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Browse all of our neurotechnology articles over the years. Remember you can click on the tags or search for specific articles.

This shows a young girl's head and brain waves.
FeaturedNeurosciencePsychology
··7 min read

Brain Signal Predicts and Restores Attention in Children

Researchers discovered a neural signature that predicts when a child is about to lose focus. By delivering a targeted pulse at the exact millisecond this signal appears, scientists were able to restore attentional flexibility in children with ADHD and epilepsy. This world-first study paves the way for non-invasive, personalized technologies that support learning and engagement in real-time.
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This shows a head and soundwaves.
Auditory NeuroscienceFeaturedNeuroscience
··10 min read

First Real-Time Brain-Controlled Hearing Device

Researchers have developed a brain-controlled hearing system that uses real-time neural signals to solve the "cocktail party problem." By matching a listener's brain waves to specific voices in a crowd, the device can automatically amplify a chosen conversation while silencing others, paving the way for a new generation of "neural extension" hearing aids that align with human intent.
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This shows a brain made of smoke.
FeaturedNeuroscience
··9 min read

Brain Stimulation Boosts Willpower to Quit Smoking

Addiction is a biological imbalance where reward systems overpower self-control. Researchers have demonstrated that using rTMS to stimulate the dorsolateral prefrontal cortex can restore this balance, reducing cigarette use by 11 per day. This "top-down" approach strengthens the brain's ability to resist cravings, offering a promising precision-medicine tool for those struggling to quit smoking.
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This shows a prism, math equations and a neural network.
FeaturedNeuroscience
··11 min read

Why Massive AI Models Actually Generalize Better

Physicists have developed a mathematical "toy model" using statistical physics to explain one of the great mysteries of deep learning: why massive neural networks learn patterns instead of just memorizing data. By applying renormalization theory, the team has shown how high-dimensional fluctuations stabilize learning, paving the way for more efficient and predictable artificial intelligence.
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