Topics for Master Theses

Beschreibung: Recent EEG literature has highlighted the functional significance of a so far largely neglected EEG signal component - the aperiodic signal. While robust evidence shows that this component undergoes age-related changes during resting-state recordings, emerging studies have demonstrated that it also modulates dynamically during visual working memory tasks.
This master thesis project aims to replicate these findings in young adults and to investigate how accounting for the aperiodic modulations affects established observations of occipital alpha and frontal theta oscillations. Furthermore, the project seeks to extend current knowledge by exploring whether incorporating the aperiodic signal can provide deeper insights into the mechanisms underlying age-related decline in visual working memory function.

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.
- van Engen, Q., Chau, G., Smith, A., Adam, K. C., Donoghue, T., & Voytek, B. (2024). Dissociating Contributions of Theta and Alpha Oscillations from Aperiodic Neural Activity in Human Visual Working Memory. bioRxiv, 2024-12.
- Adam, K. C., Robison, M. K., & Vogel, E. K. (2018). Contralateral delay activity tracks fluctuations in working memory performance. Journal of Cognitive Neuroscience, 30(9), 1229-1240.
Fukuda, K., Kang, M. S., & Woodman, G. F. (2016). Distinct neural mechanisms for spatially lateralized and spatially global visual working memory representations. Journal of neurophysiology, 116(4), 1715-1727.
Kontakt: Dr. Marius Troendle, E-Mail

Beschreibung: A multiverse analysis is a statistical approach that explores multiple analytical pathways for the same research question, making the variability of results across different analytical choices transparent. This method addresses the challenge of researcher degrees of freedom by systematically varying key assumptions and parameters to assess the robustness of findings. For EEG data sets, which are complex and sensitive to various preprocessing and analysis decisions, a multiverse analysis is particularly beneficial. It allows researchers to demonstrate how conclusions about brain activity might vary with different analytical strategies. This approach not only enhances the credibility and reproducibility of the findings but also helps to prevent publication of p-hacked results. The multiverse analysis will be performed on an EEG data set of a commonly used working memory task: the Sternberg task.

Literature
Master's Thesis Arne Hansen

Gelman, A., & Loken, E. (2013). The garden of forking paths: Why multiple comparisons can be a problem, even when there is no "fishing expedition" or "p-hacking" and the research hypothesis was posited ahead of time. Department of Statistics, Columbia University, 348(1-17), 3.

Sarma, A., Kale, A., Moon, M., Taback, N., Chevalier, F., Hullman, J., & Kay, M. (2021). multiverse: Multiplexing Alternative Data Analyses in R Notebooks [Preprint]. Open Science Framework. https://doi.org/10.31219/osf.io/yfbwm

Sternberg, S. (1966). High-Speed Scanning in Human Memory. Science, 153(3736):652-654

Kontakt: MSc Arne Hansen, E-Mail

Beschreibung: The hippocampus, a key region implicated in Alzheimer's disease (AD), comprises distinct subfields such as CA1, CA3, dentate gyrus, and subiculum. Emerging evidence suggests that specific subfields may show prominent outlier patterns in AD, reflecting varying levels of vulnerability. Furthermore, linking these patterns to cognitive decline and clinical severity could provide a deeper understanding of disease progression and heterogeneity.

This thesis focuses on deriving normative models for hippocampal subfield volumes using pre-extracted information from T1-weighted MRI scans and analyzing the deviation patterns obtained. The extensive data available from the UK Biobank will be used to establish a baseline for healthy aging, while deviations in these subfields will be examined in relation to AD using the OASIS-3 dataset. By comparing these baselines and deviations, the project will explore subfield-specific patterns of neurodegeneration and their potential links to cognitive decline and disease severity.

Further directions of the project include investigating sex differences in subfield vulnerability, examining brain asymmetry in atrophy patterns, and exploring the relationship between hippocampal subfield changes and AD subtypes. This study seeks to enhance our understanding of hippocampal subfield involvement in AD and its contribution to disease heterogeneity.

Literature:
La Joie, R., Perrotin, A., de La Sayette, V., Egret, S., Doeuvre, L., Belliard, S., et al. (2013). Hippocampal subfield volumetry in mild cognitive impairment, Alzheimer's disease, and semantic dementia. NeuroImage: Clinical, 3, 155-162. DOI: 10.1016/j.nicl.2013.08.007

Marquand, A. F., Rezek, I., Buitelaar, J., & Beckmann, C. F. (2016). Understanding heterogeneity in clinical cohorts using normative models: Beyond case-control studies. Biological Psychiatry, 80(7), 552-61. DOI: 10.1016/j.biopsych.2015.12.023

Verdi, S., Marquand, A. F., Schott, J. M., & Cole, J. H. (2021). Beyond the average patient: How neuroimaging models can address heterogeneity in dementia. Brain, 144(10), 2946-2953. DOI: 10.1093/brain/awab165


Kontakt: MSc Camille Elleaume, E-Mail