André Mascioli Cravo

Acute Biphasic Effects of Ayahuasca

Ritual use of ayahuasca, an amazonian Amerindian medicine turned sacrament in syncretic religions in Brazil, is rapidly growing around the world. Because of this internationalization, a comprehensive understanding of the pharmacological mechanisms of action of the brew and the neural correlates of the modified states of consciousness it induces is important. Employing a combination of electroencephalogram (EEG) recordings and quantification of ayahuascas compounds and their metabolites in the systemic circulation we found ayahuasca to induce a biphasic effect in the brain. This effect was composed of reduced power in the alpha band (8–13 Hz) after 50 minutes from ingestion of the brew and increased slow- and fast-gamma power (30–50 and 50–100 Hz, respectively) between 75 and 125 minutes. Alpha power reductions were mostly located at left parieto-occipital cortex, slow-gamma power increase was observed at left centro-parieto-occipital, left fronto-temporal and right frontal cortices while fast-gamma increases were significant at left centro-parieto-occipital, left fronto-temporal, right frontal and right parieto-occipital cortices. These effects were significantly associated with circulating levels of ayahuasca’s chemical compounds, mostly N,N-dimethyltryptamine (DMT), harmine, harmaline and tetrahydroharmine and some of their metabolites. An interpretation based on a cognitive and emotional framework relevant to the ritual use of ayahuasca, as well as its potential therapeutic effects is offered.

Lexical-retrieval and semantic memory in Parkinson's disease: The question of noun and verb dissociation

ABSTRACT The dissociation between the processing of verbs and nouns has been debated in light of the Embodied Cognition Theory (EC). The objective of this paper is to verify how action and verb processing deficits of PD patients are modulated by different tasks with different cognitive demands. Action and object lexical‐semantic processing was evaluated in patients with Parkinson’s Disease (PD) and cognitively healthy controls through three different tasks (verbal fluency, naming and semantic association). Compared to controls, PD patients presented worse performance in naming actions and in the two semantic association tasks (action/object). Action verbal fluency performance was significantly associated with PD severity whereas object semantic association deficits and noun verbal fluency scores were associated to lower scores in measures of global cognitive functioning. Our data suggest that semantic deficits are related to the type of cognitive processing and this is in the line with more flexible EC accounts.

Action/Verb processing: Debates in neuroimaging and the contribution of studies in patients with Parkinson’s disease

The objective of the current review was to verify whether studies investigating lexical-semantic difficulties in patients with Parkinsons disease (PD) support the Embodied Cognition model. Under this framework, it is predicted that patients with PD will have more difficulties in the semantic processing of action concepts (action verbs) than of motionless objects. We also verified how and whether these studies are following current debates of Neuroscience, particularly the debate between the Lexical and the Embodied Cognition models. Recent neuroimaging studies on the neural basis of the semantics of verbs were presented, as well as others that focused on the neural processing of verbs in PD. We concluded that few studies suitably verified the Embodied Cognition theory in the context of PD, especially using neuroimaging techniques. These limitations show there is much to investigate on the semantic difficulties with action verbs in these patients, where it is particularly important to control for psycholinguistic variables and the inherent semantic characteristics of verbs in future studies.

Dynamic representation of time in brain states

The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view from computational and in vitro studies, there is still a lack of results from experiments in humans. We show that high-dimensional brain states revealed by multivariate pattern analysis of human EEG are correlated to temporal judgements. First, we show that, as participants estimate temporal intervals, the spatiotemporal dynamics of their brain activity are consistent across trials. Second, we present evidence that these dynamics exhibit properties of temporal perception, such as scale invariance. Lastly, we show that it is possible to predict temporal judgements based on brain states. These results show how scalp recordings can reveal the spatiotemporal dynamics of human brain activity related to temporal processing.

Low-frequency cortical oscillations are modulated by temporal prediction and temporal error coding.

Abstract Monitoring and updating temporal predictions are critical abilities for adaptive behavior. Here, we investigated whether neural oscillations are related to violation and updating of temporal predictions. Human participants performed an experiment in which they had to generate a target at an expected time point, by pressing a button while taking into account a variable delay between the act and the stimulus occurrence. Our behavioral results showed that participants quickly adapted their temporal predictions in face of an error. Concurrent electrophysiological (EEG) data showed that temporal errors elicited markers that are classically related to error coding. Furthermore, intertrial phase coherence of frontal theta oscillations was modulated by error magnitude, possibly indexing the degree of surprise. Finally, we found that delta phase at stimulus onset was correlated with future behavioral adjustments. Together, our findings suggest that low frequency oscillations play a key role in monitoring and in updating temporal predictions. HighlightsTemporal predictions are quickly adjusted in face of an error.Temporal errors elicit an increase in frontal intertrial theta phase coherence.Delta phase at stimulus onset is correlated with future behavioral adjustments.

Temporal Anticipation Based on Memory

The fundamental role that our long-term memories play in guiding perception is increasingly recognized, but the functional and neural mechanisms are just beginning to be explored. Although experimental approaches are being developed to investigate the influence of long-term memories on perception, these remain mostly static and neglect their temporal and dynamic nature. Here, we show that our long-term memories can guide attention proactively and dynamically based on learned temporal associations. Across two experiments, we found that detection and discrimination of targets appearing within previously learned contexts are enhanced when the timing of target appearance matches the learned temporal contingency. Neural markers of temporal preparation revealed that the learned temporal associations trigger specific temporal predictions. Our findings emphasize the ecological role that memories play in predicting and preparing perception of anticipated events, calling for revision of the usual conceptualization of contextual associative memory as a reflective and retroactive function.

Predicting affective valence using cortical hemodynamic signals

Ascribing affective valence to stimuli or mental states is a fundamental property of human experiences. Recent neuroimaging meta-analyses favor the workspace hypothesis for the neural underpinning of valence, in which both positive and negative values are encoded by overlapping networks but are associated with different patterns of activity. In the present study, we further explored this framework using functional near-infrared spectroscopy (fNIRS) in conjunction with multivariate analyses. We monitored the fronto-temporal and occipital hemodynamic activity of 49 participants during the viewing of affective images (passive condition) and during the imagination of affectively loaded states (active condition). Multivariate decoding techniques were applied to determine whether affective valence is encoded in the cortical areas assessed. Prediction accuracies of 89.90 ± 13.84% and 85.41 ± 14.43% were observed for positive versus neutral comparisons, and of 91.53 ± 13.04% and 81.54 ± 16.05% for negative versus neutral comparisons (passive/active conditions, respectively). Our results are consistent with previous studies using other neuroimaging modalities that support the affective workspace hypothesis and the notion that valence is instantiated by the same network, regardless of whether the affective experience is passively or actively elicited.

Decoding affective states across databases using functional near-infrared spectroscopy

Affective decoding is the inference of human emotional states using brain signal measurements. This approach is crucial to develop new therapeutic approaches for psychiatric rehabilitation, such as affective neurofeedback protocols. To reduce the training duration and optimize the clinical outputs, an ideal clinical neurofeedback could be trained using data from an independent group of volunteers before being used by new patients. Here, we investigated if this subject-independent design of affective decoding can be achieved using functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas. For this purpose, a linear discriminant analysis classifier was first trained in a dataset (49 participants, 24.65±3.23 years) and then tested in a completely independent one (20 participants, 24.00±3.92 years). Significant balanced accuracies between classes were found for positive vs. negative (64.50 ± 12.03%, p<0.01) and negative vs. neutral (68.25 ± 12.97%, p<0.01) affective states discrimination during a reactive block consisting in viewing affective-loaded images. For an active block, in which volunteers were instructed to recollect personal affective experiences, significant accuracy was found for positive vs. neutral affect classification (71.25 ± 18.02%, p<0.01). In this last case, only three fNIRS channels were enough to discriminate between neutral and positive affective states. Although more research is needed, for example focusing on better combinations of features and classifiers, our results highlight fNIRS as a possible technique for subject-independent affective decoding, reaching significant classification accuracies of emotional states using only a few but biologically relevant features.Multivariate brain decoding (MBD) can be applied to estimate mental states using brain signal measurements. In the best scenario, a MBD model should be trained in a first set of volunteers and then validated in a new and independent dataset. Here, we aimed to evaluate whether functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas provide enough information to discriminate affective states. For this purpose, a linear discriminant analysis classifier was trained in a first database (49 participants, 24.65 ± 3.23 years) and tested in an independent database (20 participants, 24.00 ± 3.92 years). Significant accuracies were found for positive vs. negative (64.50 ± 12.44%, p

Semantic memory manifestations in normal aging and parkinson’s disease and their implications to the embodied cognition theory

3.27/12.81, respectively. We retrospectively analyzed the prevalence, conversion rate to dementia, and neurobehavioral background among the participants in the Kurihara project. Methods: 1) The database of 513 participants aged 75+ years in the Kurihara Project was analyzed according to the following criteria: cognitive complaints as the GDS-15 item; 1 SD below the mean gait speed by the maximum speed; no dementia or ADL disability by CDR 0/0.5 and DSM-IV. 2) Conversion rates to dementia (3-5 years) from the MCR/Non-MCR groups were calculated. 3) Neurobehavioral backgrounds were investigated using the executive test scores of TrailMaking Tests and Digit Symbol, and MRI-based diagnoses of very mild Alzheimer’s disease (AD) or subcortical vascular dementia (SVD). Results: 1) We found 57 participants that met the criteria for MCR syndrome (11.1%). 2) No group difference was noted for conversion to dementia. The effect of CDR was higher than that of MCR .3) One-way ANCOVA with the covariance of MMSE revealed decreased scores on TMT-A and Digit Symbol in the MCR group. No diagnostic differences were noted for very mild AD or SVD. Conclusions: Our calculated prevalence value for MCR was within the CI of Verghese et al. However, there were no significant differences in the incidence of dementia or the neurological background. We considered executive dysfunction as a surrogate marker of MCI. As TMT-A or Digit symbol test were at the upper extremities, maximum gait velocity was at the lower extremity.