Decoding gait phases from neural activity in rat

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2017Introdução. A assistência médica prevista em casos de traumatismo na medula espinhal é escassa, o que em conjunto com a incapacidade de autorregeneração do sistema nervoso central, implica que a recuperação após trauma seja lenta e muitas vezes impossível. O conceito de uma interface cérebro-espinhal aparece quando exploramos o potencial da estimulação elétrica epidural como técnica de restauração da locomoção após trauma na medula espinhal. Esta técnica já provou ser eficaz em macacos, porém não em ratos. O modelo do rato é significativamente diferente, especialmente quando consideramos a complexidade da sua organização neuronal. Partindo desta problemática procurámos descobrir se é possível decodificar fases da marcha a partir da atividade neuronal em ratos. Este projeto foi desenvolvido durante um estágio de seis meses no laboratório de Gregoire Courtine, localizado no EPFL (École Polytechnique Fédérale de Lausanne), Suíça. Este laboratório especializa-se em neuro-reabilitação e neuro-regeneração. Ao longo desta dissertação será feita a análise e discussão deste projeto. Revisão da literatura. A marcha humana é produzida por uma série de contrações de músculos extensores e flexores a um ritmo predeterminado. Duas fases podem ser identificadas, uma fase de apoio seguida de uma fase de balanço. Os mecanismos que controlam a locomoção ainda não são completamente conhecidos, e a maioria da evidência encontrada surge de estudos realizados em modelos animais. No entanto, podem fornecer alguma orientação. Atualmente, sabe-se que não é necessário controlo supra-espinhal para produzir o ritmo básico da marcha, e que este padrão pode ser gerado por circuitos neuronais que existem na medula espinhal. Porém, várias estruturas do cérebro controlam e regulam as variantes da marcha em situações que envolvem uma marcha mais precisa e criteriosa. Os propriocetores musculares também têm um papel importante neste processo. Contudo considera-se que a marcha de um ser humano está mais dependente de um controlo cerebral. O córtex motor tem um papel de supervisão durante o decorrer da marcha e é a estrutura com o maior nível de abstração em termos da sua atividade elétrica, comparativamente a outras estruturas envolvidas na marcha. Apresenta muita atividade, especialmente quando um movimento requer a ativação de vários grupos musculares. Aquando de uma lesão espinhal, técnicas de reabilitação como a fisioterapia e a estimulação elétrica são utlizadas com algum grau de sucesso. Geralmente, o foco da reabilitação encontra-se em readquirir alguma qualidade de vida e destreza motora por parte do doente. No entanto nos casos em que a gravidade da lesão é tal que não existem células neuronais que mantenham qualquer ligação da espinhal medula as perspetivas de reabilitação tornam-se significativamente inferiores. Técnicas que potenciem a plasticidade neuronal e técnicas que viabilizem a regeneração neuronal devem ser então exploradas. A interface cérebro-espinhal utiliza a estimulação elétrica neuronal, controlando o seu ritmo, recorrendo a primitivas descodificadas de atividade neuronal que identificam momentos específicos do ciclo da marcha. Procuramos então obter uma prova de conceito, de que é possível obter variáveis discretas de locomoção a partir de atividade neuronal usando o modelo do rato. Métodos. A área que é conhecida por codificar informações sobre a locomoção no rato é o córtex sensoriomotor primário. Esta informação é transmitida através do caminho descendente do córtex sensoriomotor através da medula para os nervos eferentes que acionam os grupos musculares necessários na locomoção, garantindo a flexão e a extensão faseadas dos membros inferiores. Nos casos onde há uma lesão na medula espinhal e subsequente paralisia dos membros inferiores, a gravidade dos danos neuronais impedem a transmissão do sinal. O objetivo da interface cérebroespinal é capturar a atividade neuronal relacionada com a locomoção implantando uma matriz de microeléctrodos de 32 canais no córtex sensorimotor primário direito e usando métodos de classificação para prever momentos específicos do ciclo da marcha, que neste caso foram: o aplanamento e o impulso do pé. A nomenclatura usada para estes dois momentos foi de foot strike e foot off , respetivamente. Dois ratos fêmeas da raça Lewis designados por r263 e r328 receberam o implante cortical. Após o tempo de recuperação recomendado pós-cirurgia, prosseguimos com os ensaios, que consistiam na execução de aproximadamente um metro e meio de caminhada quadrupede. Um sistema de captura e análise de movimentos tridimensionais (Vicon Motion Systems®) foi utilizado para gravar as variáveis cinemáticas e o vídeo. No total, considerámos vinte e quatro sessões para r263 e trinta e uma sessão para r328. Após a análise das variáveis obtidas pelo sistema Vicon, extraímos o tempo real dos dois momentos do ciclo da marcha: foot strike e foot off. Os potenciais de campo locais (LFPs) obtidos durante os ensaios foram processados de modo a obter três componentes diferentes do signal: uma no domínio do tempo (LPC), e outras duas no domínio das frequências (TRFT-low and TRFT-high). Primeiramente, o sinal sofreu common average re-referencing e os ensaios e canais anormais foram removidos. Depois, para obtermos a LPC aplicamos um filtro Savitzky-Golay de segunda ordem. As outras duas componentes foram obtidas através da utilização de uma transformada de Fourier. A identificação da banda de frequência de TRFT-high e TRFT-low foi feita olhando para os valores de SNR ( Signal-to-noise ratio ). Para r263 TRFT-high estava entre os 3 e 15 Hz e TRFT-low entre os 39 e os 747 Hz. Para r328 TRFT-high estava entre os 3 e 21 Hz e TRFT-low entre os 105 e os 693 Hz. No final, para cada evento (foot strike, foot off e baseline) um total de 93 características foram extraídas sendo usadas para treinar um classificador de análise discriminante regularizado. Usando o método de validação cruzada, treinamos diferentes classificadores com diferentes combinações de parâmetros e selecionámos os valores de informação mútua como preditor do modelo que seria o ótimo. Toda a análise relativa à atividade neuronal foi feita com o auxílio do software Matlab®. Resultados & Discussão. Dos três componentes de sinal extraídos, TRFT-low demonstrou possuir a informação mais relevante em torno do momento de cada evento. O valor mais alto de informação mútua obtido para eventos relativos ao lado esquerdo da marcha foi de 0,617, considerando 1 o máximo. Relativamente aos eventos do lado direito, o desempenho do algoritmo foi 25-30% mais baixo, comparativamente. Facto este que pode ser justificado visto que o implante foi colocado no córtex sensório-motor direito. A continuação deste trabalho, requer mais ensaios e se possível num maior número de ratos. Conjuntamente, um algoritmo mais sofisticado e com uma maior precisão deve ser estudado. Também é importante continuar os esforços no sentido de perceber a dinâmica neuronal e de que maneira todos os sistemas se integram para garantir funções motoras num estado saudável de modo a otimizar a abordagem terapêutica em patologias que comprometem estes sistemas. Conclui-se dizendo que a ideia de uma interface cérebroespinal revela-se viável usando o modelo do rato, uma vez que é possível descodificar primitivas de marcha utilizando a atividade neuronal registada a partir do córtex sensório-motor. No entanto, isto foi apenas o primeiro passo no desenvolvimento de uma interface cérebroespinal completamente funcional.Introduction. Clinical assistance when it comes to nerve damage and spinal cord trauma falls short, and rehabilitation and recovery can sometimes be impossible due to the inability to self-regenerating. The brain spinal interface (BSI) is a concept that arises when exploring epidural electrical stimulation as a potential technique that is able to restore locomotion after a spinal cord injury. BSI’s in monkeys and humans have already been proven successful, however not in rats. The rat model is significantly different from the other ones, especially when it comes to its neural organization and complexity. For this reason we searched for proof that it is also possible to decode gait phases from neural activity in rat. This thesis was originated from the work done in a six month internship in Gregoire Courtine laboratory, based in Switzerland. Background. In rats the area that is known to encode information about movement is the primary sensorimotor cortex. This information is passed on through the descending neural pathway in the medulla and then on to the efferent nerves that trigger the necessary muscle groups that enforce motion and ensure time specific flexion and extension. In case of a spinal cord injury and subsequent lower limbs paralyses, the nerves are severed in such a way that this signal is lost. The BSI aims to capture gait related neural activity by implanting a 32-channel microelectrode array (Tucker-Davis Technologies (TDT), Alachua, FL, USA) in the right sensorimotor cortex and use classification methods to obtain quantitative prediction outputs. For the purposes of this thesis these outputs were the conditions of foot strike and foot off. Methods. We implanted two female Lewis rats designated by r263 and r328 and used a dedicated motion capture system (Vicon Motion Systems®) to record 3D kinematics and video. After sufficient recovery time after the surgery we proceeded to do the overground recordings. Each recording session consisted of one rat performing a full length runway walk walking quadrupely. We had 24 sessions for r263 and 31 for r328. From the Vicon files we extracted the real time of left foot off and left foot strike. The data sets containing the neural activity were pre-processed, and at the end we preserved 31 channels and extracted three different signal components (LPC, TRFT-low, TRFT-high). For each event (left foot off, left foot strike and baseline) we had a total of 93 extracted features that were used to train a regularized discriminant analysis classifier. Using cross-validation we trained different classifiers using different combinations of model parameters and choose the mutual information values to be our predictor for the optimum detection model. Results & Discussion. From the three extracted signal components, the TRFT-low showed the most information around the time of the event. The highest mutual information value found was of 0.617, considering that 1 was the highest possible number. We also built a decoder for predicting right side events, however it had a performance around 25-30 percent lower, comparatively to the left side prediction. This is justified by the fact that the implant was placed on the right sensorimotor cortex. The idea of a BSI, proves to be feasible on the rat model since it is possible to decode gait primitives using neural activity recorded from the sensorimotor cortex

Engagement of the rat hindlimb motor cortex across natural locomotor behaviors

Contrary to cats and primates, cortical contribution to hindlimb locomotor movements is not critical in rats. However, the importance of the motor cortex to regain locomotion after neurological disorders in rats suggests that cortical engagement in hindlimb motor control may depend on the behavioral context. To investigate this possibility, we recorded whole-body kinematics, muscle synergies, and hindlimb motor cortex modulation in freely moving rats performing a range of natural locomotor procedures. We found that the activation of hindlimb motor cortex preceded gait initiation. During overground locomotion, the motor cortex exhibited consistent neuronal population responses that were synchronized with the spatiotemporal activation of hindlimb motoneurons. Behaviors requiring enhanced muscle activity or skilled paw placement correlated with substantial adjustment in neuronal population responses. In contrast, all rats exhibited a reduction of cortical activity during more automated behavior, such as stepping on a treadmill. Despite the facultative role of the motor cortex in the production of locomotion in rats, these results show that the encoding of hindlimb features in motor cortex dynamics is comparable in rats and cats. However, the extent of motor cortex modulations appears linked to the degree of volitional engagement and complexity of the task, reemphasizing the importance of goal-directed behaviors for motor control studies, rehabilitation, and neuroprosthetics. © 2016 the authors

Cortical Neuromodulations Associated with Local and Global Strategies Used to Improve Performance in a Novel Brain Machine Interface Task

It is becoming increasingly evident that neurons used to control an external device (i.e. direct neurons) in a Brain Machine Interface (BMI) task modulate their activity to enhance performance in the task. Research has also shown that neurons not directly linked to the BMI (i.e. indirect neurons) also modulate their activity but their role and the extent of modulation is unclear. Understanding the role of these indirect neurons is especially important when considering nervous system injuries such as spinal cord injury (SCI) in order to optimize performance in the injured state. In an effort to increase our understanding of indirect neurons, I developed a novel bilateral perturbation-based BMI tilt task that can be executed by rats with and without SCI. Within this task, I demonstrate that both hemispheres are equally engaged pre and post-SCI, starting performance begins well above chance and both animal types increase task performance with practice. Uniquely, animals can achieve performance improvements without traditional water rewards and be divided into distinct learning and non-learning groups. As animals learned, information changes suggest that learning animals use a combination of global (direct and indirect neuron modulations) and local strategies (direct-neuron specific modulations), whereas non-learning animals primarily used primarily global strategies. Interestingly in learning animals, only direct neurons increased information by increasing firing rate and timing differences between select tilt types, while indirect neurons only modulated firing rate differences. Additionally, only these direct neurons increased redundancy with practice. These results show that the cortex selectively modulates regions associated with BMI use but that neural effects can be seen in regions as far as the opposite hemisphere.Ph.D., Biomedical Engineering -- Drexel University, 201

Interfacing a salamander brain with a salamander-like robot: Control of speed and direction with calcium signals from brainstem reticulospinal neurons

An important topic in designing neuroprosthetic devices for animals or patients with spinal cord injury is to find the right brain regions with which to interface the device. In vertebrates, an interesting target could be the reticulospinal (RS) neurons, which play a central role in locomotor control. These brainstem cells convey the locomotor commands to the spinal locomotor circuits that in turn generate the complex patterns of muscle contractions underlying locomotor movements. The RS neurons receive direct input from the Mesencephalic Locomotor Region (MLR), which controls locomotor initiation, maintenance, and termination, as well as locomotor speed. In addition, RS neurons convey turning commands to the spinal cord. In the context of interfacing neural networks and robotic devices, we explored in the present study whether the activity of salamander RS neurons could be used to control off-line, but in real time, locomotor speed and direction of a salamander robot. Using a salamander semi-intact preparation, we first provide evidence that stimulation of the RS cells on the left or right side evokes ipsilateral body bending, a crucial parameter involved during turning. We then identified the RS activity corresponding to these steering commands using calcium (Ca2+) imaging of RS neurons in an isolated brain preparation. Then, using a salamander robot controlled by a spinal cord model, we used the ratio of RS Ca2+ signals on left and right sides to control locomotion direction by modulating body bending. Moreover, we show that the robot locomotion speed can be controlled based on the amplitude of the Ca2+ response of RS cells, which is controlled by MLR stimulation strength as recently demonstrated in salamanders

Brain-controlled modulation of spinal circuits improves recovery from spinal cord injury.

The delivery of brain-controlled neuromodulation therapies during motor rehabilitation may augment recovery from neurological disorders. To test this hypothesis, we conceived a brain-controlled neuromodulation therapy that combines the technical and practical features necessary to be deployed daily during gait rehabilitation. Rats received a severe spinal cord contusion that led to leg paralysis. We engineered a proportional brain-spine interface whereby cortical ensemble activity constantly determines the amplitude of spinal cord stimulation protocols promoting leg flexion during swing. After minimal calibration time and without prior training, this neural bypass enables paralyzed rats to walk overground and adjust foot clearance in order to climb a staircase. Compared to continuous spinal cord stimulation, brain-controlled stimulation accelerates and enhances the long-term recovery of locomotion. These results demonstrate the relevance of brain-controlled neuromodulation therapies to augment recovery from motor disorders, establishing important proofs-of-concept that warrant clinical studies

Implantable Neural Probes for Brain-Machine Interfaces - Current Developments and Future Prospects

A Brain-Machine interface (BMI) allows for direct communication between the brain and machines. Neural probes for recording neural signals are among the essential components of a BMI system. In this report, we review research regarding implantable neural probes and their applications to BMIs. We first discuss conventional neural probes such as the tetrode, Utah array, Michigan probe, and electroencephalography (ECoG), following which we cover advancements in next-generation neural probes. These next-generation probes are associated with improvements in electrical properties, mechanical durability, biocompatibility, and offer a high degree of freedom in practical settings. Specifically, we focus on three key topics: (1) novel implantable neural probes that decrease the level of invasiveness without sacrificing performance, (2) multi-modal neural probes that measure both electrical and optical signals, (3) and neural probes developed using advanced materials. Because safety and precision are critical for practical applications of BMI systems, future studies should aim to enhance these properties when developing next-generation neural probes

Robot-driven epidural spinal cord stimulation compared with conventional stimulation in adult spinalized rats

Epidural stimulation to trigger locomotion is a promising treatment after spinal cord injury (SCI). Continuous stimulation during locomotion is the conventional method. To improve recovery, we designed and tested an innovative robot-driven epidural stimulation method, coupled with a trunk-based neurorobotic system. The system was tested in rats, and the results were compared with the results of the neurorobotic therapy combined with the conventional epidural stimulation method, and with robotic rehabilitation alone. The rats had better recovery after treatment with the robot-driven epidural stimulation than conventional stimulation or controls in our neurorobotic rehabilitation system.Ph.D., Biomedical Engineering -- Drexel University, 201

Suitability of the dorsal column nuclei for a neural prosthesis: functional considerations

The brainstem dorsal column nuclei (DCN) may be an ideal target for a future neural prosthesis to restore somatosensation in tetraplegic patients. We aimed to investigate the functional and structural characteristics of the DCN, with the overarching goal of determining their suitability as a somatosensory neural prosthetic target. First, we review the neuroanatomy of the DCN and surrounding nuclei, including the cuneate, gracile, external cuneate, X, and Z nuclei, which together comprise the DCN-complex. We reveal that the DCN are not organised to only process and relay tactile information, as is commonly thought, but instead are a complex sensorimotor integration and distribution hub, with diverse projection targets throughout the hindbrain and midbrain. Next, we sought to show that somatosensory signals arriving in the DCN are reproducible, and that they carry decodable information about the location and quality of somatosensory stimuli, which we propose are necessary conditions for a potential somatosensory neural prosthetic target. We record somatosensory-evoked signals from various locations across the surface of the DCN in 8-week-old anaesthetised male Wistar rats. We characterised somatosensory-evoked DCN surface signals and demonstrated that they have robust and reproducible high-frequency and low-frequency features within and across animals. Using a machine-learning approach, we developed a metric for evaluating the relevance of machine-learning inputs to target outputs, which we coined feature-learnability. Using feature-learnability allowed us to determine the DCN signal features that were most relevant to peripheral somatosensory events, which facilitated very high accuracy prediction of the location and quality of somatosensory events, from small numbers of features. This thesis supports the DCN as a potential somatosensory neural prosthetic target by: i) showing DCN connectivity with sensorimotor targets essential for movement modulation in conscious and non-conscious neural pathways; ii) determining DCN signal features that are most relevant to peripheral tactile and proprioceptive events. New knowledge about the most relevant DCN signal features may inform the development of biomimetic stimulus patterns designed to artificially activate the DCN in future neural prosthetic devices for restoring somatosensory feedback

A Robust Role for Motor Cortex

The function of mammalian motor cortex has remained a persistent mystery. There is a long history of research linking activity in this part of the brain with the control of voluntary movements but surprisingly there is an equally large body of evidence in non-human animals describing all kinds of complex behaviours that are not impaired when motor cortex is fully removed. What is the reason behind this discrepancy? What kind of movements are actually controlled by motor cortex? This thesis attempts to reconcile the many con icting views on the cortical control of movement and outline a strategy for investigating the teleology of this brain region. We start out by introducing a new set of hardware and software tools for neuroscience that aim to make it easier to study in detail more naturalistic motor behaviours in rodents. These tools allow the experimenter to quickly recon gure the physical and virtual environment of a behaviour task while simultaneously tracking in real-time ne-scale measurements of motor performance. (...)Sainsbury Wellcome Centre for Neural Circuits and Behaviour at University College LondonChampalimaud Foundatio