Rationale: Ayahuasca is a South American psychoactive plant tea which contains the serotonergic psychedelic N,N-dimethyltryptamine (DMT) and monoamine-oxidase inhibitors that render DMT orally active. Previous investigations with ayahuasca have highlighted a psychotropic effect profile characterized by enhanced introspective attention, with individuals reporting altered somatic perceptions and intense emotional modifications, frequently accompanied by visual imagery. Despite recent advances in the study of ayahuasca pharmacology, the neural correlates of acute ayahuasca intoxication remain largely unknown. Objectives: To investigate the effects of ayahuasca administration on regional cerebral blood flow. Methods: Fifteen male volunteers with prior experience in the use of psychedelics received a single oral dose of encapsulated freeze-dried ayahuasca equivalent to 1.0 mg DMT/kg body weight and a placebo in a randomized double-blind clinical trial. Regional cerebral blood flow was measured 100-110 min after drug administration by means of single photon emission tomography (SPECT). Results: Ayahuasca administration led to significant activation of frontal and paralimbic brain regions. Increased blood perfusion was observed bilaterally in the anterior insula, with greater intensity in the right hemisphere, and in the anterior cingulate/frontomedial cortex of the right hemisphere, areas previously implicated in somatic awareness, subjective feeling states, and emotional arousal. Additional increases were observed in the left amygdala/parahippocampal gyrus, a structure also involved in emotional arousal. Conclusions: The present results suggest that ayahuasca interacts with neural systems that are central to interoception and emotional processing and point to a modulatory role of serotonergic neurotransmission in these processes.

Purpose The Patient-Reported Outcomes Measurement Information System® (PROMIS®) was designed to develop, validate, and standardize item banks to measure key domains of physical, mental and social health in chronic conditions. This paper reports the calibration and validation testing of the PROMIS Self-Efficacy for Managing Chronic Conditions measures. Methods PROMIS Self-Efficacy for Managing Chronic Conditions item banks comprise five domains, Self-Efficacy for Managing: Daily Activities, Symptoms, Medications and Treatments, Emotions, and Social Interactions. Banks were calibrated in 1087 subjects from two data sources: 837 patients with chronic neurologic conditions (epilepsy, multiple sclerosis, neuropathy, Parkinson disease, and stroke) and 250 subjects from an online internet sample of adults with general chronic conditions. Scores were compared with one legacy scale: Self-Efficacy for Managing Chronic Disease 6-Item scale (SEMCD6) and five PROMIS short forms: Global Health (Physical and Mental), Physical Function, Fatigue, Depression, and Anxiety. Results The sample was 57% female, mean age=53.8 (SD=14.7), 76% white, 21% African American, 6% Hispanic and 76% with greater than high school education. Full item banks were created for each domain. All measures had good internal consistency and correlated well with SEMCD6 (r=0.56–0.75). Significant correlations were seen between the Self-Efficacy measures and other PROMIS short forms (r>0.38). Conclusions The newly developed PROMIS Self-Efficacy for Managing Chronic Conditions measures include five domains of self-efficacy that were calibrated across diverse chronic conditions and show good internal consistency and cross-sectional validity.

Eye movement artifacts represent a critical issue for quantitative electroencephalography (EEG) analysis and a number of mathematical approaches have been proposed to reduce their contribution in EEG recordings. The aim of this paper was to objectively and quantitatively evaluate the performance of ocular filtering methods with respect to spectral target variables widely used in clinical and functional EEG studies. In particular the following methods were applied: regression analysis and some blind source separation (BSS) techniques based on second-order statistics (PCA, AMUSE and SOBI) and on higher-order statistics (JADE, INFOMAX and FASTICA). Considering blind source decomposition methods, a completely automatic procedure of BSS based on logical rules related to spectral and topographical information was proposed in order to identify the components related to ocular interference. The automatic procedure was applied in different montages of simulated EEG and electrooculography (EOG) recordings: a full montage with 19 EEG and 2 EOG channels, a reduced one with only 6 EEG leads and a third one where EOG channels were not available. Time and frequency results in all of them indicated that AMUSE and SOBI algorithms preserved and recovered more brain activity than the other methods mainly at anterior regions. In the case of full montage: (i) errors were lower than 5% for all spectral variables at anterior sites; and (ii) the highest improvement in the signal-to-artifact (SAR) ratio was obtained up to 40 dB at these anterior sites. Finally, we concluded that second-order BSS-based algorithms (AMUSE and SOBI) provided an effective technique for eye movement removal even when EOG recordings were not available or when data length was short. ᭧