How AI can read our scrambled inner thoughts

The crackle of electricity inside your brain has long been too complex to decode. Artificial intelligence is changing that.

The woman didn't move, apart from the rise and fall of her breathing – eyes fixed in concentration, hand clenched in a fist. Words were forming on a screen in front of her, slowly piecing together into whole sentences. Sentences she couldn't say out loud.

The 52-year-old woman had been paralysed by a stroke 19 years earlier, leaving her unable to speak clearly. Here, however, her internal monologue was appearing before her eyes. 

The women, identified only as participant T16, had been fitted with a tiny array of electrodes that was surgically inserted into a lobe at the front of her brain. Now a computer, powered by a form of artificial intelligence, was decoding the signals produced by her neurons as she imagined saying words, with the system translating them into text on a screen. She was taking part in a study at Stanford University in California, US, alongside three patients with the neurodegenerative disease amyotrophic lateral sclerosis (ALS), to test a technique capable of translating thoughts into real time text.

It was the closest scientists had come yet to a form of "mind reading".

The researchers unveiled their success in August 2025. A few months later, researchers in Japan revealed a "mind captioning" technique capable of generating detailed, accurate descriptions of what a person is seeing or picturing in their mind. It combined three different AI tools with non-invasive brain scans to translate a person's brain activity.

Both studies are the latest in a string of breakthroughs that are giving neuroscientists a new window into the inner workings of the human brain and providing opportunities to help people who are unable to communicate in other ways. Eventually, however, it could radically transform the way we all interact with the world around us and even with each other.

"In the next few years, we will see these technologies being commercialised and deployed at scale," says Maitreyee Wairagkar, a neuroengineer who has been developing brain-computer interfaces at the neuroprosthetics laboratory at University of California, Davis, in the US. Several companies including Elon Musk's Neuralink are already seeking to produce commercial brain chips that will bring this technology out of the lab and into the real world. "It's very exciting," says Wairagkar.

Scientists have been working on devices capable of communicating directly with the human brain – know as brain computer interfaces (BCIs) – for a surprisingly long time. In 1969, the American neuroscientist Eberhard Fetz demonstrated that monkeys could learn to move the needle of a meter with the activity of a single neuron in their brains if they were given a food pellet in return. In a more idiosyncratic experiment from the same period, Spanish scientist Jose Delgado was able to remotely stimulate the brain of an enraged bull, causing it to halt mid-charge.

BCIs have been able to decode the brain signals that accompany movement so that users can control a prosthetic limb or a cursor on a screen for decades. But BCIs that translate speech signals or other complex thoughts from brain signals have been slower to evolve. "A lot of early work was done on non-human primates… and obviously, with monkeys you cannot study speech," says Wairagkar.

In recent years, however, the field has made impressive advances in its efforts to decode the speech of people with impaired communication capabilities – for example, patients suffering from ALS resulting in paralysis or "locked in" syndrome. 

Stanford University researchers announced in 2021, for example, a successful proof-of-concept that allowed a quadriplegic man to produce English sentences by picturing himself drawing letters in the air with his hand. Using this method, he was able to write 18 words per minute.

Natural human speech is about 150 words per minute, so the next stage was decoding words from the neural activity associated with speech itself. In 2024, Wairagkar's lab trialled a technique that translated the attempted speech of a 45-year-old man with ALS directly into text on a computer screen. Achieving approximately 32 words per minute with 97.5% accuracy, this was the first demonstration of how speech BCIs could aid everyday communication, says Wairagkar.

These methods rely on tiny "arrays" of microelectrodes which are surgically implanted in the brain's surface. The arrays record patterns of neural activity from the area of the brain they are placed in, with the signals are converted into meaning by a computer algorithm. It is here that........

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