EpiGauss : caracterização espacio-temporal da actividade cerebral em epilepsia

Doutoramento em Engenharia ElectrotécnicaA epilepsia é uma patologia cerebral que afecta cerca de 0,5% da população mundial. Nas epilepsias focais, o principal objectivo clínico é a localização da zona epileptogénica (área responsável pelas crises), uma informação crucial para uma terapêutica adequada. Esta tese é centrada na caracterização da actividade cerebral electromagnética do cérebro epiléptico. As contribuições nesta área, entre a engenharia e neurologia clínica, são em duas direcções. Primeiro, mostramos que os conceitos associados às pontas podem ser imprecisos e não ter uma definição objectiva, tornando necessária uma reformulação de forma a definir uma referência fiável em estudos relacionados com a análise de pontas. Mostramos que as características das pontas em EEG são estatisticamente diferentes das pontas em MEG. Esta constatação leva a concluir que a falta de objectividade na definição de ponta na literatura pode induzir utilizações erradas de conceitos associados ao EEG na análise de MEG. Também verificamos que o uso de conjuntos de detecções de pontas efectuadas por especialistas (MESS) como referência pode fornecer resultados enganadores quando apenas baseado em critérios de consenso clínico, nomeadamente na avaliação da sensibilidade e especificidade de métodos computorizados de detecção de pontas Em segundo lugar, propomos o uso de métodos estatísticos para ultrapassar a falta de precisão e objectividade das definições relacionadas com pontas. Propomos um novo método de neuroimagem suportado na caracterização de geradores electromagnéticos – EpiGauss – baseado na análise individual dos geradores de eventos do EEG que explora as suas estruturas espacio-temporais através da análise de “clusters”. A aplicação de análise de “clusters” à análise geradores de eventos do EEG tem como objectivo usar um método não supervisionado, para encontrar estruturas espacio-temporais dps geradores relevantes. Este método, como processo não supervisionado, é orientado a utilizadores clínicos e apresenta os resultados sob forma de imagens médicas com interpretação similar a outras técnicas de imagiologia cerebral. Com o EpiGauss, o utilizador pode determinar a localização estatisticamente mais provável de geradores, a sua estabilidade espacial e possíveis propagações entre diferente áreas do cérebro. O método foi testado em dois estudos clínicos envolvendo doentes com epilepsia associada aos hamartomas hipotalâmicos e o outro com doentes com diagnóstico de epilepsia occipital. Em ambos os estudos, o EpiGauss foi capaz de identificar a zona epileptogénica clínica, de forma consistente com a história e avaliação clínica dos neurofisiologistas, fornecendo mais informação relativa à estabilidade dos geradores e possíveis percursos de propagação da actividade epileptogénica contribuindo para uma melhor caracterização clínica dos doentes. A conclusão principal desta tese é que o uso de técnicas não supervisionadas, como a análise de “clusters”, associadas as técnicas não-invasivas de EMSI, pode contribuir com um valor acrescido no processo de diagnóstico clínico ao fornecer uma caracterização objectiva e representação visual de padrões complexos espaciotemporais da actividade eléctrica epileptogénica.Epilepsy is a brain pathology that affects 0.5% of the world population. In focal epilepsies, the main clinical objective is the localization of the epileptogenic zone (brain area responsible for the epileptic seizures – EZ), a key information to decide an adequate therapeutic approach. This thesis is centred on electromagnetic activity characterization of the epileptic brain. Our contribution to this boundary area between engineering and clinical neurology is two-folded. First we show that spike related clinical concepts can be unprecise and some do not have objective definitions making necessary a reformulation in order to have a reliable reference in spike related studies. We show that EEG spike wave quantitative features are statistically different from their MEG counterparts. This finding leads to the conclusion that the lack of objective spike feature definitions in the literature can induce the wrong usage of EEG feature definition in MEG analysis. We also show that the use of multi-expert spike selections sets (MESS) as gold standard, although clinically useful, may be misleading whenever defined solely in terms of clinical agreement criteria, namely as references for automatic spike detection algorithms in sensitivity and specificity method analysis. Second, we propose the use of statistical methods to overcome some lack of precision and objectivity in spike related definitions. In this context, we propose a new ElectroMagnetic Source Imaging (EMSI) method – EpiGauss – based on cluster analysis that explores both spatial and temporal information contained in individual events sources analysis characterisation. This automatic cluster method for the analysis of spike related electric generators based in EEG is used to provide an unsupervised tool to find their relevant spatio-temporal structures. This method enables a simple unsupervised procedure aimed for clinical users and presents its results in an intuitive representation similar to other brain imaging techniques. With EpiGauss, the user is able to determine statistically probable source locations, their spatial stability and propagation patterns between different brain areas. The method was tested in two different clinical neurophysiology studies, one with a group of Hypothalamic Hamartomas and another with a group of Occipital Epilepsy patients. In both studies EpiGauss identified the clinical epileptogenic zone, consistent with the clinical background and evaluation of neurophysiologists, providing further information on stability of source locations and their probable propagation pathways that enlarges their clinical interpretation. This thesis main conclusion is that the use of unsupervised techniques, such as clustering, associated with EMSI non-invasive techniques, can bring an added value in clinical diagnosis process by providing objective and visual representation of complex epileptic brain spatio-temporal activity patterns

Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging

Magnetoencephalography for the investigation and diagnosis of Mild Traumatic Brain Injury

Mild Traumatic Brain Injury (mTBI), (or concussion), is the most common type of brain injury. Despite this, it often goes undiagnosed and can cause long term disability—most likely caused by the disruption of axonal connections in the brain. Objective methods for diagnosis and prognosis are needed but clinically available neuroimaging modalities rarely show structural abnormalities, even when patients suffer persisting functional deficits. In the past three decades, new powerful techniques to image brain structure and function have shown promise in detecting mTBI related changes. Magnetoencephalography (MEG), which measures electrical brain activity by detecting magnetic fields outside the head generated by neural currents, is particularly sensitive and has therefore gained interest from researchers. Numerous studies are proposing abnormal low-frequency neural oscillations and functional connectivity—the statistical interdependency of signals from separate brain regions—as potential biomarkers for mTBI. However, typically small sample sizes, the lack of replication between groups, the heterogeneity of the cohorts studied, and the lack of longitudinal studies impedes the adoption of MEG as a clinical tool in mTBI management. In particular, little is known about the acute phase of mTBI. In this thesis, some of these gaps will be addressed by analysing MEG data from individuals with mTBI, using novel as well as conventional methods. The potential future of MEG in mTBI research will also be addressed by testing the capabilities of a wearable MEG system based on optically pumped magnetometers (OPMs). The thesis contains three main experimental studies. In study 1, we investigated the signal dynamics underlying MEG abnormalities, found in a cohort of subjects scanned within three months of an mTBI, using a Hidden Markov Model (HMM), as growing evidence suggests that neural dynamics are (in part) driven by transient bursting events. Applying the HMM to resting-state data, we show that previously reported findings of diminished intrinsic beta amplitude and connectivity in individuals with mTBI (compared to healthy controls) can be explained by a reduction in the beta-band content of pan-spectral bursts and a loss in the temporal coincidence of bursts respectively. Using machine learning, we find the functional connections driving group differences and achieve classification accuracies of 98%. In a motor task, mTBI resulted in reduced burst amplitude, altered modulation of burst probability during movement and decreased connectivity in the motor network. In study 2, we further test our HMM-based method in a cohort of subjects with mTBI and non-head trauma—scanned within two weeks of injury—to ensure specificity of any observed effects to mTBI and replicate our previous finding of reduced connectivity and high classification accuracy, although not the reduction in burst amplitude. Burst statistics were stable over both studies—despite data being acquired at different sites, using different scanners. In the same cohort, we applied a more conventional analysis of delta-band power. Although excess low-frequency power appears to be a promising candidate marker for persistently symptomatic mTBI, insufficient data exist to confirm this pattern in acute mTBI. We found abnormally high delta power to be a sensitive measure for discriminating mTBI subjects from healthy controls, however, similarly elevated delta amplitude was found in the cohort with non-head trauma, suggesting that excess delta may not be specific to mTBI, at least in the acute stage of injury. Our work highlights the need for longitudinal assessment of mTBI. In addition, there appears to be a need to investigate naturalistic paradigms which can be tailored to induce activity in symptom-relevant brain networks and consequently are likely to be more sensitive biomarkers than the resting state scans used to date. Wearable OPM-MEG makes naturalistic scanning possible and may offer a cheaper and more accessible alternative to cryogenic MEG, however, before deploying OPMs clinically, or in pitch-side assessment for athletes, for example, the reliability of OPM-derived measures needs to be verified. In the third and final study, we performed a repeatability study using a novel motor task, estimating a series of common MEG measures and quantifying the reliability of both activity and connectivity derived from OPM-MEG data. These initial findings—presently limited to a small sample of healthy controls—demonstrate the utility of OPM-MEG and pave the way for this technology to be deployed on patients with mTBI

Magnetoencephalography for the investigation and diagnosis of Mild Traumatic Brain Injury

Mild Traumatic Brain Injury (mTBI), (or concussion), is the most common type of brain injury. Despite this, it often goes undiagnosed and can cause long term disability—most likely caused by the disruption of axonal connections in the brain. Objective methods for diagnosis and prognosis are needed but clinically available neuroimaging modalities rarely show structural abnormalities, even when patients suffer persisting functional deficits. In the past three decades, new powerful techniques to image brain structure and function have shown promise in detecting mTBI related changes. Magnetoencephalography (MEG), which measures electrical brain activity by detecting magnetic fields outside the head generated by neural currents, is particularly sensitive and has therefore gained interest from researchers. Numerous studies are proposing abnormal low-frequency neural oscillations and functional connectivity—the statistical interdependency of signals from separate brain regions—as potential biomarkers for mTBI. However, typically small sample sizes, the lack of replication between groups, the heterogeneity of the cohorts studied, and the lack of longitudinal studies impedes the adoption of MEG as a clinical tool in mTBI management. In particular, little is known about the acute phase of mTBI. In this thesis, some of these gaps will be addressed by analysing MEG data from individuals with mTBI, using novel as well as conventional methods. The potential future of MEG in mTBI research will also be addressed by testing the capabilities of a wearable MEG system based on optically pumped magnetometers (OPMs). The thesis contains three main experimental studies. In study 1, we investigated the signal dynamics underlying MEG abnormalities, found in a cohort of subjects scanned within three months of an mTBI, using a Hidden Markov Model (HMM), as growing evidence suggests that neural dynamics are (in part) driven by transient bursting events. Applying the HMM to resting-state data, we show that previously reported findings of diminished intrinsic beta amplitude and connectivity in individuals with mTBI (compared to healthy controls) can be explained by a reduction in the beta-band content of pan-spectral bursts and a loss in the temporal coincidence of bursts respectively. Using machine learning, we find the functional connections driving group differences and achieve classification accuracies of 98%. In a motor task, mTBI resulted in reduced burst amplitude, altered modulation of burst probability during movement and decreased connectivity in the motor network. In study 2, we further test our HMM-based method in a cohort of subjects with mTBI and non-head trauma—scanned within two weeks of injury—to ensure specificity of any observed effects to mTBI and replicate our previous finding of reduced connectivity and high classification accuracy, although not the reduction in burst amplitude. Burst statistics were stable over both studies—despite data being acquired at different sites, using different scanners. In the same cohort, we applied a more conventional analysis of delta-band power. Although excess low-frequency power appears to be a promising candidate marker for persistently symptomatic mTBI, insufficient data exist to confirm this pattern in acute mTBI. We found abnormally high delta power to be a sensitive measure for discriminating mTBI subjects from healthy controls, however, similarly elevated delta amplitude was found in the cohort with non-head trauma, suggesting that excess delta may not be specific to mTBI, at least in the acute stage of injury. Our work highlights the need for longitudinal assessment of mTBI. In addition, there appears to be a need to investigate naturalistic paradigms which can be tailored to induce activity in symptom-relevant brain networks and consequently are likely to be more sensitive biomarkers than the resting state scans used to date. Wearable OPM-MEG makes naturalistic scanning possible and may offer a cheaper and more accessible alternative to cryogenic MEG, however, before deploying OPMs clinically, or in pitch-side assessment for athletes, for example, the reliability of OPM-derived measures needs to be verified. In the third and final study, we performed a repeatability study using a novel motor task, estimating a series of common MEG measures and quantifying the reliability of both activity and connectivity derived from OPM-MEG data. These initial findings—presently limited to a small sample of healthy controls—demonstrate the utility of OPM-MEG and pave the way for this technology to be deployed on patients with mTBI

Serotonergic modulation of the ventral pallidum by 5HT1A, 5HT5A, 5HT7 AND 5HT2C receptors

Introduction: Serotonin's involvement in reward processing is controversial. The large number of serotonin receptor sub-types and their individual and unique contributions have been difficult to dissect out, yet understanding how specific serotonin receptor sub-types contribute to its effects on areas associated with reward processing is an essential step. Methods: The current study used multi-electrode arrays and acute slice preparations to examine the effects of serotonin on ventral pallidum (VP) neurons. Approach for statistical analysis: extracellular recordings were spike sorted using template matching and principal components analysis, Consecutive inter-spike intervals were then compared over periods of 1200 seconds for each treatment condition using a student’s t test. Results and conclusions: Our data suggests that excitatory responses to serotonin application are pre-synaptic in origin as blocking synaptic transmission with low-calcium aCSF abolished these responses. Our data also suggests that 5HT1a, 5HT5a and 5HT7 receptors contribute to this effect, potentially forming an oligomeric complex, as 5HT1a antagonists completely abolished excitatory responses to serotonin application, while 5HT5a and 5HT7 only reduced the magnitude of excitatory responses to serotonin. 5HT2c receptors were the only serotonin receptor sub-type tested that elicited inhibitory responses to serotonin application in the VP. These findings, combined with our previous data outlining the mechanisms underpinning dopamine's effects in the VP, provide key information, which will allow future research to fully examine the interplay between serotonin and dopamine in the VP. Investigation of dopamine and serotonins interaction may provide vital insights into our understanding of the VP's involvement in reward processing. It may also contribute to our understanding of how drugs of abuse, such as cocaine, may hijack these mechanisms in the VP resulting in sensitization to drugs of abuse

Good scientific practice in MEEG Research: Progress and Perspectives

Good Scientific Practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization.For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be periodically revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research.This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges.Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons

A study of behavioural, cognitive and neural markers underlying visuospatial learning

Visuospatial (VS) learning is an education format noted for encouraging an individual to use visual exploration and their innate spatial ability in constructing a flexible ‘internal mental representation’ of three-dimensional information. Being a discipline reliant upon this informed consideration, VS methods have found particular application in anatomy education – with tangential evidence linking the inclusion of these methods to greater student understanding of anatomical concepts. Building on these findings, this thesis investigates: (i) the extent of individual and group learning benefits that accompany VS instruction within anatomy education, and (ii) a novel exploration of the cognitive and neuroscientific mechanisms that govern their success. To chart the success of instructional methodology in our reporting, we selected an array of academic performance and accompanying engagement indices. These items had been expressed by numerous modestly-powered prior studies, encompassing a diversity of anatomy cohorts, to be heightened under VS learning. Our initial work in Chapter 2 was therefore to determine if these effects were preserved when VS instruction was introduced within a substantially larger undergraduate anatomy cohort. Findings substantiated the wider applicability of this teaching method, with academic scores in each of the examined categories (didactic, spatial, and extrapolation) being superior to standard course delivery. Conflictingly, lower engagement and desire for VS inclusion was noted in the group receiving this instruction – leading us to attribute this to prevailing misconceptions about the nature of VS learning. In order to determine whether benefits found to characterise VS teaching in anatomy were universally applicable, or attributable to a myriad of demographic and cognitive factors, Chapter 3 explored variation in individual spatial capacity. Interestingly, the prevailing advantage of raw spatial aptitude in males was not associated with improved practical performance. This subsequently allowed a component of underlying psychological reasoning, namely visualisation (Vz) ability, to be highlighted as the clearest indicator of one’s ability to transfer raw spatial intelligence into practical VS understanding. Accompanying the misconceptions of VS learning reported in Chapter 2, participants were found to be poor estimators of their VS ability. Having established that spatial reasoning in anatomy possesses a physiological basis, we conducted a novel exploration of the neuroscientific mechanism evoked in VS learning using electroencephalography (EEG) technology (Chapter 4). This was evaluated by monitoring the neural signals of individuals engaged in two anatomical education workshops (featuring standard or VS instruction). No significant differences in oscillatory power accounted for the influence of VS instruction within any of the assessed frequency ranges (2-45Hz). Objective task outcomes were consistent with those in Chapter 2, finding a similarly elevated ability to address spatial questions following VS instruction. When placed together, the results of Chapters 2, 3 and 4 demonstrate the explicit advantages present for VS instruction in anatomy education. Though further work is required to isolate the specific underlying neural pathways, this appears linked to passive changes in how the human brain processes and later consolidates this information. Findings have important implications for advancing medical educational strategy (Appendix Descriptive Review), and wider understanding of the mechanisms that govern learning.Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 202

Neuroimaging of human motor control in real world scenarios: from lab to urban environment

The main goal of this research programme was to explore the neurophysiological correlates of human motor control in real-world scenarios and define mechanism-specific markers that could eventually be employed as targets of novel neurorehabilitation practice. As a result of recent developments in mobile technologies it is now possible to observe subjects' behaviour and monitor neurophysiological activity whilst they perform natural activities freely. Investigations in real-world scenarios would shed new light on mechanisms of human motor control previously not observed in laboratory settings and how they could be exploited to improve rehabilitative interventions for the neurologically impaired. This research programme was focussed on identifying cortical mechanisms involved in both upper- (i.e. reaching) and lower-limb (i.e. locomotion) motor control. Complementary results were obtained by the simultaneous recordings of kinematic, electromyographic and electrocorticographic signals. To study motor control of the upper-limb, a lab­based setup was developed, and the reaching movement of healthy young individuals was observed in both stable and unstable (i.e. external perturbation) situations. Robot-mediated force-field adaptation has the potential to be employed in rehabilitation practice to promote new skills learning and motor recovery. The muscular (i.e. intermuscular couplings) and neural (i.e. spontaneous oscillations and cortico­muscular couplings) indicators of the undergoing adaptation process were all symbolic of adaptive strategies employed during early stages of adaptation. The medial frontal, premotor and supplementary motor regions appeared to be the principal cortical regions promoting adaptive control and force modulation. To study locomotion control, a mobile setup was developed and daily life human activities (i.e. walking while conversing, walking while texting with a smartphone) were investigated outside the lab. Walking in hazardous environments or when simultaneously performing a secondary task has been demonstrated to be challenging for the neurologically impaired. Healthy young adults showed a reduced motor performance when walking in multitasking conditions, during which whole-brain and task-specific neural correlates were observed. Interestingly, the activity of the left posterior parietal cortex was predictive of the level of gait stability across individuals, suggesting a crucial role of this area in gait control and determination of subject specific motor capabilities. In summary, this research programme provided evidence on different cortical mechanisms operative during two specific scenarios for "real­world" motor behaviour in and outside the laboratory-setting in healthy subjects. The results suggested that identification of neuro-muscular indicators of specific motor control mechanisms could be exploited in future "real-world" rehabilitative practice