title: Structural connectivity changes in temporal lobe epilepsy: Spatial features contribute more than topological measures.
abstract: BACKGROUND
  Previous studies reported reduced volumes of many brain regions for temporal lobe epilepsy (TLE). It has also been suggested that there may be widespread changes in network features of TLE patients. It is not fully understood, however, how these two observations are related.
  
  
  METHODS
  Using magnetic resonance imaging data, we perform parcellation of the brains of 22 patients with left TLE and 39 non-epileptic controls. In each parcellated region of interest (ROI) we computed the surface area and, using diffusion tensor imaging and deterministic tractography, infer the number of streamlines and their average length between each pair of connected ROIs. For comparison to previous studies, we use a connectivity 'weight' and investigate how ROI surface area, number of streamlines & mean streamline length contribute to such weight.
  
  
  RESULTS
  We find that although there are widespread significant changes in surface area and position of ROIs in patients compared to controls, the changes in connectivity are much more subtle. Significant changes in connectivity weight can be accounted for by decreased surface area and increased streamline count.
  
  
  CONCLUSIONS
  Changes in the surface area of ROIs can be a reliable biomarker for TLE with a large influence on connectivity. However, changes in structural connectivity via white matter streamlines are more subtle with a relatively lower influence on connection weights.
authors.affiliation: Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing Science, Newcastle University, United Kingdom.
authors.forename: Peter N
authors.initials: PN
authors.lastname: Taylor
authors.affiliation: Dept. of Biomedical Engineering, Korea University, Seoul, Republic of Korea ; Dept. of Brain and Cognitive Sciences, Seoul National University, Republic of Korea.
authors.forename: Cheol E
authors.initials: CE
authors.lastname: Han
authors.affiliation: Center for Pediatric and Adolescent Medicine, Freiburg University, Freiburg, Germany ; Dept. of Epileptology, University of Bonn, Bonn, Germany.
authors.forename: Jan-Christoph
authors.initials: JC
authors.lastname: Schoene-Bake
authors.affiliation: Dept. of Epileptology, University of Bonn, Bonn, Germany ; Center for Economics and Neuroscience, University of Bonn, Bonn, Germany.
authors.forename: Bernd
authors.initials: B
authors.lastname: Weber
authors.affiliation: Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing Science, Newcastle University, United Kingdom ; Institute of Neuroscience, Newcastle University, United Kingdom.
authors.forename: Marcus
authors.initials: M
authors.lastname: Kaiser
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D063132:Connectome / Q000379:methods*; D004833:Epilepsy, Temporal Lobe / Q000473:pathology*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000473:pathology*; D055815:Young Adult
keywords: Brain network; Connectome; Diffusion MRI; Epilepsy; Temporal lobe