title: Decoding three-dimensional reaching movements using electrocorticographic signals in humans.
abstract: OBJECTIVE
  Electrocorticography (ECoG) signals have emerged as a potential control signal for brain-computer interface (BCI) applications due to balancing signal quality and implant invasiveness. While there have been numerous demonstrations in which ECoG signals were used to decode motor movements and to develop BCI systems, the extent of information that can be decoded has been uncertain. Therefore, we sought to determine if ECoG signals could be used to decode kinematics (speed, velocity, and position) of arm movements in 3D space.
  
  
  METHODS
  To investigate this, we designed a 3D center-out reaching task that was performed by five epileptic patients undergoing temporary placement of ECoG arrays. We used the ECoG signals within a hierarchical partial-least squares (PLS) regression model to perform offline prediction of hand speed, velocity, and position.
  
  
  RESULTS
  The hierarchical PLS regression model enabled us to predict hand speed, velocity, and position during 3D reaching movements from held-out test sets with accuracies above chance in each patient with mean correlation coefficients between 0.31 and 0.80 for speed, 0.27 and 0.54 for velocity, and 0.22 and 0.57 for position. While beta band power changes were the most significant features within the model used to classify movement and rest, the local motor potential and high gamma band power changes, were the most important features in the prediction of kinematic parameters.
  
  
  CONCLUSIONS
  We believe that this study represents the first demonstration that truly three-dimensional movements can be predicted from ECoG recordings in human patients. Furthermore, this prediction underscores the potential to develop BCI systems with multiple degrees of freedom in human patients using ECoG.
authors.affiliation: Department of Biomedical Engineering, Washington University in St. Louis, Campus Box 8057, 660 South Euclid, St Louis, MO 63130, USA.
authors.forename: David T
authors.initials: DT
authors.lastname: Bundy
authors.forename: Mrinal
authors.initials: M
authors.lastname: Pahwa
authors.forename: Nicholas
authors.initials: N
authors.lastname: Szrama
authors.forename: Eric C
authors.initials: EC
authors.lastname: Leuthardt
mesh_terms: D000293:Adolescent; D000328:Adult; D062207:Brain-Computer Interfaces; D000069280:Electrocorticography / Q000379:methods*; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000379:methods; D006225:Hand / Q000502:physiology*; D006801:Humans; D008875:Middle Aged; D009044:Motor Cortex / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D010775:Photic Stimulation / Q000379:methods; D011897:Random Allocation