Cocaine use disorder (CUD) is a substance use disorder (SUD) characterized by compulsion to seek, use and abuse of cocaine, with severe health and economic consequences for the patients, their families and society. Due to the lack of successful treatments and high relapse rate, more research is needed to understand this and other SUD. Here, we present the SUDMEX CONN dataset, a Mexican open dataset of 74 CUD patients (9 female) and matched 64 healthy controls (6 female) that includes demographic, cognitive, clinical, and magnetic resonance imaging (MRI) data. MRI data includes: 1) structural (T1-weighted), 2) multishell high-angular resolution diffusion-weighted (DWI-HARDI) and 3) functional (resting state fMRI) sequences. The repository contains unprocessed MRI data available in brain imaging data structure (BIDS) format with corresponding metadata available at the OpenNeuro data sharing platform. Researchers can pursue brain variability between these groups or use a single group for a larger population sample.

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Cocaine use disorder (CUD) is characterized by compulsive searching for cocaine that produces cognitive deficits, including lack of inhibition and decision-making. Several studies have shown that cocaine users exhibit brain volume and diffusion-based white-matter alterations in a wide variety of brain regions. However, the non-specificity of standard volumetric and diffusion-tensor methods to detect structural micropathology may lead to wrong conclusions. To better understand microstructural pathology in CUD, we analyzed 60 CUD participants (3 female) and 43 non-CUD controls (HC; 2 female) retrospectively from our cross-sectional Mexican SUD neuroimaging dataset (SUDMEX-CONN), using multi-shell diffusion-weighted imaging and the neurite orientation dispersion and density imaging (NODDI) analysis whose aims to more accurately model micro-structural pathology . We used Viso values of NODDI that employ a three-compartment model in white (WM) and gray-matter (GM). These values were correlated with clinical measures, including psychiatric severity status, impulsive behavior and pattern of cocaine and tobacco use in the CUD group. As hypothesized, we found higher whole-brain microstructural pathology in WM and GM in CUD patients than controls. ROI analysis revealed higher Viso-NODDI values in superior longitudinal fasciculus, cingulum, hippocampus cingulum, forceps minor and Uncinate fasciculus, as well as in frontal and parieto-temporal GM structures. Correlations between significant ROIs showed a dependency of impulsivity and years of cocaine consumption over Viso-NODDI. However, we did not find correlations with psychopathology measures. Overall, microstructural pathology seems to be present in CUD both in gray and white-matter, however their clinical relevance remains questionable.

Speakers use a variety of contextual information, such as facial emotional expressions for the successful transmission of their message. Listeners must decipher the meaning by understanding the intention behind it (Recanati, 1986). A traditional approach to the study of communicative intention has been through speech acts (Escandell, 2006). The objective of the present study is to further the understanding of the influence of facial expression to the recognition of communicative intention. The study sought to: verify the reliability of facial expressions recognition, find if there is an association between a facial expression and a category of speech acts, test if words contain an intentional load independent of the facial expression presented, and test whether facial expressions can modify an utterance’s communicative intention and the neural correlates associated using univariate and multivariate approaches. We found that previous observation of facial expressions associated with emotions can modify the interpretation of an assertive utterance that followed the facial expression. The hemodynamic brain response to an assertive utterance was moderated by the preceding facial expression and that classification based on the emotions expressed by the facial expression could be decoded by fluctuations in the brain’s hemodynamic response during the presentation of the assertive utterance. Neuroimaging data showed activation of regions involved in language, intentionality and face recognition during the utterance’s reading. Our results indicate that facial expression is a relevant contextual cue that decodes the intention of an utterance, and during decoding it engages different brain regions in agreement with the emotion expressed.

Fibromyalgia is a chronic condition characterized by widespread pain, as well as numerous symptoms related to central sensitization such as: fatigue, cognitive disturbances, constipation/diarrhea and sensory hypersensitivity. Furthermore, depression and anxiety are prevalent comorbidities, accompanied by emotion processing and regulation difficulties. Although fibromyalgia physiopathology is still not fully understood, neuroimaging research methods have shown brain structural and functional alterations as well as neuroinflammation abnormalities. We believe that open access to data may help fibromyalgia research advance more. Here, we present an open dataset of 33 fibromyalgia female patients and 33 paired healthy controls recruited from a Mexican population. Dataset includes demographic, clinical, behavioural and magnetic resonance imaging (MRI) data. The MRI data consists of: structural (T1- and T2- weighted) and functional (task-based and resting state) sequences. The task was an emotion processing and regulation task based on visual stimuli. The MRI data contained in the repository are unprocessed, presented in Brain Imaging Data Structure (BIDS) format and available on the OpenNeuro platform for future analysis.