Toggle light / dark theme

A multi-university research team co-led by University of Virginia engineering professor Gustavo K. Rohde has developed a system that can spot genetic markers of autism in brain images with 89 to 95% accuracy.

Their findings suggest that doctors may one day see, classify and treat autism and related neurological conditions with this method, without having to rely on or wait for behavioral cues. And that means this truly personalized medicine could result in earlier interventions.

“Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first approach could transform understanding and treatment of autism,” the researchers wrote in a paper published in the journal Science Advances.

A long-running research endeavor reveals key chemical players that cement memories in place—and still more have yet to be discovered.

By Simon Makin

The persistence of memory is crucial to our sense of identity, and without it, there would be no learning, for us or any other animal. It’s little wonder, then, that some researchers have called how the brain stores memories the most fundamental question in neuroscience.

Researchers at the École Polytechnique Fédérale de Lausanne (EPFL) have developed a revolutionary miniaturized brain-machine interface (MiBMI) that converts brain activity directly into text. This breakthrough technology, housed on silicon chips with a total area of just 8mm², marks a significant advancement in brain-computer interface technology.

The study, published in the IEEE Journal of Solid-State Circuits and presented at the International Solid-State Circuits Conference, highlights a device that could dramatically improve communication for individuals with severe motor impairments.

The study, published by a multi-institutional team of researchers…


Researchers used D-Wave’s quantum computing technology to explore the relationship between prefrontal brain activity and academic achievement, particularly focusing on the College Scholastic Ability Test (CSAT) scores in South Korea.

The study, published by a multi-institutional team of researchers across Korea in Scientific Reports, relied on functional near-infrared spectroscopy (fNIRS) to measure brain signals during various cognitive tasks and then applied a quantum annealing algorithm to identify patterns correlating with higher academic performance.

The team identified several cognitive tasks that might boost CSAT score — and that could have significant implications for educational strategies and cognitive neuroscience. The use of a quantum computer as a partner in the research process could also be a step towards practical applications of quantum computing in neuroimaging and cognitive assessment.