ObjectiveAn obsessive-compulsive disorder (OCD) subtype has been associated with streptococcal infections and is called pediatric autoimmune neuropsychiatric disorders associated with streptococci (PANDAS). The neuroanatomical characterization of subjects with this disorder is crucial for the better understanding of its pathophysiology; also, evaluation of these features as classifiers between patients and controls is relevant to determine potential biomarkers and useful in clinical diagnosis. This was the first multivariate pattern analysis (MVPA) study on an early-onset OCD subtype.MethodsFourteen pediatric patients with PANDAS were paired with 14 healthy subjects and were scanned to obtain structural magnetic resonance images (MRI). We identified neuroanatomical differences between subjects with PANDAS and healthy controls using voxel-based morphometry, diffusion tensor imaging (DTI), and surface analysis. We investigated the usefulness of these neuroanatomical differences to classify patients with PANDAS using MVPA.ResultsThe pattern for the gray and white matter was significantly different between subjects with PANDAS and controls. Alterations emerged in the cortex, subcortex, and cerebellum. There were no significant group differences in DTI measures (fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity) or cortical features (thickness, sulci, volume, curvature, and gyrification). The overall accuracy of 75% was achieved using the gray matter features to classify patients with PANDAS and healthy controls.ConclusionThe results of this integrative study allow a better understanding of the neural substrates in this OCD subtype, suggesting that the anatomical gray matter characteristics could have an immune origin that might be helpful in patient classification.

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Emotional processing has an important role in social interaction. We report the findings about the Independent Component Analysis carried out on a fMRI set obtained with a paradigm of face emotional processing. The results showed that an independent component, mainly cerebellar-medial-frontal, had a positive modulation associated with fear processing. Also, another independent component, mainly parahippocampal-prefrontal, showed a negative modulation that could be associated with implicit reappraisal of emotional stimuli. Independent Component Analysis could serve as a method to understand complex cognitive processes and their underlying neural dynamics.

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Introduction: The Food Disgust Scale (FDS) was recently developed and validated in Swiss adult population. This study aims to: (1) validate the FDS for the first time in a Spanish-speaking Mexican population, (2) correlate food disgust sensitivity with picky eating measures, and (3) explore the association between food disgust sensitivity and body mass index (BMI).Materials and Methods: A Spanish version of the FDS (FDS-Sp) and its short version (FDS-Sp short) were tested with confirmatory factor analysis (CFA) in order to test the original item/factor structure. Bivariate correlations were performed to determine the association between FDS-Sp/FDS-Sp short scores and picky eating. Lastly, hierarchical linear regression analysis was carried out to determine the relationship between food disgust sensitivity and BMI. Results:The factor structure of the FDS was replicated and acceptable internal consistency values were observed for FDS-Sp subscales (α varied between 0.781 and 0.955). Moreover, FDS-Sp subscales and FDS-Sp short were correlated with picky eating. Higher score in VEGI subscale of the FDS-Sp was a significant predictor for higher BMI, explaining 4% of the variance. Conclusion:FDS-Sp is a useful, reliable and robust psychometric instrument to measure the sensitivity to unpleasant food situations in a Mexican adult Spanishspeaking population. A relationship between food disgust sensitivity and picky eating, selective eating behaviors and neophobia in Mexicans was confirmed. BMI is multifactorial and only one subscale of FDS-Sp is a significant predictor for BMI status. These results are helpful to continue exploring food disgust in diverse populations.