A study led by Georgia Institute of Technology's Associate Professor Costas Arvanitis takes a major step toward safer and ...

The hardware isn't new, but a UC Davis research team's machine learning-powered method of translating brain activity in an ALS patient into sentences with 92% accuracy is ...

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 ...

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

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 ...

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 ...

A new study offers insight into the health and lifestyle indicators - including diet, physical activity and weight - that align most closely with healthy brain function across the lifespan. The study ...

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 ...

A Cornell professor designed a room-size network of sensors that represented a single neuron. He claimed it would grow wiser ...

The Diagnostic Window Bottleneck: Neurologists rely heavily on EEGs to diagnose epilepsy, but standard clinical sessions provide only a 20-minute snapshot of brain activity, making manual detection ...

Epilepsy isn't always easy to diagnose. Seizures often don't occur during routine brain-wave recordings (EEGs), leaving ...

Studying physics can be very useful—even when it comes to machine learning. A digital "super-brain" with built-in knowledge ...