Researchers translate brain signals using microelectrodes

The move is a first step towards the development of a system that might, one day, allow severely paralysed people to speak with their thoughts.

’We have been able to decode spoken words using only signals from the brain with a device that has promise for long-term use in paralysed patients who cannot now speak,’ said Bradley Greger, an assistant professor of bioengineering at the university.

As the method involves placing electrodes on the brain and still needs improving, he expects it will be a few years before clinical trials will take place on paralysed people who are unable to speak.

In a trial, the university research team placed grids of tiny non-penetrating microelectrodes called microECoGs over speech centres in the brain of a volunteer with severe epileptic seizures. The man already had a craniotomy – temporary partial skull removal – so doctors could place larger, conventional electrodes to locate the source of his seizures and surgically stop them.

Since the microelectrodes do not penetrate brain matter, they are considered safe to place on speech areas of the brain – something that cannot be done with penetrating electrodes that have been used in experimental devices to help paralysed people control a computer cursor or an artificial arm.

Using the experimental microelectrodes, the scientists recorded brain signals as the patient repeatedly read each of 10 words that might be useful to a paralysed person: ’yes’, ’no’, ’hot’, ’cold’, ’hungry’, ’thirsty’, ’hello’, ’goodbye’, ’more’ and ’less’.

Later, they tried figuring out which brain signals represented each of the 10 words. When they compared any two brain signals – such as those generated when the man said the words ’yes’ and ’no’ – they were able to distinguish brain signals for each word 76 per cent to 90 per cent of the time.

When they examined all 10 brain signal patterns at once, they were able to pick out the correct word that any one signal represented only 28 per cent to 48 per cent of the time – better than chance (which would have been 10 per cent) but not good enough for a device to translate a paralysed person’s thoughts into words spoken by a computer.

’This is proof of concept. We’ve proven these signals can tell you what the person is saying well above chance,’ said Greger. ’But we need to be able to do more words with more accuracy before it is something a patient really might find useful.’