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1.
Dev Cogn Neurosci ; 61: 101244, 2023 06.
Article in English | MEDLINE | ID: mdl-37062244

ABSTRACT

Pediatric neuroimaging datasets are rapidly increasing in scales. Despite strict protocols in data collection and preprocessing focused on improving data quality, the presence of head motion still impedes our understanding of neurodevelopmental mechanisms. Large head motion can lead to severe noise and artifacts in magnetic resonance imaging (MRI) studies, inflating correlations between adjacent brain areas and decreasing correlations between spatial distant territories, especially in children and adolescents. Here, by leveraging mock-scans of 123 Chinese children and adolescents, we demonstrated the presence of increased head motion in younger participants. Critically, a 5.5-minute training session in an MRI mock scanner was found to effectively suppress the head motion in the children and adolescents. Therefore, we suggest that mock scanner training should be part of the quality assurance routine prior to formal MRI data collection, particularly in large-scale population-level neuroimaging initiatives for pediatrics.


Subject(s)
Brain , Magnetic Resonance Imaging , Adolescent , Child , Humans , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Motion , Neuroimaging , Head Movements , Artifacts
2.
Neuroscience ; 493: 109-118, 2022 06 15.
Article in English | MEDLINE | ID: mdl-35569642

ABSTRACT

Characterizing the functional involvement of specific brain regions has long been a central challenge in cognitive neuroscience. Functional magnetic resonance imaging (fMRI) techniques have offered solutions for mapping functional neural networks. The complex nature of structure-function correspondence makes an elaborate task design difficult to fully capture higher-order cognitive function. Other research practices, such as brain-behavior association or between-group comparisons, are thus widely used to explore cognitive correlations with specific brain regions. However, interpreting the results derived from a specific brain region with their underlying cognitive functions has been too general in publications. Here, we use two examples, i.e., a brain-intelligence correlation study and a depression-control comparison meta-study, to demonstrate use of two neuroimaging online databases, BrainMap and Neurosynth. One key utility of the two databases is collecting results from massive cognitive task-based fMRI (tb-fMRI) studies, i.e., coordinates in standard brain space. Just like looking up a "coordinate-based cognition dictionary", researchers can receive a plethora of related tb-fMRI activation information characterized by cognitive domains, specific cognitive functions, cognitive task paradigms, and related publications. Surprisingly, we found that only less than 1% of brain-behavior association or between-group comparison studies have utilized this dictionary approach. We encourage the community to further engage with the existing databases for specific and comprehensive interpretation of neuroimaging as well as guidance of future experimental tb-fMRI design.


Subject(s)
Brain Mapping , Cognition , Brain/diagnostic imaging , Brain/physiology , Brain Mapping/methods , Cognition/physiology , Magnetic Resonance Imaging/methods , Neuroimaging
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