Functional Neuroimaging (Stöcklein) 

Department / Institute
Department of Radiology
Subject area
Functional Neuroimaging
Name of supervisor
Prof. Dr. Sophia Stöcklein
Number of open positions
Project title
Use of machine learning for the investigation of the deviant functional connectome of neurological and psychiatric diseases
Language requirements
Fluency in English
Academic requirements
4-year Bachelor's plus Master's degree; experience with MRI desirable, statistics and machine learning techniques, programming experience in Matlab, Python, Bash
Study model
Full doctoral study model: 36 or 48 months

Project description

In recent years, Intrinsic Functional Connectivity Magnetic Resonance Imaging (fcMRI) has become a valuable tool for understanding how different parts of the human brain communicate with each other. This technology helps us create maps of the brain's functional connectivity architecture. These maps provide insights into how the human brain is organised and offer potential insights into changes in network structure in psychiatric disorders, brain tumours, or chronic pain. Using resting-state functional MRI scans, recent research has revealed several intrinsic networks and specific connections that can help us understand abnormal processes in the brain.

The future research conducted by Professor Stoecklein's group aims to combine information from various brain regions using advanced machine learning techniques. The goal is to track the progression of diseases in individual patients and identify patterns of brain activity that reflect their current medical condition. This information could potentially be used to predict the success of planned treatments and will enable doctors to tailor their medical treatments more effectively. (Stoecklein et al., 2020)

Stoecklein S, Hilgendorff A, Li M, Förster K, Flemmer AW, Galiè F, Wunderlich S, Wang D, Stein S, Ehrhardt H, Dietrich O, Zou Q, Zhou S, Ertl-Wagner B, Liu H. 2020. Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation. Proc Natl Acad Sci U S A 117:1201–1206. doi:10.1073/pnas.1907892117

Stoecklein VM, Stoecklein S, Galiè F, Ren J, Schmutzer M, Unterrainer M, Albert NL, Kreth F-W, Thon N, Liebig T, Ertl-Wagner B, Tonn J-C, Liu H. 2020. Resting-state fMRI detects alterations in whole brain connectivity related to tumor biology in glioma patients. Neuro Oncol 22:1388–1398. doi:10.1093/neuonc/noaa044

Stoecklein VM, Wunderlich S, Papazov B, Thon N, Schmutzer M, Schinner R, Zimmermann H, Liebig T, Ricke J, Liu H, Tonn J-C, Schichor C, Stoecklein S. 2023. Perifocal Edema in Patients with Meningioma is Associated with Impaired Whole-Brain Connectivity as Detected by Resting-State fMRI. AJNR Am J Neuroradiol 44:814–819. doi:10.3174/ajnr.A7915

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