Application of Higuchi fractal dimension and indepenedent component method in analysis of garden snail Br neuron bursting activity modulated by static magnetic field and ouabain.

Nelinearne i napredne statističke metode, pored linearnih metoda, zauzimaju sve značajnije mesto u analizi fizioloških signala, posebno u svetlu nelinearnog i haotičnog ponašanja bioloških sistema. Stoga je zajednička upotreba Higučijeve fraktalne dimenzije i analize nezavisnih komponentata (ICA), značajan i nov pristup u analizi signala a posebno u analizi aktivnosti jednog neurona. Najprepoznatljiviji tip spontane bioelektrične aktivnosti neurona beskičmenjaka i kičmenjaka jeste pojava akcionih potencijala u paketićima. U radu je po prvi put primenjen, jedinstven i inovativan pristup u razdvajanju komponenata spontane bioelektrične aktivnosti Br neurona vinogradskog puža i to na akcione potencijale (AP), intervale između akcionih potencijala (ISI) i tihe intervale bez aktivnosti (IBI) uz pomoć Higučijeve fraktalne dimenzije i aproksimacije Gausovim funkcijama. Taj metodološki pristup je omogućio praćenje uticaja konstantnog magnetnog polja i uabaina inhibitora Na+/K+ pumpe na promene u kompleksnosti spontane bioelektrične aktivnosti Br neurona. Sa druge strane, po prvi put je testirana upotreba ICA metode u različitim eksperimentalnim uslovima po AP, ISI i IBI komponentama spontane bioelektrične aktivnosti. Na taj način, u ovom radu demonstrirana je snaga zajedničke upotrebe navedenih metoda uz predlog da se proširi njihova upotreba za potrebe analize spontano aktivnih neurona različitih vrsta u fiziološkim i patološkim stanjima.Nonlinear and advanced statistical methods, in addition to linear methods, occupy a prominent place in the analysis of physiological signals, especially in light of the non-linear and chaotic behavior of biological systems. Therefore, the use of Higuchi fractal dimension and independent component analysis (ICA), reperesents a new approach to signal analysis, especially regarding the activities of one neuron. The most recognizable type of spontaneous bioelectric activity in neurons of invertebrates as well as vertebrates is the appearance of bursting activity. This study presents a unique and innovative approach to the separation of the components of spontaneous bioelectric activity of the garden snail Br neuron - action potential (AP), interspike interval (ISI) and interburst interval (IBI), by using Higuchi’s fractal dimension and Gaussian fitting functions. This methodological approach allows monitoring of the effect of static magnetic field and the inhibitor of the Na+/K+ pump, ouabain, on the changes in the complexity of the spontaneous bioelectric activity of the Br neuron. On the other hand, for the first time ICA method was tested in different experimental conditions on AP, ISI and IBI components of spontaneous bioelectric activity. This study demonstrates the power of the common use of the above mentioned methods and proposes to extend their use for the purpose of analyzing spontaneously active neurons of different species in physiological and patological conditions

Application of Higuchi fractal dimension and indepenedent component method in analysis of garden snail Br neuron bursting activity modulated by static magnetic field and ouabain.

Nelinearne i napredne statističke metode, pored linearnih metoda, zauzimaju sve značajnije mesto u analizi fizioloških signala, posebno u svetlu nelinearnog i haotičnog ponašanja bioloških sistema. Stoga je zajednička upotreba Higučijeve fraktalne dimenzije i analize nezavisnih komponentata (ICA), značajan i nov pristup u analizi signala a posebno u analizi aktivnosti jednog neurona. Najprepoznatljiviji tip spontane bioelektrične aktivnosti neurona beskičmenjaka i kičmenjaka jeste pojava akcionih potencijala u paketićima. U radu je po prvi put primenjen, jedinstven i inovativan pristup u razdvajanju komponenata spontane bioelektrične aktivnosti Br neurona vinogradskog puža i to na akcione potencijale (AP), intervale između akcionih potencijala (ISI) i tihe intervale bez aktivnosti (IBI) uz pomoć Higučijeve fraktalne dimenzije i aproksimacije Gausovim funkcijama. Taj metodološki pristup je omogućio praćenje uticaja konstantnog magnetnog polja i uabaina inhibitora Na+/K+ pumpe na promene u kompleksnosti spontane bioelektrične aktivnosti Br neurona. Sa druge strane, po prvi put je testirana upotreba ICA metode u različitim eksperimentalnim uslovima po AP, ISI i IBI komponentama spontane bioelektrične aktivnosti. Na taj način, u ovom radu demonstrirana je snaga zajedničke upotrebe navedenih metoda uz predlog da se proširi njihova upotreba za potrebe analize spontano aktivnih neurona različitih vrsta u fiziološkim i patološkim stanjima.Nonlinear and advanced statistical methods, in addition to linear methods, occupy a prominent place in the analysis of physiological signals, especially in light of the non-linear and chaotic behavior of biological systems. Therefore, the use of Higuchi fractal dimension and independent component analysis (ICA), reperesents a new approach to signal analysis, especially regarding the activities of one neuron. The most recognizable type of spontaneous bioelectric activity in neurons of invertebrates as well as vertebrates is the appearance of bursting activity. This study presents a unique and innovative approach to the separation of the components of spontaneous bioelectric activity of the garden snail Br neuron - action potential (AP), interspike interval (ISI) and interburst interval (IBI), by using Higuchi’s fractal dimension and Gaussian fitting functions. This methodological approach allows monitoring of the effect of static magnetic field and the inhibitor of the Na+/K+ pump, ouabain, on the changes in the complexity of the spontaneous bioelectric activity of the Br neuron. On the other hand, for the first time ICA method was tested in different experimental conditions on AP, ISI and IBI components of spontaneous bioelectric activity. This study demonstrates the power of the common use of the above mentioned methods and proposes to extend their use for the purpose of analyzing spontaneously active neurons of different species in physiological and patological conditions

Nonlinear dynamics and modeling of heart and brain signals

Ph.DDOCTOR OF PHILOSOPH

Development of nonlinear techniques based on time-frequency representation and information theory for the analysis of EEG signals to assess different states of consciousness

Electroencephalogram (EEG) recordings provide insight into the changes in brain activity associated with various states of anesthesia, epilepsy, brain attentiveness, sleep disorders, brain disorders, etc. EEG's are complex signals whose statistical properties depend on both space and time. Their randomness and non-stationary characteristics make them impossible to be described in an accurate way with a simple technique, requiring analysis and characterization involves techniques that take into account their non-stationarity. For that, new advanced techniques in order to improve the efficiency of the EEG based methods used in the clinical practice have to be developed. The main objective of this thesis was to investigate and implement different methods based on nonlinear techniques in order to develop indexes able to characterize the frequency spectrum, the nonlinear dynamics and the complexity of the EEG signals recorded in different state of consciousness. Firstly, a new method for removing peak and spike in biological signal based on the signal envelope was successfully designed and applied to simulated and real EEG signals, obtaining performances significantly better than the traditional adaptive filters. Then, several studies were carried out in order to extract and evaluate EEG measures based on nonlinear techniques in different contexts such as the automatic detection of sleepiness and the characterization and prediction of the nociceptive stimuli and the assessment of the sedation level. Four novel indexes were defined by calculating entropy of the Choi-Williams distribution (CWD) with respect to time or frequency, by using the probability mass function at each time instant taken independently or by using the probability mass function of the entire CWD. The values of these indexes tend to decrease, with different proportion, when the behavior of the signals evolved from chaos or randomness to periodicity and present differences when comparing EEG recorded in eyes-open and eyes-closed states and in ictal and non-ictal states. Measures obtained with time-frequency representation, mutual information function and correntropy, were applied to EEG signals for the automatic sleepiness detection in patients suffering sleep disorders. The group of patients with excessive daytime sleepiness presented more power in ¿ band than the group without sleepiness, which presented higher spectral and cross-spectral entropy in the frontal zone in d band. More complexity in the occipital zone was found in the group of patients without sleepiness in ß band, while a stronger nonlinear coupling between the occipital and frontal regions was detected in patients with excessive daytime sleepiness, in ß band. Time-frequency representation and non-linear measures were also used in order to study how adaptation and fatigue affect the event-related brain potentials to stimuli of different modalities. Differences between the responses to infrequent and frequent stimulation in different recording periods were found in series of averaged EEG epochs recorded after thermal, electrical and auditory stimulation. Nonlinear measures calculated on EEG filtered in the traditional frequency bands and in higher frequency bands improved the assessment of the sedation level. These measures were obtained by applying all the developed techniques on signals recorded from patients sedated, in order to predict the responses to pain stimulation such as nail bad compression and endoscopy tube insertion. The proposed measures exhibit better performances than the bispectral index (BIS), a traditional indexes used for hypnosis assessment. In conclusion, nonlinear measures based on time-frequency representation, mutual information functions and correntropy provided additional information that helped to improve the automatic sleepiness detection, the characterization and prediction of the nociceptive responses and thus the assessment of the sedation level.El registro de la señal Electroencefalografíca (EEG) proporciona información sobre los cambios en la actividad cerebral asociados con varios estados de la anestesia, la epilepsia, la atención cerebral, los trastornos del sueño, los trastornos cerebrales, etc. Los EEG son señales complejas cuyas propiedades estadísticas dependen del espacio y del tiempo. Sus características aleatorias y no estacionarias hacen imposible que el EEG se describa de forma precisa con una técnica sencilla requiriendo un análisis y una caracterización que implica técnicas que tengan en cuenta su no estacionariedad. Todo esto aumenta la necesidad de desarrollar nuevas técnicas avanzadas con el fin de mejorar la eficiencia de los métodos utilizados en la práctica clínica que son basados en el análisis de EEG. En esta tesis se han investigado y aplicado diferentes métodos utilizando técnicas no lineales con el fin de desarrollar índices capaces de caracterizar el espectro de frecuencias, la dinámica no lineal y la complejidad de las señales EEG registradas en diferentes estados de conciencia. En primer lugar, se ha desarrollado un nuevo algoritmo basado en la envolvente de la señal para la eliminación de ruido de picos en las señales biológicas. Este algoritmo ha sido aplicado a señales simuladas y reales obteniendo resultados significativamente mejores comparados con los filtros adaptativos tradicionales. Seguidamente, se han llevado a cabo varios estudios con el fin de extraer y evaluar las medidas de EEG basadas en técnicas no lineales en diferentes contextos. Se han definido nuevos índices mediante el cálculo de la entropía de la distribución de Choi-Williams (DCW) con respecto al tiempo o la frecuencia. Se ha observado que los valores de estos índices tienden a disminuir, en diferentes proporciones, cuando el comportamiento de las señales evoluciona de caótico o aleatorio a periódico. Además, se han encontrado valores diferentes de estos índices aplicados a la señal EEG registrada en diferentes estados. Diferentes medidas basadas en la representación tiempo-frecuencia, la función de información mutua y la correntropia se han aplicado al EEG para la detección automática de la somnolencia en pacientes que sufren trastornos del sueño. Se ha observado en la zona frontal que la potencia en la banda θ es mayor en los pacientes con somnolencia diurna excesiva, mientras que la entropía espectral y la entropía espectral cruzada en la banda δ es mayor en los pacientes sin somnolencia. En el grupo sin somnolencia se ha encontrado más complejidad en la zona occipital, mientras que el acoplamiento no lineal entre las regiones occipital y frontal ha resultado más fuerte en pacientes con somnolencia diurna excesiva, en la banda β. La representación tiempo-frecuencia y las medidas no lineales se han utilizado para estudiar cómo la adaptación y la fatiga afectan a los potenciales cerebrales relacionados con estímulos térmicos, eléctricos y auditivos. Analizando el promedio de varias épocas de EEG grabadas después de la estimulación, se han encontrado diferencias entre las respuestas a la estimulación frecuente e infrecuente en diferentes períodos de registro. Todas las técnicas que se han desarrollado, se han aplicado a señales EEG registradas en pacientes sedados, con el fin de predecir las respuestas a la estimulación del dolor. Un conjunto de medidas calculadas en señales EEG filtradas en diferentes bandas de frecuencia ha permitido mejorar la evaluación del nivel de sedación. Las medidas propuestas han presentado un mejor rendimiento comparado con el índice bispectral, un indicador de hipnosis tradicional. En conclusión, las medidas no lineales basadas en la representación tiempofrecuencia, funciones de información mutua y correntropia han proporcionado informaciones adicionales que contribuyeron a mejorar la detección automática de la somnolencia, la caracterización y predicción de las respuestas nociceptivas y por lo tanto la evaluación del nivel de sedación

The utility of latency and spectral analysis methods in evoked potential recordings from patients with hepatic encephalopathy

Evoked potentials (EPs) are small phasic potentials that are elicited in conjunction with sensory, motor and cognitive events. EP variables have been assessed in patients with cirrhosis but in general, methods were inadequately standardized and study populations incompletely characterized, leading to some studies questioning the validity of EP’s in diagnosing and monitoring hepatic encephalopathy, while other studies indicated that there is only a low positive yield with these investigations. Few studies have attempted tri-modal sensory and cognitive recordings. Recorded waveforms may demonstrate altered morphology while possessing broadly normal latencies. Since EP analysis is usually performed solely in the time domain, latency measurements do not therefore highlight morphological changes to the waveform and so abnormalities may go unreported. The aim of this study was twofold (i) to measure sensory and cognitive EPs in patients with cirrhosis in relation to their neuropsychiatric status and (ii) to address frequency content in relation to neuropsychiatric status by examining EPs with two spectral techniques, the Fourier Transform (FT) and the Power Spectral Density Estimate (PSD). Seventy patients with biopsy–proven cirrhosis were classified using clinical, psychometric and EEG criteria as unimpaired or as having minimal or overt hepatic encephalopathy (HE). Forty-eight healthy individuals served as controls. Visual (VEPs), brainstem auditory (BAEPs) somatosensory (SSEPs) and cognitive auditory (P300) EPs were recorded under standardized conditions. Significant latency differences were observed in sensory EPs between patients and controls with patient subgroups differences being less significant. The cognitive auditory P300 however, distinguished the patient subpopulations from one another. Frequency shifts are observed in all EP modalities with significant differences also occurring between patient groups. The sensitivity and specificity of the frequency-domain is comparable to that of the time-domain. Paired EP investigations analysed by latency indicate BAEP and P300 best discriminate any degree of encephalopathy; in the frequency domain it is the VEP combined with SEP and in the time-frequency domain it is the SEP. These findings suggest that EPs, when performed as a bank of multimodal tests and with spectral analysis, could provide a sensitive and specific method for the diagnosis and monitoring of hepatic encephalopathy

Neuromodulation and rehabilitation with brain-computer interfaces and Spinal Cord Stimulation

Consequences of spinal cord injury (SCI) are often severe and life-altering. Recovery of hand and arm function is consistently reported by SCI individuals as their greatest priority in terms of rehabilitation. Yet current strategies provide poor-to-modest outcomes. Innovation is required to improve traditional approaches to upper limb rehabilitation. The current view is that, due to the multi-faceted nature of SCI pathology, effective treatment will take a combinational approach. This thesis brings together two emerging and promising technologies—transcutaneous spinal cord stimulation (tSCS) and brain-computer interfaces (BCIs)—in order to judge their complimentary nature as tools for neurophysiological assessment and rehabilitation following SCI. There is growing evidence that cervical tSCS combined with intensive physical training can lead to lasting functional improvements in individuals with chronic SCI. The mechanisms underpinning tSCS-facilitated recovery, however, are still a matter of ongoing research, with conflicting reports of the impact of tSCS on cortical and spinal excitability. Evoked and reflexes have so far been the primary method of quantifying corticospinal excitability. The research undertaken in this thesis first explores electroencephalography (EEG) as a potential complementary method for assessing neuromodulation following tSCS. Due the novelty of the research, a preliminary investigation was undertaken to establish the feasibility of EEG monitoring during cervical tSCS. In a cohort of twenty-one able-bodied individuals, it was demonstrated that tSCS presented as low-latency, high-amplitude artefacts in EEG time series, at a rate equal to the stimulation frequency. Descriptive statistics were used to characterise the impact of tSCS, and judge the effectiveness of noise-attenuation techniques. Results showed that, with artefact-suppression, EEG recorded during tSCS could be returned to levels statistically similar to that of EEG acquired without tSCS interference. Additionally, it was established that neural components, such as the individual alpha frequency, were recoverable, demonstrating the feasibility of EEG as a tool for tracking cortical activity during tSCS. A subsequent study was conducted to investigate the neuromodulatory potential of tSCS on cortical activity. EEG was recorded during upper limb movements in 30 individuals both with and without concurrent cervical tSCS. Stimulation was delivered to the cervical region of the neck at intensities matching the individual’s highest tolerance without causing pain. It was found that cortical oscillatory dynamics were unaffected over a cohort of neurologically intact participants. However, a weak inhibitory effect was measured amoing individuals who received the highest stimulation intensities. A final study was devised to explore the potential of movement priming for tSCS-facilitated upper limb therapy in an individual with chronic AIS A cervical SCI. Movement priming was achieved by encouraging the participant to engage in repetitive bimanual hand movements with respect to their sensorimotor cortical activity as measured with EEG. A BCI provided real time feedback of the participant’s motor engagement in the form of a computer game, allowing them to actively engage regardless of impairment level. The participant first underwent an initial phase of 15 sessions of tSCS training alone followed by a second phase of 15 sessions of BCI priming and tSCS training. The participant’s strength and dexterity improved across both phases of the study. BCI priming may have contributed to an enhanced effect in some measures such as improved bilateral finger strength, but due to mixed results across functional measures no firm conclusions can be drawn. Nevertheless, the functional improvements lend greater credibility to cervical tSCS as a strategy for upper limb rehabilitation

Interdisciplinary cardiovascular health research: quantitative methods, heliogeophysical influence, demographics, and spatial trends

The study of cardiovascular health involves myriad scientific disciplines associated with diverse factors that contribute to health which further necessitates interdisciplinary endeavors. The current series of studies concern cardiovascular health from multiple interdisciplinary perspectives including biomedical signal processing, heliobiology, and public health, with a particular focus on quantitative methods throughout. The first study examined heart rate variability (HRV) derived from healthy and arrhythmia human electrocardiograph records. Data processed using wavelet entropy was quantitatively novel compared to traditional indices of HRV and also demonstrated significant accuracy for prediction and classification of arrhythmia. Next, heliobiological perspectives of cardiovascular physiology were examined beginning with experimental verification of previous correlational results. Artificially simulated geomagnetic impulses were associated with significant increases in participant HRV, particularly for frequency-based components. An additional pilot case study demonstrated similar effects for natural geomagnetic storms, while a nonlinear relationship was observed overall for HRV and geomagnetic activity. National data regarding mortalities due to hypertensive diseases in Canada from 1979 to 2009 were aggregated and investigated for periodic components and relationships with space weather parameters. Time-lagged linear correlations were observed along with conspicuously overlapping temporal trends, for which geomagnetic activity and solar wind pressures were identified as central sources of variance. Finally, three ecological cross-sectional studies investigated sub-provincial cardiovascular concerns across Canada at the health region level with emphasis on demography and spatial statistics. Hospitalizations due to myocardial infarction demonstrated significant relationships with socioeconomic and behavioral factors as well as significant geospatial clustering of high rates in Northern Ontario and Quebec. Aggregate rates of self-reported hypertension were similarly related to income and demographics with spatial results demonstrating high rates clustered in the North Atlantic, particularly Newfoundland. Furthermore, analyses for hypertension specifically among older adult Canadians (≥ 65 years of age) suggested that education was the strongest contributor at the health region level and there were no significant spatial relationships, in contrast to age-standardized rates. Various implications and other relevant associations are discussed throughout.Doctor of Philosophy (PhD) in Human Studie