Post-movement Rebound Research Articles

Discrete cortical control during quiet stance revealed by desynchronization and rebound of beta oscillations

Postural sway during quiet stance often exhibits a repetition of micro-fall and the subsequent micro-recovery. The classical view –that the quiet bipedal stance is stabilized by the ankle joint stiffness– has been challenged by paradoxical non-spring-like behaviors of calf muscles: gastrocnemius muscles are shortened and then lengthened, respectively, during the micro-fall and the micro-recovery. Here, we examined EEG based brain activity during quiet stance, and identified desynchronization and synchronization of beta oscillations that were associated, respectively, with the micro-fall and the micro-recovery. Based on a widely accepted scenario for beta-band desynchronization during movement and post-movement rebound in the control of discrete voluntary movement, our results reveal that the beta rebound can be considered as a manifestation of stop command to punctuate the motor control for every fall-recovery cycle. Namely, cortical interventions to the automatic postural control are discrete, rather than continuous modulations. The finding is highly compatible with the intermittent control model, rather than the stiffness control model.

On-line identification of the end of motor imageries based on the alpha rebound detection

Limb movement execution and imagination elicit in a mutually exclusive manner sensorimotor rhythms that can be detected in electroencephalographic (EEG) recordings; in particular over the primary motor cortex, where an oscillatory modulation has been observed prior, during and following the execution of voluntary movement, passive movement, imagined movement, and even tactile stimulation [1, 2]. The modulation following the movement termination consists of an event-related synchronization (ERS) that increases the oscillatory power for a few hundred milliseconds [3]. Since it is known to be specific of the beta band [13-25] Hz, it is denoted as post-movement beta rebound, although in recent studies it has been shown that this phenomenon is enhanced when analyzed in the alpha range [8-13] Hz (see Figure 1) [1, 4]. The characteristics of this post-movement rebound, as it will be shown in the present study, are preserved independently of the involved limb during the motor execution. From database 2a of the BCI competition IV [4], an on-line method for identifying the end of motor imageries on a single trial detection is presented. By using an overlapped sliding window over each trial from four different motor imageries (left hand, right hand, feet and tongue), two contrasting classes are generated according to the occurring condition (i.e., segments with rebound and segments without it) to generate a classification model based on a linear discriminant analysis. Results show that the classification performance is 5% superior over the alpha band than the beta band for almost all subjects, and that the rebound detection is independent from the limb used in the motor imagery. Conclusions On-line detection of the end of motor imageries of various body parts is feasible by detecting the post-movement alpha rebound. The accuracy reached by the proposed method within the alpha band across all subjects is 79.17% with a sensitivity value of 0.81 and specificity of 0.71. This method improves the detection of the end of motor imageries by considering the alpha post-movement rebound, which is of interest for the design of self-paced brain-computer interfaces. Review of the BCI competition iv, Front Neurosci, vol. 6, p. 55, 2012. Figure 1. Averaged post-movement rebound for subject 7 in electrode C4 across the A. alpha and B. beta bands. The yellow box indicates the duration of the motor imageries.

Aging reduces experience-induced sensorimotor plasticity. A magnetoencephalographic study

Modulation of the mu-alpha and mu-beta spontaneous rhythms reflects plastic neural changes within the primary sensorimotor cortex (SM1). Using magnetoencephalography (MEG), we investigated how aging modifies experience-induced plasticity after learning a motor sequence, looking at post- vs. pre-learning changes in the modulation of mu rhythms during the execution of simple hand movements. Fifteen young (18–30 years) and fourteen older (65–75 years) right-handed healthy participants performed auditory-cued key presses using all four left fingers simultaneously (Simple Movement task — SMT) during two separate sessions. Following both SMT sessions, they repeatedly practiced a 5-elements sequential finger-tapping task (FTT). Mu power calculated during SMT was averaged across 18 gradiometers covering the right sensorimotor region and compared before vs. after sequence learning in the alpha (9/10/11Hz) and the beta (18/20/22Hz) bands separately. Source power maps in the mu-alpha and mu-beta bands were localized using Dynamic Statistical Parametric Mapping (dSPM). The FTT sequence was performed faster at retest than at the end of the learning session, indicating an offline boost in performance. Analyses conducted on SMT sessions revealed enhanced rebound after learning in the right SM1, 3000–3500ms after the initiation of movement, in young as compared to older participants. Source reconstruction indicated that mu-beta is located in the precentral gyrus (motor processes) and mu-alpha is located in the postcentral gyrus (somatosensory processes) in both groups. The enhanced post-movement rebound in young subjects potentially reflects post-training plastic changes in SM1. Age-related decreases in post-training modulatory effects suggest reduced experience-dependent plasticity in the aging brain.

Post-movement beta rebound is generated in motor cortex: Evidence from neuromagnetic recordings

Voluntary movements are accompanied by amplitude changes in cortical rhythms presumably as a result of functional activation of sensorimotor areas. Recently, the location of the neural generators involved in increasing power within the beta (15–30 Hz) frequency band following movement (post-movement beta rebound, PMBR) has come into question [Parkes, L.M, Bastiaansen, M.C.M, Norris, D.G., 2006. Combining EEG and fMRI to investigate the post-movement beta rebound. NeuroImage 29, 685–696.]. We used the synthetic aperture magnetometry (SAM) spatial filtering method to identify the time course and location of oscillatory changes within the beta and mu (8–14 Hz) frequency bands during the performance of voluntary movements. Neuromagnetic activity was recorded from 10 adult subjects during abduction of the right index finger. Changes in beta and mu source power were calculated for periods during and following movement, relative to pre-movement baseline activity. Decreases in beta band activity (event-related desynchronization, ERD) were observed during movement, with a strong increase (PMBR) beginning 230 ± 170 ms following movement, lasting for 680 ± 170 ms. Mu band ERD was observed both during and following movement, with little to no post-movement rebound. Beta and mu ERD were localized bilaterally to the hand region of postcentral gyrus whereas PMBR was localized bilaterally to the hand region of precentral gyrus (motor cortex). Both PMBR and beta ERD were strongest contralateral to the side of movement. These results provide further evidence that movement influences independent cortical rhythms in sensorimotor areas, and confirm previous reports of precentral generators of PMBR in the region of motor cortex, with postcentral generators of beta and mu ERD during movement.

Motor Cortex Dynamics in Visuomotor Production of Speech and Non-speech Mouth Movements

We investigated timing and hemispheric balance of motor cortex activation when kinetically similar speech and non-speech mouth movements and sequences of such movements were triggered by visually presented letter- and symbol-strings. As an index of motor cortex activation, we used magnetoencephalographic recording of task-related change of precentral 20 Hz (16-24 Hz) activity. Suppression of the 20 Hz rhythm revealed pre-movement activation in the face representation areas that was tied to visual instruction, not movement onset. The 20 Hz rhythm remained suppressed throughout the preparation and execution of mouth movements and was followed by post-movement rebound. Left hemisphere preceded the right at the onset and offset of the suppression, similarly for isolated and sequential speech and non-speech movements. Pattern of task-related change in 20 Hz activity was otherwise symmetrical. In the face areas, the overall modulation of 20 Hz activity increased with sequence length and motor demands. Hand representation areas showed also weak reactivity, with systematically larger modulation of 20 Hz activity for non-speech than speech movements. Our results suggest an active role for the motor cortex in cognitive control of visually triggered mouth movements, not limited to movement execution.

Preface

Modulation of the mu-alpha and mu-beta spontaneous rhythms reflects plastic neural changes within the primary sensorimotor cortex (SM1). Using magnetoencephalography (MEG), we investigated how aging modifies experience-induced plasticity after learning a motor sequence, looking at post- vs. pre-learning changes in the modulation of mu rhythms during the execution of simple hand movements. Fifteen young (18–30 years) and fourteen older (65–75 years) right-handed healthy participants performed auditory-cued key presses using all four left fingers simultaneously (Simple Movement task — SMT) during two separate sessions. Following both SMT sessions, they repeatedly practiced a 5-elements sequential finger-tapping task (FTT). Mu power calculated during SMT was averaged across 18 gradiometers covering the right sensorimotor region and compared before vs. after sequence learning in the alpha (9/10/11 Hz) and the beta (18/20/22 Hz) bands separately. Source power maps in the mu-alpha and mu-beta bands were localized using Dynamic Statistical Parametric Mapping (dSPM). The FTT sequence was performed faster at retest than at the end of the learning session, indicating an offline boost in performance. Analyses conducted on SMT sessions revealed enhanced rebound after learning in the right SM1, 3000–3500 ms after the initiation of movement, in young as compared to older participants. Source reconstruction indicated that mu-beta is located in the precentral gyrus (motor processes) and mu-alpha is located in the postcentral gyrus (somatosensory processes) in both groups. The enhanced post-movement rebound in young subjects potentially reflects post-training plastic changes in SM1. Age-related decreases in post-training modulatory effects suggest reduced experience-dependent plasticity in the aging brain.

Motor cortex involvement during verbal versus non‐verbal lip and tongue movements

We evaluated left and right motor cortex involvement during verbal and non-verbal lip and tongue movements in seven healthy subjects using whole-head magnetoencephalography. The movements were paced by tone pips. The non-verbal tasks included a kissing movement and touching the teeth with the tongue. The verbal tasks comprised silent articulation of the Finnish vowel /o/, which requires mouth movement similar to that in the kissing task, pronouncing the same self-selected word repeatedly, and producing a new word for every tone pip. Motor cortex involvement was quantified by task-related suppression and subsequent rebound of the 20-Hz activity. The modulation concentrated to two sites along the central sulcus, identified as the motor face and hand representations. The 20-Hz suppression in the face area was relatively similar during all tasks. The post-movement rebound, however, was significantly left-lateralized during word production. In the non-verbal tasks, hand areas showed pronounced suppression of 20-Hz activity that was significantly diminished for the verbal tasks. The latencies of the 20-Hz suppression in the left and right face representations were correlated across subjects during verbal mouth movements. Increasing linguistic content of lip and tongue movements was thus manifested in spatially more focal motor cortex involvement, left-hemisphere lateralization of face area activation, and correlated timing across hemispheres.