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

Nonlinear functional muscle network based on information theory tracks sensorimotor integration post stroke

Sensory information is critical for motor coordination. However, understanding sensorimotor integration is complicated, especially in individuals with impairment due to injury to the central nervous system. This research presents a novel functional biomarker, based on a nonlinear network graph of muscle connectivity, called InfoMuNet, to quantify the role of sensory information on motor performance. Thirty-two individuals with post-stroke hemiparesis performed a grasp-and-lift task, while their muscle activity from 8 muscles in each arm was measured using surface electromyography. Subjects performed the task with their affected hand before and after sensory exposure to the task performed with the less-affected hand. For the first time, this work shows that InfoMuNet robustly quantifies changes in functional muscle connectivity in the affected hand after exposure to sensory information from the less-affected side. > 90% of the subjects conformed with the improvement resulting from this sensory exposure. InfoMuNet also shows high sensitivity to tactile, kinesthetic, and visual input alterations at the subject level, highlighting its potential use in precision rehabilitation interventions.

Alterations in EEG connectivity in healthy young adults provide an indicator of sleep depth

Current sleep analyses have used electroencephalography (EEG) to establish sleep intensity through linear and nonlinear measures. Slow wave activity (SWA) and entropy are the most commonly used markers of sleep depth. The purpose of this study is to evaluate changes in brain EEG connectivity during sleep in healthy subjects and compare them with SWA and entropy. Four different connectivity metrics: coherence (MSC), synchronization likelihood (SL), cross mutual information function (CMIF), and phase locking value (PLV), were computed focusing on their correlation with sleep depth. These measures provide different information and perspectives about functional connectivity. All connectivity measures revealed to have functional changes between the different sleep stages. The averaged CMIF seemed to be a more robust connectivity metric to measure sleep depth (correlations of 0.78 and 0.84 with SWA and entropy, respectively), translating greater linear and nonlinear interdependences between brain regions especially during slow wave sleep. Potential changes of brain connectivity were also assessed throughout the night. Connectivity measures indicated a reduction of functional connectivity in N2 as sleep progresses. The validation of connectivity indexes is necessary because they can reveal the interaction between different brain regions in physiological and pathological conditions and help understand the different functions of deep sleep in humans.

Resting State EEG Characteristics During Sedation With Midazolam or Propofol in Older Subjects

Background. Despite widespread application, little is known about the neurophysiological effects of light sedation with midazolam or propofol, particularly in older subjects. The aim of this study was to assess the effects of light sedation with midazolam or propofol on a variety of EEG measures in older subjects. Methods. In patients (≥60 years without neuropsychiatric disease such as delirium), 2 EEG recordings were performed, before and after administration of either midazolam (n = 22) or propofol (n = 26) to facilitate an endoscopic procedure. Power spectrum, functional connectivity, and network topology based on the minimum spanning tree (MST) were compared within subjects. Results. Midazolam and propofol administration resulted in Richmond Agitation and Sedation Scale levels between 0 and -4 and between -2 and -4, respectively. Both agents altered the power spectra with increased delta (0.5-4 Hz) and decreased alpha (8-13 Hz) power. Only propofol was found to significantly reduce functional connectivity. In the beta frequency band, the MST was more integrated during midazolam sedation. Propofol sedation resulted in a less integrated network in the alpha frequency band. Conclusion. Despite the different levels of light sedation with midazolam and propofol, similar changes in power were found. Functional connectivity and network topology showed differences between midazolam and propofol sedation. Future research should establish if these differences are caused by the different levels of sedation or the mechanism of action of these agents.

Multiscale Entropy Analysis for Recognition of Visually Elicited Negative Stress From EEG Recordings

Automatic identification of negative stress is an unresolved challenge that has received great attention in the last few years. Many studies have analyzed electroencephalographic (EEG) recordings to gain new insights about how the brain reacts to both short- and long-term stressful stimuli. Although most of them have only considered linear methods, the heterogeneity and complexity of the brain has recently motivated an increasing use of nonlinear metrics. Nonetheless, brain dynamics reflected in EEG recordings often exhibit a multiscale nature and no study dealing with this aspect has been developed yet. Hence, in this work two nonlinear indices for quantifying regularity and predictability of time series from several time scales are studied for the first time to discern between visually elicited emotional states of calmness and negative stress. The obtained results have revealed the maximum discriminant ability of 86.35% for the second time scale, thus suggesting that brain dynamics triggered by negative stress can be more clearly assessed after removal of some fast temporal oscillations. Moreover, both metrics have also been able to report complementary information for some brain areas.

Quantitative methods in electroencephalography to access therapeutic response

Pharmacometrics or Quantitative Pharmacology aims to quantitatively analyze the interaction between drugs and patients whose tripod: pharmacokinetics, pharmacodynamics and disease monitoring to identify variability in drug response. Being the subject of central interest in the training of pharmacists, this work was out with a view to promoting this idea on methods to access the therapeutic response of drugs with central action. This paper discusses quantitative methods (Fast Fourier Transform, Magnitude Square Coherence, Conditional Entropy, Generalised Linear semi-canonical Correlation Analysis, Statistical Parametric Network and Mutual Information Function) used to evaluate the EEG signals obtained after administration regimen of drugs, the main findings and their clinical relevance, pointing it as a contribution to construction of different pharmaceutical practice. Peter Anderer et. al in 2000 showed the effect of 20mg of buspirone in 20 healthy subjects after 1, 2, 4, 6 and 8h after oral ingestion of the drug. The areas of increased power of the theta frequency occurred mainly in the temporo-occipital - parietal region. It has been shown by Sampaio et al., 2007 that the use of bromazepam, which allows the release of GABA (gamma amino butyric acid), an inhibitory neurotransmitter of the central nervous system could theoretically promote dissociation of cortical functional areas, a decrease of functional connectivity, a decrease of cognitive functions by means of smaller coherence (electrophysiological magnitude measured from the EEG by software) values. Ahmad Khodayari-Rostamabad et al. in 2015 talk that such a measure could be a useful clinical tool potentially to assess adverse effects of opioids and hence give rise to treatment guidelines. There was the relation between changes in pain intensity and brain sources (at maximum activity locations) during remifentanil infusion despite its potent analgesic effect. The statement of mathematical and computational aspects in the use of clinical data is frequent and elucidation of these aspects we use PhysioNet https://www.physionet.org/, Clinical Database online supported by the National Institutes of Health (National Institutes of Health of United States of America/NIH-USA) for the acquisition of EEG data and the Matlab program to do the simulations with the methods and thus create opportunities greater understanding.

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.