title: An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.
abstract: BACKGROUND
  Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks.
  
  
  METHODS
  In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity.
  
  
  RESULTS
  Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition.
  
  
  METHODS
  Most of the current literature does not examine stationarity prior to processing.
  
  
  CONCLUSIONS
  The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data.
authors: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors: Othman
authors: O
authors: Muhei-aldin
authors: Department of Physical Therapy, University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors: Jessie
authors: J
authors: VanSwearingen
authors: Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors: Helmet
authors: H
authors: Karim
authors: Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15261, USA.
authors: Theodore
authors: T
authors: Huppert
authors: Department of Physical Therapy, University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors: Patrick J
authors: PJ
authors: Sparto
authors: Department of Psychology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
authors: Kirk I
authors: KI
authors: Erickson
authors: Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA. Electronic address: esejdic@ieee.org.
authors: Ervin
authors: E
authors: Sejdić
mesh_terms: D000328:Adult; D001921:Brain / Q000098:blood supply* / Q000502:physiology; D005260:Female; D005528:Foot / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D010100:Oxygen / Q000097:blood; D011597:Psychomotor Performance / Q000502:physiology*; D012691:Serial Learning / Q000502:physiology*; D013997:Time Factors; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: Foot tapping; Functional magnetic resonance imaging; Reverse arrangement test; Stationarity; Time series