Evaluation of connectivity measures to identify Seizure Onset and Propagation Zones in Refractory Epilepsy: A Case study with two different Post- Surgical Outcomes.

High Frequency Oscillations (HFO) have been found very useful in refractory epilepsy. They have been used to identify the epileptogenic zone and as a promising clinical biomarker for presurgical evaluation in childhood epilepsy. There is controversy about whether there is a spread of HFOs and their propagation. Some researchers reinforce the idea of dealing with epilepsy as a network disorder, so the fact of propagation can promote this research. The hypothesis of this study is that connectivity methods can be useful to detect the seizure onset and propagation zones. Methodology has been applied to two cases where the clinical outcomes after surgery were free of seizures and not free. Promising results were obtained to understand both situations. A future study with more cases is necessary to obtain strong conclusions.Clinical Relevance- This exploratory study shows the relationship between connectivity measures and the propagation of HFOs and this can be useful to know the epileptogenic function of these waves that, nowadays, are unknown. Connectivity features in conjunction with other multivariate estimators can be a tool to help in identifying the regions of interest in refractory epilepsy.

Cortical inhibition on TMS-EEG: interstimulus interval effect on short-interval paired-pulse.

In mental disorders, paired-pulse (PP) transcranial magnetic stimulation and electroencephalography (TMS-EEG) recordings usage is increasing to directly evaluate the cortical inhibition of motor and nonmotor regions. One of the most common measures to assess the inhibition is the short-interval cortical inhibition (SICI), which depends on the interstimulus interval (ISI). This measure has been widely used in the motor cortex. However, the number of studies that evaluate other nonmotor regions, such as the dorsolateral prefrontal cortex (DLPFC), are increasing and there is still little knowledge on how the ISI affects those areas.In this pilot study, six subjects underwent a SICI protocol over the DLPFC using ISI values of 2 and 4ms with the aim of comparing them. TMS-EEG signals for both ISIs were characterized regarding the amplitude and latency of the TMS-evoked potentials (TEP) P60 and N100. Whereas the variation of cortical inhibition between ISIs is almost significant for N100, with higher inhibition for an ISI of 2ms, for TEP P60 the variation was not appreciable. Findings are in accordance with the ones in the state-of-the-art obtained in the motor cortex and suggest that a greater inhibition is likely to be produced with an ISI of 2ms.Clinical relevance- This pilot study indicates that cortical inhibition might be better assessed when DLPFC is stimulated with an ISI of 2ms in the SICI protocol.

Cognitive stimulation has potential for brain activation in individuals with Rett syndrome.

BACKGROUND: Knowledge regarding neuropsychological training in Rett syndrome (RS) is scarce. The aim of this study was to assess the outcome and the duration of the effect of cognitive stimulation on topographic electroencephalography (EEG) data in RS. METHODS: Twenty female children diagnosed with RS were included in the analysis. Girls with RS conducted a cognitive task using an eye-tracker designed to evaluate access and choice skills. EEG data were acquired during the experimental procedure including two 10-min baseline stages before and after the task. Topographical changes of several EEG spectral markers including absolute and relative powers, Brain Symmetry Index and entropy were assessed. RESULTS: Topographic significance probability maps suggested statistical decreases on delta activity and increases on beta rhythm associated with the cognitive task. Entropy increased during and after the task, likely related to more complex brain activity. A significant positive interaction was obtained between Brain Symmetry Index and age showing that the improvement of interhemispheric symmetry was higher in younger girls (5-10 years). CONCLUSIONS: According to our findings, significant alterations of brain rhythms were observed during and after cognitive stimulation, suggesting that cognitive stimulation may have effects on brain activity beyond the stimulation period. Finally, our promising results also showed an increase brain symmetry that was especially relevant for the younger group. This could suggest an interaction of the eye-tracking cognitive task; however, further studies in this field are needed to assess the relation between brain asymmetries and age.

Stress assessment based on EEG univariate features and functional connectivity measures.

The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.

Changes of HD-sEMG maps of the upper limb during isometric endurance contractions.

Recent research in the field of surface EMG recorded with 2D electrode arrays have shown muscle adaptations as reflected on the spatial activation of motor units in response to pain, direction of movement or fatigue. The purpose of this study was to evaluate time- changes in the activation maps of upper limb muscles during endurance tasks associated with the degrees of freedom at the elbow joint. Preliminary results show time-variations in the distribution of intensity, that is, in the spatial recruitment of motor units, and that such changes may be dependent on the type of task.

Identification of isometric contractions based on High Density EMG maps.

Identification of motion intention and muscle activation strategy is necessary to control human-machine interfaces like prostheses or orthoses, as well as other rehabilitation devices, games and computer-based training programs. Pattern recognition from sEMG signals has been extensively investigated in the last decades, however, most of the studies did not take into account different strengths and EMG distributions associated to the intended task. The identification of such quantities could be beneficial for the training of the subject or the control of assistive devices. Recent studies have shown the need to improve pattern-recognition classification by reducing sensitivity to changes in the exerted strength, muscle-electrode shifts and bad contacts. Surface High Density EMG (HD-EMG) obtained from 2-dimensional arrays can provide much more information than electrode pairs for inferring not only motion intention but also the strategy adopted to distribute the load between muscles as well as changes in the spatial distribution of motor unit action potentials within a single muscle because of it. The objectives of this study were: (a) the automatic identification of four isometric motor tasks associated with the degrees of freedom of the forearm: flexion-extension and supination-pronation and (b) the differentiation among levels of voluntary contraction at low-medium efforts. For this purpose, monopolar HD-EMG maps were obtained from five muscles of the upper-limb in healthy subjects. An original classifier is proposed, based on: (1) Two steps linear discriminant analysis of the EMG information for each type of contraction, and (2) features extracted from HD-EMG maps and related to its intensity and distribution in the 2D space. The classifier was trained and tested with different effort levels. Spatial distribution-based features by themselves are not sufficient to classify the type of task or the effort level with an acceptable accuracy; however, when calculated with the "isolated masses" method proposed in this study and combined with intensity-base features, the performance of the classifier is improved. The classifier is capable of identifying the tasks even at 10% of Maximum Voluntary Contraction, in the range of effort level developed by patients with neuromuscular disorders, showing that intention end effort of motion can be estimated from HD-EMG maps and applied in rehabilitation.

A cross-sectional study comparing strength profile of dorsal and palmar flexor muscles of the wrist in epicondylitis and healthy men.

BACKGROUND: Strength training has been proposed by several authors to treat Lateral Epicondylitis. However, there is still a lack of information concerning muscle weakness and its relationship to imbalances and fatigability of forearm muscles during dynamic conditions in subjects after epicondylitis recovery. AIM: To analyze the relationship between lateral humeral epicondylitis, and forearm muscle strength and fatigue. SETTING: Rehabilitation specialized center POPULATION: Cross-sectional study in eight former epicondylitis men free of symptoms and actively working at the moment of the evaluation and eight healthy men volunteers. METHODS: Isokinetic tests were performed at different velocities in order to assess strength in concentric and eccentric contractions. Additionally, a long-term concentric test was carried out in order to analyze strength during endurance. The following variables were analyzed: Average torque of dorsal and palmar flexors of the wrist and ratio of agonist/antagonist for non-endurance contractions; length of initial and final plateaus and the slope of average torque decay during the endurance test. RESULTS: In both groups, average torque produced by palmar flexor muscles was higher than that produced by dorsal flexor muscles. Patients showed higher strength in palmar flexor muscles, whereas dorsal flexor strength was similar for both populations. Palmar flexor vs. dorsal flexor ratio was significantly higher in patients for eccentric contractions. Regarding fatigue, results showed that torque decreased earlier in patients. CONCLUSIONS AND CLINICAL REHABILITATION IMPACT: Both palmar flexor force and palmar/dorsal ratio in eccentric exercise were significantly higher in patients. This finding indicates a muscular imbalance in patients underlying the epicondylitis condition. Additionally, former patients fatigued earlier. Findings indicate that muscle imbalances and fatigability might be related to lateral epicondylitis. This information may be useful in the design and monitoring of programs intended for lateral epicondylitis rehabilitation. More studies are necessary to conclude if these differences are cause or consequence of the epicondylitis.

Cross-conditional entropy and coherence analysis of pharmaco-EEG changes induced by alprazolam.

RATIONALE: Quantitative analysis of electroencephalographic signals (EEG) and their interpretation constitute a helpful tool in the assessment of the bioavailability of psychoactive drugs in the brain. Furthermore, psychotropic drug groups have typical signatures which relate biochemical mechanisms with specific EEG changes. OBJECTIVES: To analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches. METHODS: EEG signals were recorded after alprazolam administration in a placebo-controlled crossover clinical trial. Nonlinear couplings assessed by means of corrected cross-conditional entropy were compared to linear couplings measured with the classical magnitude squared coherence. RESULTS: Linear variables evidenced a statistically significant drug-induced decrease, whereas nonlinear variables showed significant increases. All changes were highly correlated to drug plasma concentrations. The spatial distribution of the observed connectivity changes clearly differed from a previous study: changes before and after the maximum drug effect were mainly observed over the anterior half of the scalp. Additionally, a new variable with very low computational cost was defined to evaluate nonlinear coupling. This is particularly interesting when all pairs of EEG channels are assessed as in this study. CONCLUSIONS: Results showed that alprazolam induced changes in terms of uncoupling between regions of the scalp, with opposite trends depending on the variables: decrease in linear ones and increase in nonlinear features. Maps provided consistent information about the way brain changed in terms of connectivity being definitely necessary to evaluate separately linear and nonlinear interactions.

Ocular reduction in EEG signals based on adaptive filtering, regression and blind source separation.

Quantitative electroencephalographic (EEG) analysis is very useful for diagnosing dysfunctional neural states and for evaluating drug effects on the brain, among others. However, the bidirectional contamination between electrooculographic (EOG) and cerebral activities can mislead and induce wrong conclusions from EEG recordings. Different methods for ocular reduction have been developed but only few studies have shown an objective evaluation of their performance. For this purpose, the following approaches were evaluated with simulated data: regression analysis, adaptive filtering, and blind source separation (BSS). In the first two, filtered versions were also taken into account by filtering EOG references in order to reduce the cancellation of cerebral high frequency components in EEG data. Performance of these methods was quantitatively evaluated by level of similarity, agreement and errors in spectral variables both between sources and corrected EEG recordings. Topographic distributions showed that errors were located at anterior sites and especially in frontopolar and lateral-frontal regions. In addition, these errors were higher in theta and especially delta band. In general, filtered versions of time-domain regression and of adaptive filtering with RLS algorithm provided a very effective ocular reduction. However, BSS based on second order statistics showed the highest similarity indexes and the lowest errors in spectral variables.

Evaluation of muscle activity and fatigue in extensor forearm muscles during isometric contractions.

Work-related upper extremity disorders as epycondylitis and tendonitis are closely related to localized muscle fatigue of extensor forearm muscles. The aim of this work is to evaluate levels of activity, fatigue and interactions between the main extensor muscles of the wrist. Surface EMG signals were acquired from extensor carpi radialis (ECR), extensor digitorum comunis (EDC) and extensor carpi ulnaris (ECU) muscles during isometric contractions using linear electrode array technique. Parameters such as muscle fiber conduction velocity (CV), EMG average rectified value (ARV) and frequency parameters were estimated to study muscle activity during selective contractions, during a non specific task at different percentage of the maximum voluntary contraction (MVC) level and during a fatiguing exercise at 50% MVC. Results show that it is possible to enhance significantly ECR and ECU muscle ARV during their selective activation. Moreover, in the non selective task, ECU muscle ARV significantly decreases with respect to the other muscles with the increase of the MVC level. The activity of ECR muscle in a non specific task is predominant with respect to the other muscles at 80%MVC. EMG spectral parameters and CV show fatigue in all muscles during a sustained contraction at 50%MVC.

Analysis of respiratory and muscle activity by means of cross information function between ventilatory and myographic signals.

Analysis of respiratory muscle activity is a promising technique for the study of pulmonary diseases such as obstructive sleep apnea syndrome (OSAS). Evaluation of interactions between muscles is very useful in order to determine the muscular pattern during an exercise. These interactions have already been assessed by means of different linear techniques like cross-spectrum, magnitude squared coherence or cross-correlation. The aim of this work is to evaluate interactions between respiratory and myographic signals through nonlinear analysis by means of cross mutual information function (CMIF), and finding out what information can be extracted from it. Some parameters are defined and calculated from CMIF between ventilatory and myographic signals of three respiratory muscles. Finally, differences in certain parameters were obtained between OSAS patients and healthy subjects indicating different respiratory muscle couplings.

Evaluation of an automatic ocular filtering method for awake spontaneous EEG signals based on independent component analysis.

Electroencephalographic artifacts associated with eye movements are a potential source of error in the EEG analysis when its interpretation is performed for evaluating the influence of drugs and the diagnosis of neurological disorders. In this study, a new automatic method for artifact filtering based on independent component analysis (ICA) is proposed. Automatic artifact identification is based on frequency domain and scalp topography aspects of the independent components. A comparative study between ICA and the 'gold standard' method based on linear regression analysis is performed. The latter does not take into account the mutual contamination between EEG and electrooculographic activity, reducing not only the ocular movements but also interesting cerebral activity, mainly in anteriorly placed electrodes. This limitation is overcome by ICA and the efficiency of this approach is shown for a double-blind, placebo-controlled crossover drug trial in healthy volunteers.

Influence of estimators of spectral density on the analysis of electromyographic and vibromyographic signals.

Electromyographic (EMG) and vibromyographic (VMG) signals are related to electrical and mechanical muscle activity, respectively. It is known that variations in their frequency components are related to changes in muscle activity and fatigue. The aims of this study were: (1) to analyse the resolution, variance and bias of different estimations of power spectral density function (PSD); and (2) to evaluate the influence of the spectral estimation method on three indices calculated from the PSD of EMG and VMG signals: mean (f(m)) and median (f(c)) frequencies and the ratio of high and low frequency components (H/L ratio) to select the most suitable estimator. Myographic signals were recorded from the sternomastoid muscle, an accessory respiratory muscle, during breathing. For non-parametric methods, Welch periodograms and correlograms were analysed with different windows. Autoregressive (AR) moving average (MA) and ARMA models with different orders were evaluated in the parametric methods. The reproducibility of the results was also studied. Frequency indices, particularly the H/L ratio and f(c), changed considerably when varying the following parameters of the estimators: periodogram with segment durations longer than 150 ms in EMG and with any duration in VMG signals; correlogram with window length shorter than 10% of the total number of samples; and AR models with an order lower than 10, 20 and 40 in f(c), fm and H/L ratio, respectively, in both myographic signals.

Study of myographic signals from sternomastoid muscle in patients with chronic obstructive pulmonary disease.

Analysis of the respiratory muscle activity is a promising technique for diagnosis of respiratory diseases, such as chronic obstructive pulmonary disease (COPD). The sternomastoid muscle (SMM) was selected to study the activity of respiratory muscles due to its accessibility in order to define a noninvasive analysis. The aims of this work are two: analyze the relationship between the SMM function and pulmonary obstruction, and study the influence of spectral estimator on frequency parameters related with the muscle activity. For the first goal, we propose the analysis of vibromyographic and electromyographic signals from the SMM to study the muscle function during two ventilatory tests. Activity of SMM was found by means of several indexes: root-mean-square (rms) values, mean and median frequencies, and ratio between high and low-frequency components. For the second goal, spectral analysis was performed by means of nonparametric methods: Correlogram and Welch periodogram, and parametric methods: autoregressive (AR), moving average (MA), and ARMA models. It is deduced that these indexes show muscle activity and certain fatigue of the SMM, whose muscle function depends on the level of pulmonary obstruction, and they depend a lot of spectral estimator being the more suitable an AR model with high order.

Acoustic analysis of snoring sound in patients with simple snoring and obstructive sleep apnoea.

Snoring, a symptom which may indicate the presence of the obstructive sleep apnoea syndrome (OSA), is also common in the general population. Recent studies have suggested that the acoustic characteristics of snoring sound may differ between simple snorers and OSA patients. We have studied a small number of patients with simple snoring and OSA, analysing the acoustic characteristics of the snoring sound. Seventeen male patients, 10 with OSA (apnoea/hypopnoea index (AHI) 26.2 events x h(-1)) and seven simple snorers (AHI 3.8 events x h(-1)), were studied. Full night polysomnography was performed and the snoring sound power spectrum was analysed. Spectral analysis of snoring sound showed the existence of two different patterns. The first pattern was characterized by the presence of a fundamental frequency and several harmonics. The second pattern was characterized by a low frequency peak with the sound energy scattered on a narrower band of frequencies, but without clearly identified harmonics. The seven simple snorers and two of the 10 patients with OSA (AIH 13 and 14 events x h(-1), respectively) showed the first pattern. The rest of the OSA patients showed the second pattern. The peak frequency of snoring was significantly lower in OSA patients, with all but one OSA patient and only one simple snorer showing a peak frequency below 150 Hz. A significant negative correlation was found between AHI and peak and mean frequencies of the snoring power spectrum (p<0.0016 and p<0.0089, respectively). In conclusion, this study demonstrates significant differences in the sound power spectrum of snoring sound between subjects with simple snoring and obstructive sleep apnoea patients.