Researchers have eavesdropped on the internal monologue in our brains for the first time. The achievement is a step towards helping people who cannot physically speak communicate with the outside world.
Pasley and his colleagues recorded brain activity in people who already had electrodes implanted in their brain to treat epilepsy, while they listened to speech. The team found that certain neurons in the brain’s temporal lobe were only active in response to certain aspects of sound, such as a specific frequency. The team built an algorithm that could decode the words heard based on neural activity alone.
The algorithm isn’t perfect, says Stephanie Martin, who worked on the study with Pasley. “We got significant results but it’s not good enough yet to build a device.”
Electrodes distributed over the brain Credit: Adeen Flinker, UC Berkeley
In practice, if the decoder is to be used by people who are unable to speak it would have to be trained on what they hear rather than their own speech. “We don’t think it would be an issue to train the decoder on heard speech because they share overlapping brain areas,” says Martin.
The team is now fine-tuning their algorithms, by looking at the neural activity associated with speaking rate and different pronunciations of the same word, for example. “The bar is very high,” says Pasley. “Its preliminary data, and we’re still working on making it better.”
“Ultimately, if we understand covert speech well enough, we’ll be able to create a medical prosthesis that could help someone who is paralysed, or locked in and can’t speak,” he says.
Several other researchers are also investigating ways to read the human mind. Some can tell what pictures a person is looking at, others have worked out what neural activity represents certain concepts in the brain, and one team has even produced crude reproductions of movie clips that someone is watching just by analysing their brain activity. So is it possible to put it all together to create one multisensory mind-reading device?
In theory, yes, says Martin, but it would be extraordinarily complicated. She says you would need a huge amount of data for each thing you are trying to predict. “It would be really interesting to look into. It would allow us to predict what people are doing or thinking,” she says. “But we need individual decoders that work really well before combining different senses.”
Abstract- Decoding spectrotemporal features of overt and covert speech from the human cortex
Auditory perception and auditory imagery have been shown to activate overlapping brain regions. We hypothesized that these phenomena also share a common underlying neural representation. To assess this, we used electrocorticography intracranial recordings from epileptic patients performing an out loud or a silent reading task. In these tasks, short stories scrolled across a video screen in two conditions: subjects read the same stories both aloud (overt) and silently (covert). In a control condition the subject remained in a resting state. We first built a high gamma (70–150 Hz) neural decoding model to reconstruct spectrotemporal auditory features of self-generated overt speech. We then evaluated whether this same model could reconstruct auditory speech features in the covert speech condition. Two speech models were tested: a spectrogram and a modulation-based feature space. For the overt condition, reconstruction accuracy was evaluated as the correlation between original and predicted speech features, and was significant in each subject (p less than 10−5; paired two-sample t-test). For the covert speech condition, dynamic time warping was first used to realign the covert speech reconstruction with the corresponding original speech from the overt condition. Reconstruction accuracy was then evaluated as the correlation between original and reconstructed speech features. Covert reconstruction accuracy was compared to the accuracy obtained from reconstructions in the baseline control condition. Reconstruction accuracy for the covert condition was significantly better than for the control condition . The superior temporal gyrus, pre- and post-central gyrus provided the highest reconstruction information. The relationship between overt and covert speech reconstruction depended on anatomy. These results provide evidence that auditory representations of covert speech can be reconstructed from models that are built from an overt speech data set, supporting a partially shared neural substrate.
SOURCES – New Scientist, University of Berkeley
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