As part of its ongoing quest to advance better brain health and performance, new research led by Center for BrainHealth at The University of Texas at Dallas investigated neural biomarkers associated with improvements on a brain health index. The study, “Toward Precision Brain Health: Accurate Prediction of a Cognitive Index Trajectory Using Neuroimaging Metrics,” was … Read more
In a recent study published in JAMA Network Open, researchers assess the link between adverse life experiences and changes in brain reactivity using the multilevel kernel density analysis (MKDA) method on task-based functional magnetic resonance imaging (fMRI) studies. Study: Adverse Life Experiences and Brain Function: A Meta-Analysis of Functional Magnetic Resonance Imaging Findings. Image Credit: Tushchakorn … Read more
In a recent study published in Nature Communications, researchers examine neural networks in the left language-dominant hemisphere responsible for semantic integration using intracranial recordings in epilepsy patients during reading tasks. These experiments were also used to distinguish between effects driven by semantic coherence and task-based referentiality. Study: The spatiotemporal dynamics of semantic integration in the human … Read more
In certain cases, a new method can provide as much information from brain images taken with computed tomography (CT) as images captured with magnetic resonance imaging (MRI). The method, presented in a study from the University of Gothenburg, could enhance diagnostic support, particularly in primary care, for conditions such as dementia and other brain disorders. … Read more
In a recent study published in the journal Science Advances, researchers described a deep learning (DL)-based reconstruction framework to accelerate brain magnetic resonance imaging (MRI) at 0.055 tesla (T). MRI is an invaluable imaging modality due to its non-invasive, non-ionizing, quantitative, three-dimensional (3D), and multiparametric nature. Research has focused on high-field (1.5 T or 3 … Read more