It usually takes some time to understand someone speaking in a different accent, or speech that seems garbled or the lyrics of a song. But the brain finally gets it.
Neuroscientisst from University of California, Berkeley, tried to understand this phenomenon by studying brain activity when pieces of garbled or unintelligible speeches were played to subjects. They have found that the brain appears to be retuning itsels to recognise speech that was previously incomprehensible, said a press release from the university.
The study was published in Nature Commons in December. The authors include Christopher R. Holdgraf, Robert T Knight, and Fredreic E Theunissen, and others from the University
The scientists conducted an experiment with seven people and placed electrodes on the surfaces of their brains. First, a highly garbled sentence was played, which almost no one understood initially. Then a slightly less distorted version of the audio was played, followed immediately by the garbled version. The second time around, almost everyone understood the previously incomprehensible audio. The scientists called it a “pop out” effect.
The observations confirm speculation that neurons in the auditory cortex that pick out aspects of sound associated with language - the components of pitch, amplitude and timing that distinguish words or smaller sound bits called phonemes – continually tune themselves to pull meaning out of a noisy environment, the press release stated.
You can take the test yourself here.
“Something is changing in the auditory cortex to emphasize anything that might be speech-like, and increasing the gain for those features, so that I actually hear that sound in the noise,” said co-author Frédéric Theunissen, a UC Berkeley professor of psychology and a member of the Helen Wills Neuroscience Institute in the release. “It’s not like I am generating those words in my head. I really have the feeling of hearing the words in the noise with this pop-out phenomenon. It is such a mystery.”
Holdgraf explains how pop-outs work in this video.