Beta- and gamma-range human lower limb corticomuscular coherence

Coherence between electroencephalography (EEG) recorded on the scalp above the motor cortex and electromyography (EMG) recorded on the skin of the limbs is thought to reflect corticospinal coupling between motor cortex and muscle motor units. Beta-range (13–30 Hz) corticomuscular coherence has been extensively documented during static force output while gamma-range (31–45 Hz) coherence has been linked to dynamic force output. However, the explanation for this beta-to-gamma coherence shift remains unclear. We recorded 264-channel EEG and 8-channel lower limb EMG while eight healthy subjects performed isometric and isotonic, knee, and ankle exercises. Adaptive mixture independent component analysis (AMICA) parsed EEG into models of underlying source signals. We computed magnitude squared coherence between electrocortical source signals and EMG. Significant coherence between contralateral motor cortex electrocortical signals and lower limb EMG was observed in the beta- and gamma-range for all exercise types. Gamma-range coherence was significantly greater for isotonic exercises than for isometric exercises. We conclude that active muscle movement modulates the speed of corticospinal oscillations. Specifically, isotonic contractions shift corticospinal oscillations toward the gamma-range while isometric contractions favor beta-range oscillations. Prior research has suggested that tasks requiring increased integration of visual and somatosensory information may shift corticomuscular coherence to the gamma-range. The isometric and isotonic tasks studied here likely required similar amounts of visual and somatosensory integration. This suggests that muscle dynamics, including the amount and type of proprioception, may play a role in the beta-to-gamma shift.

[1]  Daniel P. Ferris,et al.  An EEG-based study of discrete isometric and isotonic human lower limb muscle contractions , 2012, Journal of NeuroEngineering and Rehabilitation.

[2]  R. Oostenveld,et al.  Independent EEG Sources Are Dipolar , 2012, PloS one.

[3]  Daniel P. Ferris,et al.  High-density EEG and independent component analysis mixture models distinguish knee contractions from ankle contractions , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  D. Farina,et al.  Linear transmission of cortical oscillations to the neural drive to muscles is mediated by common projections to populations of motoneurons in humans , 2011, The Journal of physiology.

[5]  Daniel P. Ferris,et al.  Electrocortical activity is coupled to gait cycle phase during treadmill walking , 2011, NeuroImage.

[6]  Daniel P. Ferris,et al.  Visual Evoked Responses During Standing and Walking , 2010, Front. Hum. Neurosci..

[7]  Daniel P. Ferris,et al.  Removal of movement artifact from high-density EEG recorded during walking and running. , 2010, Journal of neurophysiology.

[8]  Frank Huethe,et al.  Beta-range EEG-EMG coherence with isometric compensation for increasing modulated low-level forces. , 2009, Journal of neurophysiology.

[9]  G. Yue,et al.  Weakening of functional corticomuscular coupling during muscle fatigue , 2009, Brain Research.

[10]  G. Deuschl,et al.  Cortical representation of rhythmic foot movements , 2008, Brain Research.

[11]  P. Rossini,et al.  Functional cortico-muscular coupling during upright standing in athletes and nonathletes: a coherence electroencephalographic-electromyographic study. , 2008, Behavioral neuroscience.

[12]  Bhaskar D. Rao,et al.  Newton method for the ICA mixture model , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Lena H Ting,et al.  Neuromechanics of muscle synergies for posture and movement , 2007, Current Opinion in Neurobiology.

[14]  Jose Luis Patino,et al.  Beta-range cortical motor spectral power and corticomuscular coherence as a mechanism for effective corticospinal interaction during steady-state motor output , 2007, NeuroImage.

[15]  Marie-Claude Hepp-Reymond,et al.  Gamma-range corticomuscular coherence during dynamic force output , 2007, NeuroImage.

[16]  S. Makeig,et al.  Imaging human EEG dynamics using independent component analysis , 2006, Neuroscience & Biobehavioral Reviews.

[17]  Kenneth Kreutz-Delgado,et al.  Super-Gaussian Mixture Source Model for ICA , 2006, ICA.

[18]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[19]  R. Oostenveld,et al.  Validating the boundary element method for forward and inverse EEG computations in the presence of a hole in the skull , 2002, Human brain mapping.

[20]  J. B. Nielsen,et al.  Coupling of antagonistic ankle muscles during co-contraction in humans , 2002, Experimental Brain Research.

[21]  T. Fukunaga,et al.  Muscle and Tendon Interaction During Human Movements , 2002, Exercise and sport sciences reviews.

[22]  R. Kristeva-Feige,et al.  Effects of attention and precision of exerted force on beta range EEG-EMG synchronization during a maintained motor contraction task , 2002, Clinical Neurophysiology.

[23]  T. Sejnowski,et al.  Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects , 2000, Clinical Neurophysiology.

[24]  H. Freund,et al.  Cortico‐muscular synchronization during isometric muscle contraction in humans as revealed by magnetoencephalography , 2000, The Journal of physiology.

[25]  P. Ashby,et al.  Organization of Cortical Activities Related to Movement in Humans , 2000, The Journal of Neuroscience.

[26]  T. Sejnowski,et al.  Removing electroencephalographic artifacts by blind source separation. , 2000, Psychophysiology.

[27]  A. E. Schulman,et al.  Electroencephalographic measurement of motor cortex control of muscle activity in humans , 2000, Clinical Neurophysiology.

[28]  M. Hallett,et al.  Corticomuscular coherence: a review. , 1999, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[29]  J. Rothwell,et al.  Cortical correlate of the Piper rhythm in humans. , 1998, Journal of neurophysiology.

[30]  J. R. Rosenberg,et al.  Using electroencephalography to study functional coupling between cortical activity and electromyograms during voluntary contractions in humans , 1998, Neuroscience Letters.

[31]  Tzyy-Ping Jung,et al.  Independent Component Analysis of Electroencephalographic Data , 1995, NIPS.

[32]  A M Amjad,et al.  A framework for the analysis of mixed time series/point process data--theory and application to the study of physiological tremor, single motor unit discharges and electromyograms. , 1995, Progress in biophysics and molecular biology.

[33]  J. R. Rosenberg,et al.  The Fourier approach to the identification of functional coupling between neuronal spike trains. , 1989, Progress in biophysics and molecular biology.

[34]  S. Bouisset,et al.  [Voluntary movement]. , 1953, Journal de physiologie.