Interesting Works

[Article] Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics

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.

Chen, Jingyuan E., et al. “Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics.” NeuroImage 245 (2021): 118658.

[Article] Multidataset Independent Subspace Analysis With Application to Multimodal Fusion

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.

Silva, Rogers F., et al. “Multidataset independent subspace analysis with application to multimodal fusion.” IEEE Transactions on Image Processing 30 (2020): 588-602.

[Article] Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes

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.

Lombardo, Michael V., et al. “Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes.” Nature neuroscience 21.12 (2018): 1680-1688.

[Article] Associations between resting-state functional connectivity and a hierarchical dimensional structure of psychopathology in middle childhood

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.

Karcher, N. R., Michelini, G., Kotov, R., & Barch, D. M. (2021). Associations between resting-state functional connectivity and a hierarchical dimensional structure of psychopathology in middle childhood. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(5), 508-517.

[Article] Prediction of stimulus-independent and task-unrelated thought from functional brain networks

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.

Kucyi, A., Esterman, M., et al. “Prediction of stimulus-independent and task-unrelated thought from functional brain networks.” Nature communications(2021), 12(1), 1-17.

[Article] Human neuroimaging reveals the subcomponents of grasping, reaching and pointing actions

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.

Cavina-Pratesi, Cristiana, et al. “Human neuroimaging reveals the subcomponents of grasping, reaching and pointing actions.” Cortex 98 (2018): 128-148.

[Article] Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

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).

Cui, Z., Pines, A. R., Larsen, B., Sydnor, V. J., Li, H., Adebimpe, A., … & Satterthwaite, T. D. (2021). Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth. bioRxiv.

[Article] Computational models of category-selective brain regions enable high-throughput tests of selectivity

Summary: A CNN model of the ventral stream was used to predict responses to the ROIs: FFA, PPA, and EBA. The model accurately predicted activations and the result was shown by synthesized stimuli using GAN. Moreover, they generated importance map for photographs where each ROI showed difference

Ratan Murty, N. A., Bashivan, P., Abate, A., DiCarlo, J. J., & Kanwisher, N. (2021). Computational models of category-selective brain regions enable high-throughput tests of selectivity. Nature communications, 12(1), 1-14.

[Article] The cortical network of emotion regulation: insights from advanced EEG-fMRI integration analysis.

Summary: This study uses their recently developed Spatio-temporal fMRI constrained EEG source imaging approach to perform source analysis on a simultaneous EEG-fMRI emotion regulation paradigm. They found cortical dynamics underlying negative emotional responses and reappraisal-based regulation using a newly developed multimodal EEG-fMRI integration technique. By using this method they could get detailed timecourses regional activities and causality analyses based on cortical current density could be identified.

Nguyen, Thinh, et al. “The cortical network of emotion regulation: insights from advanced EEG-fMRI integration analysis.” IEEE transactions on medical imaging 38.10 (2019): 2423-2433.

[Article] A framework for linking resting-state chronnectome/genome features in schizophrenia: a pilot study

Summary: They propose a novel framework to combine features corresponding to functional magnetic resonance imaging including dynamic functional network connectivity (dFNC) and SNP data from schizophrenia patients and healthy controls. For each subject, both the functional and SNP data are selected as features for a parallel ICA based imaging-genomic framework. They also assessed the correlations between the polygenic risk scores (PRS) and both dFNC and SNP components’ loading parameters.

Rashid, Barnaly, et al. “A framework for linking resting-state chronnectome/genome features in schizophrenia: a pilot study.” Neuroimage 184 (2019): 843-854.