title: Improving functional magnetic resonance imaging motor studies through simultaneous electromyography recordings.
abstract: Specially designed optoelectronic and data postprocessing methods are described that permit electromyography (EMG) of muscle activity simultaneous with functional MRI (fMRI). Hardware characterization and validation included simultaneous EMG and event-related fMRI in 17 healthy participants during either ankle (n = 12), index finger (n = 3), or wrist (n = 2) contractions cued by visual stimuli. Principal component analysis (PCA) and independent component analysis (ICA) were evaluated for their ability to remove residual fMRI gradient-induced signal contamination in EMG data. Contractions of ankle tibialis anterior and index finger abductor were clearly distinguishable, although observing contractions from the wrist flexors proved more challenging. To demonstrate the potential utility of simultaneous EMG and fMRI, data from the ankle experiments were analyzed using two approaches: 1) assuming contractions coincided precisely with visual cues, and 2) using EMG to time the onset and offset of muscle contraction precisely for each participant. Both methods produced complementary activation maps, although the EMG-guided approach recovered more active brain voxels and revealed activity better in the basal ganglia and cerebellum. Furthermore, numerical simulations confirmed that precise knowledge of behavioral responses, such as those provided by EMG, are much more important for event-related experimental designs compared to block designs. This simultaneous EMG and fMRI methodology has important applications where the amplitude or timing of motor output is impaired, such as after stroke.
authors.affiliation: Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada. bmac@swri.ca
authors.forename: Bradley J
authors.initials: BJ
authors.lastname: MacIntosh
authors.forename: S Nicole
authors.initials: SN
authors.lastname: Baker
authors.forename: Richard
authors.initials: R
authors.lastname: Mraz
authors.forename: John R
authors.initials: JR
authors.lastname: Ives
authors.forename: Anne L
authors.initials: AL
authors.lastname: Martel
authors.forename: William E
authors.initials: WE
authors.lastname: McIlroy
authors.forename: Simon J
authors.initials: SJ
authors.lastname: Graham
mesh_terms: D000328:Adult; D000669:Amplifiers, Electronic; D000842:Ankle / Q000294:innervation / Q000502:physiology; D001921:Brain / Q000502:physiology; D015331:Cohort Studies; D003198:Computer Simulation; D003463:Cues; D004576:Electromyography / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D005385:Fingers / Q000294:innervation / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D015233:Models, Statistical; D009068:Movement / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology; D010100:Oxygen / Q000097:blood; D011597:Psychomotor Performance / Q000502:physiology; D014953:Wrist / Q000294:innervation / Q000502:physiology
chemical_list: D010100:Oxygen