@article{WehrheimFaskowitzSpornsetal.2023,
  author    = {Wehrheim, Maren H. and Faskowitz, Joshua and Sporns, Olaf and Fiebach, Christian J. and Kaschube, Matthias and Hilger, Kirsten},
  title     = {Few temporally distributed brain connectivity states predict human cognitive abilities},
  series = {NeuroImage},
  volume    = {277},
  journal   = {NeuroImage},
  doi       = {10.1016/j.neuroimage.2023.120246},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-349874},
  year      = {2023},
  abstract  = {Highlights • Brain connectivity states identified by cofluctuation strength. • CMEP as new method to robustly predict human traits from brain imaging data. • Network-identifying connectivity 'events' are not predictive of cognitive ability. • Sixteen temporally independent fMRI time frames allow for significant prediction. • Neuroimaging-based assessment of cognitive ability requires sufficient scan lengths. Abstract Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities - which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5\% of 10 min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual's network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.},
  language  = {en}
}
@article{SchurigHaeuslerGrittneretal.2019,
  author    = {Schurig, Johannes and Haeusler, Karl Georg and Grittner, Ulrike and Nolte, Christian H. and Fiebach, Jochen B. and Audebert, Heinrich J. and Endres, Matthias and Rocco, Andrea},
  title     = {Frequency of Hemorrhage on Follow Up Imaging in Stroke Patients Treated With rt-PA Depending on Clinical Course},
  series = {Frontiers in Neurology},
  volume    = {10},
  journal   = {Frontiers in Neurology},
  doi       = {10.3389/fneur.2019.00368},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-234947},
  year      = {2019},
  abstract  = {Background: According to current guidelines, stroke patients treated with rt-PA should undergo brain imaging to exclude intracerebral bleeding 24 h after thrombolysis, before the start of medical secondary prevention. However, the usefulness of routine follow-up imaging with regard to changes in therapeutic management in patients without neurological deterioration is unclear. We hypothesized that follow up brain imaging solely to exclude bleeding in patients who clinically improved after rt-PA application may not be necessary. Methods: Retrospective single-center analysis including stroke patients treated with rt-PA. Records were reviewed for hemorrhagic transformation one day after systemic thrombolysis and brain imaging-based changes in therapeutic management. Twenty-four hour after thrombolysis patients were divided into four groups: (1) increased NIHSS score; (2) unchanged NIHSS score; (3) improved NIHSS score and; (4) NIHSS score = 0. Results: Out of 188 patients (mean age 73 years, 100 female) receiving rt-PA, 32 (17\%) had imaging-proven hemorrhagic transformation including 11 (6\%) patients with parenchymal hemorrhage. Patients in group (1, 2) more often had hypertension (p = 0.015) and more often had parenchymal hemorrhage (9 vs. 4\%; p < 0.206) compared to group (3, 4) and imaging-based changes in therapeutic management were more frequent (19\% vs. 6\%; p = 0.007). Patients of group (3, 4) had no changes in therapeutic management in 94\% of the cases. Patients in group (4) had no hemorrhagic transformation in routine follow-up brain imaging. Conclusions: Frequency of hemorrhagic transformation in Routine follow-up brain imaging and consecutive changes in therapeutic management were different depending on clinical course measured by NHISS score.},
  language  = {en}
}