Localization of sources in electroencephalographic registers during working memory tasks

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2020-2021. Director: Albert Compte. Tutor: Santiago Marco.EEG source localization is a non-invasive imaging technique developed to locate the anatomical sources recorded at the scalp during an EEG recording. The reconstruction of the sources can be computed by solving the so-called inverse problem. This is an ill-posed problem which aims in estimating the sources that fit the recorded measurements. There exist several powerful commercial and academic software packages that cover multiple methods on data processing, source localization, and statistical analysis. In this work, the open-source MNE-Python package was selected as the working environment used to address the challenge of characterizing and locating neural activation. This study provides a pipeline with practical steps on the EEG source localization technique. The results obtained in this project have been validated by experts in the Theoretical Neurobiology and Computational Neuroscience fields In this project, the EEG source localization has been computed over a group of encephalitic patients and a control group. The two groups had shown differences regarding the electrical activity in a working memory trial. This study aimed in localizing the anatomical brain regions that were responsible of the electrical differences. It has been observed that instants before the stimulus, the activated sites between control groups and encephalitic groups differ. In the case of the control group, the activated region was located at the frontal lobe of the left hemisphere. Whereas, in the case of the encephalitic group the activated region was located at the temporal lobe of the right hemisphere

A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD)

Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities

Source reconstruction of the neural correlates of ongoing pain using magnetoencephalography

Pain is a pervasive, complex, and subjective phenomenon that can be described by many features and researched using many paradigms; chronic pain has a significant impact on the quality of life of patients experiencing it and constitutes a large burden on the National Health Service. Discovering neural biomarkers for ongoing pain and pain sensitivity has the potential to elucidate underlying mechanisms, evaluate therapy effectiveness, and identify regions of interest within the brain for further study or intervention; something that is possible with functional imaging of brain activity. Magnetoencephalography (MEG) is a non-invasive technique that records brain activity through magnetic fields unobstructed by tissue of the head. This thesis utilises modern source reconstruction of MEG data to explore brain activity that characterises tonic pain conditions, and explores the future of tonic pain research by evaluating the utility of the PATHWAY Contact Heat Evoked Potentials Stimulator (CHEPS) – a tool used both as an experimental pain stimulus, and a clinical evaluation method in chronic pain – in current and future MEG research. A systematic review of studies exploring the CHEPS and MEG, which highlights the paucity of the literature combining the two despite the potential benefits of each, is presented within. Study one investigates the brain activity changes resulting from paraesthesia-based Spinal Cord Stimulation for chronic pain: significant enhancements in synchrony for theta and delta frequency bands during SCS-on resting-state are demonstrated, and a significant reduction in Somatosensory Evoked Potential (SSEP) power spectra in the SCS-on condition – providing evidence that conventional SCS influences resting and ascending processing in the brain, but does not necessarily suppress the field strength of SSEPs. Study two compared the neural activity of participants with high and low pain sensitivity during the Cold Pressor Test, and identifies regions of interest for future study. Study three is a methodological chapter which attempts to mitigate the methodological challenges involved in utilising the PATHWAY CHEPS in MEG research: The thorough exploration of independent component analysis, signal space separation and beamforming parameters demonstrates that it is possible to suppress the artefacts generated by the non-fMRI compatible CHEPS’ thermode with the application of signal attenuation techniques, but only in an empty room dataset; the implications of this for future research are discussed

Gedächtniskonsolidierung im Schlaf: über die Funktion neuronaler Oszillationen für die Hirnplastizität.

Why do we sleep? Loosing consciousness makes us completely vulnerable to any dangers of the environment for a third of our life time and must therefore yield a critical evolutionary advantage. A likely core function of sleep is the regulation of neuronal plasticity. The absence of interfering conscious information processing sets the stage for the basic maintenance of synaptic homeostasis to the complex reorganization and consolidation of memories. However, the underlying neuronal mechanisms subserving these processes are still largely unknown. The aim of this thesis is to further elucidate the essential role of sleep-specific neuronal oscillations in brain plasticity. In a multimodal neuroscientific approach, non-invasive imaging methods (EEG and fMRI) and brain stimulation techniques (TMS and tDCS) are combined in a series of empirical studies to investigate how slow oscillations and sleep spindles are influenced by and in turn mediate plastic changes in the sleeping brain