Open Thesis Topics

Our research group offers a variety of projects (Bachelor theses, Practicals, Master theses) on the following topics:

  • Causality and causal inference
  • Machine learning and causal modeling in cognitive neuroscience
  • Brain-Computer Interfaces (BCIs) for communication and rehabilitation

If you want to do a project with us, please send an email to student-project-application.ni@univie.ac.at with your name, student ID, study programme, type of project (e.g., bachelor's or master's project) and topics you’re interested in.

Projects for Bachelor & Master theses


Msc/Bsc Thesis Proposal

Multi-Scale analysis of Neuro-Cognitive Multilevel Causal Modeling using Human fMRI Data across Anatomical Resolutions

A fundamental challenge in neuroscience is bridging the explanatory gap between localized neuronal activity and complex cognitive processes. The Neuro-Cognitive Multilevel Causal Modeling (NC-MCM), proposed by Grosse-Wentrup et al. (Plos Comp Bio 2021) formalizes a causal hierarchy, linking interventions at the neuronal level to changes in network dynamics and, ultimately, to cognitive and behavioral outcomes. However, this framework was developed and demonstrated primarily in theoretical and invertebrate model systems (e.g., C. elegans). Its applicability, robustness, and explanatory power in the human brain, particularly with non-invasive neuroimaging data like fMRI, remain largely unexplored. 

Research Aim and Objectives:
This thesis aims to study and validate the NC-MCM framework to human task-based fMRI data, systematically investigating the impact of anatomical parcellation scale on the resulting causal models. We seek to apply this approach using standard brain atlases parcellated at different resolutions, for example Schaefer Atlas at 100, 200, and 400 regions of interest (ROIs).

Human data will be provided, potentially already preprocessed and parcellated as time series for those ROIs, or functional connectivity from these. More specifically, we expect to see the results consistent with literature, for example related to the default mode network (Crimi et al. Neuroimage 2021). Code related to NC-MCM and other effective connectivity approaches will be given.

This work will significantly advance the field by moving beyond correlation to test explicit causal hypotheses about human brain function, directly addressing the explanatory gap between neural activity and cognition.

References

  • Grosse-Wentrup, M., Kumar, A., Meunier, A., & Zimmer, M. (2021). Neuro-cognitive multilevel causal modeling: A framework for bridging the explanatory gap between neuronal activity and cognition. PNAS.
  • Schaefer, A., et al. (2018). Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI. Cerebral Cortex.
  • A Crimi, L Dodero, F Sambataro, V Murino, D Sona (2021). Structurally Constrained Effective Brain Connectivity NeuroImage 239 (1), 118288

Contacts: Akshey Kumar, Moritz Grosse-Wentrup, Alessandro Crimi