Publications by authors named "Martins M Gatavins"
Neuroimaging research has uncovered a multitude of neural abnormalities associated with psychopathology, but few prediction-based studies have been conducted during adolescence, and even fewer used neurobiological features that were extracted across multiple neuroimaging modalities. This gap in the literature is critical, as deriving accurate brain-based models of psychopathology is an essential step towards understanding key neural mechanisms and identifying high-risk individuals. As such, we trained adaptive tree-boosting algorithms on multimodal neuroimaging features from the Lifespan Human Connectome Developmental (HCP-D) sample that contained 956 participants between the ages of 8 to 22 years old.
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- * The study investigates how various interlinked features of a child's environment, called the "exposome," relate to their unique brain network organization and cognitive abilities using advanced computational models.
- * Results from over 10,000 children show that the exposome is associated with both current and future cognitive performance, indicating that a holistic view of children's environments is crucial for predicting cognitive outcomes, even more so than detailed neuroimaging data.
Background: Allostatic load is the cumulative "wear and tear" on the body due to chronic adversity We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health.
Methods: We analyzed data on N = 5,035 diverse youth (mean age 12) from the Adolescent Brain Cognitive Development Study (ABCD). Using dimensionality reduction method, we calculated and overall allostatic load score (AL) using body mass index [BMI], waist circumference, blood pressure, blood glycemia, blood cholesterol, and salivary DHEA.
Growing up in a high poverty neighborhood is associated with elevated risk for academic challenges and health problems. Here, we take a data-driven approach to exploring how measures of children's environments relate to the development of their brain structure and function in a community sample of children between the ages of 4 and 10 years. We constructed exposomes including measures of family socioeconomic status, children's exposure to adversity, and geocoded measures of neighborhood socioeconomic status, crime, and environmental toxins.
View Article and Find Full Text PDFMyelination is a key developmental process that promotes rapid and efficient information transfer. Myelin also stabilizes existing brain networks and thus may constrain neuroplasticity, defined here as the brain's potential to change in response to experiences rather than the canonical definition as the process of change. Characterizing individual differences in neuroplasticity may shed light on mechanisms by which early experiences shape learning, brain and body development, and response to interventions.
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- Brain aging is complex and challenging to model accurately for clinical use, prompting researchers to use machine learning with neuroimaging data to predict age.
- Recent studies have moved from using single imaging types (unimodal) to multiple types (multimodal), which enhances the accuracy and sensitivity to chronic brain disorders.
- While multimodal imaging shows promise in refining brain age models, there remains significant room for improvement in making these models practically useful in clinical settings.