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Predictive coding of spoken words in human auditory cortex

In a recent MEG study by Pierre Gagnepain, Rik Henson and Matt Davis we show how the brain achieves incredible speed and accuracy in recognising speech. The study published on 10th April 2012 in Current Biology shows that the brain is constantly using knowledge of familiar words to predict what speech sounds will be heard next.

Matt Davis explains: "Many of us are familiar with using predictive texting on mobile phones – these systems try to guess what you want to say to save you the trouble of typing it. What we've shown is that the human brain uses a similar, but more sophisticated form of prediction in making sense of speech. The Superior Temporal Gyrus, a part of the brain involved in hearing, is constantly predicting what sounds will come next when listening to speech. So, having heard the syllable 'form...' rather than trying to guess whether the word is 'formal', 'formidable' or 'formula', the brain predicts which sounds would come next if each of these words were said. By predicting which sounds will be heard, the brain can respond to incoming speech extraordinarily quickly."

Full details of the paper can be found here:

Gagnepain, P, Henson, R. N. & Davis, M.H. (2012) Temporal predictive codes for spoken words in human auditory cortex. Current Biology, 22(7), 615-622.
PDF. Supporting Information.

The picture below, generated by Simon Strangeways, illustrates predictive coding as a neural mechanism that allows listeners to use knowledge of familiar words and their constituent sounds when understanding speech. Each speech sound is a star and familiar words are constellations. A human listener predicts future sounds when listening, so as to recognise the constellation ("formula") once the sequence of sounds ("formu...") uniquely identifies a single word.

An illustration of predictive coding in spoken word recognition.

Correction:

Iain DeWitt has spotted an error with equation (3) in the paper. The division by p(speech) is incorrect and should excluded. Thanks to Iain for his careful reading of the paper.

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