Mental workload refers to the cognitive effort required to perform tasks, and it is an important factor in various fields, including system design, clinical medicine, and industrial applications. In ...

Brain–machine interfaces (BMIs) have enabled a handful of test participants who are unable to move or speak to communicate simply by thinking. An implanted device picks up the neural signals ...

Predicting patient response to antipsychotic medication is a major challenge in schizophrenia treatment. This study investigates the predictive role of gray matter (GM) in short- and long-term ...

The hardware isn't new, but a UC Davis research team's machine learning-powered method of translating brain activity in an ...

In a recent study published in PNAS Nexus, researchers provide new insights into human cognition by prioritizing interpretability in predictive modeling of intelligence from brain connectivity, rather ...

A recent study has revealed that specific patterns of gene activity serve as a hidden map that guides the complex wiring of ...

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 ...

Mentalising brain signatures reveal distinct self/other neural patterns from adolescence and are altered in schizophrenia, suggesting candidate neuromarkers.

A machine-learning analysis of brain waves recorded during sleep may help identify people at high risk of developing dementia, according to a study led by UC San Francisco and Beth Israel Deaconess ...

Electronic ‘Brain’ Teaches Itself.” That was how the New York Times defined the Mark I Perceptron in a headline on July 13, ...

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