Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG

Mullen, Tim; Kothe, Christian; Mike, Yu; Ojeda, Alejandro; Kerth, Trevor; Makeig, Scott; Cauwenberghs, Gert; Jung, Tzyy-Ping

doi:10.1109/embc.2013.6609968

Cited by 309 publications

(261 citation statements)

References 12 publications

(14 reference statements)

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“…Offline MMN analysis was conducted with Brain Vision Analyzer 2.0 (Brain Products, Munich, Germany) and EEGlab Version v13.1.1 [53]. Artifacts were automatically corrected using the eeglab-plugins Artifact Subspace Reconstruction Version 0.13 [54] and Automatic Artifact Removal Version 1.3 [55] for short-term artifacts, e.g. ocular movements and electrocardiac artifacts.…”

Section: Methodsmentioning

confidence: 99%

Reduced Sensitivity to Non-Fear-Related Stimulus Changes in Panic Disorder

et al. 2019

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Panic disorder (PD) is associated with increased body vigilance and reduced cognitive resources directed at non-fear-related stimuli, particularly in the absence of stimulus-rich environments. To date, only few studies have investigated whether this deficit in PD is reflected in reduced mismatch negativity (MMN), an event-related potential indexing preattentive sensitivity to unexpected stimulus changes. We tested 35 patients affected by PD and 42 matched healthy controls in an oddball paradigm, using frequency and duration deviant stimuli to measure auditory MMN. PD patients displayed reduced duration MMN amplitudes in comparison to healthy controls. No group differences were detected for duration MMN latency, as well as frequency MMN indices. Results support the notion of reduced processing of non-fear-related stimuli in PD patients, particularly with regard to the preattentive processing of sound duration deviants. Additionally, our findings are in line with clinical studies reporting divergent deficits in preattentive processing of frequency and duration deviants.

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Section: Methodsmentioning

confidence: 99%

Reduced Sensitivity to Non-Fear-Related Stimulus Changes in Panic Disorder

et al. 2019

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“…The data was preprocessed by using a 3 rd order zero-phase Butterworth band-pass filter to constrain it to the delta-band (1-4Hz), and standardized by subtracting the mean and dividing by the standard deviation. High-amplitude artifacts were removed automatically using the Artifact Subspace Removal (ASR) method 17 . Additionally, peripheral channels are excluded from the data analysis in an effort to minimize myoelectric artifact contamination.…”

Section: Representative Resultsmentioning

confidence: 99%

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Cruz-Garza

Hernandez

Tse

et al. 2015

JoVE

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Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental paradigms and analysis tools have been limited to constrained laboratory tasks and contexts due to technical limitations imposed by the available set of measuring and analysis techniques and the age of the subjects. These limitations severely limit the study of developmental neural dynamics and associated neural networks engaged in cognition, perception and action in infants performing "in action and in context". This protocol presents a novel approach to study infants and young children as they freely organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment. The proposed methodology integrates synchronized highdensity active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. This setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.

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“…EEG was re-referenced to average reference. Artifact Subspace Reconstruction [35] was used to clean eye blink, muscle movement artifacts and reject bad time windows. This method works using sliding window Principal Component Analysis (PCA), which estimates the signal values of high-variance components exceeding a threshold relative to a covariance matrix calculated using 1 minute of empirically determined clean data.…”

Section: Methodsmentioning

confidence: 99%

Quantifying and Characterizing Tonic Thermal Pain Across Subjects From EEG Data Using Random Forest Models

Vijayakumar

Case

Shirinpour

et al. 2017

IEEE Trans. Biomed. Eng.

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Objective Effective pain assessment and management strategies are needed to better manage pain. In addition to self-report, an objective pain assessment system can provide a more complete picture of the neurophysiological basis for pain. In this study, a robust and accurate machine learning approach is developed to quantify tonic thermal pain across healthy subjects into a maximum of ten distinct classes. Methods A random forest model was trained to predict pain scores using time-frequency wavelet representations of independent components obtained from electroencephalography (EEG) data, and the relative importance of each frequency band to pain quantification is assessed. Results The mean classification accuracy for predicting pain on an independent test subject for a range of 1–10 is 89.45%, highest among existing state of the art quantification algorithms for EEG. The gamma band is the most important to both inter-subject and intra-subject classification accuracy. Conclusion The robustness and generalizability of the classifier is demonstrated. Significance Our results demonstrate the potential of this tool to be used clinically to help improve chronic pain treatment, and establish spectral biomarkers for future pain-related studies using EEG.

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Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG

Cited by 309 publications

References 12 publications

Reduced Sensitivity to Non-Fear-Related Stimulus Changes in Panic Disorder

Reduced Sensitivity to Non-Fear-Related Stimulus Changes in Panic Disorder

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

Quantifying and Characterizing Tonic Thermal Pain Across Subjects From EEG Data Using Random Forest Models

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