Christian Georgiev

The beta oscillations of the human primary sensorimotor cortex (SM1) play a crucial role in regulating motor and cognitive behavior in health and disease. However, their assessment relies on costly and complex neuroimaging techniques, limiting scalability and translational applications. We present a novel method for assessing beta oscillations from easily obtained peripheral electromyography and force recordings. We show that movement-induced modulations in SM1 beta oscillations can be assessed from the electromyography or force recordings of a contracted contralateral hand muscle. We demonstrate the fidelity of this method in young and elderly healthy participants and in Parkinson’s disease patients. We also demonstrate that the resting-state SM1 beta interhemispheric coupling can be assessed from an interhand coupling between the electromyography or force of contracted homologous hand muscles. This methodology enables scalable and cost-effective investigations of beta oscillations for all fields of human neuroscience and for the development of accessible disease/therapeutic markers.

An event‐related desynchronization (ERD) of the 13–30 Hz sensorimotor (SM1) beta oscillations is commonly observed during movement preparation and execution. Human electrophysiological measurements suggest that such a beta ERD has a wide topographical distribution along the SM1; however, no accessible means of quantifying the degree of its focality exist. Here, we tested the suitability of a method to investigate how the movement‐induced beta ERD in one somatotopic SM1 area affects beta oscillations in a neighboring SM1 area. Thirty‐six participants performed right brachium movements while holding a submaximal isometric contraction with their right first dorsal interosseous (FDI) muscle. Beta ERD in the left SM1 brachium area was assessed with electroencephalography (EEG). The effect of that ERD on beta activity in the neighboring SM1 FDI area was assessed through the corticomuscular coherence (CMC) between SM1 EEG signals and the electromyography and force signals recorded from the stationary isometrically contracted right FDI muscle. Our results showed a strong movement‐induced beta ERD in the SM1 brachium area that co‐occurred with an attenuation of CMC with both FDI signals. These findings imply that beta ERD may not be a strictly focal phenomenon as it could spread to a neighboring SM1 area. Importantly, we introduced a novel approach that combines a dual motor task paradigm with CMC to assess beta propagatory effects. This approach could allow for investigating the topographical properties of beta oscillations and their role for motor control in healthy and clinical populations.

An Event-Related Desynchronization (ERD) of the 13–30 Hz sensorimotor (SM1) beta oscillations is commonly observed during movement preparation and execution. Human electrophysiological measurements suggest that such a beta ERD has a wide topographical distribution along the SM1, however, no accessible means of quantifying the degree of its focality exist. Here, we tested the suitability of a method to investigate how the movement-induced beta ERD in one somatotopic SM1 area affects beta oscillations in a neighbouring SM1 area. Thirty-six participants performed right brachium movements while holding a submaximal isometric contraction with their right first dorsal interosseous (FDI) muscle. Beta ERD in the left SM1 brachium area was assessed with electroencephalography (EEG). The effect of that ERD on beta activity in the neighbouring SM1 FDI area was assessed through the corticomuscular coherence (CMC) between SM1 EEG signals and the electromyography and force signals recorded from the stationary isometrically contracted right FDI muscle. Our results showed a strong movement-induced beta ERD in the SM1 brachium area that co-occurred with an attenuation of CMC with both FDI signals. These findings imply that beta ERD may not be a strictly focal phenomenon as it could spread to a neighbouring SM1 area. Importantly, we introduced a novel approach that combines a dual motor task paradigm with CMC to assess beta propagatory effects. This approach could allow for investigating the topographical properties of beta oscillations and their role for motor control in healthy and clinical populations.

Background: Sensorimotor beta oscillations are critical for motor control and become synchronized with muscle activity during sustained contractions, forming corticomuscular coherence (CMC). Although beta activity manifests in transient bursts, suggesting nonlinear behavior, most studies rely on linear analyses, leaving the underlying dynamic structure of brain–muscle interactions underexplored. Objectives: To investigate the nonlinear dynamics underlying beta oscillations during isometric contraction. Methods: MEG and EMG were recorded from 17 right-handed healthy adults performing a 10 min isometric pinch task. Lyapunov exponent (LE), fractal dimension (FD), and correlation dimension (CD) were computed in 10 s windows to assess temporal stability. Signal similarity was assessed using Pearson correlation of amplitude envelopes and the nonlinear features. Burstiness was estimated using the coefficient of variation (CV) of the beta envelope to examine how transient fluctuations in signal amplitude relate to underlying nonlinear dynamics. Phase-randomized surrogate signals were used to validate the nonlinearity of the original data. Results: In contrast to FD, LE and CD revealed consistent, structured dynamics over time and significantly differed from surrogate signals, indicating sensitivity to non-random patterns. Both MEG and EMG signals demonstrated temporal stability in nonlinear features. However, MEG–EMG similarity was captured only by linear envelope correlation, not by nonlinear features. CD was strongly associated with beta burstiness in MEG, suggesting it reflects information similar to that captured by the amplitude envelope. In contrast, LE showed a weaker, inverse relationship, and FD was not significantly associated with burstiness. Conclusions: Nonlinear features capture intrinsic, stable dynamics in cortical and muscular beta activity, but do not reflect cross-modal similarity, highlighting a distinction from conventional linear analyses.

The excitability of the sensorimotor (SM1) cortices is reflected in the bilateral ~20 Hz beta oscillations. The extent to which these oscillations subtend the interhemispheric inhibition (IHI) captured by the Transcranial Magnetic Stimulation (TMS) ipsilateral Silent Period (iSP) protocol remains unclear. Therefore, we investigated the relationship between movement-related beta suppression and the iSP, along with their role for manual dexterity. Forty adults underwent an Electroencephalography assessment of beta suppression during volitional left-hand movement and a TMS assessment of iSP recorded from the right hand. In both cases, left SM1 beta oscillations (contralateral to the activated right SM1) were monitored through a proxy signal—the Electromyography of the contracted right hand. Bimanual dexterity was assessed with the Purdue Pegboard. Volitional movement caused significant bilateral SM1 beta suppression in nearly all participants (≥85%). ISPs were observed in every participant. In the proxy signal for the left SM1, the iSP coincided with TMS-evoked high-amplitude beta bursts. These bursts showed significant phase alignment across participants 10–70 ms after the TMS pulse. There was no significant association between the left-/right-hemisphere beta suppression, iSP, and bimanual dexterity. Our results highlight the distinct nature of beta oscillation changes during volitional movement compared with TMS-iSP and show that TMS induces IHI via transcallosal generation of phase-aligned beta bursts. Furthermore, our data suggest that only the initial phase of a beta burst carries an inhibitory effect. It also highlights the possibility of evoking a beta burst with the iSP protocol, opening perspectives for future neuroimaging and modeling studies.

Acquiring efficient postural control strategies is key to children’s proper motor development. For that, the brain needs to continuously integrate sensory information and convert it into corrective motor commands. Although this entire process naturally hinges on the reliability of early senses, very few studies have investigated early sensory acuity and its role in postural stability during development. Clarifying this could lead to a better understanding of conditions, such as developmental coordination disorder (DCD), where the impairment of balance control is substantial. Here, we tested 25 typically developed school-aged children with a Visual Motion Detection test (VMDT), an ankle Joint Position Sense test (aJPST), force-plate assessed posturography, and the Movement Assessment Battery for Children - Second edition (MABC-2). We found a significant correlation between the balance score of the MABC-2 and both VMDT score ( r = 0.60, p = 0.003) and aJPST score ( r = -0.47, p = 0.02). However, no such relationship was found between the force-plate assessed sway amplitude during upright standing and the two sensory acuity scores. Importantly, the MABC-2 balance scores were associated with upright stability, but only to a limited extent. Given that the MABC-2 balance component factors in static and dynamic balance while posturography focuses only on static balance, our results point at a key role of early sensory acuity for dynamic balance. Together, these findings bring attention to possible clinical tools for motor impairment detection and subsequent rehabilitation strategies during development.

The excitability of the sensorimotor (SM1) cortices is reflected in the bilateral ~20 Hz beta oscillations. The extent to which these oscillations subtend the interhemispheric inhibition (IHI) captured by the Transcranial Magnetic Stimulation (TMS) ipsilateral Silent Period (iSP) protocol remains unclear. Therefore, we investigated the relationship between movement-related beta suppression and the iSP, along with their role for manual dexterity. Forty adults underwent an Electroencephalography assessment of beta suppression during volitional left hand movement and a TMS assessment of iSP recorded from the right hand. In both cases, left SM1 beta oscillations (contralateral to the activated right SM1), were monitored through a proxy signal - the Electromyography of the contracted right hand. Bimanual dexterity was assessed with the Purdue Pegboard. Volitional movement caused significant bilateral SM1 beta suppression in nearly all participants (85 %). ISPs were observed in every participant. In the proxy signal for the left SM1, the iSP coincided with TMS-evoked high-amplitude beta bursts. These bursts showed significant phase alignment across participants 10-70 ms after the TMS pulse. There was no significant association between the left-/right-hemisphere beta suppression, iSP, and bimanual dexterity. Our results highlight the distinct nature of beta oscillation changes during volitional movement compared to TMS-iSP and show that TMS induces IHI via transcallosal generation of phase aligned beta bursts. Furthermore, our data suggests that only the initial phase of a beta burst carries an inhibitory effect. It also highlights the possibility of evoking a beta burst with the iSP protocol, opening perspectives for future neuroimaging and modeling studies.

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (Normal), kinematically unnatural and goal-intact (How), or kinematically natural and goal-violating (What), directed toward 15 different objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy (Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss' Kappa = 0.702), establishing excellent validity and reliability. Videos' exact timing of motion onset was identified using a custom motion detection frame-differencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos' timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framework (https://osf.io/zexc4/).

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact ( Normal ), kinematically unnatural and goal-intact ( How ), or kinematically natural and goal-violating ( What ), directed towards 15 different objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy ( Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss’ Kappa = 0.702), establishing excellent validity and reliability. Videos’ exact timing of motion onset was identified using a custom motion detection frame-differencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos’ timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framework ( https://osf.io/zexc4/ ).