Effects of beta- and gamma-band rhythmic stimulation on motor inhibition

Leunissen, Inge; M, Van Steenkiste; Heise, Kirstin; T, Santos Monteiro; Dunovan, Kyle; Mantini, Dante; Coxon, James P.; Swinnen, Stephan

doi:10.1101/2020.12.11.422006

Cited by 2 publications

(1 citation statement)

References 87 publications

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“…Increased Stop trial probability may recruit a more proactive response inhibition (Castro-Meneses et al, 2015). Some studies suggested that pre-SMA is more strongly activated during proactive response inhibition (Sharp et al, 2010;Hu et al, 2015), potentially explaining a more fronto-central signature in the external dataset (also cf., Leunissen et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition

et al. 2021

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In humans, impaired response inhibition is characteristic of a wide range of psychiatric diseases and of normal aging. It is hypothesised that the right inferior frontal cortex plays a key role by inhibiting the motor cortex via the basal ganglia. The electroencephalographyderived β-rhythm (15-29 Hz) is thought to reflect communication within this network, with increased right frontal β-power often observed prior to successful response inhibition. Recent literature suggests that averaging spectral power obscures the transient, burst-like nature of β-activity. There is evidence that the rate of β-bursts following a Stop signal is higher when a motor response is successfully inhibited. However, other characteristics of β-burst events, and their topographical properties, have not yet been examined. Here, we used a large human (male and female) electroencephalography Stop Signal Task dataset (n=218) to examine averaged normalised β-power, β-burst rate and β-burst 'volume' (which we defined as burst duration x frequency span x amplitude). We first sought to optimise the β-burst detection method. In order to find predictors across the whole scalp, and with high temporal precision, we then used machine learning to (1) classify successful vs. failed stopping and to (2) predict individual Stop Signal Reaction Time. β-Burst volume was significantly more predictive of successful and fast stopping than β-burst rate and normalised β-power. The classification model generalised to an external dataset (n=201). We suggest β-burst volume is a sensitive and reliable measure for investigation of human response inhibition. 3 Significance StatementThe electroencephalography-derived β-rhythm (15-29 Hz) is associated with the ability to inhibit ongoing actions. In this study, we sought to identify the specific characteristics of βactivity that contribute to successful and fast inhibition. In order to search for the most relevant features of β-activityacross the whole scalp and with high temporal precisionwe employed machine learning on two large datasets. Spatial and temporal features of β-burst 'volume' (duration x frequency span x amplitude) predicted response inhibition outcomes in our data significantly better than β-burst rate and normalised β-power. These findings suggest that multidimensional measures of β-bursts, such as burst volume, can add to our understanding of human response inhibition.

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Section: Discussionmentioning

confidence: 99%

Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition

et al. 2021

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Delta waves as a sign of cortical plasticity after full-face transplantation

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et al. 2024

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This study focused on detecting the reflections of healing and change in cortex activation in full-face transplantation and lesions patients on EEG activity. Face transplant patients have facial lesions before transplantation and, to identify pre-face transplant patients' brain activity in the absence of pre-transplant recordings, we used data obtained from pre-transplant facial lesion patients. Ten healthy, four facial lesion and three full-face transplant patients participated in this study. EEG data recorded for four different sensory stimuli (brush from the right face, right hand, left face, and left-hand regions) were analyzed using wavelet packet transform method. EEG waves were analyzed for standard bands. Our findings indicate significant change in the 2–4 Hz frequency range which may be a result of ongoing or previous cortical reorganization for face lesion and transplant patients. Alterations of the delta wave seen in patients with facial lesion and face transplant can also be explained by the intense central plasticity. Our findings show that the delta band differences might be used as a marker in the evaluation of post-transplant cortical plasticity in the future.

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Effects of beta- and gamma-band rhythmic stimulation on motor inhibition

Cited by 2 publications

References 87 publications

Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition

Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition

Delta waves as a sign of cortical plasticity after full-face transplantation

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