Towards Decoding of Depersonalisation Disorder Using EEG: A Time Series Analysis Using CDTW

Depersonalisation/derealisation refers to a transient psychological condition characterised by losing the sense of body ownership and feeling detached from the outside world. It is often accompanied by a lack of emotional responsiveness and sometimes memory fragmentation. Studies have shown the temporary occurrence of this condition among 34-70% of the general population during their life span. However, if the symptoms become consistent, they can be intolerable and can profoundly affect the quality of life in such an extent that it would be considered as one type of the dissociative disorders, depersonalisation disorder (DPD). Currently, there is no laboratory method to diagnose DPD, and studies have expressed a period of seven to 12 years for the correct diagnosis of DPD. We recently aimed to investigate DPD and its symptoms based on inexpensive and convenient electroencephalogram (EEG) neuroimaging technique, using calculation of event-related-potentials (ERPs) over the somatosensory cortex. We showed that DPD symptoms could be as a result of impairment in early (implicit) stages of information processing in the brain. We also introduced P45 as a potential electrophysiological biomarker to study DPD. In this paper, we first replicated our results and then used P45 as a feature to discriminate between individuals with high and low tendency to DPD symptoms. We used Continuous Dynamic Time Warping (CDTW) to address the possible time shift and distortion in the ERP signals and to reach better classification performance. We reached 85% accuracy (Kappa 0.7) using leave-one-subject-out cross-validation, which confirms the feasibility for discrimination between DPD patients and a control group using EEG signals

Multimodal Analysis of Cell Types in a Hypothalamic Node Controlling Social Behavior in Mice

The advent and recent advances of single-cell RNA sequencing (scRNA-seq) have yielded transformative insights into our understanding of cellular diversity in the central nervous system (CNS) with unprecedented detail. However, due to current experimental and computational limitations on defining transcriptomic cell types (T-types) and the multiple phenotypic features of cell types in the CNS, an integrative and multimodal approach should be required for the comprehensive classification of cell types. To this end, performing multimodal analysis of scRNA-seq in hypothalamus would be very beneficial in that hypothalamus, controlling homeostatic and innate survival behaviors which known to be highly conserved across a wide range of species and encoded in hard-wired brain circuits, is likely to display the more straightforward relationship between transcriptomic identity, axonal projections, and behavioral activation, respectively. In my dissertation, I have been focused on the cell type characterizations of a hypothalamic node controlling innate social behavior in mice, the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl). VMHvl only contains ~4,000 neurons per hemisphere in mice but due to its behavioral, anatomical, and molecular heterogeneity, which T-types in VMHvl are related to connectivity and behavioral function is largely unknown. In Chapter II, I described my main thesis work to perform scRNA-seq in VMHvl using two independent platforms: SMART-seq2 (~4,500 neurons sequenced) and 10x (~78,000 neurons sequenced). Specifically, 17 joint VMHvl T-types including several sexually dimorphic clusters were identified by canonical correlation analysis (CCA) in Seurat, and the majority of them were validated by multiplexed single-molecule FISH (seqFISH). Correspondence between transcriptomic identity, and axonal projections or behavioral activation, respectively, was also investigated. Immediate early gene analysis identified T-types exhibiting preferential responses to intruder males versus females but only rare examples of behavior-specific activation. Unexpectedly, many VMHvl T-types comprise a mixed population of neurons with different projection target preferences. Overall our analysis revealed that, surprisingly, few VMHvl T-types exhibit a clear correspondence with behavior-specific activation and connectivity. In Chapter III, I will discuss about future directions for a deeper and better understanding of VMHvl cell types. Briefly, my previous data from whole-cell patch clamp recording in VMHvl slices suggested that there were at least 4 distinct electrophysiological cell types (E-types). Additionally, two distinct neuromodulatory effects on VMHvl were observed (persistently activated by vasopressin/oxytocin vs. silenced by nitric oxide) by monitoring populational activities using two-photon Ca2+ imaging in slices. Based on the results from the first part and combined with advanced molecular techniques (e.g. Patch-seq and CRISPR-Cas9), we can further dissect out the cellular diversity in VMHvl and their functional implications.</p

Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age

While many structural and biochemical changes in the brain have been previously associated with aging, the findings concerning electrophysiological signatures, reflecting functional properties of neuronal networks, remain rather controversial. To try resolve this issue, we took advantage of a large population study (N=1703) and comprehensively investigated the association of multiple EEG biomarkers (power of alpha and theta oscillations, individual alpha peak frequency (IAF), the slope of 1/f power spectral decay), aging, and aging and cognitive performance. Cognitive performance was captured with three factors representing processing speed, episodic memory, and interference resolution. Our results show that not only did IAF decline with age but it was also associated with interference resolution over multiple cortical areas. To a weaker extent, 1/f slope of the PSD showed age-related reductions, mostly in frontal brain regions. Finally, alpha power was negatively associated with the speed of processing in the right frontal lobe, despite the absence of age-related alterations. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered when investigating the association between age, neuronal activity, and cognitive performance

Investigation of the central regulation of taste perception and metabolism in human and animal experiments

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Computational Approaches to Understanding Structure-Function Relationships at the Intersection of Cellular Organization, Mechanics, and Electrophysiology

The heart is a complex mechanical and electrical environment and small changes at the cellular and subcellular scale can have profound impacts at the tissue, organ, and organ system levels. The goal of this research is to better understand structure-function relationships at these cellular and subcellular levels of the cardiac environment. This improved understanding may prove increasingly important as medicine begins shifting toward engineered replacement tissues and organs. Specifically, we work towards this goal by presenting a framework to automatically create finite element models of cells based on optical images. This framework can be customized to model the effects of subcellular structure and organization on mechanical and electrophysiological properties at the cellular level and has the potential for extension to the tissue level and beyond. In part one of this work, we present a novel algorithm is presented that can generate physiologically relevant distributions of myofibrils within adult cardiomyocytes from confocal microscopy images. This is achieved by modelling these distributions as directed acyclic graphs, assigning a cost to each node based on observations of cardiac structure and function, and determining to minimum-cost flow through the network. This resulting flow represents the optimal distribution of myofibrils within the cell. In part two, these generated geometries are used as inputs to a finite element model (FEM) to determine the role the myofibrillar organization plays in the axal and transverse mechanics of the whole cell. The cardiomyocytes are modeled as a composite of fiber trusses within an elastic solid matrix. The behavior of the model is validated by comparison to data from combined Atomic Force Microscopy (AFM) and Carbon Fiber manipulation. Recommendations for extending the FEM framework are also explored. A secondary goal, discussed in part three of this work, is to make computational models and simulation tools more accessible to novice learners. Doing so allows active learning of complicated course materials to take place. Working towards this goal, we present CellSpark: a simulation tool developed for teaching cellular electrophysiology and modelling to undergraduate bioengineering students. We discuss the details of its implementation and implications for improved student learning outcomes when used as part of a discovery learning assignment

Discrete Cosine Transform for the Analysis of Essential Tremor

Essential tremor (ET) is the most common movement disorder. In fact, its prevalence is about 20 times higher than that of Parkinson's disease. In addition, studies have shown that a high percentage of cases, between 50 and 70%, are estimated to be of genetic origin. The gold standard test for diagnosis, monitoring and to differentiate between both pathologies is based on the drawing of the Archimedes' spiral. Our major challenge is to develop the simplest system able to correctly classify Archimedes' spirals, therefore we will exclusively use the information of the x and y coordinates. This is the minimum information provided by any digitizing device. We explore the use of features from drawings related to the Discrete Cosine Transform as part of a wider cross-study for the diagnosis of essential tremor held at Biodonostia. We compare the performance of these features against other classic and already analyzed ones. We outperform previous results using a very simple system and a reduced set of features. Because the system is simple, it will be possible to implement it in a portable device (microcontroller), which will receive the x and y coordinates and will issue the classification result. This can be done in real time, and therefore without needing any extra job from the medical team. In future works these new drawing-biomarkers will be integrated with the ones obtained in the previous Biodonostia study. Undoubtedly, the use of this technology and user-friendly tools based on indirect measures could provide remarkable social and economic benefits.We thank the Ministry of Business and Knowledge of the Government of Catalonia that partially supported this study through the Industrial Doctorates Plan to IA-E. We also thank the grant of Domus Vi Foundation "Kms para recordar," the programs of Basque Government, ETORTEK and IT115-16, the Gipuzkoa Goverment, Red Guipuzcoana de Ciencia, Tecnologia e Innovacion, and the Ministry of Science and Innovation for the TEC2016-77791-C04-R grant, which partially supported the study. Finally we would like to thank reviewers for their detailed and helpful comments to the manuscript

Auditory and cognitive performance in elderly musicians and nonmusicians

Musicians represent a model for examining brain and behavioral plasticity in terms of cognitive and auditory profile, but few studies have investigated whether elderly musicians have better auditory and cognitive abilities than nonmusicians. The aim of the present study was to examine whether being a professional musician attenuates the normal age-related changes in hearing and cognition. Elderly musicians still active in their profession were compared with nonmusicians on auditory performance (absolute threshold, frequency intensity, duration and spectral shape discrimination, gap and sinusoidal amplitude-modulation detection), and on simple (short-term memory) and more complex and higher-order (working memory [WM] and visuospatial abilities) cognitive tasks. The sample consisted of adults at least 65 years of age. The results showed that older musicians had similar absolute thresholds but better supra-threshold discrimination abilities than nonmusicians in four of the six auditory tasks administered. They also had a better WM performance, and stronger visuospatial abilities than nonmusicians. No differences were found between the two groups\u2019 short-term memory. Frequency discrimination and gap detection for the auditory measures, and WM complex span tasks and one of the visuospatial tasks for the cognitive ones proved to be very good classifiers of the musicians. These findings suggest that life-long music training may be associated with enhanced auditory and cognitive performance, including complex cognitive skills, in advanced age. However, whether this music training represents a protective factor or not needs further investigation