Reconstruction of electroencephalographic data using radial basis functions

Jäger, Janin; Klein, Alexander; Buhmann, Martin D.; Skrandies, Wolfgang

doi:10.1016/j.clinph.2016.01.003

Cited by 17 publications

(9 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This step was not necessary in the NO and STN groups. Channels showing a bad signal were interpolated (mean: 2.3 channels) using multiquadric interpolation relying on radial basis functions (Buhmann & Jäger, 2019 ; Jäger, Klein, Buhmann, & Skrandies, 2016 ). Epochs with at least one time‐frame ±80 μV were automatically rejected and the remaining epochs were averaged across trial for each cue separately.…”

Section: Methodsmentioning

confidence: 99%

Proactive inhibition is not modified by deep brain stimulation for Parkinson's disease: An electrical neuroimaging study

Pretto

Mouthon

Debove

et al. 2021

Human Brain Mapping

View full text Add to dashboard Cite

In predictable contexts, motor inhibitory control can be deployed before the actual need for response suppression. The brain functional underpinnings of proactive inhibition, and notably the role of basal ganglia, are not entirely identified. We investigated the effects of deep brain stimulation of the subthalamic nucleus or internal globus pallidus on proactive inhibition in patients with Parkinson's disease. They completed a cued go/no-go proactive inhibition task ON and (unilateral) OFF stimulation while EEG was recorded. We found no behavioural effect of either subthalamic nucleus or internal globus pallidus deep brain stimulation on proactive inhibition, despite a general improvement of motor performance with subthalamic nucleus stimulation. In the non-operated and subthalamic nucleus group, we identified periods of topographic EEG modulation by the level of proactive inhibition. In the subthalamic nucleus group, source estimation analysis suggested the initial involvement of bilateral frontal and occipital areas, followed by a right lateralized fronto-basal network, and finally of right premotor and left parietal regions. Our results confirm the overall preservation of proactive inhibition capacities in both subthalamic nucleus and internal globus pallidus deep brain stimulation, and suggest a partly segregated network for proactive inhibition, with a preferential recruitment of the indirect pathway.

show abstract

Section: Methodsmentioning

confidence: 99%

Proactive inhibition is not modified by deep brain stimulation for Parkinson's disease: An electrical neuroimaging study

Pretto

Mouthon

Debove

et al. 2021

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…In the last five years there has been a tremendous amount of publications stating new results on positive definite functions on spheres, see for example [1, 4-6, 9, 13, 17, 19, 20]. Isotropic positive definite functions are used in approximation theory, where they are often referred to as spherical radial basis functions [2,3,12,22] and are for example applied in geostatistics and physiology [8,14]. They are also of importance in statistics where they occur as correlation functions of homogeneous random fields on spheres [15].…”

Section: Introduction and Main Resultsmentioning

confidence: 99%

A Note on the Derivatives of Isotropic Positive Definite Functions on the Hilbert Sphere

Jäger

2019

SIGMA

Self Cite

View full text Add to dashboard Cite

In this note we give a recursive formula for the derivatives of isotropic positive definite functions on the Hilbert sphere. We then use it to prove a conjecture stated by Trübner and Ziegel, which says that for a positive definite functions on the Hilbert sphere to be in C 2 ([0, π]), it is necessary and sufficient for its ∞-Schoenberg sequence to satisfy ∞ m=0 a m m < ∞. key words: positive definite, isotropic, Hilbert sphere, Schoenberg sequences 2010 MSC: 33B10; 33C45; 42A16; 42A82; 42C10 arXiv:1905.08655v1 [math.CA]

show abstract

“…Heat maps were calculated to provide a topographic impression of the myogenic activity distribution over the face for both schemes. A modified 4-nearest neighbor interpolation of the EMG RMS values was used similar to the EEG mapping with the inverse square of the distance as weight (Jäger et al, 2016). Interpolation in EEG mapping is often performed on the basis of spherical functions because the conducting area in EEG is approximately a hemisphere (Lehmann, 1992).…”

Section: Heat Maps For Visualization Of the Semg Activitymentioning

confidence: 99%

High-resolution surface electromyographic activities of facial muscles during mimic movements in healthy adults: A prospective observational study

Mueller

Trentzsch

Grassme

et al. 2022

Front. Hum. Neurosci.

View full text Add to dashboard Cite

ObjectivesSurface electromyography (sEMG) is a standard tool in clinical routine and clinical or psychosocial experiments also including speech research and orthodontics to measure the activity of selected facial muscles to objectify facial movements during specific facial exercises or experiments with emotional expressions. Such muscle-specific approaches neglect that facial muscles act more as an interconnected network than as single facial muscles for specific movements. What is missing is an optimal sEMG setting allowing a synchronous measurement of the activity of all facial muscles as a whole.MethodsA total of 36 healthy adult participants (53% women, 18–67 years) were included. Electromyograms were recorded from both sides of the face using an arrangement of electrodes oriented by the underlying topography of the facial muscles (Fridlund scheme) and simultaneously by a geometric and symmetrical arrangement on the face (Kuramoto scheme). The participants performed a standard set of different facial movement tasks. Linear mixed-effects models and adjustment for multiple comparisons were used to evaluate differences between the facial movement tasks, separately for both applied schemes. Data analysis utilized sEMG amplitudes and also their maximum-normalized values to account for amplitude differences between the different facial movements.ResultsSurface electromyography activation characteristics showed systematic regional distribution patterns of facial muscle activation for both schemes with very low interindividual variability. The statistical significance to discriminate between the different sEMG patterns was good for both schemes (significant comparisons for sEMG amplitudes: 87.3%, both schemes, normalized values: 90.9%, Fridlund scheme, 94.5% Kuramoto scheme), but the Kuramoto scheme performed considerably superior.ConclusionFacial movement tasks evoke specific patterns in the complex network of facial muscles rather than activating single muscles. A geometric and symmetrical sEMG recording from the entire face seems to allow more specific detection of facial muscle activity patterns during facial movement tasks. Such sEMG patterns should be explored in more clinical and psychological experiments in the future.

show abstract

Reconstruction of electroencephalographic data using radial basis functions

Cited by 17 publications

References 15 publications

Proactive inhibition is not modified by deep brain stimulation for Parkinson's disease: An electrical neuroimaging study

Proactive inhibition is not modified by deep brain stimulation for Parkinson's disease: An electrical neuroimaging study

A Note on the Derivatives of Isotropic Positive Definite Functions on the Hilbert Sphere

High-resolution surface electromyographic activities of facial muscles during mimic movements in healthy adults: A prospective observational study

Contact Info

Product

Resources

About