Summary: Researchers aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. They analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers. Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy.
Summary: In this paper, they used confirmatory factor analysis (CFA) to examine the relationship between the p-factor(from Michelini) and executive functions. Also, they examined the longitudinal measurement invariance of the p-factor over the 3 different time points, baseline, 1-year follow-up, and 2-year follow-up. They found negative cross-sectional relationships between executive functions and p-factor at the baseline and 2-year follow-up.
Summary: In this review paper, they show representational similarity analysis (RSA) as a complementary approach that can powerfully inform representational components of cognitive control theories. Their aim is to illustrate how RSA can be incorporated into cognitive control investigations to shed new light on old questions.
Summary: Many studies had reported that fast fMRI can track neural activity well above the temporal limit of the canonical HRF model but the biophysical mechanisms under those techniques were not much investigated. In this study, they use visual and somatosensory tasks with simultaneous EEG-fMRI data to show the difference of the HRF’s timing and shapes by the differences of the stimulus intensity. Secondly, they show that as the spatial resolution of fMRI increases, voxel-wise HRFs begin to deviate from the canonical model, with a considerable portion of voxels exhibiting faster temporal dynamics than predicted by the canonical HRF.
Summary: They tried to take advantage of the complex multidimensional subspace structures that capture underlying modes of shared and unique variability across and within datasets. They designed a new method called multi dataset independent subspace analysis (MISA) that leverages joint information from multiple heterogeneous datasets in a flexible and synergistic fashion.
Summary: Researchers identified a large-scale association between multiple coordinated blood leukocyte gene coexpression modules and the multivariate fMRI response to speech. Associated coexpression modules were enriched in genes that are broadly expressed in the brain and many other tissues. These coexpression modules were also enriched in ASD-associated, prenatal, human-specific, and language-relevant genes. This work highlights distinctive neurobiology in ASD subtypes with different early language outcomes that is present well before such outcomes are known.
Summary: Previously, they gained factor scores using factor analysis to CBCL of ABCD data. With this hierarchical structure level, they tried to figure out the association between these factors and resting-state functional connectivity. Using the hierarchical linear model (HLM), they found a significant increment in variance with the p-factor model & 3-factor(internalizing, externalizing, and neurodevelopmental) model.
Summary: This study aims to develop and test the generalizability, specificity, and clinical relevance of a functional brain network-based marker for a well-defined feature of mind-wandering. The result was that SITUT is represented within a common pattern of brain network interactions across multiple time scales and contexts.
Summary: This study shows us that the contributions of subcomponents of visuomotor activities have not been studied in detail (i.e., The contributions of subcomponents of visuomotor actions have not been explored in detail). Here, the Authors designed a Kinematic control experiment using hand. And they conducted selectivity analysis and compared it. They found/elucidated the different subcomponents of hand actions and the roles of specific brain regions in their computation.
Summary: They utilized machine learning models to find associations between functional topography and four correlated dimensions of psychopathology and overall psychopathology (general psychopathology factor; p-factor).