A team of researchers led by Kim Hong Ji and Woo Choong-Wan at the Center for Neuroscience Imaging Research (CNIR) within the Institute for Basic Science (IBS), in collaboration with Emily FINN at ...

The idea of “reading minds” has shifted from science fiction to a concrete engineering challenge, and the latest breakthroughs suggest the brain’s private code is finally yielding. Researchers are not ...

Practical brain–computer interfaces should be able to decipher brain signals and dynamically adapt to brain fluctuations. This, however, requires a decoder capable of flexible updates with ...

BrainWhisperer is Tether’s Brain-to-text project. Tether is earmarking resources to build technologies that push the borders of intracranial electrocortical decoding. The latest result is a variable ...

A new brain chip rival is challenging Neuralink by claiming 20x faster neural decoding. Reports highlight technological ...

Speech brain-computer interfaces (BCIs) combine neural recordings with large language models to achieve real-time intelligible speech. However, these decoders rely on dense, intact cortical coverage ...

Scientists at the University of California, San Francisco have developed a bilingual brain implant that uses artificial intelligence to help a stroke survivor communicate in Spanish and English for ...

A new machine learning algorithm developed by researchers from the USC Viterbi School of Engineering and NYU's Center for Neural Science can isolate brain signals and decode how neural dynamics in the ...

First, the data was independently segmented into quintiles (5 levels) for self-relevance and valence based on participant’s ratings. Next, time points (TRs) were assigned according to the levels of ...