The work developed in this thesis focusses on the electrical activity of the heart, from the modeling of the action potential originating from cardiac cells and propagating through the heart, as well as its electrical manifestation at the body surface. The study is divided in two main parts: modeling the action potential, and numerical simulations. For modeling the action potential a dimensional and asymptotic analysis is done. The key advance in this part of the work is that this analysis gives the steps to reliably control the action potential. It allows predicting the time/space scales and speed of any action potential that is to say the shape of the action potential and its propagation. This can be done as the explicit relations on all the physiological constants are defined precisely. This method facilitates the integrative modeling of a complete human heart with tissue-specific ionic models. It even proves that using a single model for the cardiac action potential is enough in many situations. For efficient numerical simulations, a numerical method for solving the heart-torso coupling problem is explored according to a level set description of the domains. This is done in the perspective of using directly medical images for building computational domains. A finite element method is then developed to manage meshes not adapted to internal interfaces. Finally, an anisotropic adaptive remeshing methods for unstructured finite element meshes is used to efficiently capture propagating action potentials within complex, realistic two dimensional geometries.

The work developed in this thesis focusses on the electrical activity of the heart, from the modeling of the action potential originating from cardiac cells and propagating through the heart, as well as its electrical manifestation at the body surface. The study is divided in two main parts: modeling the action potential, and numerical simulations. For modeling the action potential a dimensional and asymptotic analysis is done. The key advance in this part of the work is that this analysis gives the steps to reliably control the action potential. It allows predicting the time/space scales and speed of any action potential that is to say the shape of the action potential and its propagation. This can be done as the explicit relations on all the physiological constants are defined precisely. This method facilitates the integrative modeling of a complete human heart with tissue-specific ionic models. It even proves that using a single model for the cardiac action potential is enough in many situations. For efficient numerical simulations, a numerical method for solving the heart-torso coupling problem is explored according to a level set description of the domains. This is done in the perspective of using directly medical images for building computational domains. A finite element method is then developed to manage meshes not adapted to internal interfaces. Finally, an anisotropic adaptive remeshing methods for unstructured finite element meshes is used to efficiently capture propagating action potentials within complex, realistic two dimensional geometries.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 5 uppsatser.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The detection of physiological signals from the Motor System (electromyographic signals), studied by electromyography, is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of electromyographic signals (EMG) that includes the identification and classification of Motor Unit Action Potential (MUAP) of EMG signals, is very import to help the therapist in the evaluation of motor disorders The EMG decomposition is a complex task due to the features of the EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date the majority of research on EMG decomposition utilizes EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively little research has been conducted using surface based EMG signals. As such this thesis aims to contribute to the clinical practice and Biofeedback therapies by presenting a system permitting the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of Differential Evolution and Spectral Clustering techniques. The developed system presented coherent results in: a) Identification of the number of Motor Units actives in the EMG signal; b) Presentation of the morphological patterns of MUAPs in the EMG signal; c) Identification of the firing sequence of the Motor Units. The Techniques utilized in this work have not yet been applied in the field of EMG decomposition and, in the end of this work, it was proved that they are excellent techniques for the surface EMG decomposition. The model proposed in this work is an advance in the research of decomposition of surface EMG signals. / A captação de sinais fisiológicos provenientes do Sistema Motor, que pode ser realizada pela eletromiografia, tem sido cada vez mais utilizada na prática clínica para auxiliar o terapeuta no diagnóstico de distúrbios motores. Desta forma, o processo de decomposição de sinais eletromiográficos (EMG), que inclui a identificação e classificação dos potenciais de ação de Unidade Motora (MUAP) de um sinal EMG de superfície é de extrema importância para a prática clínica, para auxiliar os profissionais na detecção de patologias do Sistema Motor. O processo de decomposição de um sinal EMG é uma tarefa complexa, pois as características de um sinal EMG dependem do tipo de eletrodo utilizado (intramuscular ou de superfície), do seu posicionamento em relação ao músculo, o nível de contração e o estado clínico do Sistema Neuromuscular do paciente. A maior parte dos sistemas de decomposição de sinais EMG são específicos para o sinal proveniente de eletrodos invasivos, devido às facilidades e vantagens em processar este tipo de sinal. Assim, poucos esforços foram concentrados no que tange à decomposição de sinais EMG de superfície. Neste contexto, este trabalho apresenta um sistema de decomposição de sinais EMG de superfície utilizando Modelos Ocultos de Markov, com o apoio das técnicas Evolução Diferencial e Agrupamento Espectral, no intuito de auxiliar a prática clínica e as terapias de Biofeedback. O sistema desenvolvido apresentou resultados coerentes no que tange a: a) Identificação da quantidade de Unidades Motoras ativas no sinal EMG; b) Apresentação dos padrões morfológicos de MUAPs presentes no sinal EMG; c) Identificação da seqüência de disparos das Unidades Motoras no sinal EMG analisado. As técnicas utilizadas neste trabalho ainda não tinham sido fruto de pesquisa na área de decomposição de sinais EMG, e se destacam como excelentes técnicas para processamento de sinal EMG de superfície. A arquitetura do modelo proposto constitui um avanço nas pesquisas de decomposição de eletromiografia de superfície. / Doutor em Ciências

Introdução. Nos últimos a função motora vem sendo associada com a atenuação sensitiva e de dor, logo antes, durante e apos a contração muscular. No entanto as vias anatômicas e funcionais deste fenômeno não são conhecidas. O objetivo deste estudo é o de criar um modelo animal e investigar o efeito da estimulação subliminar do córtex motor (ECM) no limiar nociceptivo e na atividade neuronal subcortical. Método. O limiar nociceptivo foi avaliado por teste plantar e reflexo de retirada da cauda antes e após o implante dos eletródios epidurais sobre o córtex motor da pata posterior orientado por mapa funcional na mesma cepa de ratos. Os mesmos testes foram repetidos antes, durante e após a ECM. Antagonismo sistêmico do por naloxona foi incluído neste protocolo para investigar a relação com mediação opióide. O registro neuronal multiunitário do núcleo centro mediano (CM) e ventral posterolateral (VPL) do tálamo e da substância periaqüeductal (SPM) foi realizado antes, durante e após ECM ipso e contralateral. Resultados. O implante per se não causou alterações no limiar nociceptivo. ECM induziu significativa antinocicepção seletiva na pata contralateral mas não na ipsolateral. Este efeito não mais foi observado 15 minutos após o término da estimulação. Nenhuma alteração motora e comportamental foi observada nos testes de campo aberto. A mesma estimulação no córtex sensitivo e parietal posterior não causou quaisquer alterações de limiar nociceptivo. Administração sistêmica de naloxone reverteu completamente o efeito antes observado com a ECM. O registro neuronal multiunitário evidenciou diminuição na atividade do CM durante e após a ECM contra e ipsolateral. O ritmo de disparos neuronais no VPL também mostrou diminuição apenas com a ECM ipsolateral. No entanto os neurônios da SPM aumentaram significativamente a freqüência de disparos com ECM ipsolateral e não com a contralateral. Conclusão. A ECM subliminar está relacionada consistentemente com a atenuação sensitiva durante o comportamento, provavelmente mediado por inibição talâmica e ativação da SPM. / Background. The motor function has been associated to sensory and pain attenuation, before during and shortly after the muscle activity. How ever the anatomical and functional basis of this phenomenon is not yet defined. The present study was designed to set an animal model and investigate the effect of subthreshold electrical stimulation of motor cortex (MCS) on pain threshold and neuron activity of thalamus and periaqüedutal gray. Method. Nociceptive thresholds of hind paws and the tail flick reflex were evaluated before and after surgical placement of epidural electrodes; before during and after electrical stimulation of motor cortex. Opioid antagonism was also included in this protocol in order to define neurotransmitter mediation of this process. Multiunit recording of thalamic median center (CM) and ventral posterolateral nuclei (VPL) and lateral periaqüedutal gray (SPM) were performed before and after electrical stimulation of ipso and contralateral motor cortex. Results. The procedure itself did not induce any threshold changes. MCS induced selective antinociception of contralateral paw, but no changes were detected in the nociceptive threshold of the ipsolateral side. This effect disappeared completely 15 minutes after the stimulation was ceased. No behavioral or motor impairment were observed during and after the stimulation session in the open field test. The same stimulation on sensory and posterior parietal cortex did not elicit any changes in behavioral and nociceptive tests. Systemic administration of naloxone completely reversed the previous observed antinociceptive effect. Multiunit recording evidenced decrease in spontaneous neuron firing in CM with short recovery time during ipso and contralateral MCS. Neuron activity in VPL was also significantly decreased during ipsolateral MCS but not with contralateral stimulation. How ever, neuron firing in SPM was significantly increased during and long after ipsolateral MCS but not with contralateral stimulation. Conclusion. Subthreshold MCS is consistently related to sensory attenuation during behavior, probably through thalamic inhibition and SPM activation.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-07T12:02:26Z No. of bitstreams: 1 danielepiresmagalhaesespiritosanto.pdf: 19885258 bytes, checksum: cc404305a80b23fea7d1a26415bf75bf (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-07T15:03:55Z (GMT) No. of bitstreams: 1 danielepiresmagalhaesespiritosanto.pdf: 19885258 bytes, checksum: cc404305a80b23fea7d1a26415bf75bf (MD5) / Made available in DSpace on 2017-03-07T15:03:55Z (GMT). No. of bitstreams: 1 danielepiresmagalhaesespiritosanto.pdf: 19885258 bytes, checksum: cc404305a80b23fea7d1a26415bf75bf (MD5) Previous issue date: 2014-08-29 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A arritmia ventricular maligna é uma das principais causas de morte no mundo. Muitas vezes o início de um episódio de arritmia está associado a uma excitação inoportuna no coração, também denominada extra-sístole, ou Potencial de Ação Espontâneo (PAE). O surgimento de PAEs pode estar relacionado a mudanças estruturais ou moleculares nos canais iônicos e a alterações no ciclo de cálcio intracelular. Anormalidades no ciclo de cálcio podem gerar transientes de cálcio espontâneos (TCEs) e estes podem desencadear Potenciais de Ação Espontâneos (PAEs). Estudos experimentais mostram que o surgimento de TCEs é mais frequente sob a estimulação β-Adrenérgica. Em experimentos recentes, notou-se que a presença de episódios de TCEs em cardiomiócitos saudáveis não desencadeia a geração de PAEs. Em contrapartida, em camundongos com a mutação de super expressão da bomba NCX (NaCa), PAEs foram observados em miócitos isolados e foram relacionados a episódios de TCEs. O principal objetivo deste trabalho foi a simulação da formação de PAEs utilizando modelos computacionais desenvolvidos para cardiomiócitos do ventrículo esquerdo de camundongos. Em particular os modelos computacionais foram capazes de reproduzir os cenários experimentais descritos acima, relacionando a geração de PAEs com a estimulação β-Adrenérgica e alterações de canais iônicos como a mutação NCX. Dessa forma, as simulações computacionais apresentadas neste trabalho permitem uma melhor compreensão dos complexos fenômenos associados a arritmias cardíacas. / Malignant ventricular arrhythmias are the major cause of death around the world. The beginning of an episode of arrhythmia is often associated with ectopic beats in the heart, also called extrasystole, or Spontaneous Action Potential (SAP). The development of SAP may be related to structural or molecular changes in ion channels and changes in intracellular calcium cycle. Abnormalities in calcium cycle can result in Spontaneous Calcium Transientes (SCT) and these can trigger SAP. Experimental studies show that the development of SCT is more common under β1-adrenergic stimulation. However, we found, in recent experiments, that the presence of episodes of SCT in healthy cardiomyocytes does not trigger the development of SAP. On the other hand, on mice presenting mutation of overexpression of NCX (NaCa) pump, SAP were observed in isolated cardiomyocytes and were related to episodes of SCT. Thus, we aimed, in this study, to simulate development of SAP using computational models developed for cardiomyocytes of left ventricle of mice. The computational models were able to reproduce the experimental scenarios described above, relating the development of SAP to the β-adrenergic stimulation and to the changes of ion channels as the NCX mutation. Therefore, the computational simulations showed in this work allow the best comprehension of the complex phenomena associated with cardiac arrhythmia.

Abstract Excitation-contraction coupling (ECC) is a process linking the electrical excitation of the muscle cell (myocyte) membrane to the contraction of the cell. In this study the possibilities of mathematical modeling were studied in current ECC research. Mathematical modeling was employed in two distinct ECC research areas, the enzymatic regulation of ECC and ECC during cardiac myocyte development. Despite the distinction, both of these are extremely complex biological systems characterized by diverse and partly contradictory reported experimental results, with a large part based on genetically engineered animal models. Novel mathematical models were developed for both of these research areas. The model of ventricular myocyte ECC with calmodulin-dependent protein kinase II (CaMKII)-mediated regulation faithfully reproduced the heart-rate dependent regulation of ECC. This regulation is thought to be the major effect of CaMKII-mediated regulation. The model of the embryonic ventricular myocyte provided the first comprehensive system analysis of how the embryonic heartbeat is generated at the cellular level. A similar type of model was also developed to show the notable differences between neonatal and adult ventricular myocyte ECC. The mathematical models of ECC presented in this study were further used to simulate ECC in genetically engineered myocytes. The cellular mechanisms of genetically engineered animal models could be better understood by employing mathematical modeling in parallel to experimental characterization of the animal model. It was found in simulations that the indirect consequences and the compensatory mechanisms induced by genetic modification may have a more significant effect on ECC than the direct consequences of the modification. To understand the overwhelming complexity of biological systems including ECC, competent system analysis tools, such as mathematical modeling, are required. The purpose of mathematical modeling is not to replace the experimental studies, but to provide a more comprehensive system analysis based on the experimental data. This system analysis will help in planning subsequent experiments needed to gain the most relevant information about the studied biological system.

The work developed in this thesis focusses on the electrical activity of the heart, from the modeling of the action potential originating from cardiac cells and propagating through the heart, as well as its electrical manifestation at the body surface. The study is divided in two main parts: modeling the action potential, and numerical simulations. For modeling the action potential a dimensional and asymptotic analysis is done. The key advance in this part of the work is that this analysis gives the steps to reliably control the action potential. It allows predicting the time/space scales and speed of any action potential that is to say the shape of the action potential and its propagation. This can be done as the explicit relations on all the physiological constants are defined precisely. This method facilitates the integrative modeling of a complete human heart with tissue-specific ionic models. It even proves that using a single model for the cardiac action potential is enough in many situations. For efficient numerical simulations, a numerical method for solving the heart-torso coupling problem is explored according to a level set description of the domains. This is done in the perspective of using directly medical images for building computational domains. A finite element method is then developed to manage meshes not adapted to internal interfaces. Finally, an anisotropic adaptive remeshing methods for unstructured finite element meshes is used to efficiently capture propagating action potentials within complex, realistic two dimensional geometries.

In the beginning of this thesis is a short introduction into plasmid DNA which is in the form of a vector used in molecular biology. Plasmids can be used in the form of fluorescent probes to measure changes in membrane potential. Into their structure is added a dye called fluorophore. As an important representative of this thesis is a fluorescent probe ASAP1 which contains green fluorescent protein whose response to the membrane potential change is the decrease in the intensity of emitted light. The aim of this thesis was to make chemical transfection of this plasmid into the HEK293 cell line and carry out its characterization. In the work is also described the design of a method for the analysis of the time course of changes in fluorescence depending on the cell membrane depolarisation. In the end of this thesis is also desribed realized experiment including the discussion of aquired results.

<p dir="ltr">The vagus nerve (VN) is the tenth cranial nerve that mediates most of the parasympathetic functions of the autonomic nervous system. The axons of the human VN comprise a mix of unmyelinated and myelinated axons, where ~80% of the axons are unmyelinated C fibers (Havton et al., 2021). Understanding that most VN axons are unmyelinated, there is a need to map the pathways of these axons to and from organs to understand their function(s) and whether C fiber morphology or signaling characteristics yield insights into their functions. Developing a machine learning model that detects and predicts the morphology of VN single fiber action potentials based on select fiber characteristics, e.g., diameter, myelination, and position within the VN, allows us to more readily categorize the nerve fibers with respect to their function(s). Additionally, the features of this machine learning model could help inform peripheral neuromodulation devices that aim to restore, replace, or augment one or more specific functions of the VN that have been lost due to injury, disease, or developmental abnormalities.</p><p dir="ltr">We designed and trained four types of Multi-layer Perceptron Artificial Deep Neural Networks (MLP-ANN) with 10,000 rat abdominal vagal C-fibers simulated via the peripheral neural interface model ViNERS. We analyze the accuracy of each MLP-ANN’s SFAP predictions by conducting normalized cross-correlation and morphology analyses with the ViNERS C-fiber SFAP counterparts. Our results showed that our best MLP predicted over 94% of the C-fiber SFAPs with strong normalized cross-correlation coefficients of 0.7 through 1 with the ViNERS SFAPs. Overall, this novel tool can use a C-fiber’s biophysical characteristics (i.e., fiber diameter size, fiber position on the x/y axis, etc.) to predict C-fiber SFAP morphology.</p>