Biology subjects

Rayson, H.

Publications and source records attributed to Rayson, H..

3 recordsLinked to original sources

bioRxiv2025

Sensorimotor beta burst dynamics and interhemispheric connectivity in children with developmental coordination disorder

Activity in the beta frequency band appears to play a critical role in sensorimotor processing, with transient bursts exhibiting distinct waveform motifs that may reflect different neural computations. However, how these dynamics relate to motor development and neurodevelopmental conditions remains unclear. Here, we used EEG to investigate sensorimotor beta bursts in children with and without developmental coordination disorder (DCD). We characterized beta bursts during action execution and observation of gross and fine motor actions. Conventional spectral features and overall burst rates did not differ between groups. In contrast, children with DCD showed altered rate modulation of specific burst waveform motifs, including atypical hemispheric lateralization and disrupted interhemispheric connectivity. Critically, motif-specific burst rates were systematically related to motor performance across individuals, with similar relations observed across groups. These findings indicate that waveform-specific beta burst dynamics track graded variation in motor performance, rather than mapping selectively onto diagnostic status. Beta burst variability may therefore reflect the functional expression of motor performance, rather than a disorder-specific neural mechanism underlying DCD. This work highlights the importance of beta burst waveform diversity for understanding variability in sensorimotor function across development.

neuroscience↗

bioRxiv2024

Multi-scale parameterization of neural rhythmicity with lagged Hilbert autocoherence

Analysis of neural activity in different frequency bands is ubiquitous in systems and cognitive neuroscience. Recent analytical breakthroughs and theoretical developments rely on phase maintenance of oscillatory signals without considering whether or not this assumption is met. Lagged (auto)coherence, the coherence between a signal and itself at increasing temporal delays, has been proposed as a way to quantify the rhythmicity, or periodicity, of a signal. However, current Fourier-based lagged autocoherence algorithms suffer from poor spectral accuracy and resolution, aliasing effects that become more pronounced at higher frequencies, and conflation with amplitude covariation, especially in frequency ranges in which the signal-to-noise ratio is low. We introduce a continuous estimator, lagged Hilbert autocoherence (LHaC), which addresses these limitations by using multiplication in the frequency domain for precise bandpass filtering, computing instantaneous analytic signals via the Hilbert transform, and thresholding using the amplitude covariation of phase-shuffled surrogate data. While LHaC and lagged Fourier autocoherence (LFaC) estimate distinct theoretical quantities, we compare their empirical behavior in simulations with controlled rhythmic structure. These analyses show that LHaC provides more spectrally resolved estimates of rhythmicity and is more sensitive to the duration of transient, short-lived oscillatory events. We further demonstrate the utility of LHaC for identifying frequency-specific differences in rhythmicity between conditions and tracking learning-related changes in neural oscillations. Lagged Hilbert autocoherence thus offers a refined and practically useful approach to characterizing neurophysiological rhythmicity.

neuroscience↗

bioRxiv2023

Bursting with potential: How sensorimotor beta bursts develop from infancy to adulthood

Beta activity is thought to play a critical role in sensorimotor processes. However, little is known about how activity in this frequency band develops. Here, we investigated the developmental trajectory of sensorimotor beta activity from infancy to adulthood. We recorded electroencephalography (EEG) from adults, 12-month-olds, and 9-month-olds while they observed and executed grasping movements. We analysed beta burst activity using a novel method that combines time-frequency decomposition and principal component analysis (PCA). We then examined the changes in burst rate and waveform motifs along the selected principal components. Our results reveal systematic changes in beta activity during action execution across development. We found a decrease in beta burst rate during movement execution in all age groups, with the greatest decrease observed in adults. Additionally, we identified four principal components that defined waveform motifs that systematically changed throughout the trial. We found that bursts with waveform shapes closer to the median waveform were not rate-modulated, whereas those with waveform shapes further from the median were differentially rate-modulated. Interestingly, the decrease in the rate of certain burst motifs occurred earlier during movement and was more lateralized in adults than in infants, suggesting that the rate modulation of specific types of beta bursts becomes increasingly refined with age.

neuroscience↗