Brain connectivity during verbal working memory in children and adolescents

Working memory (WkM) is a fundamental cognitive process that serves as a building block for higher order cognitive functions. While studies have shown that children and adolescents utilize similar brain regions during verbal WkM, there have been few studies that evaluate the developmental differences in brain connectivity. Our goal was to study the development of brain connectivity related to verbal WkM in typically developing children and adolescents. Thirty‐five healthy children and adolescents, divided into three groups: 9–12 (children), 13–16 (young adolescents), and 17–19 (older adolescents) years, were included in this functional magnetic resonance imaging (fMRI) study. The verbal WkM task involved a modified Sternberg item recognition paradigm using three different loads. Brain connectivity analysis was performed using independent component analyses and regressing the components with the design matrix to determine task‐related networks. Connectivity analyses resulted in four components associated solely with encoding, four solely with recognition and two with both. Two networks demonstrated age‐related differences with respect to load, (1) the left motor area and right cerebellum, and 2) the left prefrontal cortex, left parietal lobe, and right cerebellum. Post hoc analyses revealed that the first network showed significant effects of age between children and the two older groups. There was increasing connectivity with increasing load for adolescents. The second network demonstrated age‐related differences between children and older adolescents. Children have higher task‐related connectivity at lower loads, but they tend to equalize with the adolescents with higher loads. Finally, a non‐load related network involving the orbital frontal and anterior cingulate cortices showed less connectivity in children. Hum Brain Mapp 35:698–711, 2014. © 2012 Wiley Periodicals, Inc.     

Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data

Advances in imaging acquisition techniques allow multiple imaging modalities to be collected from the same subject. Each individual modality offers limited yet unique views of the functional, structural, or dynamic temporal features of the brain. Multimodal fusion provides effective ways to leverage these complementary perspectives from multiple modalities. However, the majority of current multimodal fusion approaches involving functional magnetic resonance imaging (fMRI) are limited to 3D feature summaries that do not incorporate its rich temporal information. Thus, we propose a novel three‐way parallel group independent component analysis (pGICA) fusion method that incorporates the first‐level 4D fMRI data (temporal information included) by parallelizing group ICA into parallel ICA via a unified optimization framework. A new variability matrix was defined to capture subject‐wise functional variability and then link it to the mixing matrices of the other two modalities. Simulation results show that the three‐way pGICA provides highly accurate cross‐modality linkage estimation under both weakly and strongly correlated conditions, as well as comparable source estimation under different noise levels. Results using real brain imaging data identified one linked functional–structural–diffusion component associated to differences between schizophrenia and controls. This was replicated in an independent cohort, and the identified components were also correlated with major cognitive domains. Functional network connectivity revealed visual–subcortical and default mode‐cerebellum pairs that discriminate between schizophrenia and controls. Overall, both simulation and real data results support the use of three‐way pGICA to identify multimodal spatiotemporal links and to pursue the study of brain disorders under a single unifying multimodal framework.     

Hippocampal and parahippocampal volumes vary by sex and traumatic life events in children

BackgroundChildhood trauma is reliably associated with smaller hippocampal volume in adults; however, this finding has not been shown in children, and even less is known about how sex and trauma interact to affect limbic structural development in children.MethodsTypically developing children aged 9 to 15 years who completed a trauma history questionnaire and structural T₁-weighted MRI were included in this study (n = 172; 85 female, 87 male). All children who reported 4 or more traumas (n = 36) composed the high trauma group, and all children who reported 3 or fewer traumas (n = 136) composed the low trauma group. Using multivariate analysis of covariance, we compared FreeSurfer-derived structural MRI volumes (normalized by total intracranial volume) of the amygdalar, hippocampal and parahippocampal regions by sex and trauma level, controlling for age and study site.ResultsWe found a significant sex × trauma interaction, such that girls with high trauma had greater volumes than boys with high trauma. Follow-up analyses indicated significantly increased volumes for girls and generally decreased volumes for boys, specifically in the hippocampal and parahippocampal regions for the high trauma group; we observed no sex differences in the low trauma group. We noted no interaction effect for the amygdalae.LimitationsWe assessed a community sample and did not include a clinical sample. We did not collect data about the ages at which children experienced trauma.ConclusionResults revealed that psychological trauma affects brain development differently in girls and boys. These findings need to be followed longitudinally to elucidate how structural differences progress and contribute to well-known sex disparities in psychopathology.