In a recent study published in the journal Science Advances, researchers in the United States used 3D transport-based morphometry (TBM) to identify and visualize brain changes linked to 16p11.2 ...
Relating brain activity to behavior is an ongoing aim of neuroimaging research as it would help scientists understand how the brain begets behavior — and perhaps open new opportunities for ...
Scientists have recently detailed how automation and machine learning can aid clinicians treating patients with spreading depolarizations, sometimes referred to as 'brain tsunamis.' A University of ...
The study is part of the PsychENCODE Consortium, which brings together multidisciplinary teams to generate large-scale gene expression and regulatory data from human brains across several major ...
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Machine learning helps tailor deep brain stimulation to improve gait in Parkinson’s disease
A team of researchers at the University of California, San Francisco has developed a data-driven method for optimizing deep brain stimulation (DBS) settings that significantly improved walking ...
In a comprehensive Genomic Press interview, Stanford University researcher Eric Sun reveals how machine learning is revolutionizing our understanding of brain aging at an unprecedented cellular ...
Researchers at the University of Houston and the University of Cincinnati are using machine learning to create a clearer picture of how heroin affects the brain, potentially opening new doors for ...
Melbourne, Australia - 12 August 2025 - Researchers have demonstrated that brain cells learn faster and carry out complex networking more effectively than machine learning by comparing how both a ...
RIT computing students and Professor Rui Li are working on a National Institutes of Health-funded project to use AI in ...
A study reveals that the effectiveness of brain stimulation on motor skills is determined by an individual's learning ability rather than age, highlighting the need for a more personalized approach to ...
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