ARIMOP

Degree:  Master

Project description: Für komplexe Bewegungsabläufe hat unser Gehirn internale Vorhersagemodelle, die uns helfen, diese Bewegungen erfolgreich auszuführen. Für diese Modelle sind Sinneseindrücke wichtig, zum Beispiel was wir hören uns sehen, während wir eine Bewegung ausführen oder beobachten. Im ARIMOP Projekt interessieren wir uns dafür, wie das Gehirn damit umgeht, wenn Sinneseindrücke teilweise fehlen und untersuchen dies am Beispiel Hürdenlauf. Dafür führen wir eine Reihe von fMRT-Messungen durch. Im Rahmen Deiner Masterarbeit hilfst Du bei der Erhebung der fMRT-Daten und führst eine Teilanalyse der Daten (fMRT, Verhalten) mit Hilfe Deiner BetreuerInnen durch.

Timeframe: ab Juli 2025

Supervisor(s): Sophie Siestrup und Marc Dührkop

Contact: s_sies01@uni-muenster.de und marc.duehrkop@uni-muenster.de

Groups in Past and Future

Degree:  Bachelor or Master

Project description: How we remember and imagine our future is strongly influenced by the groups that we belong to, ranging from our family or book club to the country we live in. This raises many interesting research questions. Thesis students can continue work about how we remember hearing about important public events (Flashbulb Memories), how we imagine the future of our country or other groups, compared to our own, or how predicting events can shape our own memories.

Tasks in the project: These projects would involve an own data collection with extensive help and support. 

Timeframe: anytime

Supervisor(s): Marius Boeltzig

Contact: marius.boeltzig@uni-muenster.de

 

MUCOJA

Degree:  Bachelor or Master

Project description:  The research focus is to explore whether shared intention, sub-goal coordination, and movement-level coordination can be modeled as three layers of a flexibly coupled dual predictive hierarchy in joint action. The current study aims to examine these three layers from neuro and behavioural responses using EEG and Eye tracking in a naturalistic scenario (a card game) and map onto a hierarchical action architecture in the brain.

Tasks in the project: Data analysis

Timeframe: Anytime

Supervisor(s): Rosari Naveena Selvan

Contact:  rselvan@uni-muenster.de

Key references

Kahl, S., & Kopp, S. (2018). A Predictive Processing Model of Perception and Action for Self-Other Distinction. Frontiers in psychology, 9, 2421. https://doi.org/10.3389/fpsyg.2018.02421

Pesquita, A., Whitwell, R. L., & Enns, J. T. (2018). Predictive joint-action model: A hierarchical predictive approach to human cooperation. Psychonomic Bulletin and Review, 25(5), 1751–1769. https://doi.org/10.3758/s13423-017-1393-6

ARIMOP

Degree:  Master

Project description: ARIMOP hMRI: Welchen Zusammenhang gibt es zwischen Myelinisierung im Gehirn und der Performanz in einer audio-visuellen Aufgabe? Ggf. in Zusammenhang mit der Erstellung eines Protokolls für die hMRI-Analyse allgemein.

Supervisor(s): Sophie Siestrup

Contact: s_sies01@uni-muenster.de

VATRA

Degree:  Bachelor or Master

Bachelor:

Project description: Behaviorale Pilotstudie zu VATRA: Was sind behaviorale Korrelate von sich aufbauenden und ändernden Gedächtnisspuren in verschiedenen Kontexten?

Master:

Project description: VATRA fMRT Studie: Was sind neuronale Korrelate von sich aufbauenden und ändernden Gedächtnisspuren in verschiedenen Kontexten?

Supervisor(s): Sophie Siestrup

Contact: s_sies01@uni-muenster.de

Designing Consistent Sound Stimuli An Empirical Study on Feature Optimization

Field of Research: Stimulus standardization

Degree: Bachelor

Project description: This study focuses on the standardization of an auditory stimuli bank by assessing certain stimulus features and their variance. The selection of appropriate stimuli is critical in psychological and neuroscience research, particularly within experimental settings. In EEG studies, the use of unsuitable stimuli can significantly compromise data quality. To ensure experimental validity, researchers must carefully select and standardize stimuli to align with the experimental design. Standardization aims to maintain features consistency across stimuli, preventing unintended influences that could introduce confounding variables and bias results.

Tasks in the project: Behavioral data collection, descriptive data analysis

Timeframe: Anytime soon.

Supervisor(s): Anas Al-Naji

Contact: alnaji@uni-muenster.de

Key references:
1.    Belin, P., Fillion-Bilodeau, S., & Gosselin, F. (2008). The montreal affective voices: A validated set of nonverbal affect bursts for research on auditory affective processing. Behavior Research Methods, 40(2), 531–539. https://doi.org/10.3758/brm.40.2.531
2.    Yang, W., Makita, K., Nakao, T., Kanayama, N., Machizawa, M. G., Sasaoka, T., Sugata, A., Kobayashi, R., Hiramoto, R., Yamawaki, S., Iwanaga, M., & Miyatani, M. (2018). Affective auditory stimulus database: An expanded version of the International Affective Digitized Sounds (IADS-e). Behavior Research Methods, 50(4), 1415–1429. https://doi.org/10.3758/s13428-018-1027-6

A fresh look on memory for conversations

Field of Research: Memories as Internal Models

Degree: Master

Project description: Previous research has found that memory for conversations is remarkably bad, especially when it comes to the exact phrasing of the statements. However, research has often used conversations in which participants themselves were participating, often while meeting a new person. In this project, we will therefore investigate whether passive listening to conversations enhances encoding. Additionally, several manipulations that may increase memory for conversations could be explored, including listening goals, self-reference, multiple encoding opportunities, context, and testing effects.

Tasks in the project: Own study
 

Timeframe: anytime

Supervisor(s): Marius Boeltzig

Contact: marius.boeltzig@uni-muenster.de

Key references:
Brown-Schmidt, S., & Benjamin, A. S. (2018). How we remember conversation: Implications in legal    settings. Policy Insights from the Behavioral and Brain Sciences, 5(2), 187–194.    https://doi.org/10.1177/2372732218786975

Getting into the rhythm of resting

Field of Research: Cortical hierarchies

Degree: Master

Project description: Previous research could demonstrate the brain regions vary in respect to their internal rhythms during rest (Raut et al., 2020). In a recent paper, we compared various cortical organizational schemes to find the structures underlying these temporal variations. We found that a gradient from unimodal to multimodal cortices stands out to best explain the different cortical rhythms, which multimodal cortices showing slower rhythms than unimodal cortices (Mecklenbrauck et al., 2024). As a next step we would like to validate this finding by replicating it in an independent dataset and different cortical atlas. Therefore, we seek to use of the publicly available data sets of the Human Connectome Project, that provides state-of-the-art fMRI Data (Van Essen et al., 2013).

Tasks in the project: Data analysis

Timeframe: anytime

Supervisor(s): Falko Mecklenbrauck

Contact:  f_meck01@uni-muenster.de

Key references

Mecklenbrauck, F., Sepulcre, J., Fehring, J., & Schubotz, R. I. (2024). Decoding Cortical Chronotopy-        Comparing the Influence of Different Cortical Organizational Schemes. NeuroImage, 120914.   https://doi.org/10.1016/j.neuroimage.2024.120914

Raut, R. V., Snyder, A. Z., & Raichle, M. E. (2020). Hierarchical dynamics as a macroscopic organizing       principle of the human brain. Proceedings of the National Academy of Sciences, 117(34),  20890-20897. https://doi.org/10.1073/pnas.2003383117

Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E., Yacoub, E., Ugurbil, K., & Wu-Minn HCP          Consortium. (2013). The WU-Minn human connectome project: an overview. NeuroImage, 80, 62-79. http://dx.doi.org/10.1016/j.neuroimage.2013.05.041

What makes the Rich Club so rich?

Field of Research: Cortical hierarchies

Degree: Master

Project description: The structural network of the human brain was consistently found to be organized according to the so-called Rich Club architecture (van den Heuvel & Sporns, 2011). The Rich Club describes a set of network nodes that not only well connected to the rest of the network, but also are connected especially to each other, thus forming a club. The structural Rich Club was previously suggested to play an important role in the communication throughout the network and variations in Rich Club architecture have been related to various neurological disorders (Griffa & van den Heuvel, 2018). However, despite its importance, the identification of Rich Club hubs is poorly defined. This project seeks to compare different definitions of the Rich Club on a way to establishing a gold standard.


Tasks in the project: Data analysis, (Literature work/Review)

Timeframe: anytime

Supervisor(s): Falko Mecklenbrauck

Contact: f_meck01@uni-muenster.de

Key references

Van Den Heuvel, M. P., & Sporns, O. (2011). Rich-club organization of the human connectome. Journal of Neuroscience, 31(44), 15775-15786.     https://doi.org/10.1523/JNEUROSCI.3539-11.2011

Griffa, A., & Van den Heuvel, M. P. (2018). Rich-club neurocircuitry: function, evolution, and vulnerability. Dialogues in clinical neuroscience, 20(2), 121-132.  https://doi.org/10.31887/DCNS.2018.20.2/agriffa

Neurocinematics: Watching a movie with your brain?!

Field of Research: Processing natural stimuli

Degree:  Bachelor or Master

Project description: Watching a movie engages a wide range of regions across the brain. Interestingly, the structure of the movie is also reflected by our brains as previous studies could show that the change of scenes is detectable from the cortical activation patterns (Baldassano et al., 2017). In this study, the participants will watch parts of a movie during an fMRI session. The Bachelor or Master student in this project can work with us in developing a task the participants have to complete in the scanner and are free to design a behavioural experiment around the fMRI session. Alternatively or additionally, there is the option to analyse the fMRI data as well. Possible research questions include but are not limited to the investigation of emotional processing, memory or cortical hierarchies (Hasson et al., 2008).

Tasks in the project: Data analysis, Own study, Data collection (depending when you start)

Timeframe: Data collection will start January 2025

Supervisor(s): Falko Mecklenbrauck

Contact: f_meck01@uni-muenster.de

Key references

Baldassano, C., Chen, J., Zadbood, A., Pillow, J. W., Hasson, U., & Norman, K. A. (2017). Discovering event structure in continuous narrative perception and memory. Neuron, 95(3), 709-721. https://doi.org/10.1016/j.neuron.2017.06.041

Hasson, U., Landesman, O., Knappmeyer, B., Vallines, I., Rubin, N., & Heeger, D. J. (2008).  Neurocinematics: The neuroscience of film. Projections, 2(1), 1-26. https://doi.org/10.3167/proj.2008.020102

PEGI

Field of Research: Memories as Internal Models

Degree: Master

Project description: In a previous study we found that under certain circumstances, prediction errors can lead to updating of memory for conversations. To that end, participants encoded dialogues (3 or 5 times) that were later modified to varying degrees. A behavioral study could test whether these effects are robust across different presentation times for the original and the modified version (e.g. 1, 2, 3 vs. 1, 2, 3 encodings). Apart from encoding frequency, other manipulations (e.g. speaker effects) can be studied.

Tasks in the project: Own study

Timeframe: anytime

Supervisor(s): Nina Liedtke

Contact: nina.liedtke@uni-muenster.de

Key references:

Boeltzig, M., Liedtke, N., & Schubotz, R. I. (2024). Prediction errors lead to updating of memories for conversations. Memory, 1-11. https://doi.org/10.1080/09658211.2024.2404498