abstract: Brain-machine interfaces (BMIs) were first imagined as a technology that would allow subjects to have direct communication with prosthetics and external devices (e.g. control over a computer cursor or robotic arm movement). Operation of these devices was not automatic, and subjects needed calibration and training in order to master this control. In short, learning became a key component in controlling these systems. As a result, BMIs have become ideal tools to probe and explore brain activity, since they allow the isolation of neural inputs and systematic altering of the relationships between the neural signals and output. I have used BMIs to explore the process of brain adaptability in a motor-like task. To this end, I trained non-human primates to control a 3D cursor and adapt to two different perturbations: a visuomotor rotation, uniform across the neural ensemble, and a decorrelation task, which non-uniformly altered the relationship between the activity of particular neurons in an ensemble and movement output. I measured individual and population level changes in the neural ensemble as subjects honed their skills over the span of several days. I found some similarities in the adaptation process elicited by these two tasks. On one hand, individual neurons displayed tuning changes across the entire ensemble after task adaptation: most neurons displayed transient changes in their preferred directions, and most neuron pairs showed changes in their cross-correlations during the learning process. On the other hand, I also measured population level adaptation in the neural ensemble: the underlying neural manifolds that control these neural signals also had dynamic changes during adaptation. I have found that the neural circuits seem to apply an exploratory strategy when adapting to new tasks. Our results suggest that information and trajectories in the neural space increase after initially introducing the perturbations, and before the subject settles into workable solutions. These results provide new insights into both the underlying population level processes in motor learning, and the changes in neural coding which are necessary for subjects to learn to control neuroprosthetics. Understanding of these mechanisms can help us create better control algorithms, and design training paradigms that will take advantage of these processes. / Dissertation/Thesis / Doctoral Dissertation Bioengineering 2015

<p>In recent years, large-scale brain recordings in nonhuman primates have been a driving force for both fundamental neuroscience and the field of brain-machine interfaces (BMIs). This required monkey implants connected to external amplifiers and computers with ever increasing number of cables. As shown with our recent demonstration of 2,000 neurons recorded in one monkey, a tethered recording system begins to get bulky and complex, particularly for our BMI and neurophysiological research. To address this problem, we developed a multichannel wireless recording framework. The system was been tested in freely moving rhesus monkey by integrating wireless neural recordings with external computers performing BMI decoding, behavioral manipulanda and optical tracking. This technology can be applied to primate behavior research and, in the near future, wireless, fully implantable human neuroprosthetics, which is of great significance to those suffering from locomotor deficiencies, such as those brought on by spinal cord injury and stroke. Aided with these advances, I was able to study monkeys in unrestrained locomotion while their cortical activity was continuously monitored. I also explored unrestrained behaviors and how they showed distinct transitions in neural dynamics as monkeys engaged in different behavioral activities or learned new motor skills, such as bipedal walking. I was able to decode them many of these behavioral states from cortical activity with neural classifiers. Lastly, monkeys were able to perform BMI tasks continuously for many hours, allowing us to prove the relevance of unrestrained noise in BMI performance. Lastly, I present my role in developing two brain actuated movement platforms, a robotic exoskeleton under the guise of the WalkAgain project, and a microelectrode BMI enabled wheelchair. This body of work should assist those on the path to the next generation of clinical neuroprostheses and neural communication systems.</p> / Dissertation

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Within the field of neuroprosthetics the possibility to use implanted electrodes for communication with the nervous system is explored. Much effort is put into the material aspects of the electrode implant to increase charge injection capacity, suppress foreign body response and build micro sized electrode arrays allowing close contact with neurons. Conducting polymers, in particular poly(3,4-ethylene dioxythiophene) (PEDOT), have been suggested as materials highly interesting for such neural communication electrodes. The possibility to tailor the material both mechanically and biochemically to suit specific applications, is a substantial benefit with polymers when compared to metals. PEDOT also have hybrid charge transfer properties, including both electronic and ionic conduction, which allow for highly efficient charge injection.   Part of this thesis describes a method of tailoring PEDOT through exchanging the counter ion used in electropolymerisation process. Commonly used surfactants can thereby be excluded and instead, different biomolecules can be incorporated into the polymer. The electrochemical characteristics of the polymer film depend on the ion. PEDOT electropolymerised with heparin was here determined to have the most advantageous properties. In vitro methods were applied to confirm non-cytotoxicity of the formed PEDOT:biomolecular composites. In addition, biocompatibility was affirmed for PEDOT:heparin by evaluation of inflammatory response and neuron density when implanted in rodent cortex.   One advantage with PEDOT often stated, is its high stability compared to other conducting polymers. A battery of tests simulating the biological environment was therefore applied to investigate this stability, and especially the influence of the incorporated heparin. These tests showed that there was a decline in the electroactivity of PEDOT over time. This also applied in phosphate buffered saline at body temperature and in the absence of other stressors. The time course of degradation also differed depending on whether the counter ion was the surfactant polystyrene sulphonate or heparin, with a slightly better stability for the former.   One possibility with PEDOT, often overlooked for biological applications, is the use of its semi conducting properties in order to include logic functions in the implant. This thesis presents the concept of using PEDOT electrochemical transistors to construct textile electrode arrays with in-built multiplexing. Using the electrolyte mediated interaction between adjacent PEDOT coated fibres to switch the polymer coat between conducting and non conducting states, then transistor function can be included in the conducting textile. Analogue circuit simulations based on experimentally found transistor characteristics proved the feasibility of these textile arrays. Developments of better polymer coatings, electrolytes and encapsulation techniques for this technology, were also identified to be essential steps in order to make these devices truly useful.   In summary, this work shows the potential of PEDOT to improve neural interfaces in several ways. Some weaknesses of the polymer and the polymer electronics are presented and this, together with the epidemiological data, should point in the direction for future studies within this field. / QC 20100623

Dans ce projet nous nous intéresserons à la création d’un nouveau modèle permettant de simuler des enregistrements extracellulaires de l’activité électrique neurale dans le système nerveux périphérique. Ce modèle fut développé pour permettre une meilleure compréhension de l’impact des différentes propriétés des interfaces sur la qualité des signaux recueillis. Ce projet fut en particulier conduit pour répondre au contexte actuel qui voit le développement de nombreuses applications dans le domaine des neuro-prothèses et autres interfaces neurales à but biomédical. Nos intentions étaient de fournir un nouvel outil permettant de mieux comprendre les particularités des interfaces existantes ou d’aider à leur amélioration et à la planification de futures innovations. Ce modèle est construit comme la synthèse de la compréhension actuelle des différents rouages biophysiques impactant les enregistrements. Sa structure peut être perçue comme l’assemblage de différents sous-systèmes interconnectés et représentant chacun une dimension du processus. Il s’avère particulièrement efficace pour l’analyse comparative des performances entre diffèrent types/géométries d’électrodes invasives. Dans ce document, nous nous efforcerons d’expliquer en détail la structure et les paramètres de notre modèle. Nous décrirons ensuite les différents tests que nous avons entrepris pour sa validation expérimentale, ainsi que les différentes voies d’applications que nous avons commencé à explorer. Nous finirons par décrire les améliorations qui nous sont apparues comme nécessaires ou possibles et par une discussion sur les ouvertures futures offerte à ce domaine de recherche. / Neural interfaces are becoming a newly dynamic and promising field especially thanks to the numerous applications they could have in the biomedical domain. A great deal of these applications requires a monitoring of targeted neural activity. Among the different technologies available for such recording practice, chronic electrodes implanted in the peripheral nervous system offer a good compromise on the resolution versus invasiveness technological constraint. A large array of electrodes has been developed in this intention but there is still only a limited comprehension of their recording principles and weakness. This makes difficult any targeted improvement of the electrodes and led this field to be mainly dominated by a trial and error empirical approach simultaneously costly in funds, animal lives and time. In particular, intrafascicular electrodes, while providing exiting results for stimulation, have often failed in recordings. These electrodes typically show interesting recording performance right after implantation but have rapid decline of their efficacy up to the points that they often become useless after a few weeks. Such performance proves problematic as they drastically limit the transfer of experimental results to human applications. The extent of our work has been the development of a theoretical framework for the study of implantable electrodes. Our goal here has been to construct a model that could be used as a platform to better understand implanted electrode and compare their performance and possible improvement. We focused our work on intrafascicular electrode for the peripheral nervous system. However, our procedure could easily be applied to other type of interface. During this project we first constructed a detailed model of the recording biophysical process happening at the peripheral nerve electrical interface. This model encompasses all the mechanism known to influence the quality and shape of neural activity recordings. We have then recreated within our model specific controlled experiments and by comparing the properties of the simulated recording with their experimental counterparts demonstrated the potency of our approach to produce bio-plausible signals. This validated our model as an in silico alternative to compare and test electrodes. We then further developed this model to also simulate some of the changes happening in the nerve post implantation. In particular, we found that the growth of the fibrotic scar could already explain a large part of the signal degradation happening in the first weeks. Then to demonstrate the adaptability of this model we used it to compare the performance of the main type of electrodes implanted nowadays peripherally. Finally, as the main weakness of our model relied in its relative complexity and the related long computing time, we started to analyze how this model could be simplified without losing the precision necessary for the intended applications. In conclusion, this project led to the creation of a model which in its current form can be used as an in silico platform to test and compare electrodes. This will facilitate the planning and development of future peripheral neural interface by proving both more economical and informative that current strategies. Conjointly, we opened the way to future improvement of our model, leading to more practicality.

<div>The present thesis was completed to satisfy two functions in our laboratory: (1) explore carbon-black (CB) as an additive for electrodeposited intrinsically conductive polymers (ICPs) to improve electrical properties across the electrode-electrolyte interface for use in neuromodulation; and (2) design a histology protocol that will analyze peripheral nerve system (PNS) tissue following implantation of conventional metal and modified conventional metal electrodes with the ICP poly(3,4-ethylenedioxythiophere):poly(styrenesulfonate)/carbon-black (PEDOT:PSS/CB). It would appear that the functions explored may seem unrelated, however, these two topics play a crucial role in designing a viable electrode for use in acute and chronic neuromodulation and the subsequent analysis required to determine the mechanical properties and overall biocompatibility of design.</div><div><br></div><div><div>A series of experiments with different PEDOT:PSS solutions containing varying amounts of suspended CB (n=19; 0 mg/mL to 2 mg/mL) were explored. Solutions were characterized using cyclic voltammetry (CV) using the intended electrode for deposition, composed of stainless steel (SS), as the working electrode (WE) to determine respective redox potentials. SS was chosen because of its inherently bad electrochemical properties, meaning that improved functionality post electrodeposition would be easy to identify. Immediately following CV, stainless-steel electrodes were electrodeposited using one of two techniques: (1) potentiostat, allowing the cell to rest at the redox potential required for bipolaron formation (0.9 V); or (2) galvanostat, where the electrode was submitted to a constant current of 200 mA and allowed to coat. Rapid electrochemical impedance spectroscopy was performed prior to and immediately following coating to determine the pre-electrochemical and post-electrochemical impedance characteristics. Results indicate that there was a positive relationship between the amount of CB additive and the relative impedance drop between the uncoated and coated counterparts. Furthermore, the modified electrochemical interfaces are substantially improved for use in frequency ranges of 10 Hz to 50 kHz, which encompass the ranges of our labs recently discovered low frequency alternating current (LFAC) for use in neuromodulation; thus indicating that PEDOT:PSS/CB modification may be used to improve impedance characteristics during our future LFAC experiments. This protocol, the one that contains the ideal concentration of carbon-black, was then recorded and will be used in our lab.</div></div><div><br></div><div><div>Histology protocols were developed to improve our labs capabilities of post-mortem analysis of PNS tissue. Processing and embedding preparations that explored included paraffin, acrylic, and frozen. Subsequently, staining protocols were developed; however, they varied as a function of the embedding media used; staining protocols developed incorporated progressive and regressive hematoxylin and eosin (H&E) staining as well as toluidine blue (TB). Tissue was sectioned and observed using light microscopy.</div></div>

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