamic and cortical neurons in response to a sensory event or reward information. During the pause striatal dopamine concentration excursions are observed. However, functional interactions between the TAN pause and striatal dopamine release are poorly understood. Here we propose a TAN activity-dopamine relationship model and demonstrate that the TAN pause is likely a time window to gate phasic dopamine release and dopamine variations reciprocally modulate the TAN pause duration. Furthermore, this model is integrated into our previously published model of reward-based motor adaptation to demonstrate how phasic dopamine release is gated by the TAN pause to deliver reward information for reinforcement learning in a timely manner. We also show how TAN-dopamine interactions are affected by striatal dopamine deficiency to produce poor performance of motor adaptation.

Low doses of methylmercury exposure during adulthood in rats display oxidative stress, neurodegeneration in the motor cortex and lead to impairment of motor skills

Despite the vast distribution among tissues, the central nervous system (CNS) represents the main target of methylmercury (MeHg) toxicity. However, few studies have evaluated the effects of MeHg exposure on the CNS at equivalent doses to human environmental exposure. In our study, we evaluated the motor cortex, an important area of motor control, in adult rats chronically exposed to MeHg in a concentration equivalent to those found in fish-eating populations exposed to mercury (Hg). The parameters evaluated were total Hg accumulation, oxidative stress, tissue damage, and behavioral assessment in functional actions that involved this cortical region. Our results show in exposed animals a significantly greater level of Hg in the motor cortex; increase of nitrite levels and lipid peroxidation, associated with decreased antioxidant capacity against peroxyl radicals; reduction of neuronal and astrocyte density; and poor coordination and motor learning impairment. Our data showed that chronic exposure at low doses to MeHg is capable of promoting damages to the motor cortex of adult animals, with changes in oxidative biochemistry misbalance, neurodegeneration, and motor function impairment.

Hebbian Plasticity in CPG Controllers Facilitates Self-Synchronization for Human-Robot Handshaking

It is well-known that human social interactions generate synchrony phenomena which are often unconscious. If the interaction between individuals is based on rhythmic movements, synchronized and coordinated movements will emerge from the social synchrony. This paper proposes a plausible model of plastic neural controllers that allows the emergence of synchronized movements in physical and rhythmical interactions. The controller is designed with central pattern generators (CPG) based on rhythmic Rowat-Selverston neurons endowed with neuronal and synaptic Hebbian plasticity. To demonstrate the interest of the proposed model, the case of handshaking is considered because it is a very common, both physically and socially, but also, a very complex act in the point of view of robotics, neuroscience and psychology. Plastic CPGs controllers are implemented in the joints of a simulated robotic arm that has to learn the frequency and amplitude of an external force applied to its effector, thus reproducing the act of handshaking with a human. Results show that the neural and synaptic Hebbian plasticity are working together leading to a natural and autonomous synchronization between the arm and the external force even if the frequency is changing during the movement. Moreover, a power consumption analysis shows that, by offering emergence of synchronized and coordinated movements, the plasticity mechanisms lead to a significant decrease in the energy spend by the robot actuators thus generating a more adaptive and natural human/robot handshake.

Virtual Reality for Upper Limb Rehabilitation in Subacute and Chronic Stroke: A Randomized Controlled Trial

OBJECTIVE

To evaluate the effectiveness of reinforced feedback in virtual environment (RFVE) treatment combined with conventional rehabilitation (CR) in comparison with CR alone, and to study whether changes are related to stroke etiology (ie, ischemic, hemorrhagic).

DESIGN

Randomized controlled trial.

SETTING

Hospital facility for intensive rehabilitation.

PARTICIPANTS

Patients (N=136) within 1 year from onset of a single stroke (ischemic: n=78, hemorrhagic: n=58).

INTERVENTIONS

The experimental treatment was based on the combination of RFVE with CR, whereas control treatment was based on the same amount of CR. Both treatments lasted 2 hours daily, 5d/wk, for 4 weeks.

MAIN OUTCOME MEASURES

Fugl-Meyer upper extremity scale (F-M UE) (primary outcome), FIM, National Institutes of Health Stroke Scale (NIHSS), and Edmonton Symptom Assessment Scale (ESAS) (secondary outcomes). Kinematic parameters of requested movements included duration (time), mean linear velocity (speed), and number of submovements (peak) (secondary outcomes).

RESULTS

Patients were randomized in 2 groups (RFVE with CR: n=68, CR: n=68) and stratified by stroke etiology (ischemic or hemorrhagic). Both groups improved after treatment, but the experimental group had better results than the control group (Mann-Whitney U test) for F-M UE (P<.001), FIM (P<.001), NIHSS (P≤.014), ESAS (P≤.022), time (P<.001), speed (P<.001), and peak (P<.001). Stroke etiology did not have significant effects on patient outcomes.

CONCLUSIONS

The RFVE therapy combined with CR treatment promotes better outcomes for upper limb than the same amount of CR, regardless of stroke etiology.

Reward Based Motor Adaptation Mediated by Basal Ganglia

It is widely accepted that the basal ganglia (BG) play a key role in action selection and reinforcement learning. However, despite considerable number of studies, the BG architecture and function are not completely understood. Action selection and reinforcement learning are facilitated by the activity of dopaminergic neurons, which encode reward prediction errors when reward outcomes are higher or lower than expected. The BG are thought to select proper motor responses by gating appropriate actions, and suppressing inappropriate ones. The direct striato-nigral (GO) and the indirect striato-pallidal (NOGO) pathways have been suggested to provide the functions of BG in the two-pathway concept. Previous models confirmed the idea that these two pathways can mediate the behavioral choice, but only for a relatively small number of potential behaviors. Recent studies have provided new evidence of BG involvement in motor adaptation tasks, in which adaptation occurs in a non-error-based manner. In such tasks, there is a continuum of possible actions, each represented by a complex neuronal activity pattern. We extended the classical concept of the two-pathway BG by creating a model of BG interacting with a movement execution system, which allows for an arbitrary number of possible actions. The model includes sensory and premotor cortices, BG, a spinal cord network, and a virtual mechanical arm performing 2D reaching movements. The arm is composed of 2 joints (shoulder and elbow) controlled by 6 muscles (4 mono-articular and 2 bi-articular). The spinal cord network contains motoneurons, controlling the muscles, and sensory interneurons that receive afferent feedback and mediate basic reflexes. Given a specific goal-oriented motor task, the BG network through reinforcement learning constructs a behavior from an arbitrary number of basic actions represented by cortical activity patterns. Our study confirms that, with slight modifications, the classical two-pathway BG concept is consistent with results of previous studies, including non-error based motor adaptation experiments, pharmacological manipulations with BG nuclei, and functional deficits observed in BG-related motor disorders.