A portable system to measure knee extensor spasticity after spinal cord injury.

BACKGROUND: The pendulum test is a quantitative method used to assess knee extensor spasticity in humans with spinal cord injury (SCI). Yet, the clinical implementation of this method remains limited. The goal of our study was to develop an objective and portable system to assess knee extensor spasticity during the pendulum test using inertial measurement units (IMU). METHODS: Spasticity was quantified by measuring the first swing angle (FSA) using a 3-dimensional optical tracking system (with external markers over the iliotibial band, lateral knee epicondyle, and lateral malleolus) and two wireless IMUs (positioned over the iliotibial band and mid-part of the lower leg) as well as a clinical exam (Modified Ashworth Scale, MAS). RESULTS: Measurements were taken on separate days to assess test-retest reliability and device agreement in humans with and without SCI. We found no differences between FSA values obtained with the optical tracking system and the IMU-based system in control subjects and individuals with SCI. FSA values from the IMU-based system showed excellent agreement with the optical tracking system in individuals with SCI (ICC > 0.98) and good agreement in controls (ICC > 0.82), excellent test-retest reliability across days in SCI (ICC = 0.93) and good in controls (ICC = 0.87). Notably, FSA values measured by both systems showed a strong association with MAS scores ( ρ  ~ -0.8) being decreased in individuals with SCI with higher MAS scores, reflecting the presence of spasticity. CONCLUSIONS: These findings suggest that our new portable IMU-based system provides a robust and flexible alternative to a camera-based optical tracking system to quantify knee extensor spasticity following SCI.

Distinctive electro-clinical, neuroimaging and histopathological features of temporal encephaloceles associated to epilepsy.

OBJECTIVE: Encephaloceles (ENCs) may cause clinical complications, including drug-resistant epilepsy that can be cured with epilepsy surgery. METHODS: We describe clinical, diagnostic, and neuropathological findings of 12 patients with temporal ENC and epilepsy evaluated for surgery and compare them with a control group of 26 temporal lobe epilepsy (TLE) patients. RESULTS: Six patients had unilateral and 6 bilateral temporal ENCs. Compared to TLEs, ENCs showed i) later epilepsy onset, ii) higher prevalence of psychiatric comorbidities, iii) no history of febrile convulsions, and iv) ictal semiology differences. Seven patients had MRI signs of gliosis, and 9 of intracranial hypertension. Interictal EEG analysis in ENCs demonstrated significant differences with controls: prominent activity in the beta/gamma frequency bands in frontal regions, interictal short sequences of low-voltage fast activity, and less frequent and more localized interictal epileptiform discharges. Ictal EEG patterns analyzed in 9 ENCs showed delayed and slower contralateral spread compared to TLEs. All ENCs that underwent surgery (7 lobectomies and 1 lesionectomy) are in Engel class I. Neuropathological examination revealed 4 patterns: herniated brain fragments, focal layer I distortion, white matter septa extending into the cortex, and altered gyral profile. CONCLUSIONS AND SIGNIFICANCE: The described peculiarities might help clinicians to suspect the presence of largely underdiagnosed ENCs.

Dendritic pathology, spine loss and synaptic reorganization in human cortex from epilepsy patients.

Neuronal dendritic arborizations and dendritic spines are crucial for a normal synaptic transmission and may be critically involved in the pathophysiology of epilepsy. Alterations in dendritic morphology and spine loss mainly in hippocampal neurons have been reported both in epilepsy animal models and in human brain tissues from patients with epilepsy. However, it is still unclear whether these dendritic abnormalities relate to the cause of epilepsy or are generated by seizure recurrence. We investigated fine neuronal structures at the level of dendritic and spine organization using Golgi impregnation, and analysed synaptic networks with immunohistochemical markers of glutamatergic (vGLUT1) and GABAergic (vGAT) axon terminals in human cerebral cortices derived from epilepsy surgery. Specimens were obtained from 28 patients with different neuropathologically defined aetiologies: type Ia and type II focal cortical dysplasia, cryptogenic (no lesion) and temporal lobe epilepsy with hippocampal sclerosis. Autoptic tissues were used for comparison. Three-dimensional reconstructions of Golgi-impregnated neurons revealed severe dendritic reshaping and spine alteration in the core of the type II focal cortical dysplasia. Dysmorphic neurons showed increased dendritic complexity, reduction of dendritic spines and occasional filopodia-like protrusions emerging from the soma. Surprisingly, the intermingled normal-looking pyramidal neurons also showed severe spine loss and simplified dendritic arborization. No changes were observed outside the dysplasia (perilesional tissue) or in neocortical postsurgical tissue obtained in the other patient groups. Immunoreactivities of vGLUT1 and vGAT showed synaptic reorganization in the core of type II dysplasia characterized by the presence of abnormal perisomatic baskets around dysmorphic neurons, in particular those with filopodia-like protrusions, and changes in vGLUT1/vGAT expression. Ultrastructural data in type II dysplasia highlighted the presence of altered neuropil engulfed by glial processes. Our data indicate that the fine morphological aspect of neurons and dendritic spines are normal in epileptogenic neocortex, with the exception of type II dysplastic lesions. The findings suggest that the mechanisms leading to this severe form of cortical malformation interfere with the normal dendritic arborization and synaptic network organization. The data argue against the concept that long-lasting epilepsy and seizure recurrence per se unavoidably produce a dendritic pathology.

pCREB expression in human tissues from epilepsy surgery.

OBJECTIVE: Activity-dependent changes have been reported in animal models and in human epileptic specimens and could potentially be used as tissue biomarkers to evaluate the propensity of a tissue to generate seizure activity. In this context, cAMP-response element binding protein (CREB) activation was specifically reported in human epileptic foci and related mainly to interictal spike activity. To get further insights into CREB activation in human epilepsy, we analyzed pCREB expression on brain tissue samples from patients who underwent surgery for drug-resistant focal epilepsy, correlating this expression with intracranial stereo-electroencephalography (SEEG) recording in a subgroup. METHODS: Neocortical specimens from patients with neuropathological diagnosis of no lesion (cryptogenic), malformations of cortical development,mainly type II focal cortical dysplasia (FCD), and hippocampi with and without hippocampal sclerosis have been analyzed by immunohistochemistry. Peritumoral cortex from non-epileptic patients and autoptic samples were used as controls, whereas rat brains were used to test possible loss of pCREB antigenicity due to fixation procedures and postmortem delay. RESULTS: pCREB was consistently expressed in layer II neuronal nuclei in regions with normal cortical lamination both in epileptic and non-epileptic surgical tissues. In patients with SEEG recordings, this anatomical pattern was unrelated to the presence of interictal spike activity. Conversely, in the core of type II FCD, as well as in other developmental malformations, pCREB was scattered without any laminar specificity. Furthermore, quantitative data did not reveal significant differences between epileptic and non-epileptic tissues, except for an increased immunoreactivity in the core of type IIB FCD lesion related mainly to reactive glial and balloon cells. SIGNIFICANCE: The present data argue against the reliability of pCREB immunohistochemistry as a marker of epileptic focus but underscores its layer-related expression, suggesting a potential application in the study of malformations of cortical development, a wide range of diseases arising from perturbations of normal brain development.

Guiding functional reorganization of motor redundancy using a body-machine interface.

BACKGROUND: Body-machine interfaces map movements onto commands to external devices. Redundant motion signals derived from inertial sensors are mapped onto lower-dimensional device commands. Then, the device users face two problems, a) the structural problem of understanding the operation of the interface and b) the performance problem of controlling the external device with high efficiency. We hypothesize that these problems, while being distinct are connected in that aligning the space of body movements with the space encoded by the interface, i.e. solving the structural problem, facilitates redundancy resolution towards increasing efficiency, i.e. solving the performance problem. METHODS: Twenty unimpaired volunteers practiced controlling the movement of a computer cursor by moving their arms. Eight signals from four inertial sensors were mapped onto the two cursor's coordinates on a screen. The mapping matrix was initialized by asking each user to perform free-form spontaneous upper-limb motions and deriving the two main principal components of the motion signals. Participants engaged in a reaching task for 18 min, followed by a tracking task. One group of 10 participants practiced with the same mapping throughout the experiment, while the other 10 with an adaptive mapping that was iteratively updated by recalculating the principal components based on ongoing movements. RESULTS: Participants quickly reduced reaching time while also learning to distribute most movement variance over two dimensions. Participants with the fixed mapping distributed movement variance over a subspace that did not match the potent subspace defined by the interface map. In contrast, participant with the adaptive map reduced the difference between the two subspaces, resulting in a smaller amount of arm motions distributed over the null space of the interface map. This, in turn, enhanced movement efficiency without impairing generalization from reaching to tracking. CONCLUSIONS: Aligning the potent subspace encoded by the interface map to the user's movement subspace guides redundancy resolution towards increasing movement efficiency, with implications for controlling assistive devices. In contrast, in the pursuit of rehabilitative goals, results would suggest that the interface must change to drive the statistics of user's motions away from the established pattern and toward the engagement of movements to be recovered. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01608438, Registered 16 April 2012.

The Effect of Feedback Modality When Learning a Novel Wrist Sensorimotor Transformation Through a Body-Machine Interface.

Body-Machine Interfaces (BoMIs) are promising assistive and rehabilitative tools for helping individuals with impaired motor abilities regain independence. When operating a BoMI, the user has to learn a novel sensorimotor transformation between the movement of certain body parts and the output of the device. In this study, we investigated how different feedback modalities impacted learning to operate a BoMI. Forty-seven able-bodied participants learned to control the velocity of a 1D cursor using the 3D rotation of their dominant wrist to reach as many targets as possible in a given amount of time. The map was designed to maximize cursor speed for movements around a predefined axis of wrist rotation. We compared the user's performance and control efficiency under three feedback modalities: i) visual feedback of the cursor position, ii) proprioceptive feedback of the cursor position delivered by a wrist manipulandum, iii) both i) and ii). We found that visual feedback led to a greater number of targets reached than proprioceptive feedback alone. Conversely, proprioceptive feedback yielded greater alignment between the axis of rotation of the wrist and the optimal axis represented by the map. These results suggest that proprioceptive feedback may be preferable over visual feedback when information about intrinsic task components, i.e. joint configurations, is of interest as in rehabilitative interventions aiming to promote more effective learning strategies.

An Exploratory Multi-Session Study of Learning High-Dimensional Body-Machine Interfacing for Assistive Robot Control.

Individuals who suffer from severe paralysis often lose the capacity to perform fundamental body movements and everyday activities. Empowering these individuals with the ability to operate robotic arms, in high degrees-of-freedom (DoFs), can help to maximize both functional utility and independence. However, robot teleoperation in high DoFs currently lacks accessibility due to the challenge in capturing high-dimensional control signals from the human, especially in the face of motor impairments. Body-machine interfacing is a viable option that offers the necessary high-dimensional motion capture, and it moreover is noninvasive, affordable, and promotes movement and motor recovery. Nevertheless, to what extent body-machine interfacing is able to scale to high-DoF robot control, and whether it is feasible for humans to learn, remains an open question. In this exploratory multi-session study, we demonstrate the feasibility of human learning to operate a body-machine interface to control a complex, assistive robotic arm. We use a sensor net of four inertial measurement unit sensors, bilaterally placed on the scapulae and humeri. Ten uninjured participants are familiarized, trained, and evaluated in reaching and Activities of Daily Living tasks, using the body- machine interface. Our results suggest the manner of control space mapping (joint-space control versus task-space control), from interface to robot, plays a critical role in the evolution of human learning. Though joint-space control shows to be more intuitive initially, task-space control is found to have a greater capacity for longer-term improvement and learning.

Dendritic spine loss in epileptogenic Type II focal cortical dysplasia: Role of enhanced classical complement pathway activation.

Dendritic spines are the postsynaptic sites for most excitatory glutamatergic synapses. We previously demonstrated a severe spine loss and synaptic reorganization in human neocortices presenting Type II focal cortical dysplasia (FCD), a developmental malformation and frequent cause of drug-resistant focal epilepsy. We extend the findings, investigating the potential role of complement components C1q and C3 in synaptic pruning imbalance. Data from Type II FCD were compared with those obtained in focal epilepsies with different etiologies. Neocortical tissues were collected from 20 subjects, mainly adults with a mean age at surgery of 31 years, admitted to epilepsy surgery with a neuropathological diagnosis of: cryptogenic, temporal lobe epilepsy with hippocampal sclerosis, and Type IIa/b FCD. Dendritic spine density quantitation, evaluated in a previous paper using Golgi impregnation, was available in a subgroup. Immunohistochemistry, in situ hybridization, electron microscopy, and organotypic cultures were utilized to study complement/microglial activation patterns. FCD Type II samples presenting dendritic spine loss were characterized by an activation of the classical complement pathway and microglial reactivity. In the same samples, a close relationship between microglial cells and dendritic segments/synapses was found. These features were consistently observed in Type IIb FCD and in 1 of 3 Type IIa cases. In other patient groups and in perilesional areas outside the dysplasia, not presenting spine loss, these features were not observed. In vitro treatment with complement proteins of organotypic slices of cortical tissue with no sign of FCD induced a reduction in dendritic spine density. These data suggest that dysregulation of the complement system plays a role in microglia-mediated spine loss. This mechanism, known to be involved in the removal of redundant synapses during development, is likely reactivated in Type II FCD, particularly in Type IIb; local treatment with anticomplement drugs could in principle modify the course of disease in these patients.

A semi-automatic registration protocol to match ex-vivo high-field 7T MR images and histological slices in surgical samples from patients with drug-resistant epilepsy.

BACKGROUND: MRI is a fundamental tool to detect brain structural anomalies and improvement in this technique has the potential to visualize subtle abnormalities currently undetected. Correlation between pre-operative MRI and histopathology is required to validate the neurobiological basis of MRI abnormalities. However, precise MRI-histology matching is very challenging with the surgical samples. We previously developed a coregistration protocol to match the in-vivo MRI with ex-vivo MRI obtained from surgical specimens. Now, we complete the process to successfully align ex-vivo MRI data with the proper digitalized histological sections in an automatic way. NEW METHOD: The implemented pipeline is composed by the following steps: a) image pre-processing made of MRI and histology volumes conversion and masking; b) gross rigid body alignment between MRI volume and histology virtual slides; c) rigid alignment between each MRI section and histology slice and estimate of the correlation coefficient for each step to select the MRI slice that best matches histology; d) final linear registration of the selected slices. RESULTS: This method is fully automatic, except for the first masking step, fast and reliable in comparison to the manual one, as assessed using a Bland-Altman plot. COMPARISON WITH EXISTING METHODS: The visual assessment usually employed for choosing the best fitting ex-vivo MRI slice for each stained section takes hours and requires practice. Goubran et al. (2015) proposed an iterative registration protocol but its aim and methods were different from ours. No others similar methods are reported in the literature. CONCLUSIONS: This protocol completes our previous pipeline. The ultimate goal will be to apply the entire process to finely investigate the relationship between clinical MRI data and histopathological features in patients with drug-resistant epilepsy.

Role of NODDI in the MRI Characterization of Hippocampal Abnormalities in Temporal Lobe Epilepsy: Clinico-histopathologic Correlations.

BACKGROUND AND OBJECTIVES: The identification of possible hippocampal alterations is a crucial point for the diagnosis and therapy of patients with unilateral temporal lobe epilepsy (TLE). This study aims to investigate the role of neurite orientation dispersion and density imaging (NODDI) compared to diffusion tensor imaging (DTI) in the comprehension of hippocampal microstructure in TLE. METHODS: DTI and NODDI metrics were calculated in the hippocampi of adult patients with TLE, with and without histology-confirmed hippocampal sclerosis (HS), and in age/sex-matched healthy controls (HC). Diffusion metrics and hippocampal volumes of the pathologic side were compared within participants and between participants among the HS, non-HS, and HC groups. Diffusion metrics were also correlated with hippocampal volume and patients' clinical features. After surgery, hippocampal specimens were processed for neuropathology examinations. RESULTS: Fifteen patients with TLE (9 with and 6 without HS) and 11 HC were included. Hippocampal analyses resulted in a significant increase in fractional anisotropy (FA) and mean diffusivity (MD; mm2/s × 10-3) and decrease in orientation dispersion index (ODI) comparing the pathologic side of patients with HS and their relative nonpathologic side (0.203 vs 0.183, 0.825 vs 0.724, 0.366 vs 0.443, respectively), the pathologic side of patients without HS (0.203 vs 0.169, 0.825 vs 0.745, 0.366 vs 0.453, respectively), and HC (0.203 vs 0.172, 0.825 vs 0.729, 0.366 vs 0.447, respectively). Moreover, neurite density (ND) was significantly decreased comparing both hippocampi of patients with HS (0.416 vs 0.460). A significant increase in free-water isotropic volume fraction (fiso) was found in the comparison of pathologic hippocampi of patients with HS and nonpathologic hippocampi of patients with HS (0.323 vs 0.258) and HC (0.323 vs 0.226). Hippocampal volume of all patients with TLE negatively correlated with MD (r = -0.746, p = 0.0145) and positively correlated with ODI (r = 0.719, p = 0.0145). Fiso and ND of sclerotic hippocampi positively correlated with disease duration (r = 0.684, p = 0.0424 and r = 0.670, p = 0.0486, respectively). Immunohistochemistry in sclerotic hippocampal specimens revealed neuronal loss in the pyramidal layer and fiber reorganization at the level of stratum lacunosum-moleculare, confirming ODI and ND metrics. DISCUSSION: This study shows the capability of diffusion MRI metrics to detect hippocampal microstructural alterations. Among them, ODI seems to better highlight the fiber reorganization observed by neuropathology in sclerotic hippocampi.

A Framework for Optimizing Co-adaptation in Body-Machine Interfaces.

The operation of a human-machine interface is increasingly often referred to as a two-learners problem, where both the human and the interface independently adapt their behavior based on shared information to improve joint performance over a specific task. Drawing inspiration from the field of body-machine interfaces, we take a different perspective and propose a framework for studying co-adaptation in scenarios where the evolution of the interface is dependent on the users' behavior and that do not require task goals to be explicitly defined. Our mathematical description of co-adaptation is built upon the assumption that the interface and the user agents co-adapt toward maximizing the interaction efficiency rather than optimizing task performance. This work describes a mathematical framework for body-machine interfaces where a naïve user interacts with an adaptive interface. The interface, modeled as a linear map from a space with high dimension (the user input) to a lower dimensional feedback, acts as an adaptive "tool" whose goal is to minimize transmission loss following an unsupervised learning procedure and has no knowledge of the task being performed by the user. The user is modeled as a non-stationary multivariate Gaussian generative process that produces a sequence of actions that is either statistically independent or correlated. Dependent data is used to model the output of an action selection module concerned with achieving some unknown goal dictated by the task. The framework assumes that in parallel to this explicit objective, the user is implicitly learning a suitable but not necessarily optimal way to interact with the interface. Implicit learning is modeled as use-dependent learning modulated by a reward-based mechanism acting on the generative distribution. Through simulation, the work quantifies how the system evolves as a function of the learning time scales when a user learns to operate a static vs. an adaptive interface. We show that this novel framework can be directly exploited to readily simulate a variety of interaction scenarios, to facilitate the exploration of the parameters that lead to optimal learning dynamics of the joint system, and to provide an empirical proof for the superiority of human-machine co-adaptation over user adaptation.

Building an adaptive interface via unsupervised tracking of latent manifolds.

In human-machine interfaces, decoder calibration is critical to enable an effective and seamless interaction with the machine. However, recalibration is often necessary as the decoder off-line predictive power does not generally imply ease-of-use, due to closed loop dynamics and user adaptation that cannot be accounted for during the calibration procedure. Here, we propose an adaptive interface that makes use of a non-linear autoencoder trained iteratively to perform online manifold identification and tracking, with the dual goal of reducing the need for interface recalibration and enhancing human-machine joint performance. Importantly, the proposed approach avoids interrupting the operation of the device and it neither relies on information about the state of the task, nor on the existence of a stable neural or movement manifold, allowing it to be applied in the earliest stages of interface operation, when the formation of new neural strategies is still on-going. In order to more directly test the performance of our algorithm, we defined the autoencoder latent space as the control space of a body-machine interface. After an initial offline parameter tuning, we evaluated the performance of the adaptive interface versus that of a static decoder in approximating the evolving low-dimensional manifold of users simultaneously learning to perform reaching movements within the latent space. Results show that the adaptive approach increased the representational efficiency of the interface decoder. Concurrently, it significantly improved users' task-related performance, indicating that the development of a more accurate internal model is encouraged by the online co-adaptation process.

A hybrid Body-Machine Interface integrating signals from muscles and motions.

OBJECTIVE: Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord injury or stroke. Here, we considered the integration of two types of signals, motion signals derived from inertial measurement units (IMUs) and muscle activities recorded with electromyography (EMG), both contributing to the operation of the BoMI. APPROACH: A direct combination of IMU and EMG signals might result in inefficient control due to the differences in their nature. Accordingly, we used a nonlinear-regression-based approach to predict IMU from EMG signals, after which the predicted and actual IMU signals were combined into a hybrid control signal. The goal of this approach was to provide users with the possibility to switch seamlessly between movement and EMG control, using the BoMI as a tool for promoting the engagement of selected muscles. We tested the interface in three control modalities, EMG-only, IMU-only and hybrid, in a cohort of 15 unimpaired participants. Participants practiced reaching movements by guiding a computer cursor over a set of targets. MAIN RESULTS: We found that the proposed hybrid control led to comparable performance to IMU-based control and significantly outperformed the EMG-only control. Results also indicated that hybrid cursor control was predominantly influenced by EMG signals. SIGNIFICANCE: We concluded that combining EMG with IMU signals could be an efficient way to target muscle activations while overcoming the limitations of an EMG-only control.

Skill Learning and Skill Transfer Mediated by Cooperative Haptic Interaction.

It is known that physical coupling between two subjects may be advantageous in joint tasks. However, little is known about how two people mutually exchange information to exploit the coupling. Therefore, we adopted a reversed, novel perspective to the standard one that focuses on the ability of physically coupled subjects to adapt to cooperative contexts that require negotiating a common plan: we investigated how training in pairs on a novel task affects the development of motor skills of each of the interacting partners. The task involved reaching movements in an unstable dynamic environment using a bilateral non-linear elastic tool that could be used bimanually or dyadically. The main result is that training with an expert leads to the greatest performance in the joint task. However, the performance in the individual test is strongly affected by the initial skill level of the partner. Moreover, practicing with a peer rather than an expert appears to be more advantageous for a naive; and motor skills can be transferred to a bimanual context, after training with an expert, only if the non-expert subject had prior experience of the dynamics of the novel task.

Transferring knowledge during dyadic interaction: The role of the expert in the learning process.

Physical interaction between man and machines is increasing the interest of the research as well as the industrial community. It is known that physical coupling between active persons can be beneficial and increase the performance of the dyad compared to an individual. However, the factors that may result in performance benefits are still poorly understood. The aim of this work is to investigate how the different initial skill levels of the interacting partners influence the learning of a stabilization task. Twelve subjects, divided in two groups, trained in couples in a joint stabilization task. In the first group the couples were composed of two naive, while in the second a naive was trained together with an expert. Results show that training with an expert results in the greatest performance in the joint task. However, this benefit is not transferred to the individual when performing the same task bimanually.

Dealing with instability in bimanual and collaborative tasks.

In the context of unstable tasks, whenever the dynamics of the interaction are unknown, our ability to control an object depends on the predictability of the sensory feedback generated from the physical coupling at the interface with the object. In the case of physical human-human interaction, the haptic sensory feedback plays a primary role in the construction of a shared motor plan, being the channel for the mutual sharing of intentions. The present work addresses the issue of strategy selection in contexts in which instability is arising both from the environment, i.e. controlling a compliant object subject to nonlinear forces, and from the interaction with a partner, i.e. carrying out a bimanual balancing task in the presence of disturbing force-fields.

Motor control strategies in the bimanual stabilization of an unstable virtual tool.

Previous works have shown that, when dealing with instabilities in a bimanual manipulation paradigm, humans modulate the stiffness of the arms according to feedforward or feedback mechanisms as a function of the dynamics of the task. The aim of this work is to complement these results getting insights on how the CNS controls the muscles to achieve the stabilization goal in the two aforementioned control strategies. Surface EMG was recorded from 13 muscles of each arm and trunk while three expert subjects performed bimanual balancing of a virtual underactuated tool immersed in an unstable force-field. Results suggest the existence of an intermittent muscle ensemble recruitment that follows two distinct activation patterns, namely synchronous co-contractions and independent activations. The observed EMG patterns were independent of the motor control strategy applied in the task. These findings therefore suggest the existence of separate control strategies for the tool stabilization and the control of hand movements at the muscular level during a bimanual postural task.

Proprioceptive bimanual test in intrinsic and extrinsic coordinates.

Is there any difference between matching the position of the hands by asking the subjects to move them to the same spatial location or to mirror-symmetric locations with respect to the body midline? If the motion of the hands were planned in the extrinsic space, the mirror-symmetric task would imply an additional challenge, because we would need to flip the coordinates of the target on the other side of the workspace. Conversely, if the planning were done in intrinsic coordinates, in order to move both hands to the same spot in the workspace, we should compute different joint angles for each arm. Even if both representations were available to the subjects, the two tasks might lead to different results, providing some cue on the organization of the "body schema". In order to answer such questions, the middle fingertip of the non-dominant hand of a population of healthy subjects was passively moved by a manipulandum to 20 different target locations. Subjects matched these positions with the middle fingertip of their dominant hand. For most subjects, the matching accuracy was higher in the extrinsic modality both in terms of systematic error and variability, even for the target locations in which the configuration of the arms was the same for both modalities. This suggests that the matching performance of the subjects could be determined not only by proprioceptive information but also by the cognitive representation of the task: expressing the goal as reaching for the physical location of the hand in space is apparently more effective than requiring to match the proprioceptive representation of joint angles.

Strategy switching in the stabilization of unstable dynamics.

In order to understand mechanisms of strategy switching in the stabilization of unstable dynamics, this work investigates how human subjects learn to become skilled users of an underactuated bimanual tool in an unstable environment. The tool, which consists of a mass and two hand-held non-linear springs, is affected by a saddle-like force-field. The non-linearity of the springs allows the users to determine size and orientation of the tool stiffness ellipse, by using different patterns of bimanual coordination: minimal stiffness occurs when the two spring terminals are aligned and stiffness size grows by stretching them apart. Tool parameters were set such that minimal stiffness is insufficient to provide stable equilibrium whereas asymptotic stability can be achieved with sufficient stretching, although at the expense of greater effort. As a consequence, tool users have two possible strategies for stabilizing the mass in different regions of the workspace: 1) high stiffness feedforward strategy, aiming at asymptotic stability and 2) low stiffness positional feedback strategy aiming at bounded stability. The tool was simulated by a bimanual haptic robot with direct torque control of the motors. In a previous study we analyzed the behavior of naïve users and we found that they spontaneously clustered into two groups of approximately equal size. In this study we trained subjects to become expert users of both strategies in a discrete reaching task. Then we tested generalization capabilities and mechanism of strategy-switching by means of stabilization tasks which consist of tracking moving targets in the workspace. The uniqueness of the experimental setup is that it addresses the general problem of strategy-switching in an unstable environment, suggesting that complex behaviors cannot be explained in terms of a global optimization criterion but rather require the ability to switch between different sub-optimal mechanisms.

Human-human physical interaction in the joint control of an underactuated virtual object.

Human-human physical interaction has proven to be advantageous especially in contexts with high coordination requirements. But under which conditions can haptic communication bring to performance benefits in a challenging cooperative environment? In this work we investigate which are the dynamics that intervene when two subjects are required to switch from a bimanual to a dyadic configuration in order to solve a complex reaching and stabilization task of a virtual tool in the presence of an unstable dynamics. Results show that dyadic cooperation can improve the performance respect to the individual condition, while minimizing the effort. However, in the joint task, when the stiffness of the system becomes harder to manipulate the feedback delays appear to be critical in determining the maximum achievable level of performance.