Brain-computer interface (BCI) technology has long been a crucial bridge connecting the human brain to the external world, and recently, the field has witnessed a significant breakthrough. According to the latest reports, a research team from Stanford University in the United States has successfully identified and decoded brain activity related to "inner speech" for the first time, achieving a decoding accuracy rate of up to 74%. This achievement not only represents a major advance in technology but also brings hope for individuals with severe speech impairments to regain their natural communication abilities.

Research Background and Objectives

The core of BCI technology lies in reading brain signals and converting them into computer commands to enable interaction between humans and machines or the external environment. Previous technologies mainly relied on decoding neural signals generated when users attempted to speak, or on converting eye movements into text. However, these methods had many limitations: the former required high muscle control and was tiring, while the latter was slow and could not meet the needs of efficient communication. Therefore, the Stanford research team turned their focus to "inner speech," which involves thinking silently without any muscle involvement.

Research Methods and Process

The research team selected participants who were severely paralyzed due to amyotrophic lateral sclerosis or brainstem stroke and implanted microelectrodes in their motor cortex (the area responsible for language). The experimental results showed that attempting to speak and imagining speaking activated overlapping regions in the brain and produced similar neural activity patterns, although the signal strength of "inner speech" was usually weaker. Based on this finding, the team trained an artificial intelligence model using the collected "inner speech" data.

In the proof-of-concept experiment, the BCI system performed remarkably well, able to decode imagined sentences from a vast vocabulary of up to 125,000 words with an accuracy rate of 74%. Moreover, the system could even capture numbers that users silently recited in their minds to complete calculation tasks. This achievement not only demonstrated the potential of BCI technology in decoding complex mental activities but also laid the foundation for future more efficient and natural communication methods.

Technological Innovation and Application Prospects

Another highlight of this study was the introduction of a password control mechanism. This mechanism allowed the system to be trained to temporarily ignore "inner speech" and instead activate the decoding function through a keyword password. Users only needed to silently recite a specific phrase in their minds, and the system could recognize and activate the decoding function with an accuracy rate of over 98%. This innovation not only increased the flexibility and practicality of the system but also provided more possibilities for the promotion of BCI technology in practical applications in the future.

Although the current technology cannot perfectly handle "inner speech," the research team is confident about its future development. With continuous improvements in sensors and algorithms, more advanced devices in the future are expected to achieve smooth mind-to-mind communication akin to everyday conversation. This technological breakthrough not only brings hope to individuals with severe speech impairments but also paves the way for the widespread application of BCI technology in multiple fields, including healthcare, education, and entertainment.

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