Seeing with the eyes shut: neural basis of enhanced imagery following Ayahuasca ingestion.

The hallucinogenic brew Ayahuasca, a rich source of serotonergic agonists and reuptake inhibitors, has been used for ages by Amazonian populations during religious ceremonies. Among all perceptual changes induced by Ayahuasca, the most remarkable are vivid "seeings." During such seeings, users report potent imagery. Using functional magnetic resonance imaging during a closed-eyes imagery task, we found that Ayahuasca produces a robust increase in the activation of several occipital, temporal, and frontal areas. In the primary visual area, the effect was comparable in magnitude to the activation levels of natural image with the eyes open. Importantly, this effect was specifically correlated with the occurrence of individual perceptual changes measured by psychiatric scales. The activity of cortical areas BA30 and BA37, known to be involved with episodic memory and the processing of contextual associations, was also potentiated by Ayahuasca intake during imagery. Finally, we detected a positive modulation by Ayahuasca of BA 10, a frontal area involved with intentional prospective imagination, working memory and the processing of information from internal sources. Therefore, our results indicate that Ayahuasca seeings stem from the activation of an extensive network generally involved with vision, memory, and intention. By boosting the intensity of recalled images to the same level of natural image, Ayahuasca lends a status of reality to inner experiences. It is therefore understandable why Ayahuasca was culturally selected over many centuries by rain forest shamans to facilitate mystical revelations of visual nature.

A Deep Learning-based Model for Detecting Abnormalities on Brain MR Images for Triaging: Preliminary Results from a Multisite Experience.

PURPOSE: To develop a deep learning model for detecting brain abnormalities on MR images. MATERIALS AND METHODS: In this retrospective study, a deep learning approach using T2-weighted fluid-attenuated inversion recovery images was developed to classify brain MRI findings as "likely normal" or "likely abnormal." A convolutional neural network model was trained on a large, heterogeneous dataset collected from two different continents and covering a broad panel of pathologic conditions, including neoplasms, hemorrhages, infarcts, and others. Three datasets were used. Dataset A consisted of 2839 patients, dataset B consisted of 6442 patients, and dataset C consisted of 1489 patients and was only used for testing. Datasets A and B were split into training, validation, and test sets. A total of three models were trained: model A (using only dataset A), model B (using only dataset B), and model A + B (using training datasets from A and B). All three models were tested on subsets from dataset A, dataset B, and dataset C separately. The evaluation was performed by using annotations based on the images, as well as labels based on the radiology reports. RESULTS: Model A trained on dataset A from one institution and tested on dataset C from another institution reached an F1 score of 0.72 (95% CI: 0.70, 0.74) and an area under the receiver operating characteristic curve of 0.78 (95% CI: 0.75, 0.80) when compared with findings from the radiology reports. CONCLUSION: The model shows relatively good performance for differentiating between likely normal and likely abnormal brain examination findings by using data from different institutions.Keywords: MR-Imaging, Head/Neck, Computer Applications-General (Informatics), Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021Supplemental material is available for this article.

Association between pain drawing and psychological factors in musculoskeletal chronic pain: A systematic review.

BACKGROUND: It has been speculated that there is an association between pain area and psychological factors in chronic musculoskeletal pain conditions; however, this relation is not well established. PURPOSE: To investigate the association between pain distribution and psychological factors in chronic musculoskeletal pain conditions. STUDY DESIGN: Systematic review. METHODS: We searched the following databases using optimized search strategies: MEDLINE, PsycINFO, Scopus, Web of Science and Cochrane. Studies were included if they investigated the relation between pain area using a pain drawing (PD) and psychological factors measured by any consistent available method. RESULTS: Eleven articles were included. A total of 1301 participants with different musculoskeletal pain conditions, including low back pain, whiplash-associated disorders and fibromyalgia took part in the studies. In three studies, the correlation between pain area and depression was weak (r = 0.15, p = N/A; r = 0.26, p < 0.05; r = 0.25, p = 0.01). Depression seemed to be a risk factor for pain in more body areas in one study (relative risk = 6.09, 95% CI = 1.1-33.5; p < 0.05). The relation between pain area and other psychological factors such as anxiety, kinesiophobia, catastrophizing, memory disturbances and concentration difficulties was also reported. CONCLUSIONS: A definitive answer on the relation of psychological factors and pain area is not available; the findings suggest that only depression might have a weak relation with pain area. Future studies that investigate sensory, psychological, emotional, cognitive and behavioral aspects, and also more accurate methods of PD assessment, are needed.

Time-Perception Network and Default Mode Network Are Associated with Temporal Prediction in a Periodic Motion Task.

The updating of prospective internal models is necessary to accurately predict future observations. Uncertainty-driven internal model updating has been studied using a variety of perceptual paradigms, and have revealed engagement of frontal and parietal areas. In a distinct literature, studies on temporal expectations have also characterized a time-perception network, which relies on temporal orienting of attention. However, the updating of prospective internal models is highly dependent on temporal attention, since temporal attention must be reoriented according to the current environmental demands. In this study, we used functional magnetic resonance imaging (fMRI) to evaluate to what extend the continuous manipulation of temporal prediction would recruit update-related areas and the time-perception network areas. We developed an exogenous temporal task that combines rhythm cueing and time-to-contact principles to generate implicit temporal expectation. Two patterns of motion were created: periodic (simple harmonic oscillation) and non-periodic (harmonic oscillation with variable acceleration). We found that non-periodic motion engaged the exogenous temporal orienting network, which includes the ventral premotor and inferior parietal cortices, and the cerebellum, as well as the presupplementary motor area, which has previously been implicated in internal model updating, and the motion-sensitive area MT+. Interestingly, we found a right-hemisphere preponderance suggesting the engagement of explicit timing mechanisms. We also show that the periodic motion condition, when compared to the non-periodic motion, activated a particular subset of the default-mode network (DMN) midline areas, including the left dorsomedial prefrontal cortex (DMPFC), anterior cingulate cortex (ACC), and bilateral posterior cingulate cortex/precuneus (PCC/PC). It suggests that the DMN plays a role in processing contextually expected information and supports recent evidence that the DMN may reflect the validation of prospective internal models and predictive control. Taken together, our findings suggest that continuous manipulation of temporal predictions engages representations of temporal prediction as well as task-independent updating of internal models.

Amygdala responses to unpleasant pictures are influenced by task demands and positive affect trait.

The role of attention in emotional processing is still the subject of debate. Recent studies have found that high positive affect in approach motivation narrows attention. Furthermore, the positive affect trait has been suggested as an important component for determining human variability in threat reactivity. We employed functional magnetic resonance imaging to investigate whether different states of attention control would modulate amygdala responses to highly unpleasant pictures relative to neutral and whether this modulation would be influenced by the positive affect trait. Participants (n = 22, 12 male) were scanned while viewing neutral (people) or unpleasant pictures (mutilated bodies) flanked by two peripheral bars. They were instructed to (a) judge the picture content as unpleasant or neutral or (b) to judge the difference in orientation between the bars in an easy condition (0 or 90(∘) orientation difference) or (c) in a hard condition (0 or 6(∘) orientation difference). Whole brain analysis revealed a task main effect of brain areas related to the experimental manipulation of attentional control, including the amygdala, dorsolateral prefrontal cortex, and posterior parietal cortex. Region of interest analysis showed an inverse correlation (r = -0.51, p < 0.01) between left amygdala activation and positive affect level when participants viewed unpleasant stimuli and judged bar orientation in the easy condition. This result suggests that subjects with high positive affect exhibit lower amygdala reactivity to distracting unpleasant pictures. In conclusion, the current study suggests that positive affect modulates attention effect on unpleasant pictures, therefore attenuating emotional responses.

Effects of diazepam on BOLD activation during the processing of aversive faces.

This study aimed to measure, using fMRI, the effect of diazepam on the haemodynamic response to emotional faces. Twelve healthy male volunteers (mean age = 24.83 ± 3.16 years), were evaluated in a randomized, balanced-order, double-blind, placebo-controlled crossover design. Diazepam (10 mg) or placebo was given 1 h before the neuroimaging acquisition. In a blocked design covert face emotional task, subjects were presented with neutral (A) and aversive (B) (angry or fearful) faces. Participants were also submitted to an explicit emotional face recognition task, and subjective anxiety was evaluated throughout the procedures. Diazepam attenuated the activation of right amygdala and right orbitofrontal cortex and enhanced the activation of right anterior cingulate cortex (ACC) to fearful faces. In contrast, diazepam enhanced the activation of posterior left insula and attenuated the activation of bilateral ACC to angry faces. In the behavioural task, diazepam impaired the recognition of fear in female faces. Under the action of diazepam, volunteers were less anxious at the end of the experimental session. These results suggest that benzodiazepines can differentially modulate brain activation to aversive stimuli, depending on the stimulus features and indicate a role of amygdala and insula in the anxiolytic action of benzodiazepines.