Miquel Àngel Mañanas

Serotonergic Psychedelics Temporarily Modify Information Transfer in Humans

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.

Inhibition of alpha oscillations through serotonin-2A receptor activation underlies the visual effects of ayahuasca in humans

Ayahuasca is an Amazonian psychotropic plant tea typically obtained from two plants, Banisteriopsis caapi and Psychotria viridis. It contains the psychedelic 5-HT2A and sigma-1 agonist N,N-dimethyltryptamine (DMT) plus β-carboline alkaloids with monoamine-oxidase (MAO)-inhibiting properties. Although the psychoactive effects of ayahuasca have commonly been attributed solely to agonism at the 5-HT2A receptor, the molecular target of classical psychedelics, this has not been tested experimentally. Here we wished to study the contribution of the 5-HT2A receptor to the neurophysiological and psychological effects of ayahuasca in humans. We measured drug-induced changes in spontaneous brain oscillations and subjective effects in a double-blind randomized placebo-controlled study involving the oral administration of ayahuasca (0.75mg DMT/kg body weight) and the 5-HT2A antagonist ketanserin (40mg). Twelve healthy, experienced psychedelic users (5 females) participated in four experimental sessions in which they received the following drug combinations: placebo+placebo, placebo+ayahuasca, ketanserin+placebo and ketanserin+ayahuasca. Ayahuasca induced EEG power decreases in the delta, theta and alpha frequency bands. Current density in alpha-band oscillations in parietal and occipital cortex was inversely correlated with the intensity of visual imagery induced by ayahuasca. Pretreatment with ketanserin inhibited neurophysiological modifications, reduced the correlation between alpha and visual effects, and attenuated the intensity of the subjective experience. These findings suggest that despite the chemical complexity of ayahuasca, 5-HT2A activation plays a key role in the neurophysiological and visual effects of ayahuasca in humans.

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.

Reduction of EEG artifacts by ICA in different sleep stages

Contamination of sleep EEG signals by the eye, muscle and heart activity is a problem for EEG interpretation and analysis of sleep disorders and influence of drugs. The aim of this paper is to evaluate a method of artifact reduction applied in different sleep stages: awakeness, stage 2, delta and REM sleep. Artifacts, particularly certain types, may be more likely found in particular settings and stages of sleep. To overcome the limitation of regression methods in bidirectional contamination, a method based on Independent Component Analysis (ICA) using time structure is applied. Artifact identification is based on time, frequency and scalp topography aspects of the independent components. Influence of artifacts is evaluated by calculating some target spectral variables before and after their reduction, using significance probability maps. Results show that ICA is a useful technique for the evaluation of these variables with clinical interest in different sleep stages.

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

RationaleQuantitative 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.ObjectivesTo analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches.MethodsEEG 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.ResultsLinear 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.ConclusionsResults 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.

Neurophysiological evidence of impaired self-monitoring in schizotypal personality disorder and its reversal by dopaminergic antagonism.

Background Schizotypal personality disorder (SPD) is a schizophrenia-spectrum disorder characterized by odd or bizarre behavior, strange speech, magical thinking, unusual perceptual experiences, and social anhedonia. Schizophrenia proper has been associated with anomalies in dopaminergic neurotransmission and deficits in neurophysiological markers of self-monitoring, such as low amplitude in cognitive event-related brain potentials (ERPs) like the error-related negativity (ERN), and the error positivity (Pe). These components occur after performance errors, rely on adequate fronto-striatal function, and are sensitive to dopaminergic modulation. Here we postulated that analogous to observations in schizophrenia, SPD individuals would show deficits in self-monitoring, as measured by the ERN and the Pe. We also assessed the capacity of dopaminergic antagonists to reverse these postulated deficits. Methods We recorded the electroencephalogram (EEG) from 9 SPD individuals and 12 healthy controls in two separate experimental sessions while they performed the Eriksen Flanker Task, a classical task recruiting behavioral monitoring. Participants received a placebo or 1 mg risperidone according to a double-blind randomized design. Results After placebo, SPD individuals showed slower reaction times to hits, longer correction times following errors and reduced ERN and Pe amplitudes. While risperidone impaired performance and decreased ERN and Pe in the control group, it led to behavioral improvements and ERN amplitude increases in the SPD individuals. Conclusions These results indicate that SPD individuals show deficits in self-monitoring analogous to those in schizophrenia. These deficits can be evidenced by neurophysiological measures, suggest a dopaminergic imbalance, and can be reverted by dopaminergic antagonists.

Neurophysiological evidence of compensatory brain mechanisms in early-stage multiple sclerosis

Multiple sclerosis (MS) is a chronic central nervous system disorder characterized by white matter inflammation, demyelination and neurodegeneration. Although cognitive dysfunction is a common manifestation, it may go unnoticed in recently-diagnosed patients. Prior studies suggest MS patients develop compensatory mechanisms potentially involving enhanced performance monitoring. Here we assessed the performance monitoring system in early-stage MS patients using the error-related negativity (ERN), an event-related brain potential (ERP) observed following behavioral errors. Twenty-seven early-stage MS patients and 31 controls were neuropsychologically assessed. Electroencephalography recordings were obtained while participants performed: a) a stop task and b) an auditory oddball task. Behavior and ERP measures were assessed. No differences in performance were found between groups in most neuropsychological tests or in behavior or ERP components in the auditory oddball task. However, the amplitude of the ERN associated with stop errors in the stop task was significantly higher in patients. ERN amplitude correlated positively with scores on the Expanded Disability Status Scale and the Multiple Sclerosis Severity Score, and negatively with the time since last relapse. Patients showed higher neuronal recruitment in tasks involving performance monitoring. Results suggest the development of compensatory brain mechanisms in early-stage MS and reflect the sensitivity of the ERN to detect these changes.

Connectivity analysis of EEG under drug therapy

Analysis of human EEG constitutes a useful instrument for the evaluation of drug bioavailability at the brain. Linear and nonlinear techniques were applied to EEG signals for the assessment of brain connectivity after drug intake by coherence and cross mutual information, respectively. The main goal was to evaluate the pharmacological effect of different doses of alprazolam on the brain during wakefulness. Preliminary results reported in this work showed statistically significant differences in EEG channels coupling between the states corresponding to placebo and different drug doses. However, nonlinear variables correlated better with the expected within-doses and within-time effects.

PARS risk charts: A 10-year study of risk assessment for cardiovascular diseases in Eastern Mediterranean Region

This study was designed to develop a risk assessment chart for the clinical management and prevention of the risk of cardiovascular disease (CVD) in Iranian population, which is vital for developing national prevention programs. The Isfahan Cohort Study (ICS) is a population-based prospective study of 6504 Iranian adults ≥35 years old, followed-up for ten years, from 2001 to 2010. Behavioral and cardiometabolic risk factors were examined every five years, while biennial follow-ups for the occurrence of the events was performed by phone calls or by verbal autopsy. Among these participants, 5432 (2784 women, 51.3%) were CVD free at baseline examination and had at least one follow-up. Cox proportional hazard regression was used to predict the risk of ischemic CVD events, including sudden cardiac death due to unstable angina, myocardial infarction, and stroke. The model fit statistics such as area under the receiver-operating characteristic (AUROC), calibration chi-square and the overall bias were used to assess the model performance. We also tested the Framingham model for comparison. Seven hundred and five CVD events occurred during 49452.8 person-years of follow-up. The event probabilities were calculated and presented color-coded on each gender-specific PARS chart. The AUROC and Harrell’s C indices were 0.74 (95% CI, 0.72–0.76) and 0.73, respectively. In the calibration, the Nam-D’Agostino χ2 was 10.82 (p = 0.29). The overall bias of the proposed model was 95.60%. PARS model was also internally validated using cross-validation. The Android app and the Web-based risk assessment tool were also developed as to have an impact on public health. In comparison, the refitted and recalibrated Framingham models, estimated the CVD incidence with the overall bias of 149.60% and 128.23% for men, and 222.70% and 176.07% for women, respectively. In conclusion, the PARS risk assessment chart is a simple, accurate, and well-calibrated tool for predicting a 10-year risk of CVD occurrence in Iranian population and can be used in an attempt to develop national guidelines for the CVD management.

Analysis of sleep spindles in different NREM-REM cycles by means of bispectra

Spindles are periodic oscillations that characterize the predominant stage 2 during sleep. The aim of this paper is to study the spindle activity in different cycles of NREM-REM sleep. Higher order spectral analysis, particularly the bispectrum is used to analyze the quadratic nonlinear interaction. Ten one-second spindles from the first and the last NREM-REM cycles, with two normal subjects, are analyzed. Spindle waves are characterized using the power spectral density (PSD) function and the bispectrum to obtain: (1) differences between sleep spindles of the first and the last NREM-REM cycles, and (2) the interaction between the different components in the EEG signal. Similar results were obtained in both subjects and channels presented: no differences are observed neither in time nor in frequency domain with PSD function between spindles from the first and the last NREM-REM cycles. However, more frequency couplings were observed in the last cycle than in the first one by means of the bispectrum.