Transient beta activity and connectivity during sustained motor behaviour

Echeverria-Altuna, Irene; Quinn, Andrew; Zokaei, Nahid; Woolrich, Mark W.; Nobre, Anna C.; Ede, Freek van

doi:10.1101/2021.03.02.433514

Cited by 7 publications

(6 citation statements)

References 49 publications

(70 reference statements)

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“…Moreover, the significant β activity in the CST identified during EEG β bursting events suggested that β bursts in the MU overlapped with those present at the cortical level. This confirms previous observations made using surface EMG signals ( Echeverria-Altuna et al, 2021 ). In addition, we observed that the common input inside the β range to the MU pool was of bursting behavior and appeared to be time-locked to cortical β bursts.…”

Section: Resultssupporting

confidence: 93%

“…One possible explanation would be that subjects were able to recruit larger cortical networks involved in the projection of β activity to the muscle. It was previously shown that the duration of β bursts was not affected by the performed motor task in normal conditions ( Echeverria-Altuna et al, 2021 ). Here, we observed, although not always significant, slightly longer periods of β events during β up-modulation compared with down-modulation of MU β.…”

Section: Discussionmentioning

confidence: 88%

“…For experiment 2, it was 2.25 and 2.75 times the median for CST and EEG. Consecutive periods where the envelopes were above the threshold were marked as ON periods (β bursting events), similarly as previously performed ( Echeverria-Altuna et al, 2021 ). Hence, the length of ON periods was used to estimate the duration of β events.…”

Section: Methodsmentioning

confidence: 99%

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Reading and Modulating Cortical β Bursts from Motor Unit Spiking Activity

et al. 2022

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β Oscillations (13–30 Hz) are ubiquitous in the human motor nervous system. Yet, their origins and roles are unknown. Traditionally, β activity has been treated as a stationary signal. However, recent studies observed that cortical β occurs in “bursting events,” which are transmitted to muscles. This short-lived nature of β events makes it possible to study the main mechanism of β activity found in the muscles in relation to cortical β. Here, we assessed whether muscle β activity mainly results from cortical projections. We ran two experiments in healthy humans of both sexes ( N = 15 and N = 13, respectively) to characterize β activity at the cortical and motor unit (MU) levels during isometric contractions of the tibialis anterior muscle. We found that β rhythms observed at the cortical and MU levels are indeed in bursts. These bursts appeared to be time-locked and had comparable average durations (40–80 ms) and rates (approximately three to four bursts per second). To further confirm that cortical and MU β have the same source, we used a novel operant conditioning framework to allow subjects to volitionally modulate MU β. We showed that volitional modulation of β activity at the MU level was possible with minimal subject learning and was paralleled by similar changes in cortical β activity. These results support the hypothesis that MU β mainly results from cortical projections. Moreover, they demonstrate the possibility to decode cortical β activity from MU recordings, with a potential translation to future neural interfaces that use peripheral information to identify and modulate activity in the central nervous system. SIGNIFICANCE STATEMENT We show for the first time that β activity in motor unit (MU) populations occurs in bursting events. These bursts observed in the output of the spinal cord appear to be time-locked and share similar characteristics of β activity at the cortical level, such as the duration and rate at which they occur. Moreover, when subjects were exposed to a novel operant conditioning paradigm and modulated MU β activity, cortical β activity changed in a similar way as peripheral β. These results provide evidence for a strong correspondence between cortical and peripheral β activity, demonstrating the cortical origin of peripheral β and opening the pathway for a new generation of neural interfaces.

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Section: Resultssupporting

confidence: 93%

Section: Discussionmentioning

confidence: 88%

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Reading and Modulating Cortical β Bursts from Motor Unit Spiking Activity

et al. 2022

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“…These variations in burst probability are reflected in the slow changes in average spectral power (Feingold et al, 2015; Howe et al, 2011; Little et al, 2019; Rayson et al, 2022; Sherman et al, 2016), but suggest that single trial beta activity is more dynamic than classically thought. The rate and timing of single-trial beta events are tightly linked to behavior (Diesburg et al, 2021; Echeverria-Altuna et al, 2021; Enz et al, 2021; Feingold et al, 2015; Haufler et al, 2022; Heideman et al, 2020; Howe et al, 2011; Karvat et al, 2020; Khawaldeh et al, 2020; Kosciessa et al, 2020; Law et al, 2022; Little et al, 2019; Sherman et al, 2016; Shin et al, 2017; Sporn et al, 2020; Torrecillos et al, 2018; Walsh et al, 2022; Wessel, 2020; West et al, 2022), and are more predictive of response time and accuracy than average beta amplitude (Enz et al, 2021; Little et al, 2019). This shift in perspective from trial-averaged beta power to transient burst events has thus allowed for more fine-grained analyses of their relationship to behavior, but the functional role of beta bursts themselves is still unclear.…”

Section: Introductionmentioning

confidence: 99%

Diverse beta burst waveform motifs characterize movement-related cortical dynamics

Szul

Papadopoulos

Alavizadeh

et al. 2022

Preprint

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Classical analyses of induced, frequency-specific neural activity typically average band-limited power over trials. More recently, it has become widely appreciated that in individual trials, beta band activity occurs as transient bursts rather than amplitude-modulated oscillations. Most studies of beta bursts treat them as unitary, and having a stereotyped waveform. However, we show there is a wide diversity of burst shapes. Using a biophysical model of burst generation, we demonstrate that waveform variability is predicted by variability in the synaptic drives that generate beta bursts. We then use a novel, adaptive burst detection algorithm to identify bursts from human MEG sensor data recorded during a joystick-based reaching task, and apply principal component analysis to burst waveforms to define a set of dimensions, or motifs, that best explain waveform variance. Finally, we show that bursts with a particular range of waveform motifs, ones not fully accounted for by the biophysical model, differentially contribute to movement-related beta dynamics. Sensorimotor beta bursts are therefore not homogeneous events and likely reflect distinct computational processes.

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“…Under these conditions, both cortical beta power and corticomuscular coherence are physiologically elevated, and this may have prevented these measures to be further enhanced by TACS given at beta. Given the large fluctuations that beta activity presents in the corticospinal system during sustained contractions (Echeverria-Altuna et al, 2021;Torrecillos et al, 2014), we consider that this factor should not have a major effect on our results.…”

Section: Discussionmentioning

confidence: 97%