Markov modeling of phase singularity interaction effects in human atrial and ventricular fibrillation.

Atrial and ventricular fibrillation (AF/VF) are characterized by the repetitive regeneration of topological defects known as phase singularities (PSs). The effect of PS interactions has not been previously studied in human AF and VF. We hypothesized that PS population size would influence the rate of PS formation and destruction in human AF and VF, due to increased inter-defect interaction. PS population statistics were studied in computational simulations (Aliev-Panfilov), human AF and human VF. The influence of inter-PS interactions was evaluated by comparison between directly modeled discrete-time Markov chain (DTMC) transition matrices of the PS population changes, and M/M/∞ birth-death transition matrices of PS dynamics, which assumes that PS formations and destructions are effectively statistically independent events. Across all systems examined, PS population changes differed from those expected with M/M/∞. In human AF and VF, the formation rates decreased slightly with PS population when modeled with the DTMC, compared with the static formation rate expected through M/M/∞, suggesting new formations were being inhibited. In human AF and VF, the destruction rates increased with PS population for both models, with the DTMC rate increase exceeding the M/M/∞ estimates, indicating that PS were being destroyed faster as the PS population grew. In human AF and VF, the change in PS formation and destruction rates as the population increased differed between the two models. This indicates that the presence of additional PS influenced the likelihood of new PS formation and destruction, consistent with the notion of self-inhibitory inter-PS interactions.

The inspection paradox: An important consideration in the evaluation of rotor lifetimes in cardiac fibrillation.

Background and Objective: Renewal theory is a statistical approach to model the formation and destruction of phase singularities (PS), which occur at the pivots of spiral waves. A common issue arising during observation of renewal processes is an inspection paradox, due to oversampling of longer events. The objective of this study was to characterise the effect of a potential inspection paradox on the perception of PS lifetimes in cardiac fibrillation. Methods: A multisystem, multi-modality study was performed, examining computational simulations (Aliev-Panfilov (APV) model, Courtmanche-Nattel model), experimentally acquired optical mapping Atrial and Ventricular Fibrillation (AF/VF) data, and clinically acquired human AF and VF. Distributions of all PS lifetimes across full epochs of AF, VF, or computational simulations, were compared with distributions formed from lifetimes of PS existing at 10,000 simulated commencement timepoints. Results: In all systems, an inspection paradox led towards oversampling of PS with longer lifetimes. In APV computational simulations there was a mean PS lifetime shift of +84.9% (95% CI, ± 0.3%) (p < 0.001 for observed vs overall), in Courtmanche-Nattel simulations of AF +692.9% (95% CI, ±57.7%) (p < 0.001), in optically mapped rat AF +374.6% (95% CI, ± 88.5%) (p = 0.052), in human AF mapped with basket catheters +129.2% (95% CI, ±4.1%) (p < 0.05), human AF-HD grid catheters 150.8% (95% CI, ± 9.0%) (p < 0.001), in optically mapped rat VF +171.3% (95% CI, ±15.6%) (p < 0.001), in human epicardial VF 153.5% (95% CI, ±15.7%) (p < 0.001). Conclusion: Visual inspection of phase movies has the potential to systematically oversample longer lasting PS, due to an inspection paradox. An inspection paradox is minimised by consideration of the overall distribution of PS lifetimes.

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.

Understanding the origins of the basic equations of statistical fibrillatory dynamics.

The mechanisms governing cardiac fibrillation remain unclear; however, it most likely represents a form of spatiotemporal chaos with conservative system dynamics. Renewal theory has recently been suggested as a statistical formulation with governing equations to quantify the formation and destruction of wavelets and rotors in fibrillatory dynamics. In this perspective Review, we aim to explain the origin of the renewal theory paradigm in spatiotemporal chaos. The ergodic nature of pattern formation in spatiotemporal chaos is demonstrated through the use of three chaotic systems: two classical systems and a simulation of cardiac fibrillation. The logistic map and the baker's transformation are used to demonstrate how the apparently random appearance of patterns in classical chaotic systems has macroscopic parameters that are predictable in a statistical sense. We demonstrate that the renewal theory approach developed for cardiac fibrillation statistically predicts pattern formation in these classical chaotic systems. Renewal theory provides governing equations to describe the apparently random formation and destruction of wavelets and rotors in atrial fibrillation (AF) and ventricular fibrillation (VF). This statistical framework for fibrillatory dynamics provides a holistic understanding of observed rotor and wavelet dynamics and is of conceptual significance in informing the clinical and mechanistic research of the rotor and multiple-wavelet mechanisms of AF and VF.

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?

Renewal Theory as a Universal Quantitative Framework to Characterize Phase Singularity Regeneration in Mammalian Cardiac Fibrillation.

BACKGROUND: Despite a century of research, no clear quantitative framework exists to model the fundamental processes responsible for the continuous formation and destruction of phase singularities (PS) in cardiac fibrillation. We hypothesized PS formation/destruction in fibrillation could be modeled as self-regenerating Poisson renewal processes, producing exponential distributions of interevent times governed by constant rate parameters defined by the prevailing properties of each system. METHODS: PS formation/destruction were studied in 5 systems: (1) human persistent atrial fibrillation (n=20), (2) tachypaced sheep atrial fibrillation (n=5), (3) rat atrial fibrillation (n=4), (5) rat ventricular fibrillation (n=11), and (5) computer-simulated fibrillation. PS time-to-event data were fitted by exponential probability distribution functions computed using maximum entropy theory, and rates of PS formation and destruction (λf/λd) determined. A systematic review was conducted to cross-validate with source data from literature. RESULTS: In all systems, PS lifetime and interformation times were consistent with underlying Poisson renewal processes (human: λf, 4.2%/ms±1.1 [95% CI, 4.0-5.0], λd, 4.6%/ms±1.5 [95% CI, 4.3-4.9]; sheep: λf, 4.4%/ms [95% CI, 4.1-4.7], λd, 4.6%/ms±1.4 [95% CI, 4.3-4.8]; rat atrial fibrillation: λf, 33%/ms±8.8 [95% CI, 11-55], λd, 38%/ms [95% CI, 22-55]; rat ventricular fibrillation: λf, 38%/ms±24 [95% CI, 22-55], λf, 46%/ms±21 [95% CI, 31-60]; simulated fibrillation λd, 6.6-8.97%/ms [95% CI, 4.1-6.7]; R2≥0.90 in all cases). All PS distributions identified through systematic review were also consistent with an underlying Poisson renewal process. CONCLUSIONS: Poisson renewal theory provides an evolutionarily preserved universal framework to quantify formation and destruction of rotational events in cardiac fibrillation.

Detecting connectivity in EEG: A comparative study of data-driven effective connectivity measures.

In this paper, we perform the first comparison of a large variety of effective connectivity measures in detecting causal effects among observed interacting systems based on their statistical significance. Well-known measures estimating direction and strength of interdependence between time series are compared: information theoretic measures, model-based multivariate measures in the time and frequency domains, and phase-based measures. The performance of measures is tested on simulated data from three systems: three coupled Hénon maps; a multivariate autoregressive (MVAR) model with and without EEG as an exogenous input; and simulated EEG. No measure was consistently superior. Measures that model the data as MVAR perform well when the data are drawn from that model. Frequency domain measures perform well when the data have a clearly defined band of interest. When neither of these is true, information theoretic measures perform well. Overall, the measure with the best performance in a variety of situations and with a low computational cost is conditional Granger causality. Partial Granger causality and multivariate Granger causality are also good measures, but their computational cost rises rapidly with the number of channels. Copula Granger causality can also be used reliably, but its computational cost rises rapidly with the number of data.

Temporal stability and specificity of high bipolar electrogram entropy regions in sustained atrial fibrillation: Implications for mapping.

BACKGROUND: The potential utility of entropy (En) for atrial fibrillation (AF) mapping has been demonstrated in previous studies by multiple groups, where an association between high bipolar electrogram (EGM) entropy and the pivot of rotors has been shown. Though En is potentially attractive new approach to ablation, no studies have examined its temporal stability and specificity, which are critical to the application of entropy to clinical ablation. In the current study, we sought to objectively measure the temporal stability and specificity of bipolar EGM entropy in medium to long term recordings using three studies: i) a human basket catheter AF study, ii) a tachypaced sheep AF study and iii) a computer simulation study. OBJECTIVE: To characterize the temporal dynamics and specificity of Approximate, Sample and Shannon entropy (ApEn/SampEn/ShEn) in human (H), sheep (S), and computer simulated AF. METHODS: 64-electrode basket bi-atria sustained AF recordings (H:15 min; S:40 min) were separated into 5 s segments. ShEn/ApEn/SampEn were computed, and co-registered with NavX 3D maps. Temporal stability was determined in terms of: (i) global pattern stability of En and (ii) the relative stability the top 10% of En regions. To provide mechanistic insights into underlying mechanisms, stability characteristics were compared to models depicting various propagation patterns. To verify these results, cross-validation was performed across multiple En algorithms, across species, and compared with dominant frequency (DF) temporal characteristics. The specificity of En was also determined by looking at the association of En to rotors and areas of wave cross propagation. RESULTS: Episodes of AF were analysed (H:26 epochs, 6040 s; S:15 epochs, 14,160 s). The global pattern of En was temporally unstable (CV- H:13.42% ±â€¯4.58%; S:14.13% ±â€¯8.13%; Friedman- H: p > 0.001; S: p > 0.001). However, within this dynamic flux, the top 10% of ApEn/SampEn/ShEn regions were relatively temporally stable (Kappa >0.6) whilst the top 10% of DF regions were unstable (Kappa <0.06). In simulated AF scenarios, the experimental data were optimally reproduced in the context of an AF pattern with stable rotating waves surrounded by wavelet breakup (Kappa: 0.610; p < 0.0001). CONCLUSION: En shows global temporal instability, however within this dynamic flux, the top 10% regions exhibited relative temporal stability. This suggests that high En regions may be an appealing ablation target. Despite this, high En was associated with not just the pivot of rotors but also with areas of cross propagation, which suggests the need for future work before clinical application is possible.

Detecting synchrony in EEG: A comparative study of functional connectivity measures.

In neuroscience, there is considerable current interest in investigating the connections between different parts of the brain. EEG is one modality for examining brain function, with advantages such as high temporal resolution and low cost. Many measures of connectivity have been proposed, but which is the best measure to use? In this paper, we address part of this question: which measure is best able to detect connections that do exist, in the challenging situation of non-stationary and noisy data from nonlinear systems, like EEG. This requires knowledge of the true relationship between signals, hence we compare 26 measures of functional connectivity on simulated data (unidirectionally coupled Hénon maps, and simulated EEG). To determine whether synchrony is detected, surrogate data were generated and analysed, and a threshold determined from the surrogate ensemble. No measure performed best in all tested situations. The correlation and coherence measures performed best on stationary data with many samples. S-estimator, correntropy, mean-phase coherence (Hilbert), mutual information (kernel), nonlinear interdependence (S) and nonlinear interdependence (N) performed most reliably on non-stationary data with small to medium window sizes. Of these, correlation and S-estimator have execution times that scale slower with the number of channels and the number of samples.

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.

Information Theory and Atrial Fibrillation (AF): A Review.

Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underlying the arrhythmia, which makes detection of effective ablation targets particularly difficult. Various approaches to AF mapping have been explored in the hopes of better pinpointing these effective targets, such as Dominant Frequency (DF) analysis, complex fractionated electrograms (CFAE) and unipolar reconstruction (FIRM), but many of these methods have produced conflicting results or require further investigation. Exploration of AF using information theoretic-based approaches may have the potential to provide new insights into the complex system dynamics of AF, whilst also providing the benefit of being less reliant on empirically derived definitions in comparison to alternate mapping approaches. This work provides an overview of information theory and reviews its applications in AF analysis, with particular focus on AF mapping. The works discussed in this review demonstrate how understanding AF from a signal property perspective can provide new insights into the arrhythmic phenomena, which may have valuable clinical implications for AF mapping and ablation in the future.

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.

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.

Steps to strengthen ethics in organizations: research findings, ethics placebos, and what works.

Research shows that many organizations overlook needs and opportunities to strengthen ethics. Barriers can make it hard to see the need for stronger ethics and even harder to take effective action. These barriers include the organization's misleading use of language, misuse of an ethics code, culture of silence, strategies of justification, institutional betrayal, and ethical fallacies. Ethics placebos tend to take the place of steps to see, solve, and prevent problems. This article reviews relevant research and specific steps that create change.

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.

Spreading depression: evidence of five electroencephalogram phases.

Spreading depression (SD), a self-propagating wave of astroglial and neuronal depolarization, is an accompaniment of several neurological disorders including epilepsy. Its well-described features are initial depolarization, followed by EEG flattening. In this in vivo study in awake animals, the relationship of SDs to epileptiform activity was re-examined. We assessed SDs generated by mechanical stimulation and by metabolic inhibition with fluorocitrate. In addition to identifying prolonged EEG depression, we identified two periods, one prior to and another during depression, characterized by increases in power of specific frequencies that were sometimes associated with epileptiform discharges. The first period was characterized by ripple activity close to the induction site (88% of SDs with intracortical electrodes). The second period was characterized by localized low-frequency spikes (100% with dural screw electrodes, 65% with intracortical electrodes). By using fluorocitrate to induce SDs, the initial period was also characterized by runs of spikes (52%). Finally, with SDs induced by both methods, there was a period at the end of depression when additional, unprovoked SDs occurred (20%). Five stages of SD were defined by these phenomena, in the order: excitation, depression, excitation, depression, SD, with metabolic inhibition enhancing the expression of epileptiform spiking.

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.

Psychological assessment of torture survivors: essential steps, avoidable errors, and helpful resources.

This article provides ideas, information, and resources that may be helpful in conducting psychological evaluations of people who have been tortured. The first section discusses essential steps, including achieving competence; clarifying the purpose; selecting methods appropriate to the individual, the purpose, and the situation; addressing issues of culture and language; maintaining awareness of ways in which the presence of third parties and recording can affect the assessment; attending carefully to similarities, echoes, and triggers; and actively searching for ways to transcend our own limited experiences and misleading expectations. The second section discusses avoiding five common errors that undermine these evaluations: mismatched validity; confirmation bias; confusing retrospective and prospective accuracy (switching conditional probabilities); ignoring the effects of low base rates; and misinterpreting dual high base rates. The third section identifies resources on the web (e.g., major centers, legal services, online courses, information about asylum and refuge, networks of torture survivors, human rights organizations providing information and services, guides to assessment) that people working with torture survivors, refugees, and asylum-seekers may find helpful.