Diverse beta burst waveform motifs characterize movement-related cortical dynamics

Abstract

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.

Healthy ageing influences how the shape of alpha and beta oscillations change during reaction time tasks

“…Taken together, IF profiles and mean vectors suggest that alpha and beta cycles exist across a wide range of shapes. This is consistent with recent findings for oscillations in theta (Quinn et al 2021b) and beta (Szul et al 2022, Rayson et al 2023) bands.…”

“…Given recent evidence for temporal variance in waveform shape during a motor task (Szul et al 2022, Rayson et al 2023), a time factor was included for all analyses of cycle features. This categorised cycles as occurring either before (pre-go) or after (post-go) the go stimulus, or after the button press (post-react).…”

“…For example, recent work suggests that a given oscillatory cycle can be characterised relative to a range of waveform motifs, with cycle-by-cycle variations in the relative contribution of different motifs driving variability in shape (Quinn et al . 2021b, Szul et al . 2022, Rayson et al .…”

“…2022, Rayson et al . 2023) and having different relationships with movement (Szul et al 2022, Rayson et al 2023) and function (Quinn et al 2021b). Furthermore, research in Parkinson’s disease supports the clinical utility of examining waveform shape.…”

Spatiotemporal organisation of human sensorimotor beta burst activity

“…These burst metrics are not exhaustive. Other second-level burst characteristics include the interaction between frequency centre and spatial location ( Zich et al, 2020 ), waveform variability ( Szul et al, 2022 ), and the variability of the first-level burst characteristics, such as the variability in (instantaneous) frequency, within and across bursts. Future work may address the variability and temporal stability of bursts, for example, using methods such as empirical mode decomposition ( Huang et al, 1998 ).…”