Topics for Bachelor Theses

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
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Eingabedatum: 15.01.2025
Kontakt: MSc Arne Hansen, 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
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Eingabedatum: 15.01.2025
Kontakt: MSc Arne Hansen, E-Mail

Beschreibung: Alzheimer's disease (AD) is the most common form of dementia nowadays and poses a number of challenges due to its complex and heterogeneous nature. While advances in machine learning offer promising prospects for understanding the disease complexities and its evolution, conventional methods often overlook neuroanatomical heterogeneity between individuals, relying on case-control analyses. This thesis explores the promise of normative modeling in comparison with conventional methods for understanding disease and capturing the individual variability inherent in neurodegenerative diseases, with the aim of improving the accuracy of diagnosis and enhancing our understanding of the disease process. Literature: Marquand AF, Rezek I, Buitelaar J, Beckmann CF. Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies. Biol Psychiatry. 2016 Oct 1;80(7):552-61. Verdi S, Marquand AF, Schott JM, Cole JH. Beyond the average patient: how neuroimaging models can address heterogeneity in dementia. Brain. 2021 Nov 29;144(10):2946-53. Pinaya WHL, Scarpazza C, Garcia-Dias R, Vieira S, Baecker L, F da Costa P, et al. Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer?s disease in a cross-sectional multi-cohort study. Sci Rep. 2021 Aug 3;11(1):15746.
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Eingabedatum: 15.01.2025
Kontakt: MSc Camille Elleaume, E-Mail

Beschreibung: Background Traditional diagnostic approaches in psychology (e.g., ICD-11 and DSM-V) often categorize disorders as isolated, independent constructs. While these systems have been instrumental in standardizing diagnoses, they face several limitations. Issues such as comorbidity, symptom heterogeneity within disorders, and the inability to account for overlapping features challenge the validity of categorical diagnostic systems. In contrast, dimensional or transdiagnostic approaches offer a more integrative perspective by identifying shared features across disorders. These models seek to move beyond categorical boundaries, creating frameworks that better explain mental health phenomena and their underlying mechanisms. Prominent approaches include the Research Domain Criteria (RDoC), Hierarchical Taxonomy of Psychopathology (HiTOP), and network models. Objectives This bachelor's thesis aims to provide comprehensive literature research of dimensional models of psychopathology and explore their relevance to neuroscience. The project will focus on several key objectives: - Detailed overview of the dimensional models (structure, theoretical basis, development methods, relevance) - Outline of evidence (empirical research validating the models) in support of the models, as well as their advantages over traditional systems; address limitations - Recapitulation of the application of the models (e.g. in research, clinical integration, etc.) - In-depth review of their relevance and application in neuroscience, e.g., studies linking dimensional constructs to brain imaging, genetics, cognitive neuroscience Formalities This Bachelor's thesis must be written in English - strong English language skills are a prerequisite. The project is designed to be completed within one semester.
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Eingabedatum: 15.01.2025
Kontakt: MSc Ines Engler, E-Mail

Beschreibung: Many neurodevelopmental conditions, such as autism and ADHD, are more commonly diagnosed in males than in females. This disparity may, in part, result from diagnostic criteria that are biased toward male presentations, leading to the underdiagnosis or misdiagnosis of females. At the same time there are neurobiological differences between males and females that may also contribute to such difference. The thesis should provide an overview of sex differences in the diagnosis, presentation and neurobiology of neurodevelopmental conditions and discuss the implications for clinical and research practice.
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Eingabedatum: 15.01.2025
Kontakt: Dr. Dorothea Floris, E-Mail

Beschreibung: Alzheimer's disease (AD) is a neurocognitive disorder that results in cognitive impairment. Onset of AD is characterised by memory impairment and the neuroanatomical differences. However, the detection of these signs is often difficult and requires complex and expensive neuropsychological tests or brain imaging technologies. In this context, interest in language and how it changes over the course of the disease has increased in recent years. Research has shown that language deficits occur in the early and even prodromal stages and are therefore of interest for early diagnosis. The aim of this bachelor's thesis is to provide an overview of the research findings to date: Why is early diagnosis of Alzheimer's important? To what extent does language change in the early stages of the disease? How can language be used as a method of early diagnosis? Literature: https://pmc.ncbi.nlm.nih.gov/articles/PMC4611852/#B44
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Eingabedatum: 15.01.2025
Kontakt: MSc Jonathan Heitz, E-Mail

Beschreibung: Literature: - MacEachern, S. J. & Forkert, N. D. Machine learning for precision medicine. Genome 64, 416-425 (2021). - Plant, D. & Barton, A. Machine learning in precision medicine: lessons to learn. Nat Rev Rheumatol 17, 5-6 (2021). - Hampel, H. et al. The foundation and architecture of precision medicine in neurology and psychiatry. Trends in Neurosciences 0, (2023).
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Eingabedatum: 16.02.2024
Kontakt: Dr. Dorothea Floris, E-Mail

Beschreibung: Literature: - Groves, A. R., Smith, S. M., Fjell, A. M., Tamnes, C. K., Walhovd, K. B., Douaud, G., Woolrich, M. W. & Westlye, L. T. Benefits of multi-modal fusion analysis on a large-scale dataset: Life-span patterns of inter-subject variability in cortical morphometry and white matter microstructure. NeuroImage 63, (2012). - Floris, D. L., Llera, A., Zabihi, M., Moessnang, C., Jones, E. J. H., Mason, L., Haartsen, R., Holz, N. E., Mei, T., Elleaume, C., Vieira, B. H., Pretzsch, C. M., Forde, N., Baumeister, S., Dell?Acqua, F., Durston, S., Banaschewski, T., Ecker, C., Holt, R. J., Baron-Cohen, S., Bourgeron, T., Charman, T., Loth, E., Murphy, D. G. M., Buitelaar, J. K., Beckmann, C. F., Group, the E.-A. L. & Langer, N. A multimodal neural signature of face processing in autism within the fusiform gyrus. 2024.01.04.23300134 Preprint at https://doi.org/10.1101/2024.01.04.23300134 (2024) - Wolfers, T., Arenas, A. L., Onnink, A. M. H., Dammers, J., Hoogman, M., Zwiers, M. P., Buitelaar, J. K., Franke, B., Marquand, A. F. & Beckmann, C. F. Refinement by integration: Aggregated effects of multimodal imaging markers on adult ADHD. Journal of Psychiatry and Neuroscience 42, 386-394 (2017).
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Eingabedatum: 14.02.2024
Kontakt: Dr. Dorothea Floris, E-Mail

Beschreibung: Alpha oscillations were labelled the idling brain rhythm, because they occur during resting states. However, since alpha synchronization with increasing working memory demands was observed, this concept had to be revised. It is now commonly agreed that power modulations in alpha oscillatory activity serve as an inhibitory neural mechanism, se- lectively routing information within cerebral circuits. In visuo-spatial attention, alpha oscillations enhance the processing of relevant targets and suppress potential distractors. However, there are inconsistencies regarding alpha power modulations with increasing load in common working memory (WM) tasks. Particularly, high WM load is associated with either decreased or increased alpha power, depending on the type of WM task. Through research by Popov et al. (2021), an explanation for these inconsistencies has been proposed. According to them, the differences in posterior alpha power modulations are due to differing eye movements between WM tasks. Literature: - Pavlov, Y. G. and Kotchoubey, B. (2022). Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review. Psychophysiology, 59(5):e13735. - Popov, T., Miller, G. A., Rockstroh, B., Jensen, O., and Langer, N. (2021). Alpha oscillations link action to cognition: An oculomotor account of the brain?s dominant rhythm. preprint, Neuroscience.
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Eingabedatum: 15.02.2024
Kontakt: MSc Arne Hansen, E-Mail

Beschreibung: Episodic memory performance declines with advancing age. Previous EEG research suggests that the coupling of gamma power to the phase of the theta rhythm supports episodic memory formation. This literature review shall investigate whether age-related decline in episodic memory performance is related to compromised theta-gamma coupling. Literature: - Axmacher, N.; Henseler, M.M.; Jensen, O.; Weinreich, I.; Elger, C.E.; Fell, J. Cross-Frequency Coupling Supports Multi-Item Working Memory in the Human Hippocampus. Proc. Natl. Acad. Sci. USA 2010, 107, 3228-3233. - Sauseng, P.; Griesmayr, B.; Freunberger, R.; Klimesch, W. Control Mechanisms in Working Memory: A Possible Function of EEG Theta Oscillations. Neurosci. Biobehav. Rev. 2010, 34, 1015-1022. - Anna E. Karlsson, Ulman Lindenberger, Myriam C. Sander. Out of Rhythm: Compromised Precision of Theta-Gamma Coupling Impairs Associative Memory in Old Age. Journal of Neuroscience 2 March 2022, 42 (9) 1752-1764; DOI: 10.1523/JNEUROSCI.1678-21.2021
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Eingabedatum: 14.02.2024
Kontakt: MSc Dawid Strzelczyk, E-Mail

Beschreibung: 3 Papers: Martinez-Conde, S., Macknik, S. & Hubel, D. The role of fixational eye movements in visual perception. Nat Rev Neurosci 5, 229?240 (2004). https://doi.org/10.1038/nrn1348 Rucci, M., & Poletti, M. (2015). Control and Functions of Fixational Eye Movements. Annual review of vision science, 1, 499?518. https://doi.org/10.1146/annurev-vision-082114-035742 Krauzlis Richard J. , Goffart Laurent and Hafed Ziad M. 2017 Neuronal control of fixation and fixational eye movementsPhil. Trans. R. Soc. B3722016020520160205
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Eingabedatum: 20.07.2021
Kontakt: Dr. Tzvetan Popov, E-Mail

Beschreibung: Der Rey–Osterrieth Complex Figure Test (ROCF) ist ein neuropsychologischer Test zur Erfassung der Fähigkeit der räumlich visuellen Konstruktion und der visuellen Gedächtnisleistung. Auch wird der Test zur Erfassung exekutiver Funktionen eingesetzt. Der Test wurde ursprünglich 1941 von André Rey entwickelt und 1944 von Paul Alexandre Osterrieth standardisiert. Das Ziel des Tests war es, zwischen Wahrnehmungs- und Gedächtnisstörungen unterscheiden zu können, und ob die Störungen auf Lernschwierigkeiten oder hirnorganische Ursachen zurückzuführen sind.
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Kontakt: Prof. Dr. Nicolas Langer, E-Mail

Beschreibung: The learning process is one of the main topics of research in multiple disciplines such as psychology, neuroscience, behavioral ecology, evolutionary theory and computer science. The neural mechanism of memory formation and how it changes with age remains unclear. The use of neurophysiological measures can offer valuable insights into the learning process due to the ability of linking neural signals to complex behaviors. Electroencephalographic studies show that some components of event-related potentials (ERP) may provide information about the learning process itself and objectively measure learning success. These components include P300, a positive deflection with a latency of around 300 after stimulus onset. Polich, J. (2007). Updating P300: An integrative Theory of P3a and P3b. Clin. Neurophysiol., 118(10): 2128-2148. Tinga, A. M., de Back, T. T., Louwerse, M. M. (2019). Non-invasive neurophysiological measures of learning: A meta-analysis. Neuroscience and Biobehavioral Reviews, 99: 59-99.
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Eingabedatum: 21.01.2021
Kontakt: Dawid Strzelczyk, E-Mail

Beschreibung: 3 Papers: Kingstone A, Klein RM. What are human express saccades? Percept Psychophys. 1993 Aug;54(2):260-73. doi: 10.3758/bf03211762. PMID: 8361841. Fischer B, Boch R (1983) Saccadic eye movements after extremely short reaction times in the monkey. Brain Res 260: 21?26 Fischer, B., & Weber, H. (1993). Express saccades and visual attention. Behavioral and Brain Sciences, 16(3), 553-567. doi:10.1017/S0140525X00031575
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Eingabedatum: 20.07.2021
Kontakt: Dr. Tzvetan Popov, E-Mail

Beschreibung: Neuropsychological studies indicate that healthy ageing is associated with a decline of inhibitory control of attentional and behavioural systems, to inhibit prepotent responses is critical for successful goal-directed behaviours. A widely accepted measure of inhibitory control is the antisaccade task that requires both the inhibition of a reflexive saccadic response toward a visual target and the initiation of a voluntary eye movement in the opposite direction. This thesis aims to bring together and discuss evidence of decreasing inhibitory control in older adults using electroencephalography and eye-tracking recordings from the antisaccade task. Literature: [1] Hwang, Kai, et al. "Cortical neurodynamics of inhibitory control." Journal of Neuroscience 34.29 (2014): 9551-9561. [2] Plomecka, Martyna Beata, et al. "Aging effects and test/retest reliability of inhibitory control for saccadic eye movements." Eneuro 7.5 (2020). [3] Constantinidis, Christos, and Beatriz Luna. "Neural substrates of inhibitory control maturation in adolescence." Trends in neurosciences 42.9 (2019): 604-616.
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Eingabedatum: 26.07.2021
Kontakt: Martyna Plomecka, E-Mail

Beschreibung: Literatur: Woo CW, Chang LJ, Lindquist MA, Wager TD. (2017). Building better biomarkers: brain models in translational neuroimaging. Nature Neuroscience Zarley, D. (2019, January 28). Meet the scientists who are training AI to diagnose mental illness [Web log post]. Retrieved from https://www.theverge.com/2019/1/28/18197253/ai-mental-illness-artificial-intelligence-science-neuroimaging-mri Wardenaar, K. J., & De Jonge, P. (2013). Diagnostic heterogeneity in psychiatry: towards an empirical solution. BMC Medicine, 11(1). doi:10.1186/1741-7015-11-201 Walsh, C. G., Ribeiro, J. D., & Franklin, J. C. (2017). Predicting Risk of Suicide Attempts Over Time Through Machine Learning. Clinical Psychological Science, 5(3), 457-469. doi:10.1177/2167702617691560 Vieira, S., Pinaya, W. H., & Mechelli, A. (2017). Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications. Neuroscience & Biobehavioral Reviews, 74, 58-75. doi:10.1016/j.neubiorev.2017.01.002 Torous, J., Onnela, J., & Keshavan, M. (2017). New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices. Translational Psychiatry, 7(3), e1053-e1053. doi:10.1038/tp.2017.25 Stark, H. (2017, September/October 30). Artificial intelligence is here and it wants to revolutionize psychiatry. Forbes Torous, J. (2014). Mobile technology and global mental health. Asian Journal of Psychiatry, 10, 69-70. doi:10.1016/j.ajp.2013.07.004 Rutledge, R. B., Chekroud, A. M., & Huys, Q. J. (2019). Machine learning and big data in psychiatry: toward clinical applications. Current Opinion in Neurobiology, 55, 152-159. doi:10.1016/j.conb.2019.02.006 Reece, A. G., & Danforth, C. M. (2017). Erratum to: Instagram photos reveal predictive markers of depression. EPJ Data Science, 6(1). doi:10.1140/epjds/s13688-017-0118-4 Place, S., Blanch-Hartigan, D., Rubin, C., Gorrostieta, C., Mead, C., Kane, J., ? Azarbayejani, A. (2017). Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders. Journal of Medical Internet Research, 19(3), e75. doi:10.2196/jmir.6678 Neighborhood Psychiatry. (2018, February 13). Can artificial intelligence improve psychiatric diagnosis? Retrieved from https://www.psychologytoday.com/intl/blog/psychiatry-the-people/201802/can-artificial-intelligence-improve-psychiatric-diagnosis Meyer-Lindenberg, A. (2018). Künstliche Intelligenz in der Psychiatrie ? ein Überblick. Der Nervenarzt, 89(8), 861-868. doi:10.1007/s00115-018-0557-6 Just, M. A., Pan, L., Cherkassky, V. L., McMakin, D. L., Cha, C., Nock, M. K., & Brent, D. (2017). Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth. Nature Human Behaviour, 1(12), 911-919. doi:10.1038/s41562-017-0234-y Corcoran, C. M., Carrillo, F., Fernández-Slezak, D., Bedi, G., Klim, C., Javitt, D. C., ? Cecchi, G. A. (2018). Prediction of psychosis across protocols and risk cohorts using automated language analysis. World Psychiatry, 17(1), 67-75. doi:10.1002/wps.20491 Deshpande, G., Wang, P., Rangaprakash, D., & Wilamowski, B. (2015). Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data. IEEE Transactions on Cybernetics, 45(12), 2668-2679. doi:10.1109/tcyb.2014.2379621 Bedi, G., Carrillo, F., Cecchi, G. A., Slezak, D. F., Sigman, M., Mota, N. B., Ribeiro, S., Javitt, D. C., Copelli, M., & Corcoran, C. M. (2015). Automated analysis of free speech predicts psychosis onset in high-risk youths. Npj Schizophrenia, 1(1), 15030. https://doi.org/10.1038/npjschz.2015.30 Bedi, G., Cecchi, G. A., Slezak, D. F., Carrillo, F., Sigman, M., & de Wit, H. (2014). A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects. Neuropsychopharmacology, 39(10), 2340?2348. https://doi.org/10.1038/npp.2014.80
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Eingabedatum: 19.01.2020
Kontakt: Prof. Dr. Nicolas Langer, E-Mail

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Beschreibung: Neuropsychological studies indicate a reduction in the inhibitory control of attentional and behavioral systems in older people. A widely accepted measure of inhibitory control is the antisaccade task, in which participants inhibit a reactive saccade to a visual target to perform a voluntary saccade in the opposite direction. In addition, the EEG beta-band activity is known to be associated with the processing components during anti- and prosaccades. The aim of this thesis is to bring together and discuss evidence of decreasing inhibitory control in older adults using electroencephalography and eye-tracking recordings
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Kontakt: Martyna Plomecka, E-Mail

Beschreibung: ADHD is a frequent disorder in children and adolescents characterised by increased levels of hyperactivity and inattention. Yet, the underlying mechanisms of ADHD are not well understood. The aim of this thesis it so bring together current findings on morphologic characteristics of the cortex during brain development in ADHD. The findings shall be discussed critically with respect to their responsibility in the heterogeneity of symptoms in this disorder.
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Kontakt: Sabine Dziemian, E-Mail

Beschreibung: Deep learning is a powerful machine learning method for big data analysis. The student will summarize and evaluate recent studies using deep learning on electroencephalography (EEG) data for detecting memory impairments, such as the early onset of mild cognitive impairment or dementia. Literatur: - Bi X, Wang H (2019) Early Alzheimer's disease diagnosis based on EEG spectral images using deep learning. Neural Netw. 114:119-135. - Durstewitz D, Koppe G, Meyer-Lindenberg A (2019) Deep neural networks in psychiatry. Mol Psychiatry. 24(11):1583-1598. - Ieracitano C, Mammone N, Hussain A, Morabito FC (2019) A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia. Neural Netw. 123:176-190. - Kim D, Kim K (2018) Detection of Early Stage Alzheimer's Disease using EEG Relative Power with Deep Neural Network. Conf Proc IEEE Eng Med Biol Soc. 2018:352-355. - Liu X, Chen K, Wu T, Weidman D, Lure F, Li J (2018) Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease. Transl Res. 194:56-67. - Morabito F C, Campolo M, Ieracitano C, Ebadi J M, Bonanno L, Bramanti A, Desalvo S, Mammone N and Bramanti P (2016) Deep convolutional neural networks for classification of mild cognitive impaired and Alzheimer?s disease patients from scalp EEG recordings. IEEE 2nd Int. Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow. - Morabito FC, Campolo M, Mammone N, Versaci M, Franceschetti S, Tagliavini F, Sofia V, Fatuzzo D, Gambardella A, Labate A, Mumoli L, Tripodi GG, Gasparini S, Cianci V, Sueri C, Ferlazzo E, Aguglia U (2017) Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia. Int J Neural Syst. 27(2):1650039. - Roy Y, Banville H, Albuquerque I, Gramfort A, Falk TH, Faubert J (2019) Deep learning-based electroencephalography analysis: a systematic review. J Neural Eng. 16(5):051001.
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Eingabedatum: 07.01.2020
Kontakt: Dr. Christian Pfeiffer, E-Mail

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Beschreibung: Neural oscillations and their interaction play a key role in various cognitive processes. Phase-amplitude-coupling, a form of cross-frequency-coupling, has been reported to be directly linked to memorisation. The aim of this thesis is to bring together and critically discuss evidence of phase-amplitude-coupling in electroencephalography recordings that indicate memory processes, with the main focus on working memory.
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Beschreibung: Contralateral delay activity (CDA) is a widely studied phenomenon in memory research. Its sensitivity to working memory load is a replicated finding and advances our understanding of underlying processes. Furthermore it may be useful in the investigation of age related decline in working memory capacity.
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