Managing electromyogram contamination in scalp recordings: An approach identifying reliable beta and gamma EEG features of psychoses or other disorders.

OBJECTIVE: In publications on the electroencephalographic (EEG) features of psychoses and other disorders, various methods are utilized to diminish electromyogram (EMG) contamination. The extent of residual EMG contamination using these methods has not been recognized. Here, we seek to emphasize the extent of residual EMG contamination of EEG. METHODS: We compared scalp electrical recordings after applying different EMG-pruning methods with recordings of EMG-free data from 6 fully paralyzed healthy subjects. We calculated the ratio of the power of pruned, normal scalp electrical recordings in the six subjects, to the power of unpruned recordings in the same subjects when paralyzed. We produced "contamination graphs" for different pruning methods. RESULTS: EMG contamination exceeds EEG signals progressively more as frequencies exceed 25 Hz and with distance from the vertex. In contrast, Laplacian signals are spared in central scalp areas, even to 100 Hz. CONCLUSION: Given probable EMG contamination of EEG in psychiatric and other studies, few findings on beta- or gamma-frequency power can be relied upon. Based on the effectiveness of current methods of EEG de-contamination, investigators should be able to reanalyze recorded data, reevaluate conclusions from high-frequency EEG data, and be aware of limitations of the methods.

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. We trained two binary support vector machine classifiers such that one separates brain components from muscle components, and the other separates brain components from mains power and environmental components. We compared the performance of the proposed approach with seven currently used alternatives on three datasets, measuring mains power artefact reduction, muscle artefact reduction and retention of brain neurophysiological responses. RESULTS: The proposed approach significantly reduces the main power and muscle contamination from scalp electrical recording without affecting brain neurophysiological responses. None of the competitors outperformed the new approach. CONCLUSIONS: The proposed approach is the best choice for artefact reduction of scalp electrical recordings. Further improvements are possible with improved component analysis algorithms. SIGNIFICANCE: This paper provides a definitive answer to an important question: Which artefact removal algorithm should be used on scalp electrical recordings?

Resting cranial and upper cervical muscle activity is increased in patients with migraine.

OBJECTIVE: To compare comprehensive measures of scalp-recorded muscle activity in migraineurs and controls. METHOD: We used whole-of-head high-density scalp electrical recordings, independent component analysis (ICA) and spectral slope of the derived components, to define muscle (electromyogram-containing) components. After projecting muscle components back to scalp, we quantified scalp spectral power in the frequency range, 52-98 Hz, reflecting muscle activation. We compared healthy subjects (n = 65) and migraineurs during a non-headache period (n = 26). We also examined effects due to migraine severity, gender, scalp-region and task (eyes-closed and eyes-open). We could not examine the effect of pre-ictal versus inter-ictal versus post-ictal as this information was not available in the pre-existing dataset. RESULTS: There was more power due to muscle activity (mean ±â€¯SEM) in migraineurs than controls (respectively, -13.61 ±â€¯0.44 dB versus -14.73 ±â€¯0.24 dB, p = 0.028). Linear regression showed no relationship between headache frequency and muscle activity in any combination of region and task. There was more power during eyes-open than eyes-closed (respectively, -13.42 ±â€¯0.34 dB versus -14.92 ±â€¯0.34 dB, p = 0.002). CONCLUSIONS: There is an increase in cranial and upper cervical muscle activity in non-ictal migraineurs versus controls. This raises questions of the role of muscle in migraine, and the possible differentiation of non-ictal phases. SIGNIFICANCE: This provides preliminary evidence to date of possible cranial muscle involvement in migraine.

Improved artefact removal from EEG using Canonical Correlation Analysis and spectral slope.

BACKGROUND: Contamination of scalp measurement by tonic muscle artefacts, even in resting positions, is an unavoidable issue in EEG recording. These artefacts add significant energy to the recorded signals, particularly at high frequencies. To enable reliable interpretation of subcortical brain activity, it is necessary to detect and discard this contamination. NEW METHOD: We introduce a new automatic muscle-removal approach based on the traditional Blind Source Separation-Canonical Correlation Analysis (BSS-CCA) method and the spectral slope of its components. We show that CCA-based muscle-removal methods can discriminate between signals with high correlation coefficients (brain, mains artefact) and signals with low correlation coefficients (white noise, muscle). We also show that typical BSS-CCA components are not purely from one source, but are mixtures from multiple sources, limiting the performance of BSS-CCA in artefact removal. We demonstrate, using our paralysis dataset, improved performance using BSS-CCA followed by spectral-slope rejection. RESULT: This muscle removal approach can reduce high-frequency muscle contamination of EEG, especially at peripheral channels, while preserving steady-state brain responses in cognitive tasks. COMPARISON WITH EXISTING METHODS: This approach is automatic and can be applied on any sample of data easily. The results show its performance is comparable with the ICA method in removing muscle contamination and has significantly lower computational complexity. CONCLUSION: We identify limitations of the traditional BSS-CCA approach to artefact removal in EEG, propose and test an extension based on spectral slope that makes it automatic and improves its performance, and results in performance comparable to competitors such as ICA-based artefact removal.

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. Using a generic volume conduction model of the head, which includes three layers (brain, skull, and scalp), and sLORETA, we estimated time-series of sources distributed within the brain and scalp. The sources within the scalp were considered to be muscle and discarded in forward modelling. RESULT: (1) The method reduced EMG contamination, more strongly at peripheral channels; (2) task-induced cortical activity was retained or revealed after removing putative muscle activity. COMPARISON WITH EXISTING METHODS: This approach can decrease tonic muscle contamination in scalp measurements without relying on time-consuming processing of expensive MRI data. In addition, it is competitive to ICA in muscle reduction and can be reliably applied on any length of recorded data that captures the dynamics of the signals of interest. CONCLUSION: This study suggests that sLORETA can be used as a method to quantitate cranial muscle activity and reduce its contamination at sensor level.

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. Peaks of spectral power, including in the gamma range, were determined algorithmically for all electrodes. To determine if peaks were stable, 24-h ambulatory recordings were obtained from 16 subjects with peaks. In 10 subjects, steady-state responses to stimuli at peak frequency were compared with off-peak-frequency stimulation to determine if peaks were a feature of underlying network resonances and peaks were evaluated with easy and hard versions of oddball tasks to determine if peaks might be influenced by mental effort. RESULTS: 57% of 603 subjects exhibited peaks >2 dB above trough power at or above 25 Hz. Larger peaks (>5 dB) were present in 13% of subjects. Peaks were distributed widely over the scalp, more frequent centrally. Peaks were present through the day and were suppressed by slow-wave-sleep. Steady-state responses were the same with on- or off-peak sensory stimulation. In contrast, mental effort resulted in reductions in power and frequency of gamma peaks, although the suppression did not correlate with level of effort. CONCLUSIONS: Gamma EEG can be expressed constitutively as concentrations of power in narrow or wide frequency bands that play an, as yet, unknown role in cognitive activity. SIGNIFICANCE: These findings expand the described range of rhythmic EEG phenomena. In particular, in addition to evoked, induced and sustained gamma band activity, gamma activity can be present constitutively in spectral peaks.

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. METHODS: Subjects reclined in a supportive chair and were ventilated after paralysis (cisatracurium, 20 mg intravenously). In illumination, subjects were requested to focus alternately on the faces of investigators standing on the left and the right within peripheral vision. In darkness, subjects were instructed to look away from a point source of light. Subjects were to report their experiences after reversal of paralysis. RESULTS: During attempted eye-movement in illumination, one subject had an illusion of environmental movement but four subjects perceived faces as clearly as if they were in central vision. In darkness, four subjects reported movement of the target light in the direction of attempted eye-movements and three could control the movement of the light at will. CONCLUSION: The hypothesis that internal visual models receive intended ocular-movement-information directly from oculomotor centers is strengthened by this evidence.

Relation of gamma oscillations in scalp recordings to muscular activity.

We recorded scalp electrical activity before and after full neuro-muscular paralysis in 5 volunteers and determined differences due to elimination of muscular activity on several standard applications of EEG. Due to paralysis, there were reductions in 'noisiness' of the standard scalp recordings which were maximal over the peripheral scalp, not explained by abolition of movement artefact, and best accounted for by sustained EMG activity in resting individuals. There was a corresponding reduction in spectral power in the gamma range. In central leads, the extent of gamma frequency coherence during a non-time-locked mental task (1 s epochs) was reduced by paralysis, likely due to a reduction in gamma-frequency coherence in widely arising EMG signals. In a time-locked mental task (auditory oddball), evoked responses were qualitatively unaffected by paralysis but 3 of 4 induced gamma responses were obscured by EMG.

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. In four other subjects, neuromuscular blockade was achieved pharmacologically providing EMG-free spectra of EEG at rest and during mental tasks. RESULTS: In comparison to the paralysed condition, power of scalp electrical recordings in the gamma range varied in distribution, being maximal adjacent to cranial or cervical musculature. There were non-significant changes in mean gamma range activity due to mental tasks in paralysed subjects. In normal subjects, increases in scalp electrical activity were observed during tasks, without relationship to task difficulty, but with tasks involving limb- or eye-movement having higher power. CONCLUSIONS: Electrical rhythms in the gamma frequency range recorded from the scalp are inducible by mental activity and are largely due to EMG un-related to cognitive effort. EMG varies with requirements for somatic or ocular movement more than task difficulty. SIGNIFICANCE: Severe restrictions exist on utilizing scalp recordings for high frequency EEG.

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. RESULTS: EEG rhythms in the paralysed state differed significantly compared with the unparalysed state, with 10- to 200-fold differences in the power of frequencies above 20 Hz during paralysis. CONCLUSIONS: Most of the scalp EEG recording above 20 Hz is of EMG origin. Previous studies measuring gamma EEG need to be re-evaluated. SIGNIFICANCE: This has a significant impact on measurements of gamma rhythms from the scalp EEG in unparalysed humans. It is to be hoped that signal separation methods will be able to rectify this situation.

The symbol of modern medicine: why one snake is more than two.

Today, two serpent motifs are commonly used to symbolize the practice and profession of medicine. Internationally, the most popular symbol of medicine is the single serpent-entwined staff of Asklepios (Latin, Aesculapius), the ancient Greco-Roman god of medicine. However, in the United States, the staff of Asklepios (the Asklepian) and a double serpent-entwined staff with surmounting wings (the caduceus) are both popular medical symbols. The latter symbol is often designated as the "medical caduceus" and is equated with the ancient caduceus, the double serpent-entwined staff of the Greco-Roman god Hermes (Latin, Mercury). Many physicians would be surprised to learn that the medical caduceus has a quite modern origin: Its design is derived not from the ancient caduceus of Hermes but from the printer's mark of a popular 19th-century medical publisher. Furthermore, this modern caduceus became a popular medical symbol only after its adoption by the U.S. Army Medical Corps at the beginning of the 20th century. This paper describes the ancient origin of the Asklepian and how a misunderstanding of ancient mythology and iconography seems to have led to the inappropriate popularization of the modern caduceus as a medical symbol.