Alonso, J.F.; Romero, S.; Mañanas, M.A.; Rojas, M.; Riba, J.; Barbanoj, M.J. Medical and biological engineering and computing Vol. 53, num. 10, p. 1011-1023 DOI: 10.1007/s11517-015-1315-6 Data de publicació: 2015-10-01 Article en revista
The identification of the brain regions involved in the neuropharmacological action is a potential procedure for drug development. These regions are commonly determined by the voxels showing significant statistical differences after comparing placebo-induced effects with drug-elicited effects. LORETA is an electroencephalography (EEG) source imaging technique frequently used to identify brain structures affected by the drug. The aim of the present study was to evaluate different methods for the correction of multiple comparisons in the LORETA maps. These methods which have been commonly used in neuroimaging and also simulated studies have been applied on a real case of pharmaco-EEG study where the effects of increasing benzodiazepine doses on the central nervous system measured by LORETA were investigated. Data consisted of EEG recordings obtained from nine volunteers who received single oral doses of alprazolam 0.25, 0.5, and 1 mg, and placebo in a randomized crossover double-blind design. The identification of active regions was highly dependent on the selected multiple test correction procedure. The combined criteria approach known as cluster mass was useful to reveal that increasing drug doses led to higher intensity and spread of the pharmacologically induced changes in intracerebral current density.
Background: Psychedelics induce intense modifications in the sensorium, the sense of "self," and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects.; Methods: Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine.; Results: The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced.; Conclusions: These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain.
Alonso, J.F.; Romero, S.; Ballester, M. R.; Antonijoan, R. M.; Mañanas, M.A. Physiological measurement Vol. 36, p. 1351-1365 DOI: 10.1088/0967-3334/36/7/1351 Data de publicació: 2015-05-27 Article en revista
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.
Migliorelli, C.; Alonso, J.F.; Romero, S.; Mañanas, M.A.; Nowak, R.; Russi, A. Journal of neural engineering Vol. 12, p. 046001-1-046001-12 DOI: 10.1088/1741-2560/12/4/046001 Data de publicació: 2015-05-27 Article en revista
Objective. One of the principal drawbacks of magnetoencephalography (MEG) is its high sensitivity to metallic artifacts, which come from implanted intracranial electrodes and dental ferromagnetic prosthesis and produce a high distortion that masks cerebral activity. The aim of this study was to develop an automatic algorithm based on blind source separation (BSS) techniques to remove metallic artifacts from MEG signals. Approach. Three methods were evaluated: AMUSE, a second-order technique; and INFOMAX and FastICA, both based on high-order statistics. Simulated signals consisting of real artifact-free data mixed with real metallic artifacts were generated to objectively evaluate the effectiveness of BSS and the subsequent interference reduction. A completely automatic detection of metallic-related components was proposed, exploiting the known characteristics of the metallic interference: regularity and low frequency content. Main results. The automatic procedure was applied to the simulated datasets and the three methods exhibited different performances. Results indicated that AMUSE preserved and consequently recovered more brain activity than INFOMAX and FastICA. Normalized mean squared error for AMUSE decomposition remained below 2%, allowing an effective removal of artifactual components. Significance. To date, the performance of automatic artifact reduction has not been evaluated in MEG recordings. The proposed methodology is based on an automatic algorithm that provides an effective interference removal. This approach can be applied to any MEG dataset affected by metallic artifacts as a processing step, allowing further analysis of unusable or poor quality data.
Alonso, J.F.; Sabater, A.; Romero, S.; Mañanas, M.A.; Riba, J. A Dialogue with the Cerebral Cortex: Cortical Function and Interfacing p. 1-4 DOI: 10.3389/conf.fnsys.2015.06.00008 Data de presentació: 2015-04-29 Presentació treball a congrés
Electroencephalographic analysis techniques have become a very useful tool to assess brain activity and interactions between cerebral regions, that is, the so-called cerebral connectivity analysis. The effects of some drugs have, so far, been studied using spectral analysis and, to a lesser extent, some linear and nonlinear connectivity techniques. New indexes have recently been designed based on assumptions that make them more robust against volume conduction effects that could yield to spurious connectivity results.
These new indexes such as the imaginary coherence (IC) [Nolte et al., 2004], the phase-lag index (PLI) [Stam et al., 2007] and the weighted phase-lag index (WPLI) [Vinck et al., 2011] have proven very useful in several fields, for example in characterizing electroencephalographic (EEG) and magnetoencephalographic (MEG) activity of Alzheimer’s Disease patients compared to healthy controls.
However, these techniques have not been applied to study the effect of drugs on the brain. The main purpose of the current work was to assess the suitability and effectiveness of these innovative indexes to study the brain connectivity under psychoactive drug treatment, and concretely, the effects of a single dose of alprazolam, a short-acting drug of the benzodiazepine family.
Alprazolam is extensively prescribed for the treatment of anxiety and panic disorders, and peak plasma concentrations are obtained between 0.5 and 2 hours after intake [Greenblat and Wright, 1993]. Being a benzodiazepines, alprazolam induces an enhancement of the inhibitory pathways through their activity on the GABA A receptor complex, favouring the entrance to chloride ions into the neurons [Haefely, 1990]. Due to the enhancement of the inhibitory pathways a weakening or even an impairment of functional connectivity could be hypothesized