title: Joint cross-correlation analysis reveals complex, time-dependent functional relationship between cortical neurons and arm electromyograms.
abstract: Correlation between cortical activity and electromyographic (EMG) activity of limb muscles has long been a subject of neurophysiological studies, especially in terms of corticospinal connectivity. Interest in this issue has recently increased due to the development of brain-machine interfaces with output signals that mimic muscle force. For this study, three monkeys were implanted with multielectrode arrays in multiple cortical areas. One monkey performed self-timed touch pad presses, whereas the other two executed arm reaching movements. We analyzed the dynamic relationship between cortical neuronal activity and arm EMGs using a joint cross-correlation (JCC) analysis that evaluated trial-by-trial correlation as a function of time intervals within a trial. JCCs revealed transient correlations between the EMGs of multiple muscles and neural activity in motor, premotor and somatosensory cortical areas. Matching results were obtained using spike-triggered averages corrected by subtracting trial-shuffled data. Compared with spike-triggered averages, JCCs more readily revealed dynamic changes in cortico-EMG correlations. JCCs showed that correlation peaks often sharpened around movement times and broadened during delay intervals. Furthermore, JCC patterns were directionally selective for the arm-reaching task. We propose that such highly dynamic, task-dependent and distributed relationships between cortical activity and EMGs should be taken into consideration for future brain-machine interfaces that generate EMG-like signals.
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina;
authors.forename: Katie Z
authors.initials: KZ
authors.lastname: Zhuang
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina; Department of Neurobiology, Duke University, Durham, North Carolina;
authors.forename: Mikhail A
authors.initials: MA
authors.lastname: Lebedev
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, North Carolina; Department of Neurobiology, Duke University, Durham, North Carolina; Department of Psychology and Neuroscience, Duke University, Durham, North Carolina; Center for Neuroengineering, Duke University, Durham, North Carolina; and Edmond and Lily Safra International Institute for Neuroscience of Natal (ELS-IINN), Natal, Brazil nicoleli@neuro.duke.edu.
authors.forename: Miguel A L
authors.initials: MA
authors.lastname: Nicolelis
mesh_terms: D000818:Animals; D001132:Arm / Q000294:innervation* / Q000502:physiology; D003627:Data Interpretation, Statistical; D004576:Electromyography / Q000379:methods; D019054:Evoked Potentials, Motor; D005260:Female; D008253:Macaca mulatta; D008297:Male; D009044:Motor Cortex / Q000166:cytology / Q000502:physiology*; D009068:Movement; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D011930:Reaction Time; D013003:Somatosensory Cortex / Q000166:cytology / Q000502:physiology
keywords: EMG; JPSTH; brain-machine interface; cross-correlation; macaque; motoneuron; motor cortex; neural dynamics