title: Resting-state functional magnetic resonance imaging: the impact of regression analysis.
abstract: OBJECTIVE
  To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis.
  
  
  METHODS
  Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods.
  
  
  RESULTS
  The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas.
  
  
  CONCLUSIONS
  rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear.
authors.affiliation: Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, R.O.C.
authors.forename: Chia-Jung
authors.initials: CJ
authors.lastname: Yeh
authors.forename: Yu-Sheng
authors.initials: YS
authors.lastname: Tseng
authors.forename: Yi-Ru
authors.initials: YR
authors.lastname: Lin
authors.forename: Shang-Yueh
authors.initials: SY
authors.lastname: Tsai
authors.forename: Teng-Yi
authors.initials: TY
authors.lastname: Huang
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D015233:Models, Statistical; D009415:Nerve Net / Q000502:physiology; D012044:Regression Analysis; D015203:Reproducibility of Results; D012146:Rest / Q000502:physiology; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio
keywords: default mode network; functional connectivity; regression; resting state; rsfMRI