Researchers at Stanford University have made a significant breakthrough in developing brain-computer interfaces (BCIs) to help people with paralysis communicate more effectively. A BCI uses tiny arrays of microelectrodes implanted in the brain’s surface layer to record neural activity patterns, which are then translated into actions such as speech or computer cursor movement.
The latest study, published in Cell, focuses on decoding “inner speech,” or language-based thoughts that occur silently in the mind. This approach has the potential to be more comfortable and efficient for people with paralysis than traditional BCI systems, which often require physical attempts at speech.
Researchers used machine learning algorithms to train computers to recognize patterns of neural activity associated with phonemes, the smallest units of speech. They found that inner speech evoked clear and robust patterns in brain regions involved in motor control, suggesting that BCIs could potentially restore fluent speech to people with paralysis via inner speech alone.
While this technology is still in its early stages, it has the potential to revolutionize communication for individuals with paralysis. However, researchers acknowledge the need for careful consideration of privacy concerns, such as accidental decoding of unintended thoughts or speech.
To address these issues, the team developed two new methods: a training algorithm that ignores inner speech and a password-protection system that prevents BCIs from decoding sensitive information. These advancements bring us closer to practical realization of this approach, with improved hardware expected within the next few years and future research focused on exploring brain regions outside of the motor cortex for higher-fidelity information about imagined speech.
As researchers continue to refine this technology, they hope to make it available to those who need it most – individuals with paralysis who struggle to communicate effectively.
Source: https://news.stanford.edu/stories/2025/08/study-inner-speech-decoding-device-patients-paralysis