In 2007, the CIN started with 25 principal investigators as cluster applicants, as stipulated in the DFG call for bids. When the CIN cluster was approved further scientists from a range of institutions were incorporated, to make up the 48 'founding members' of the CIN. Since the beginning of 2014 the CIN has consisted of over 80 scientists in total. The membership process involves an application to the steering committee in which the candidate outlines his or her scientific profile and submits a list of publications. The committee's decision is based purely on the scientific excellence of each candidate.
Dr. Niels Focke
Organization: University Hospital Tübingen
Phone number: +49 (0)7071 29 80416
Department: Department of Neurology
Area: CIN Members
Field of Research
The focus of my group is structural and functional imaging in neurological diseases with a particular focus on epilepsy. As a neurologist I am interested in better understanding the neuro-biology of specific diseases and translating this information to better patient care and earlier diagnosis. To this end we apply several computational, post-processing methods including voxel-based morphometry, machine learning and network analysis based on MRI, MEG and HD-EEG.
In epilepsy we are interested in better defining the structural abnormalities associated with seizure generation (“epileptogenic zone”) by means of structural imaging including high-field MRI (3T and 9.4T) and post-processing. Moreover, we apply diffusion-tensor imaging to analyze how epilepsy and seizures affect the structural networks of the brain. On the functional side we use functional MRI together with high-density EEG (256 channels) and MEG to asses functional networks characteristics and spread of ictal discharges i.e. epileptic activity. This broad range of non-invasive methods provides us with comprehensive access to brain networks in humans and in-vivo.
Structural, volumetric MRI, quantitative MRI (T2-, T2*, T1-relaxometry, MT-imaging), functional MRI (with parallel EEG-fMRI), HD-EEG, MEG, voxel-based morphometry, surface-based analysis, machine learning, graph-theory analysis, dynamic-causal modeling, source reconstruction of EEG/MEG
Focke NK, Yogarajah M, Symms MR, Gruber O, Paulus W, Duncan JS. Automated MR image classification in temporal lobe epilepsy. (Neuroimage, 2012; 59(1):356-362)
Focke NK, Helms G, Kaspar S, Diederich C, Tóth V, Dechent P, Mohr A, Paulus W. Multi-site voxel-based morphometry - Not quite there yet. (Neuroimage, 2011; 56(3):1164-70)
Focke NK, Helms G, Pantel PM, Scheewe S, Knauth M, Bachmann CG, Ebentheuer J, Dechent P, Paulus W, Trenkwalder C. Individual voxel-based subtype prediction can differentiate progressive supranuclear palsy from idiopathic Parkinson syndrome and healthy controls. (Human Brain Mapping, 2011; 32(11):1905-1915)
Focke NK, Bonelli SB, Yogarajah M, Scott C, Symms MR, Duncan JS. Automated normalized FLAIR imaging in MRI-negative patients with refractory focal epilepsy (Epilepsia, 2009; 50(6):1484-90)
Focke NK, Yogarajah M, Bonelli SB, Bartlett PA, Symms MR, Duncan JS. Voxel-based Diffusion Tensor Imaging in Patients with Mesial Temporal Lobe Epilepsy and Hippocampal Sclerosis (Neuroimage, 2008; 40(2):728-37)