Characterizing Motor System to Improve Training Protocols Used in Brain-Machine Interfaces Based on Motor Imagery

Motor imagery (MI)-based brain-machine interface (BMI) is a technology under development that actively modifies users’ perception and cognition through mental tasks, so as to decode their intentions from their neural oscillations, and thereby bringing some kind of activation. So far, MI as control task in BMIs has been seen as a skill that must be acquired, but neither user conditions nor controlled learning conditions have been taken into account. As motor system is a complex mechanism trained along lifetime, and MI-based BMI attempts to decode motor intentions from neural oscillations in order to put a device into action, motor mechanisms should be considered when prototyping BMI systems. It is hypothesized that the best way to acquire MI skills is following the same rules humans obey to move around the world. On this basis, new training paradigms consisting of ecological environments, identification of control tasks according to the ecological environment, transparent mapping, and multisensory feedback are proposed in this chapter. These new MI training paradigms take advantages of previous knowledge of users and facilitate the generation of mental image due to the automatic development of sensory predictions and motor behavior patterns in the brain. Furthermore, the effectuation of MI as an actual movement would make users feel that their mental images are being executed, and the resulting sensory feedback may allow forward model readjusting the imaginary movement in course

Understanding upper-limb movements via neurocomputational models of the sensorimotor system and neurorobotics: where we stand

Roboticists and neuroscientists are interested in understanding and reproducing the neural and cognitive mechanisms behind the human ability to interact with unknown and changing environments as well as to learn and execute fine movements. In this paper, we review the system-level neurocomputational models of the human motor system, and we focus on biomimetic models simulating the functional activity of the cerebellum, the basal ganglia, the motor cortex, and the spinal cord, which are the main central nervous system areas involved in the learning, execution, and control of movements. We review the models that have been proposed from the early of 1970s, when the first cerebellar model was realized, up to nowadays, when the embodiment of these models into robots acting in the real world and into software agents acting in a virtual environment has become of paramount importance to close the perception-cognition-action cycle. This review shows that neurocomputational models have contributed to the comprehension and reproduction of neural mechanisms underlying reaching movements, but much remains to be done because a whole model of the central nervous system controlling musculoskeletal robots is still missing

Neural and motor basis of inter-individual interactions

The goal of my Ph.D. work was to investigate the behavioral markers and the brain activities responsible for the emergence of sensorimotor communication. Sensorimotor communication can be defined as a form of communication consisting into flexible exchanges based on bodily signals, in order to increase the efficiency of the inter-individual coordination. For instance, a soccer player carving his movements to inform another player about his intention. This form of interaction is highly dependent of the motor system and the ability to produce appropriate movements but also of the ability of the partner to decode these cues. To tackle these facets of human social interaction, we approached the complexity of the problem by splitting my research activities into two separate lines of research. First, we pursued the examination of motor-based humans\u2019 capability to perceive and \u201cread\u201d other\u2019s behaviors in focusing on single-subject experiment. The discovery of mirror neurons in monkey premotor cortex in the early nineties (di Pellegrino et al. 1992) motivated a number of human studies on this topic (Rizzolatti and Craighero 2004). The critical finding was that some ventral premotor neurons are engaged during visual presentation of actions performed by conspecifics. More importantly, those neurons were shown to encode also the actual execution of similar actions (i.e. irrespective of who the acting individual is). This phenomenon has been highly investigated in humans by using cortical and cortico-spinal measures (for review see, fMRI: Molenberghs, Cunnington, and Mattingley 2012; TMS: Naish et al. 2014; EEG: Pineda 2008). During single pulse TMS (over the primary motor cortex), the amplitude of motor evoked potentials (MEPs) provides an index of corticospinal recruitment. During action observation the modulation of this index follow the expected changes during action execution (Fadiga et al. 1995). However, dozens of studies have been published on this topic and revealed important inconsistencies. For instance, MEPs has been shown to be dependent on observed low-level motor features (e.g. kinematic features or electromyography temporal coupling; Gangitano, Mottaghy, and Pascual-Leone 2001; Borroni et al. 2005; Cavallo et al. 2012) as well as high level movement properties (e.g. action goals; Cattaneo et al. 2009; Cattaneo et al. 2013). Furthermore, MEPs modulations do not seem to be related to the observed effectors (Borroni and Baldissera 2008; Finisguerra et al. 2015; Senna, Bolognini, and Maravita 2014), suggesting their independence from low-level movement features. These contradictions call for new paradigms. Our starting hypothesis here is that the organization and function of the mirror mechanism should follow that of the motor system during action execution. Hence, we derived three action observation protocols from classical motor control theories: 1) The first study was motivated by the fact that motor redundancy in action execution do not allow the presence of a one-to-one mapping between (single) muscle activation and action goals. Based on that, we showed that the effect of action observation (observation of an actor performing a power versus a precision grasp) are variable at the single muscle level (MEPs; motor evoked potentials) but robust when evaluating the kinematic of TMS-evoked movements. Considering that movements are based on the coordination of multiple muscle activations (muscular synergies), MEPs may represent a partial picture of the real corticospinal activation. Inversely, movement kinematics is both the final functional byproduct of muscles coordination and the sole visual feedback that can be extracted from action observation (i.e. muscle recruitment is not visible). We conclude that TMS-evoked kinematics may be more reliable in representing the state of the motor system during action observation. 2) In the second study, we exploited the inter-subject variability inherent to everyday whole-body human actions, to evaluate the link between individual motor signatures (or motor styles) and other\u2019s action perception. We showed no group-level effect but a robust correlation between the individual motor signature recorded during action execution and the subsequent modulations of corticospinal excitability during action observation. However, results were at odds with a strict version of the direct matching hypothesis that would suggest the opposite pattern. In fact, the more the actor\u2019s movement was similar to the observer\u2019s individual motor signature, the smaller was the MEPs amplitude, and vice versa. These results conform to the predictive coding hypothesis, suggesting that during AO, the motor system compares our own way of doing the action (individual motor signature) with the action displayed on the screen (actor\u2019s movement). 3) In the third study, we investigated the neural mechanisms underlying the visual perception of action mistakes. According to a strict version of the direct matching hypothesis, the observer should potentially reproduce the neural activation present during the actual execution of action errors (van Schie et al. 2004). Here, instead of observing an increase of cortical inhibition, we showed an early (120 ms) decrease of intracortical inhibition (short intracortical inhibition) when a mismatch was present between the observed action (erroneous) and the observer\u2019s expectation. As proposed by the predictive coding framework, the motor system may be involved in the generation of an error signal potentially relying on an early decrease of intracortical inhibition within the corticomotor system. The second line of research aimed at the investigation of how sensorimotor communication flows between agents engaged in a complementary action coordination task. In this regard, measures of interest where related to muscle activity and/or kinematics as the recording of TMS-related indexes would be too complicated in a joint-action scenario. 1) In the first study, we exploited the known phenomenon of Anticipatory Postural Adjustments (APAs). APAs refers to postural adjustments made in anticipation of a self- or externally-generated disturbance in order to cope for the predicted perturbation and stabilize the current posture. Here we examined how observing someone else lifting an object we hold can affect our own anticipatory postural adjustments of the arm. We showed that the visual information alone (joint action condition), in the absence of efference copy (present only when the subject is unloading by himself the object situated on his hand), were not sufficient to fully deploy the needed anticipatory muscular activations. Rather, action observation elicited a dampened APA response that is later augmented by the arrival of tactile congruent feedback. 2) In a second study, we recorded the kinematic of orchestra musicians (one conductor and two lines of violinists). A manipulation was added to perturb the normal flow of information conveyed by the visual channel. The first line of violinist where rotated 180\ub0, and thus faced the second line. Several techniques were used to extract inter-group (Granger Causality method) and intra-group synchronization (PCA for musicians and autoregression for conductors). The analyses were directed to two kinematic features, hand and head movements, which are central for functionally different action. The hand is essential for instrumental actions, whereas head movements encode ancillary expressive actions. During the perturbation, we observed a complete reshaping of the whole patterns of communication going in the direction of a distribution of the leadership between conductor and violinists, especially for what regards head movements. In fact, in the perturbed condition, the second line acts as an informational hub connecting the first line to the conductor they no longer can see. This study evidences different forms of communications (coordination versus synchronization) flowing via different channels (ancillary versus instrumental) with different time-scales

Analysis of Connectivity in EMG Signals to Examine Neural Correlations in Muscular Activation of Lower Leg Muscles for Postural Stability

In quiet standing the central nervous systems implements a pre-programmed ankle strategy of postural control to maintain upright balance and stability. This strategy is comprised of a synchronized common neural drive being delivered to synergistically grouped muscles. In this study connectivity between EMG signals of unilateral and bilateral homologous muscle pairs, of the lower legs, during various standing balance conditions was evaluated using magnitude squared coherence (MSC) and mutual information (MI). The leg muscles of interest were the tibialis anterior (TA), medial gastrocnemius (MG), and the soleus (S) of both legs. MSC is a linear measure of the phase relation between two signals in the frequency domain. MI is an information theoretic measure of the amount of information two signals have in common. Both MSC and MI were analyzed in the delta (0.5 – 4 Hz), theta (4 – 8 Hz), alpha (8 – 13 Hz), beta (13 – 30 Hz), and gamma (30 – 100 Hz) neural frequency bands for feet together and feet tandem, with eyes open and eyes closed conditions. Both MSC and MI found that overall connectivity was highest in the delta band followed by the theta band. Connectivity in the beta and lower gamma bands (30 – 60 Hz) was influenced by standing balance condition and indicative of a neural drive originating from the motor cortex. Instability was evaluated by comparing less stable standing conditions with a baseline eyes open, feet together stance. Changes in connectivity in the beta and gamma bands were found be most significant in the muscle pairs of the back leg of tandem stance regardless of foot dominance. MI was found to be a better connectivity analysis method by identifying significance of increased connectivity in the agonistic muscle pair between the MG:S, the antagonistic muscle pair between TA:S, and all the bilateral homologous muscle pairs. MSC was only able to identify the MG:S muscle pair as significant. The results of this study provided insight into the neural mechanism of postural control and presented an alternative connectivity analysis method of MI

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation.

After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery

Brain-computer interface technology and neuroelectrical imaging to improve motor recovery after stroke

Stroke is defined as a focal lesion in the brain caused by acute ischemia or hemorrhage. The events that characterize acute stroke as well as the spontaneous recovery process occurring in the subacute phase, demonstrate that the focal damage affects remote interconnected areas. On the other hand, interconnected areas largely contribute to reorganization of the central nervous system (CNS) along the recovery process (plasticity) throughout compensatory or restorative mechanisms which can also lead to unwanted effects (maladaptive plasticity). Such post-stroke brain reorganization occurring spontaneously or within a rehabilitation program, is the object of wide literature in the fields of neuroimaging and neurophysiology. Brain-Computer Interfaces (BCIs) allow recognition, monitoring and reinforcement of specific brain activities as recorded eg. via electroencephalogram (EEG) and use such brain activity to control external devices via a computer. Sensorimotor rhythm (SMR) based BCIs exploit the modulation occurring in the EEG in response to motor imagery (MI) tasks: the subject is asked to perform MI of eg. left or right hand in order to control a cursor on a screen. In the context of post-stroke motor rehabilitation, such recruitment of brain activity within the motor system through MI can be used to harness brain reorganization towards a better functional outcome. Since 2009 my research activity has been focused mainly on BCI applications for upper limb motor rehabilitation after stroke within national (Ministry of Health) and international (EU) projects. I conducted (or participated to) several basic and clinical studies involving both healthy subjects and stroke patients and employing a combination of neurophysiological techniques (EEG, transcranial magnetic stimulation – TMS) and BCI technology (De Vico Fallani et al., 2013; Kaiser et al., 2012; Morone et al., 2015; Pichiorri et al., 2011). Such studies culminated in a randomized controlled trial (RCT) conducted on subacute stroke patients in which we demonstrated that a one-month training with a BCI system, which was specifically designed to support upper limb rehabilitation after stroke, significantly improved functional outcome (upper limb motor function) in the target population. Moreover, we observed changes in brain activity and connectivity (from high-density EEG recordings) occurring in motor related frequency ranges that significantly correlated to the functional outcome in the target group (Pichiorri et al., 2015). Following these promising results, my activity proceeded along two main pathways during the PhD course. On one hand, efforts were made ameliorate the prototypal BCI system used in (Pichiorri et al., 2015); the current system (called Promotœr) is an all-in-one BCI training station with several improvements in usability for both the patient and the therapist (it is easier to use, employs wireless EEG system with reduced number of electrodes) (Colamarino et al., 2017a,b). The Promotœr system is currently employed in add-on to standard rehabilitation therapy in patients admitted at Fondazione Santa Lucia. Preliminary results are available on chronic stroke patients, partially retracing those obtained in the subacute phase (Pichiorri et al., 2015) as well as explorative reports on patients with upper limb motor deficit of central origin other than stroke (eg. spinal cord injury at the cervical level). In the last year, I submitted research projects related to the Promotœr system to private and public institutions. These projects foresee i) the addition of a proprioceptive feedback to the current visual one by means of Functional Electrical Stimulation (FES) ii) online evaluation of residual voluntary movement as recorded via electromyography (EMG), and iii) improvements in the BCI control features to integrate concepts derived from recent advancements in brain connectivity. On these themes, I recently obtained a grant from a private Swedish foundation. On the other hand, I conducted further analyses of data collected in the RCT (Pichiorri et al., 2015) to identify possible neurophysiological markers of good motor recovery. Specifically, I focused on interhemispheric connectivity (EEG derived) and its correlation with the integrity of the corticospinal tract (as assessed by TMS) and upper limb function (measured with clinical scales) in subacute stroke patients. The results of these analyses were recently published on an international peer-reviewed journal (Pichiorri et al., 2018). In the first chapter of this thesis, I will provide an updated overview on BCI application in neurorehabilitation (according to the current state-of-the-art). The content of this chapter is part of a wider book chapter, currently in press in Handbook of Clinical Neurology (Pichiorri and Mattia, in press). In the second chapter, I will report on the status of BCI applications for motor rehabilitation of the upper limb according to the approach I developed along my research activity, including ongoing projects and prliminary findings. In the third chapter I will present the results of a neurophysiological study on subacute stroke patients, exploring EEG derived interhemispheric connectivity as a possible neurophysiological correlate of corticospinal tract integrity and functional impairment of the upper limb. Overall this work aims to outline the current and potential role of BCI technology and EEG based neuroimaging in post-stroke rehabilitation mainly in relation to upper limb motor function, nonetheless touching upon possible different applications and contexts in neighboring research fields

Neuroplasticity of Ipsilateral Cortical Motor Representations, Training Effects and Role in Stroke Recovery

This thesis examines the contribution of the ipsilateral hemisphere to motor control with the aim of evaluating the potential of the contralesional hemisphere to contribute to motor recovery after stroke. Predictive algorithms based on neurobiological principles emphasize integrity of the ipsilesional corticospinal tract as the strongest prognostic indicator of good motor recovery. In contrast, extensive lesions placing reliance on alternative contralesional ipsilateral motor pathways are associated with poor recovery. Within the predictive algorithms are elements of motor control that rely on contributions from ipsilateral motor pathways, suggesting that balanced, parallel contralesional contributions can be beneficial. Current therapeutic approaches have focussed on the maladaptive potential of the contralesional hemisphere and sought to inhibit its activity with neuromodulation. Using Transcranial Magnetic Stimulation I seek examples of beneficial plasticity in ipsilateral cortical motor representations of expert performers, who have accumulated vast amounts of deliberate practise training skilled bilateral activation of muscles habitually under ipsilateral control. I demonstrate that ipsilateral cortical motor representations reorganize in response to training to acquisition of skilled motor performance. Features of this reorganization are compatible with evidence suggesting ipsilateral importance in synergy representations, controlled through corticoreticulopropriospinal pathways. I demonstrate that ipsilateral plasticity can associate positively with motor recovery after stroke. Features of plastic change in ipsilateral cortical representations are shown in response to robotic training of chronic stroke patients. These findings have implications for the individualization of motor rehabilitation after stroke, and prompt reappraisal of the approach to therapeutic intervention in the chronic phase of stroke

(e)motion: The interplay between emotional processing and the sensorimotor system

This thesis aimed to explore the relationship between emotional processing and the sensorimotor system, mainly focusing on one information source derived from emotional body language (EBL). We investigated such a relationship in four different experiments and through several methodologies ranging from behavioral to neurophysiological techniques, by means of transcranial magnetic stimulation (TMS) and high-density electroencephalography (hdEEG), in healthy subjects (experiments 1, 2 and 3) and patients affected by Parkinson’s Disease (PD) (experiment 4). In the first experiment, whose aims were to explore the ability to process, discriminate and recognize emotional information carried by body language and to test motor response through response times (RTs) to emotional stimuli (i.e., EBL and IAPS), we found that fearful EBL is rapidly recognized and processed, probably because of a rapid and instinctual activation of several brain structures involved in defensive reactions. In the second experiment we investigated the effects of emotion processing (i.e., Fear, Happy and Neutral) on the sensorimotor system through a TMS protocol assessing short-latency afferent inhibition (SAI) at two timepoints (i.e., 120 and 300 ms). Our results showed that sensorimotor inhibition in the first 120 ms after stimulus onset is increased during processing of fearful emotional stimuli, reflecting the fact that automatic processing of threatening information can modulate attentional resources and cholinergic activity. In the third experiment, were a protocol involving hdEEG and a source localization workflow was implemented in the study of event-related potentials (ERPs) and mu-alpha and beta-bands rhythms during EBL processing, we confirmed what observed in the second experiment by showing that during processing of fearful body expressions there was an increased activity in the β frequency band in the somatosensory cortex which in turn may be one of the factors responsible for reducing the activation of motor related areas and, hence, increase sensorimotor inhibition. Lastly, in the fourth experiment we partly replicated the experimental design of the first experiment but in patients with Parkinson’s disease and using not only emotional body language stimuli and emotional scenes, but also emotional facial expressions. Our results showed that motor responses in PD patients are speeded when observing a potential threat, for both the embodied set of stimuli (EBL and facial expressions). We discussed this finding in relation to the “Kinesia paradoxa” phenomenon, defined as “the sudden transient ability of a patient with PD to perform a task he or she was previously unable to perform”