Prediction of forelimb muscle activities and movement phases using corticospinal signals in the rat

The targeted population for this project is primarily patients with high level spinal cord injury (SCI) and individuals with motor neuron diseases (MND). In both SCI and MND cases motor control is interrupted due to lack of communication between the brain and the musculature, although both sides are otherwise functional. The approach in this project is to use neural engineering techniques to restore the motor function that was lost because of an injury or disease. Brain-computer interfaces (BCIs) attempt to extract the volitional signals from the cortex when the brain\u27s normal outputs to the musculoskeletal system are impaired. However, BCIs that depend on the cortical activities suffer from two main impediments that are intrinsic to the BCI approach itself; firstly, under-sampling of the volitional information due to limited number of recording channels, and secondly, the long-term instability of the neuronal firings that make it difficult to track movement parameters, such as hand kinematics. As an alternative approach, a spinal cord computer interface (SCCI) can address both obstacles by providing means to access neural signals from a relatively smaller yet denser implant area in order to extract low-level movement parameters, such as muscle electromyography (EMG) signals, for prolonged signal stability. Since the descending fibers of the spinal cord influence the lower motor neurons that directly innervate the skeletal muscles, decoding the information in these fibers can provide a way to establish a robust relationship between the neural control signals and the output parameter, that is the EMG signal. The axons carrying the cortical information through the spinal cord are tightly bundled together in the descending tracts that eventually synapse with the inter-neurons and alpha motor neurons located in the spinal grey matter. The corticospinal tract (CST) is one of the descending tracts that carry the forelimb volitional information. In this study, the CST signals are recorded in rats that are implanted with custom-designed flexible multi-electrode arrays (MEAs). The power spectral density of the CST signals during the movement is notably higher than those observed during resting and anesthesia. The average inter-channel coherences up to 1.5 kHz are significantly higher for reach-to-pull task compared to face grooming and resting states, suggesting the presence of volitional information in the recorded CST signals. The results show that the CST signals can be segregated into two or three different classes using the forelimb movement components as guidance criteria with 97% and 71% accuracies, respectively. Predictions with correlation coefficients as high as 0.81 for the biceps EMG are achieved in individual sessions, although the average prediction accuracies vary considerably among rats. These results support the feasibility of an EMG-based Spinal Cord Computer Interface for patients with high level of paralysis

Characterizing motor control signals in the spinal cord

The main goal of this project is to develop a rodent model to study the central command signals generated in the brain and spinal cord for the control of motor function in the forearms. The nature of the central command signal has been debated for many decades with only limited progress. This thesis presents a project that investigated this problem using novel techniques. Rats are instrumented to record the control signals in their spinal cord while they are performing lever press task they are trained in. A haptic interface and wireless neural data amplifier system simultaneously collects dynamic and neural data. Isometric force is predicted from force signal using a combination of time-frequency analysis, Principle component analysis and linear filters. Neural-force mapping obtained at one location are subsequently applied to isometric data recorded at other locations. Prediction errors exhibited negative relationship with the isometric position at upper half of movement range. This suggests the presence of restorative forces which are consistent with positional feedback at spinal level. The animal also appears to become unstable in the lower half of their movement ranges, likely caused by a transition from bipedal to quadruped posture. The presence of local feedback and ability for animals to plan postures that are unstable in absence of external forces suggest that descending signal is a reference trajectory planned using internal models. This has important consequences in design of neuroprosthetic actuators: Inverse dynamic models of patient limbs and local positional feedbacks can improve their performance

Sensorimotor content of multi-unit activity in the paramedian lobule of the cerebellum

Based on Center for Disease Control and Prevention report 2016, around 39.5 million people in the United States suffer from motor disabilities. These disabilities are due to traumatic conditions like traumatic brain injury (TBI), neurological diseases such as amyotrophic lateral sclerosis (ALS), or congenital conditions. One of the approaches for restoring the lost motor function is to extract the volitional information from the central nervous system (CNS) and control a mechanical device that can replace the function of a paralyzed limb through systems called Brain-Computer Interfaces (BCI). One of the major challenges being faced in BCIs and also in general neural recording field is the limitations of the microelectrodes. In this study, as the first aim, a custom-made micro-electrode array (MEA) using carbon fibers is developed. After ex vivo testing, they are implanted into the paramedian lobule (PML) of the rat cerebellum to record the multi-unit activity from its cortex. Following animal termination, tissue samples are examined with histological techniques for the assessment of tissue damage caused by the electrodes. Another challenge in the BCI field is extracting the control information regarding the intended motor function from the CNS. The way the cerebellar cortex encodes sensorimotor information and contributes to motor coordination has been a topic of discussion for decades. Recent studies have revealed high correlations between Purkinje cell simple spikes and the forelimb kinematics in experimental animals. However, tracking single spike activity in long-term implants with multi-channel electrodes has well-known challenges. Therefore, as the second aim of this study, the correlation of multi-unit neural signals from the paramedian lobule (PML) of the cerebellar cortex to the forelimb muscle activities (EMG) in rats during behavior was investigated. Linear regression is performed to predict the EMG signal envelopes using the cerebellar activity for various time shifts of the data (±10, ±50, ±100, and ±200 ms) to determine if the neural signals are primarily motor or sensory. The highest correlations (~0.6 on average) between neural and EMG envelopes are observed when the EMG signals are either shifted only about ±10 ms or not shifted at all with respect to the neural signals. There were however still correlations above the chance level for larger shifts in time. The results suggest that PML cortex contains both motor and sensory information in relation to the forelimb activity, and also that the extraction of motor information is feasible from multi-unit neural recordings from the cerebellar cortex. Increased prediction success was observed in reaching and retrieval phases compared to grasping phase when predictions were tested on three phases of the behavior separately. When EMG and neural signal envelopes were clustered, they showed patterns of surges of activity in all three phases. The neural signals showed higher activity in the reaching phase. The 300-1000Hz components of neural signals contributed to the predictions more than the other frequency bands. The results of this study supports the feasibility of a BCI based on MUA extracted from the cerebellar cortex using MEAs

Cortical control of intraspinal microstimulation to restore motor function after paralysis

Phd ThesisSpinal cord injury (SCI) is a devastating condition affecting the quality of life of many otherwise healthy patients. To date, no cure or therapy is known to restore functional movements of the arm and hand, and despite considerable effort, stem cell based therapies have not been proven effective. As an alternative, nerves or muscles below the injury could be stimulated electrically. While there have been successful demonstrations of restoration of functional movement using muscle stimulation both in humans and non-human primates, intraspinal microstimulation (ISMS) could bear benets over peripheral stimulation. An extensive body of research on spinal stimulation has been accumulated – however, almost exclusively in non-primate species. Importantly, the primate motor system has evolved to be quite different from the frog’s or the cat’s – two commonly studied species –, reecting and enabling changes in how primates use their hands. Because of these functional and anatomical differences, it is fair to assume that also spinal cord stimulation will have different effects in primates. is question – what are the movements elicited by ISMS in the macaque – will be addressed in chapters and . Chronic intraspinal electrode implants so far have been difficult to realise. In chapter we describe a novel use of oating microelectrode arrays (FMAs) as chronic implants in the spinal cord. Compared to implanted microwires or other arrays, these FMAs have the benet of a high electrode density combined with different lengths of electrodes. We were able to maintain these arrays in the cord for months and could elicit movements at low thresholds throughout. If we could build a neural prosthesis stimulating the spinal cord, how would it be controlled? Remarkable progress has been recently achieved in the eld of brain-machine interfaces (BMIs), for example enabling patients to control robotic arms with neural signals recorded from chronically implanted electrodes. Chapter of this thesis examines an approach that combines ISMS with cortical control in a macaque model for upper limb paralysis for the rst time and shows that there is a behavioural improvement. We have devised an experiment in which a monkey trained to perform a grasp-and-pull task receives a temporary cortically induced paralysis of the hand reducing task performance. At the same time, cortical recordings from a different area allow us to control ISMS at sites evoking hand movements – thus partially restoring function. Finally, in appendix A we describe a system we developed in order to introduce automated positive reinforcement training (aPRT) both at the breeding facility and in our animal houses. is system potentially reduces time spent on training animals, adds enrichment to the monkeys’ home environment, and allows for suitability screening of monkeys for behavioural neuroscience experiments

On the Utility of Representation Learning Algorithms for Myoelectric Interfacing

Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steer—a gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden

Neuromuscular fatigue, muscle temperature and hypoxia: an integrative approach.

Real world exposures to physiologically and/or psychologically stressful environments are often multifactorial. For example, high-altitude typically combines exposure to hypobaric hypoxia, solar radiation and cold ambient temperatures, while sea level thermal stress is often combined with supplementary or transient stressors such as rain, solar radiation and wind. In such complex environments, the effect of one stressor on performance may be subject to change, simply due to the presence of another independent stressor. Such differential influences can occur in three basic forms; additive, antagonistic and synergistic, each term defining a fundamental concept of inter-parameter interactions. As well as the natural occurrence of stressors in combination, understanding interactions is fundamental to experimentally modelling how multiple physiological strains integrate in their influence on or regulation of - exercise intensity. In this thesis the current literature on neuromuscular fatigue and the influence of thermal and hypoxic stress is reviewed (Chapter 1). This is followed by an outline of the methodological developments used in the subsequent experiments (Chapter 2). In the first experimental study (Chapter 3) a novel approach was adopted to investigate the combined effect of muscle cooling and hypoxia on neuromuscular fatigue in humans. The results showed that the neuromuscular system s maximal force generating capacity declined by 8.1 and 13.9% during independent cold and hypoxic stress compared to control. Force generation decreased by 21.4% during combined hypoxic-cold compared to control, closely matching the additive value of hypoxia and cold individually (22%). This was also reflected in the measurement of mechanical fatigue (electromechanical ratio), demonstrating an additive response during combined hypoxic-cold. From this study, it was concluded that when moderate hypoxia and cold environmental temperatures are combined during low intensity exercise, the level of fatigue increases additively with no interaction between these stressors. Before conducting a more complex investigation on combined stressors, a better understanding of the role of muscle temperature on central fatigue - i.e. voluntary muscle activation via the afferent signalling pathways was sought. The focus of Chapter 4 was to quantify the relationship between muscle temperature and voluntary muscle activation (central fatigue) across a wide range of temperatures. The primary finding was that different muscle temperatures can induce significant changes in voluntary activation (0.5% reduction per-degree-centigrade increase in muscle temperature) when neural drive is sustained for a prolonged effort (e.g. 120-s); however this effect is not exhibited during efforts that are brief in duration (e.g. 3-s). To further explore this finding, Chapter 5 investigated the effect of metaboreceptive feedback at two different muscle temperatures, using post-exercise muscle ischemia, on voluntary activation of a remote muscle group. The results showed that at the same perceived mental effort, peripheral limb discomfort was significantly higher with increasing muscle temperature (2% increase per-degree-centigrade increase). However any influence of increased muscle temperature on leg muscle metaboreceptive feedback did not appear to inhibit voluntary muscle activation - i.e. central control - of a remote muscle group, as represented by an equal force output and voluntary activation in the thermoneutral, contralateral leg. In Chapter 6, the psycho-sensory effects of changes in muscle temperature on central fatigue during dynamic exercise were investigated. During sustained dynamic exercise, fatigue development appeared to occur at a faster rate in hot muscle (4% increase per-degree-centigrade increase) leading to a nullification of the beneficial effects of increased muscle temperature on peak power output after a period of ~60-s maximal exercise. In support of previous studies using isometric exercise (Chapter 4 and 6), participants reported significantly higher muscular pain and discomfort in hot muscle compared to cooler muscle during dynamic exercise (2 and 1% increase per-degree-centigrade increase respectively), however this did not result in a lower power output. From Chapters 4, 5 and 6 it was concluded that in addition to faster rates of metabolite accumulation due to cardiovascular strain, it is possible that a direct sensitisation of the metaboreceptive group III and IV muscle afferents occurs in warmer muscle. This likely contributes to the reduction in voluntary muscle activation during exercise in the heat, while it may attenuate central fatigue in the cold. It was also interpreted that muscle afferents may have a similar signalling role to cutaneous sensory afferents; the latter of which are recognised for their role in providing thermal feedback to the cognitive-behavioural centres of the brain and aiding exercise regulation under thermal stress. The impact of body core and active muscle temperature on voluntary muscle activation represented a similar ratio (5 to 1 respectively) to the temperature manipulated (single leg) to non-temperature manipulated mass (rest of body) in Chapters 4, 5 and 6. This indicates that voluntary muscle activation may also be regulated based on a central meta-representation of total body heat content i.e. the summed firing rates of all activated thermoreceptors in the brain, skin, muscle, viscera and spine. Building on the initial findings of Chapter 3, Chapter 7 investigated the causative factors behind the expression of different interaction types during exposure to multi-stressor environments. This was achieved by studying the interaction between thermal stress and hypoxia on the rate of peripheral and central fatigue development during a high intensity bout of knee extension exercise to exhaustion. The results showed that during combined exposure to moderate hypoxia and mild cold, the reductions in time to exhaustion were additive of the relative effects of hypoxia and cold independently. This differs from the findings in Chapter 3, in which fatigue was additive of the absolute effects of cold and hypoxia. In contrast, combining moderate hypoxia with severe heat stress resulted in a significant antagonistic interaction on both the absolute and relative reductions in time to exhaustion i.e. the combined effect being significantly less than the sum of the individual effects. Based on the results in Chapter 7, a quantitative paradigm for understanding of systematic integration of multifactorial stressors was proposed. This is, that the interaction type between stressors is influenced by the impact magnitude of the individual stressors effect on exercise capacity, whereby the greater the stressors impact, the greater the probability that one stressor will be cancelled out by the other. This is the first study to experimentally model the overarching principles characterising the presence of simultaneous physiological strains, suggesting multifactorial integration be subject to the worst strain takes precedence when the individual strains are severe

Disinhibition of intracortical networks to augment crossed and uncrossed corticospinal pathways

Multi-modal neurorehabilitation models for stroke patients recommend an approach based on severity of hemisphere damage. If the ipsilesional primary motor cortex (M1) is still intact, the crossed corticospinal tract (CST) can be targeted. However, severely affected patients rely on contralesional motor cortices and therefore the uncrossed CST. Disinhibition of intracortical networks can facilitate plasticity induction in the CST and therefore recovery. Motor execution or imagery (MI) results in an endogenous disinhibition. Exogenous modulation of inhibitory intracortical networks is achieved by a repetitive paired-pulse transcranial magnetic stimulation (TMS) protocol, referred to as DIS, or electrical stimulation (ES). A combination of the different disinhibition protocols has not been tested yet. Furthermore, the efficacy of targeting the uncrossed CST from contralesional M1 remains unclear. As the presence of ipsilateral motor evoked potentials (MEPs) from the uncrossed CST in hand muscles has escaped recognition, limited data is available. We hypothesized that lasting corticospinal excitability (CSE) changes could be achieved by associatively pairing endogenous modulation with exogenous stimulation of the same intracortical circuits. Furthermore, we investigated in detail the uncrossed CST. In this line of work, we combined MI of finger extension with DIS to modulate uncrossed CST in healthy subjects. For uncrossed CST, we tested different stimulation protocols for optimal detection of MEPs and combined DIS with active motor execution for CSE enhancement. Furthermore, modulation of ipsilateral CST was investigated in healthy subjects and severely affected stroke patients. MI combined with DIS resulted in a significant and persistent increase of contralateral CSE, e.g. of the crossed CST. A longer intervention duration further enhanced sustainability of CSE changes. MI alone, DIS alone, or MI/DIS in combination with ES did not result in changes of CSE. Ipsilateral MEPs from the uncrossed CST were reliably measured after TMS during biceps brachii (BB) contraction with a coil orientation of 45° to the sagittal line. Furthermore, paired-pulse TMS facilitated ipsilateral MEPs. DIS alone, but not in combination with MI, resulted in plasticity induction of ipsilateral CST. Additionally, DIS in combination with motor execution resulted in CSE increases in both healthy subjects and severely affected stroke patients. Taken together, we designed and improved two effective associative stimulation protocols combining endogenous and exogenous disinhibition of intracortical circuits. Each protocol was optimized to augment plasticity induction in contralateral or ipsilateral CSE, respectively. Both represent new, efficient interventions targeting either crossed or uncrossed CST and can be applied according to intactness of ipsilesional CST. This thesis may help in developing new therapeutic approaches in stroke rehabilitation, especially for severely affected stroke patients with no residual control of their paretic hand

Brain-Machine Interface for Reaching: Accounting for Target Size, Multiple Motor Plans, and Bimanual Coordination

<p>Brain-machine interfaces (BMIs) offer the potential to assist millions of people worldwide suffering from immobility due to loss of limbs, paralysis, and neurodegenerative diseases. BMIs function by decoding neural activity from intact cortical brain regions in order to control external devices in real-time. While there has been exciting progress in the field over the past 15 years, the vast majority of the work has focused on restoring of motor function of a single limb. In the work presented in this thesis, I first investigate the expanded role of primary sensory (S1) and motor (M1) cortex during reaching movements. By varying target size during reaching movements, I discovered the cortical correlates of the speed-accuracy tradeoff known as Fitts' law. Similarly, I analyzed cortical motor processing during tasks where the motor plan is quickly reprogrammed. In each study, I found that parameters relevant to the reach, such as target size or alternative movement plans, could be extracted by neural decoders in addition to simple kinematic parameters such as velocity and position. As such, future BMI functionality could expand to account for relevant sensory information and reliably decode intended reach trajectories, even amidst transiently considered alternatives.</p><p> The second portion of my thesis work was the successful development of the first bimanual brain-machine interface. To reach this goal, I expanded the neural recordings system to enable bilateral, multi-site recordings from approximately 500 neurons simultaneously. In addition, I upgraded the experiment to feature a realistic virtual reality end effector, customized primate chair, and eye tracking system. Thirdly, I modified the tuning function of the unscented Kalman filter (UKF) to conjointly represent both arms in a single 4D model. As a result of widespread cortical plasticity in M1, S1, supplementary motor area (SMA), and posterior parietal cortex (PPC), the bimanual BMI enabled rhesus monkeys to simultaneously control two virtual limbs without any movement of their own body. I demonstrate the efficacy of the bimanual BMI in both a subject with prior task training using joysticks and a subject naïve to the task altogether, which simulates a common clinical scenario. The neural decoding algorithm was selected as a result of a methodical comparison between various neural decoders and decoder settings. I lastly introduce a two-stage switching model with a classify step and predict step which was designed and tested to generalize decoding strategies to include both unimanual and bimanual movements.</p>Dissertatio

Muscle activation patterns in shoulder impingement patients

Introduction: Shoulder impingement is one of the most common presentations of shoulder joint problems 1. It appears to be caused by a reduction in the sub-acromial space as the humerus abducts between 60o -120o – the 'painful arc'. Structures between the humeral head and the acromion are thus pinched causing pain and further pathology 2. Shoulder muscle activity can influence this joint space but it is unclear whether this is a cause or effect in impingement patients. This study aimed to observe muscle activation patterns in normal and impingement shoulder patients and determine if there were any significant differences. Method: 19 adult subjects were asked to perform shoulder abduction in their symptomatic arm and non-symptomatic. 10 of these subjects (age 47.9 ± 11.2) were screened for shoulder impingement, and 9 subjects (age 38.9 ± 14.3) had no history of shoulder pathology. Surface EMG was used to collect data for 6 shoulder muscles (Upper, middle and lower trapezius, serratus anterior, infraspinatus, middle deltoids) which was then filtered and fully rectified. Subjects performed 3 smooth unilateral abduction movements at a cadence of 16 beats of a metronome set at 60bpm, and the mean of their results was recorded. T-tests were used to indicate any statistical significance in the data sets. Significance was set at P<0.05. Results: There was a significant difference in muscle activation with serratus anterior in particular showing a very low level of activation throughout the range when compared to normal shoulder activation patterns (<30%). Middle deltoid recruitment was significantly reduced between 60-90o in the impingement group (30:58%).Trends were noted in other muscles with upper trapezius and infraspinatus activating more rapidly and erratically (63:25%; 60:27% respectively), and lower trapezius with less recruitment (13:30%) in the patient group, although these did not quite reach significance. Conclusion: There appears to be some interesting alterations in muscle recruitment patterns in impingement shoulder patients when compared against their own unaffected shoulders and the control group. In particular changes in scapula control (serratus anterior and trapezius) and lateral rotation (infraspinatus), which have direct influence on the sub-acromial space, should be noted. It is still not clear whether these alterations are causative or reactionary, but this finding gives a clear indication to the importance of addressing muscle reeducation as part of a rehabilitation programme in shoulder impingement patients