More Neurotech News

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

This shows two heads and a brain.
Researchers have successfully altered human reward learning using non-invasive transcranial ultrasound stimulation directed at a deep brain structure linked to motivation. After brief stimulation, participants learned faster from positive feedback and repeated rewarding choices more consistently.
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New research using human brain organoids shows that early neural activity follows structured, time-based patterns long before sensory experience begins. These findings suggest the human brain comes preconfigured with a built-in “operating system” for organizing information, rather than relying solely on external input to form its circuits.
This shows a therapist and an AI head.
A new study demonstrates that an AI assistant can conduct psychiatric assessment interviews with greater diagnostic accuracy than widely used mental health rating scales. In a sample of 303 participants with confirmed psychiatric conditions, the AI assistant Alba provided DSM-based diagnostic suggestions after a brief conversational interview, outperforming rating scales in eight of nine disorders.
This shows the chip.
A new wearable system uses stretchable electronics and artificial intelligence to interpret human gestures with high accuracy even in chaotic, high-motion environments. Unlike traditional gesture-based wearables that fail under movement noise, this patch-based device filters interference in real time, allowing gestures to reliably control machines such as robotic arms.
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Researchers showed that large language models use a small, specialized subset of parameters to perform Theory-of-Mind reasoning, despite activating their full network for every task. This sparse internal circuitry depends heavily on positional encoding, especially rotary positional encoding, which shapes how the model tracks beliefs and perspectives.
This shows a head and text.
A new brain decoding method called mind captioning can generate accurate text descriptions of what a person is seeing or recalling—without relying on the brain's language system. Instead, it uses semantic features from vision-related brain activity and deep learning models to translate nonverbal thoughts into structured sentences.