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Beschreibung: Description: Since the first studies on electroencephalography (EEG) of Hans Berger, roughly one century ago, the main focus of human neurophysiological research was based around neural oscillations. However, recent studies pointed out the presence of the largely overlooked non-oscillatory - or aperiodic - signal component in human neurophysiology. Initially considered mere background noise, increasing evidence now suggests that the aperiodic signal contains meaningful physiological information and exhibits dynamic variability. However, the precise physiology and function of the aperiodic signal remains an open research question. The aim of this Bachelor thesis will be to explore the physiological and functional significance of the aperiodic signal in human neurophysiology, by investigating its systematic variations in response to specific task conditions and pharmacological manipulations.
Literature:
- Donoghue, T., Haller, M., Peterson, E. J., Varma, P., Sebastian, P., Gao, R., ... & Voytek, B. (2020). Parameterizing neural power spectra into periodic and aperiodic components. Nature neuroscience, 23(12), 1655-1665.
- Gyurkovics, M., Clements, G. M., Low, K. A., Fabiani, M., & Gratton, G. (2022). Stimulus-induced changes in 1/f-like background activity in EEG. Journal of Neuroscience, 42(37), 7144-7151.
- Lendner, J. D., Helfrich, R. F., Mander, B. A., Romundstad, L., Lin, J. J., Walker, M. P., ... & Knight, R. T. (2020). An electrophysiological marker of arousal level in humans. Elife, 9, e55092.
- Waschke, L., Donoghue, T., Fiedler, L., Smith, S., Garrett, D. D., Voytek, B., & Obleser, J. (2021). Modality-specific tracking of attention and sensory statistics in the human electrophysiological spectral exponent. Elife, 10, e70068.
Kontakt: Dr. Marius Troendle, E-Mail
Beschreibung: Multivariate EEG analyses are becoming increasingly popular in neuroscience and clinical applications due to their ability to capture the spatiotemporal dynamics of brain activity more comprehensively than univariate methods. While traditional EEG analyses (e.g., time-frequency analyses) focus on isolated electrodes or limited features, multivariate approaches leverage correlations, network dynamics, and high-dimensional data to uncover more nuanced insights.
Literature
Cohen MX. A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiology. Neuroimage. 2022 Feb 15;247:118809. doi: 10.1016/j.neuroimage.2021.118809. Epub 2021 Dec 11. PMID: 34906717.
Kontakt: MSc Dawid Strzelczyk, E-Mail
Beschreibung: In neuroscience, it is generally assumed that brain rhythms reflect the neural processes required to perform the cognitive operations demanded by the experiment task. This assumption has led to various theories regarding the role of gamma oscillations, proposing fundamental functions such as information binding or higher-order cognitive functions like memory and attention, among others. However, it remains unclear as to why gamma activity variation in the visual cortex primarily depends on stimuli properties such as the contrast and spatial frequency of grating stimuli. It has been reported that perception of gratings with high spatial frequency entails eye movements across the contrast border. Given that the brain continuously monitors oculomotor action, it may be crucial to consider these eye movements when investigating gamma oscillations.
Literature
Ray, S., & Maunsell, J. H. R. (2015). Do gamma oscillations play a role in cerebral cortex? Trends in Cognitive Sciences, 19(2), 78-85. https://doi.org/10.1016/j.tics.2014.12.002
Sauseng, P., & Klimesch, W. (2008). What does phase information of oscillatory brain activity tell us about cognitive processes?. Neuroscience & Biobehavioral Reviews, 32(5), 1001-1013.
Van Pelt, S., & Fries, P. (2013). Visual stimulus eccentricity affects human gamma peak frequency. NeuroImage, 78, 439?447. https://doi.org/10.1016/j.neuroimage.2013.04.040
Kontakt: MSc Arne Hansen, E-Mail
Beschreibung: Depressive disorder (DD) represents a significant public health concern, as it affects millions of people and is the leading cause of disability globally. It most often occurs in adolescence, during which various physiological, psychological, and social changes heighten vulnerability. DD during adolescence is particularly troubling due to its impact on developmental milestones, academic performance, and social relationships. The disorder exhibits a notable heterogeneity, characterized by varying symptoms, severity, and outcomes across individuals, which complicates treatment efforts and prevention of relapses. Traditional treatment methods, while effective for some, do not cater to the individualized nature of psychiatric disorders, underscoring the urgent need for novel measurements and therapies that can address this variability. One such novel measurement are specific biomarkers, e.g. Frontal Alpha Asymmetry (FAA) as a basis for tailored treatment approaches in DD. However, there are inconsistencies in the research on FAA and DD. Numerous studies struggled to replicate the original findings and discrepancies in methodological approaches, as well as uncontrolled confounding factors such as age, gender and education further cloud the association between FAA and DD.
Literature
Allen, J. J. B., Coan, J. A., & Nazarian, M. (2004). Issues and assumptions on the road from raw signals to metrics of frontal EEG asymmetry in emotion. Biological Psychology, 67(1-2), 183-218. https://doi.org/10.1016/j.biopsycho.2004.03.007
Kolodziej, A., Magnuski, M., Ruban, A., & Brzezicka, A. (2021). No relationship between frontal alpha asymmetry and depressive disorders in a multiverse analysis of five studies. ELife, 10, e60595. https://doi.org/10.7554/eLife.60595
Kontakt: MSc Arne Hansen, E-Mail
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