title: Fast construction of voxel-level functional connectivity graphs.
abstract: BACKGROUND
  Graph-based analysis of fMRI data has recently emerged as a promising approach to study brain networks. Based on the assessment of synchronous fMRI activity at separate brain sites, functional connectivity graphs are constructed and analyzed using graph-theoretical concepts. Most previous studies investigated region-level graphs, which are computationally inexpensive, but bring along the problem of choosing sensible regions and involve blurring of more detailed information. In contrast, voxel-level graphs provide the finest granularity attainable from the data, enabling analyses at superior spatial resolution. They are, however, associated with considerable computational demands, which can render high-resolution analyses infeasible. In response, many existing studies investigating functional connectivity at the voxel-level reduced the computational burden by sacrificing spatial resolution.
  
  
  METHODS
  Here, a novel, time-efficient method for graph construction is presented that retains the original spatial resolution. Performance gains are instead achieved through data reduction in the temporal domain based on dichotomization of voxel time series combined with tetrachoric correlation estimation and efficient implementation.
  
  
  RESULTS
  By comparison with graph construction based on Pearson's r, the technique used by the majority of previous studies, we find that the novel approach produces highly similar results an order of magnitude faster.
  
  
  CONCLUSIONS
  Its demonstrated performance makes the proposed approach a sensible and efficient alternative to customary practice. An open source software package containing the created programs is freely available for download.
authors.affiliation: Department of Neurology, Experimental Neurology, Otto-von-Guericke Universität, Leipziger Str, 44, 39120 Magdeburg, Germany. kl@kristianloewe.com.
authors.forename: Kristian
authors.initials: K
authors.lastname: Loewe
authors.forename: Marcus
authors.initials: M
authors.lastname: Grueschow
authors.forename: Christian M
authors.initials: CM
authors.lastname: Stoppel
authors.forename: Rudolf
authors.initials: R
authors.lastname: Kruse
authors.forename: Christian
authors.initials: C
authors.lastname: Borgelt
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D063132:Connectome / Q000379:methods*; D044962:Data Compression / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008959:Models, Neurological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity