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A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3–96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease.

Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.

The children of older fathers have increased risks of developing schizophrenia spectrum disorders, and among those who develop these disorders, those with older fathers present with more severe clinical symptoms. However, the influence of advanced paternal age on other important domains related to schizophrenia, such as quantitative endophenotype deficit levels, remains unknown. This study investigated the associations between paternal age and level of endophenotypic impairment in a well-characterized family-based sample from the Consortium on the Genetics of Schizophrenia (COGS). All families included at least one affected subject and one unaffected sibling. Subjects met criteria for schizophrenia (probands; n = 293) or were unaffected first-degree siblings of those probands (n = 382). Paternal age at the time of subjects' birth was documented. Subjects completed a comprehensive clinical assessment and a battery of tests that measured 16 endophenotypes. After controlling for covariates, potential paternal age-endophenotype associations were analyzed using one model that included probands alone and a second model that included both probands and unaffected siblings. Endophenotype deficits in the Identical Pairs version of the 4-digit Continuous Performance Test and in the Penn Computerized Neurocognitive Battery verbal memory test showed significant associations with paternal age. However, after correcting for multiple comparisons, no endophenotype was significantly associated with paternal age. These findings suggest that factors other than advanced paternal age at birth may account for endophenotypic deficit levels in schizophrenia.

Humans communicate emotion vocally by modulating acoustic cues such as pitch, intensity and voice quality. Research has documented how the relative presence or absence of such cues alters the likelihood of perceiving an emotion, but the neural underpinnings of acoustic cue-dependent emotion perception remain obscure. Using functional magnetic resonance imaging in 20 subjects we examined a reciprocal circuit consisting of superior temporal cortex, amygdala and inferior frontal gyrus that may underlie affective prosodic comprehension. Results showed that increased saliency of emotion-specific acoustic cues was associated with increased activation in superior temporal cortex (planum temporale (PT), posterior superior temporal gyrus (pSTG), and posterior superior middle gyrus (pMTG)) and amygdala, whereas decreased saliency of acoustic cues was associated with increased inferior frontal activity and temporo-frontal connectivity. These results suggest that sensory-integrative processing is facilitated when the acoustic signal is rich in affective information, yielding increased activation in temporal cortex and amygdala. Conversely, when the acoustic signal is ambiguous, greater evaluative processes are recruited, increasing activation in inferior frontal gyrus (IFG) and IFG STG connectivity. Auditory regions may thus integrate acoustic information with amygdala input to form emotion-specific representations, which are evaluated within inferior frontal regions.

La práctica de la profesión médica en nuestra especialidad requiere de aquellos que la desempeñan un perfil de competencias adecuadas que incluyen conocimientos, habilidades, actitudes y valores. El incidente crítico (IC) es una narración estructurada en donde el profesional relata un suceso ocurrido en su actividad médica diaria que le genera impacto, dudas motivando acciones y reflexiones que mejoran su desarrollo profesional. En el año 2021, se incorporó el IC al proceso de recertificación. Objetivos: describir los resultados de los IC realizados en el proceso de recertificación, los factores asociados con su aprobación y evaluar si el IC es una herramienta adecuada para incluir en este proceso. Metodología: estudio descriptivo analítico de corte transversal. Resultados:11 IC (73%) fueron aprobados; la causa más frecuente de elección del IC fue no alcanzar el puntaje para recertificar (73%). Edad:mediana 52 años (RIC 49 a 58); el 100% fueron mujeres; 48% se formó en hospitales especializados y el tiempo a la recertificación fue de 120 meses (RIC 96 a 122). Dominio del conocimiento: el 14% desarrolló adecuadamente el escenario clínico y 13% la pregunta de investigación y 20% realizó un resumen completo. Dominio del hacer: el 35% implementó estrategias adecuadas; el 13% desarrolló estrategias-efectores pertinentes y solo el 7% realizó búsquedas bibliográficas completas en su plan de acción. Dominio del aprendizaje reflexivo: resultados inherentes al paciente (33%) y al profesional (20%) realizaron un enfoque integral adecuado; en las reflexiones finales desarrollaron adecuadamente las fortalezas el 13% y el 15% las debilidades en relación con el caso clínico presentado. Conclusiones: Los IC aprobados correspondieron a aquellos profesionales que lograron un enfoque integral del paciente y su problema, en estrecha relación con haber alcanzado un adecuado aprendizaje reflexivo. En función de estos resultados podríamos asumir que el IC podría ser una herramienta adecuada para incluir en el proceso de recertificación. No se encontró asociación estadística entre las variables investigadas y la aprobación del IC.