Distortions in EEG interregional phase synchrony by spherical spline interpolation: causes and remedies

Kang, Seung Suk; Lano, Timothy J.; Sponheim, Scott R.

doi:10.1186/s40810-015-0009-5

Cited by 25 publications

(15 citation statements)

References 28 publications

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“…Bad channels were also identified based on visual inspection and were replaced using spherical spline interpolation (SSI; Perrin et al 1989); a widely used method for estimating missing data values in arrays with more than 65 electrodes (Ferree 2006). It estimates missing data using spatially weighted existing values that are approximated to positions on a sphere (Ferree 2006; Kang et al 2015). In this study, the mean number of channels interpolated per participant was 1.82 (range 0–5).…”

Section: Methodsmentioning

confidence: 99%

Dynamic Causal Modeling of the Relationship between Cognition and Theta–alpha Oscillations in Adults with Down Syndrome

et al. 2019

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Individuals with Down syndrome (DS) show high inter-subject variability in cognitive ability and have an ultra-high risk of developing dementia (90% lifetime prevalence). Elucidating factors underlying variability in cognitive function can inform us about intellectual disability (ID) and may improve our understanding of factors associated with later cognitive decline. Increased neuronal inhibition has been posited to contribute to ID in DS. Combining electroencephalography (EEG) with dynamic causal modeling (DCM) provides a non-invasive method for investigating excitatory/inhibitory mechanisms. Resting-state EEG recordings were obtained from 36 adults with DS with no evidence of cognitive decline. Theta–alpha activity (4–13 Hz) was characterized in relation to general cognitive ability (raw Kaufmann’s Brief Intelligence Test second Edition (KBIT-2) score). Higher KBIT-2 was associated with higher frontal alpha peak amplitude and higher theta–alpha band power across distributed regions. Modeling this association with DCM revealed intrinsic self-inhibition was the key network parameter underlying observed differences in 4–13 Hz power in relation to KBIT-2 and age. In particular, intrinsic self-inhibition in right V1 was negatively correlated with KBIT-2. Results suggest intrinsic self-inhibition within the alpha network is associated with individual differences in cognitive ability in adults with DS, and may provide a potential therapeutic target for cognitive enhancement.

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Section: Methodsmentioning

confidence: 99%

Dynamic Causal Modeling of the Relationship between Cognition and Theta–alpha Oscillations in Adults with Down Syndrome

et al. 2019

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“…Artifact correction and data preprocessing. Following visual inspection, any noisy EEG channel was marked as bad (average=4.5, min=0, max=10) and interpolated using a spherical spline algorithm (Perrin et al, 1989) with an interpolation order m=3, a Legendre polynomial order n=50, and a regularization parameter λ = 10e-8 (Kang et al, 2015). Correction of eye blink artifacts in the EEG data was performed using a classical PCA filtering algorithm (Wallstrom et al, 2004) on 800ms windows with 400ms overlap.…”

Section: Behavior Analysismentioning

confidence: 99%

The Human Dynamic Clamp reveals the fronto-parietal network linking real-time social coordination and cognition

Dumas

Moreau

Tognoli

et al. 2019

Preprint

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How does the brain allow us to interact with others, and above all how does it handle situations when the goals of the interactors overlap (i.e. cooperation) or differ (i.e. competition)? Social neuroscience has already provided some answers to these questions but has tended to treat highlevel, cognitive interpretations of social behavior separately from the sensorimotor mechanisms upon which they rely. The goal here is to identify the underlying neural processes and mechanisms linking sensorimotor coordination and intention attribution. We combine the Human Dynamic Clamp (HDC), a novel paradigm for studying realistic social behavior between self and other in well-controlled laboratory conditions, with high resolution electroencephalography (EEG). The collection of humanness and intention attribution reports, kinematics and neural data affords an opportunity to relate brain activity to the behavior of the HDC as well as to what the human is doing. Behavioral results demonstrate that sensorimotor coordination influences judgements of cooperativeness and humanness. Analysis of brain dynamics reveals two distinct networks related to integration of visuo-motor information from self and other. The two networks overlap over the right parietal region, an area known to be important for interpersonal motor interactions. Furthermore, connectivity analysis highlights how the judgement of humanness and cooperation of others modulate the connection between the right parietal hub and prefrontal cortex. These results reveal how distributed neural dynamics integrates information from 'low-level' sensorimotor mechanisms and 'high-level' social cognition to support the realistic social behaviors that play out in real time during interactive scenarios. Significance StatementDaily social interactions require us to coordinate with others and to reflect on their potential motives. This study investigates the brain and behavioral dynamics of these two key aspects of social cognition. Combining high-density electroencephalography and the Human Dynamic Clamp (a Virtual Partner endowed with human-based coordination dynamics), we show first, that several features of sensorimotor coordination influence attribution of intention and judgement of humanness; second, that the right parietal lobe is a key integration hub between information related to self-and other-behavior; and third, that the posterior online social hub is functionally coupled to anterior offline brain structures to support mentalizing about others. Our results stress the complementary nature of low-level and high-level mechanisms that underlie social cognition.

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“…Subsequently, missing channels, which had been rejected by the early noise reduction procedure, were interpolated using the spherical spline method (Perrin et al, 1989) implemented in the Fieldtrip toolbox (Oostenveld et al, 2011). The regularization parameter and the order of interpolation were set to 10 -8 and 3, respectively, because these values lead to fewer distortions in temporal features of interpolated channels (Kang et al, 2015). Lastly, to avoid residual artifacts not accounted for by ICA, the epochs with maximum absolute amplitude higher than 70uV in any channel were removed.…”

Section: Preprocessingmentioning

confidence: 99%

Improving source modeling of auditory steady-state responses with frequency-specific brain maps

Farahani

Wouters

Wieringen

2019

Preprint

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Auditory steady-state responses (ASSRs) are evoked brain responses to modulated or repetitive acoustic stimuli. Due to a wide range of clinical and research applications, there is a great (clinical) interest to investigate the underlying neural generators of ASSRs. The cortical sources of ASSRs mostly are located in the auditory cortex (AC), although some studies avoiding prior assumptions regarding the number and location of the sources have also reported activity of sources outside of the AC. However, little is known about the number and location of these sources. In this study, we present a novel extension to minimum-norm imaging (MNI) which facilitates ASSR source reconstruction and provides a comprehensive and consistent picture of sources in response to low-as well as high modulation frequencies, monaurally presented to the left and right ears. Results demonstrate that the proposed MNI approach is successful in reconstructing sources located both within (primary) and outside (non-primary) of the AC. The locations of the non-primary sources are consistent with the literature. Primary sources are detected in every experimental condition, thereby corroborating the robustness of the approach. Moreover, we show that the MNI approach is capable of reconstructing the subcortical activities of ASSRs. In summary, the results indicate that the MNI approach outperforms the previously used method of group-ICA, in terms of detection of sources in the AC, reconstructing the subcortical activities and reducing computational load.

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Distortions in EEG interregional phase synchrony by spherical spline interpolation: causes and remedies

Cited by 25 publications

References 28 publications

Dynamic Causal Modeling of the Relationship between Cognition and Theta–alpha Oscillations in Adults with Down Syndrome

Dynamic Causal Modeling of the Relationship between Cognition and Theta–alpha Oscillations in Adults with Down Syndrome

The Human Dynamic Clamp reveals the fronto-parietal network linking real-time social coordination and cognition

Improving source modeling of auditory steady-state responses with frequency-specific brain maps

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