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.

The prevalence of post-extubation dysphagia in critically ill adults: an Australian data linkage study.

Objective: To define the prevalence of dysphagia after endotracheal intubation in critically ill adult patients. Design: A retrospective observational data linkage cohort study using the Australian and New Zealand Intensive Care Society Adult Patient Database and a mandatory government statewide health care administration database. Setting: Private and public intensive care units (ICUs) within Victoria, Australia. Participants: Adult patients who required endotracheal intubation for the purpose of mechanical ventilation within a Victorian ICU between July 2013 and June 2018. Main outcome measures: Presence of dysphagia, aspiration pneumonia, ICU length of stay, hospital length of stay, and cost per episode of care. Results: Endotracheal intubation in the ICU was required for 71 124 patient episodes across the study period. Dysphagia was coded in 7.3% (n = 5203) of those episodes. Patients with dysphagia required longer ICU (median, 154 [interquartile range (IQR), 78-259] v 53 [IQR, 27-107] hours; P < 0.001) and hospital admissions (median, 20 [IQR, 13-30] v 8 [IQR, 5-15] days; P < 0.001), were more likely to develop aspiration pneumonia (17.2% v 5.6%; odds ratio, 3.0; 95% CI, 2.8-3.2; P < 0.001), and the median health care expenditure increased by 93% per episode of care ($73 586 v $38 108; P < 0.001) compared with patients without dysphagia. Conclusions: Post-extubation dysphagia is associated with adverse patient and health care outcomes. Consideration should be given to strategies that support early identification of patients with dysphagia in the ICU to determine if these adverse outcomes can be reduced.

Words describing feelings about death: A comparison of sentiment for self and others and changes over time.

Understanding public attitudes towards death is needed to inform health policies to foster community death awareness and preparedness. Linguistic sentiment analysis of how people describe their feelings about death can add to knowledge gained from traditional self-reports. This study provided the first description of emotive attitudes expressed towards death utilising textual sentiment analysis for the dimensions of valence, arousal and dominance. A linguistic lexicon of sentiment norms was applied to activities conducted in an online course for the general-public designed to generate discussion about death. We analysed the sentiment of words people chose to describe feelings about death, for themselves, for perceptions of the feelings of 'others', and for longitudinal changes over the time-period of exposure to a course about death (n = 1491). The results demonstrated that sadness pervades affective responses to death, and that inevitability, peace, and fear were also frequent reactions. However, words chosen to represent perceptions of others' feelings towards death suggested that participants perceived others as feeling more negative about death than they do themselves. Analysis of valence, arousal and dominance dimensions of sentiment pre-to-post course participation demonstrated that participants chose significantly happier (more positive) valence words, less arousing (calmer) words, and more dominant (in-control) words to express their feelings about death by the course end. This suggests that the course may have been helpful in participants becoming more emotionally accepting in their feelings and attitude towards death. Furthermore, the change over time appeared greater for younger participants, who showed more increase in the dominance (power/control) and pleasantness (valence) in words chosen at course completion. Sentiment analysis of words to describe death usefully extended our understanding of community death attitudes and emotions. Future application of sentiment analysis to other related areas of health policy interest such as attitudes towards Advance Care Planning and palliative care may prove fruitful.

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.

Bioplausible multiscale filtering in retino-cortical processing as a mechanism in perceptual grouping.

Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, 'Geometrical' and, in particular, 'Tilt Illusions' are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position. Over the last decade, many new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the encoding nature of the retinal representation that is sent to the cortex for further processing. Based on these neurobiological discoveries, we provide computer simulation evidence from modelling retinal ganglion cells responses to some complex Tilt Illusions, suggesting that the emergence of tilt in these illusions is partially related to the interaction of multiscale visual processing performed in the retina. The output of our low-level filtering model is presented for several types of Tilt Illusion, predicting that the final tilt percept arises from multiple-scale processing of the Differences of Gaussians and the perceptual interaction of foreground and background elements. The model is a variation of classical receptive field implementation for simple cells in early stages of vision with the scales tuned to the object/texture sizes in the pattern. Our results suggest that this model has a high potential in revealing the underlying mechanism connecting low-level filtering approaches to mid- and high-level explanations such as 'Anchoring theory' and 'Perceptual grouping'.

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.

Mimicry and expressiveness of an ECA in human-agent interaction: familiarity breeds content!

BACKGROUND: Two experiments investigated the effect of features of human behaviour on the quality of interaction with an Embodied Conversational Agent (ECA). METHODS: In Experiment 1, visual prominence cues (head nod, eyebrow raise) of the ECA were manipulated to explore the hypothesis that likeability of an ECA increases as a function of interpersonal mimicry. In the context of an error detection task, the ECA either mimicked or did not mimic a head nod or brow raise that humans produced to give emphasis to a word when correcting the ECA's vocabulary. In Experiment 2, presence versus absence of facial expressions on comprehension accuracy of two computer-driven ECA monologues was investigated. RESULTS: In Experiment 1, evidence for a positive relationship between ECA mimicry and lifelikeness was obtained. However, a mimicking agent did not elicit more human gestures. In Experiment 2, expressiveness was associated with greater comprehension and higher ratings of humour and engagement. CONCLUSION: Influences from mimicry can be explained by visual and motor simulation, and bidirectional links between similarity and liking. Cue redundancy and minimizing cognitive load are potential explanations for expressiveness aiding comprehension.

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. To maximise reduction of EMG, data were pre-processed using independent component analysis and surface Laplacian transformed data. Two non-meditative and five meditative states were used: resting baseline, mind-wandering, absorptions 1, 2, 3, 4 and 5 (corresponding to four levels of absorption and an absorption with a different object of focus, otherwise equivalent to level 4; these five meditative states produce repeatable, distinctly different experiences for experienced meditators). The experimental protocol required participants to experience the states in the order listed above, followed immediately by the reverse. We then calculated EEG power in standard frequency bands from 1 to 80Hz. We observed decreases of central scalp beta (13-25Hz), and central low gamma (25-48Hz) power in meditators during deeper absorptions. In contrast, we identified increases in frontal midline and temporo-parietal theta power in meditators, again, during deeper absorptions. Alpha activity was increased over all meditative states, not depth-related. This study demonstrates that the subjective experiences of deepening meditation partially correspond to measures of EEG. Our results are in accord with prior studies on non-graded meditative states. These results are also consistent with increased theta correlating with tightness of focus, and reduced beta/gamma with the desynchronization associated with enhanced alertness.

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. [1] to compare three measures and three ICA algorithms. Using EEG data acquired during neuromuscular paralysis, we tested the ability of the measures (spectral slope, peripherality and spatial smoothness) and algorithms (FastICA, Infomax and JADE) to identify components containing EMG. Spatial smoothness showed differentiation between paralysis and pre-paralysis ICs comparable to spectral slope, whereas peripherality showed less differentiation. A combination of the measures showed better differentiation than any measure alone. Furthermore, FastICA provided the best discrimination between muscle-free and muscle-contaminated recordings in the shortest time, suggesting it may be the most suited to EEG applications of the considered algorithms. Spatial smoothness results suggest that a significant number of ICs are mixed, i.e. contain signals from more than one biological source, and so the development of an ICA algorithm that is optimised to produce ICs that are easily classifiable is warranted.

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.

Surface Laplacian of central scalp electrical signals is insensitive to muscle contamination.

The objective of this paper was to investigate the effects of surface Laplacian processing on gross and persistent electromyographic (EMG) contamination of electroencephalographic (EEG) signals in electrical scalp recordings. We made scalp recordings during passive and active tasks, on awake subjects in the absence and in the presence of complete neuromuscular blockade. Three scalp surface Laplacian estimators were compared to left ear and common average reference (CAR). Contamination was quantified by comparing power after paralysis (brain signal, B) with power before paralysis (brain plus muscle signal, B+M). Brain:Muscle (B:M) ratios for the methods were calculated using B and differences in power after paralysis to represent muscle (M). There were very small power differences after paralysis up to 600 Hz using surface Laplacian transforms (B:M > 6 above 30 Hz in central scalp leads). Scalp surface Laplacian transforms reduce muscle power in central and pericentral leads to less than one sixth of the brain signal, two to three times better signal detection than CAR. Scalp surface Laplacian transformations provide robust estimates for detecting high-frequency (gamma) activity, for assessing electrophysiological correlates of disease, and also for providing a measure of brain electrical activity for use as a standard in the development of brain/muscle signal separation methods.

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.

Cell swelling precedes seizures induced by inhibition of astrocytic metabolism.

It is currently unknown what processes take place at the interface between non-ictal and ictal activity during seizure initiation. In this study, using paralysed awake rats, we focally inhibited astrocytic metabolism with fluorocitrate (FC), causing seizures. We measured changes in electroencephalogram (EEG) (0-300 Hz), and extracellular ion-concentrations during ictal onsets defining possible relationships with impedance-determined cell swelling. In animals showing ictal activity (69%) there were spike-wave discharges, spike-wave discharges followed by spreading depression and spreading depression without any discharges. In a high proportion of spike-wave discharges (>95%), just prior to the first spike-wave discharge, there was a decrease in the volume of the extracellular space. Following the initiation of cell swelling and prior to discharges, there were increases in high-frequency (150-300 Hz) EEG activity, increases in extracellular potassium- and decreases in extracellular calcium-concentrations. We suggest that EEG and ionic changes are not causative of cell swelling. Cell swelling due to metabolic failure in astrocytes at the injected site may release excitatory amino acids. At the same time, our results suggest ion homeostasis is not maintained and increased neuronal excitability and synchronisation occur. These could be the drivers changing normal brain activity into ictal activity.

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.