Brian Pasley states  “We build computational models that test hypotheses about how the brain accomplishes this feat, and then see if these models match the brain recordings.”
To analyze the data from the  recordings, the researchers use an algorithm designed to extract key features of spoken words, such as the time period and volume changes between syllables.
They then entered these data into a computational model to reconstruct 'voicegrams' showing how these features change over time for each word. They found that these voicegrams could reproduce the sounds the patients heard accurately enough for individual words to be recognized.
During speech perception, the brain encodes and interprets complex acoustic signals composed of multiple frequencies that change over timescales as small as ten-thousandths of a second. The latest findings are a step towards understanding the processes by which the human brain converts sounds into meanings, and could have a number of important clinical applications.
“If we can better understand how each brain area participates in this process,” says Pasley, “we can start to understand how these neural mechanisms malfunction during communication disorders such as aphasia.”
Pasley and his team are interested in the similarities between perceived and imagined speech. “There is some evidence that perception and imagery may be pretty similar in the brain,” he says.
These similarities could eventually lead to the development of brain–computer interfaces that decode brain activity associated with the imagined speech of people who are unable to communicate, such as stroke patients or those with motor neurone disease or locked-in syndrome.
Sophie Scott, a neuroscientist at University College London, who studies speech perception and production, says that she has some reservations about the accuracy of the voicegrams. She would also like to see the pattern of responses for non-speech stimuli, such as music or unintelligible sounds, for comparison. But the authors “did an amazing job of transforming recordings of the neural responses to speech and relating these to the original sounds,” she says. “This approach may enable them to start determining the kinds of transformations and representations underlying normal speech perception.”