Changes in non-oscillatory features of the cortical sensorimotor rhythm in Parkinson’s disease across age

Abstract

Parkinson's disease (PD) is associated with functional changes in the neural activity within the brain's sensorimotor network, which in turn are related to the characteristic motor symptoms in PD. The functional changes in PD are particularly prominent in terms of oscillatory neuronal activity in the characteristic sensorimotor alpha and beta rhythms. However, summaries in terms of alpha or beta power do not capture the full range of the complex dynamic nature of the signals from the somatosensory cortex. This raises the question of how to quantify and summarise the functional changes in such oscillatory features in a manner that captures the relevant disease- and symptom-related neural activity. We investigated the role of spontaneous cortical somatosensory activity in the electrophysiological alpha and beta bands among a cohort of early- to mid-stage PD patients (N=78) and age- and gender-matched healthy controls (N=60) using source reconstructed resting-state magnetoencephalography (MEG) recordings. We quantified the oscillatory features of the neural time series by its oscillatory alpha power, beta power, and 1/f broadband characteristics using power spectral density, and additionally by characterising "burst" properties in the signals. We examined the relationship between the signal features and disease state, age, sex, and cortical thickness. Using multiple regression, we examined the relative contribution of the oscillatory features on the clinical manifestation of motor symptoms in the PD group. Our results show that PD patients differ from healthy controls on several of the oscillatory features, showing higher beta-band power, higher burst amplitude, and steeper 1/f broadband characteristics compared to healthy controls, as well as a steeper age-related decrease in the bursts rate. While there was a high degree of correlation between some of the oscillatory features, several features also appeared functionally separated, showing independent feature-to-symptom relationships. For instance, oscillatory beta power increased with the severity of midline function symptoms, while burst rate decreased with the severity of bradykinesia. Our study shows that quantification of distinct features within the oscillatory sensorimotor neural time series in PD captures different underlying mechanisms related to disease progression and symptom severity, which in turn has a potential for a more individualised and precision-based approach to assessing functional neural changes in PD.

Cortex-wide topography of 1/f-exponent in Parkinson’s disease

“…Previously, Vinding et al 36 analysed the same data for 1/f slope (λ) but that analysis was restricted to the sensorimotor association regions. Consistent with our results, they also found that λ was positively correlated with age in PD patients but not in HC and the correlation between λ and UPDRS-III was not significant.…”

“…To the best of our knowledge, there is no consensus on the cortical effects of Levodopa. 36 In our study, a possible reason could be the short time (1 hour) between taking the medication and recording of MEG. A recent study by Wang et al 13 reported changes in the λ estimated from EEG.…”

Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years

“…On one hand, gradual flattening is typically associated with poorer performance – potentially reflecting an excess of excitatory to inhibitory activity, resulting in elevated noise. However, many diseases, such as Parkinson’s Disease, are characterized by an excess of inhibitory activity, and previous studies have emphasized that excessive inhibitory activity reduces behavioral flexibility (Song et al, 2021; Vinding et al, 2022; McKeown et al, 2023). These results hint at the importance of considering excitatory:inhibitory balance within an individual differences context, as what is optimal may differ based on a variety of neuroanatomical and physiological parameters.…”

Dopamine depletion can be predicted by the aperiodic component of subthalamic local field potentials

“…Furthermore, the decreased aperiodic parameters in PD animals conflict with a previous result that aperiodic parameters increased, based on MEG recordings in the somatosensory cortex during the resting state, in PD patients. 30 To circumvent these discrepancies, future studies should involve neural recordings during the awake state in multiple species, such as nonhuman primates and humans.…”

“…28,29 In a clinical study, the aperiodic offset and exponent increased, assessed with magnetoencephalography (MEG) recordings in the somatosensory cortex during the resting state, in PD patients compared to controls. 30 Specifically, the slope of the broadband (exponent) decreased while patients were engaged in voluntary movements 23 , and the aperiodic offset decreased in relation to cognitive states while patients were performing a visual working memory task. 24 Although the relationship between the aperiodic component and PD exists, it has not been conclusively demonstrated that the aperiodic component can be used as a biomarker reflecting pathological activities in the basal ganglia in PD.…”