Fast and effective removal of contamination from scalp electrical recordings.

Objective: To present a new, automated and fast artefact-removal approach which significantly reduces the effect of contamination in scalp electrical recordings.

Method: We used spectral and temporal characteristics of different sources recorded during a typical scalp electrical recording in order to improve a fast and effective artefact removal approach. Our experiments show that correlation coefficient and spectral gradient of brain components differ from artefactual components.

Evaluation of a minimum-norm based beamforming technique, sLORETA, for reducing tonic muscle contamination of EEG at sensor level.

Background: Cranial and cervical muscle activity (electromyogram, EMG) contaminates the surface electroencephalogram (EEG) from frequencies below 20 through to frequencies above 100Hz. It is not possible to have a reliable measure of cognitive tasks expressed in EEG at gamma-band frequencies until the muscle contamination is removed.

New Method: In the present work, we introduce a new approach of using a minimum-norm based beamforming technique (sLORETA) to reduce tonic muscle contamination at sensor level.

A comparison of independent component analysis algorithms and measures to discriminate between EEG and artifact components.

Independent Component Analysis (ICA) is a powerful statistical tool capable of separating multivariate scalp electrical signals into their additive independent or source components, specifically EEG or electroencephalogram and artifacts. Although ICA is a widely accepted EEG signal processing technique, classification of the recovered independent components (ICs) is still flawed, as current practice still requires subjective human decisions. Here we build on the results from Fitzgibbon et al.

Electroencephalographic correlates of states of concentrative meditation.

Meditative techniques aim for and meditators report states of mental alertness and focus, concurrent with physical and emotional calm. We aimed to determine the electroencephalographic (EEG) correlates of five states of Buddhist concentrative meditation, particularly addressing a correlation with meditative level. We studied 12 meditators and 12 pair-matched meditation-naïve participants using high-resolution scalp-recorded EEG.

Constitutive spectral EEG peaks in the gamma range: suppressed by sleep, reduced by mental activity and resistant to sensory stimulation.

Objective: In a systematic study of gamma activity in neuro-psychiatric disease, we unexpectedly observed distinctive, apparently persistent, electroencephalogram (EEG) spectral peaks in the gamma range (25-100 Hz). Our objective, therefore, was to examine the incidence, distribution and some of the characteristics of these peaks.

Methods: High sample-rate, 128-channel, EEG was recorded in 603 volunteers (510 with neuropsychiatric disorders, 93 controls), whilst performing cognitive tasks, and converted to power spectra.

Visual Experiences during Paralysis.

Rationale: Paralyzed human volunteers (n = 6) participated in several studies the primary one of which required full neuromuscular paralysis while awake. After the primary experiment, while still paralyzed and awake, subjects undertook studies of humor and of attempted eye-movement. The attempted eye-movements tested a central, intentional component to one's internal visual model and are the subject of this report.

Thinking activates EMG in scalp electrical recordings.

Objective: Fast electrical rhythms in the gamma range (30-100Hz) in scalp (but not intracranial) recordings are predominantly due to electromyographic (EMG) activity. We hypothesized that increased EMG activity would be augmented by mental tasks in proportion to task difficulty and the requirement of these tasks for motor or visuo-motor output.

Methods: EEG was recorded in 98 subjects whilst performing cognitive tasks and analysed to generate power spectra.

Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG.

Objective: To identify the possible contribution of electromyogram (EMG) to scalp electroencephalogram (EEG) rhythms at rest and induced or evoked by cognitive tasks.

Methods: Scalp EEG recordings were made on two subjects in presence and absence of complete neuromuscular blockade, sparing the dominant arm. The subjects undertook cognitive tasks in both states to allow direct comparison of electrical recordings.