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Title: Linguistic processing of task-irrelevant speech at a cocktail party. Author: Har-Shai Yahav P, Zion Golumbic E. Journal: Elife; 2021 May 04; 10():. PubMed ID: 33942722. Abstract: Paying attention to one speaker in a noisy place can be extremely difficult, because to-be-attended and task-irrelevant speech compete for processing resources. We tested whether this competition is restricted to acoustic-phonetic interference or if it extends to competition for linguistic processing as well. Neural activity was recorded using Magnetoencephalography as human participants were instructed to attend to natural speech presented to one ear, and task-irrelevant stimuli were presented to the other. Task-irrelevant stimuli consisted either of random sequences of syllables, or syllables structured to form coherent sentences, using hierarchical frequency-tagging. We find that the phrasal structure of structured task-irrelevant stimuli was represented in the neural response in left inferior frontal and posterior parietal regions, indicating that selective attention does not fully eliminate linguistic processing of task-irrelevant speech. Additionally, neural tracking of to-be-attended speech in left inferior frontal regions was enhanced when competing with structured task-irrelevant stimuli, suggesting inherent competition between them for linguistic processing. We are all familiar with the difficulty of trying to pay attention to a person speaking in a noisy environment, something often known as the ‘cocktail party problem’. This can be especially challenging when the background noise we are trying to filter out is another conversation that we can understand. In order to avoid being distracted in these kinds of situation, we need selective attention, the cognitive process that allows us to attend to one stimulus and to ignore other irrelevant sensory information. How the brain processes the sounds in our environment and prioritizes them is still not clear. One of the central questions is whether we can take in information from several speakers at the same time or whether we can only understand speech from one speaker at a time. Neuroimaging techniques can shed light on this matter by measuring brain activity while participants listen to competing speech stimuli, helping researchers understand how this information is processed by the brain. Now, Har-Shai Yahav and Zion Golumbic measured the brain activity of 30 participants as they listened to two speech streams in their native language, Hebrew. They heard each speech in a different ear and tried to focus their attention on only one of the speakers. Participants always had to attend to natural speech, while the sound they had to ignore could be either natural speech or unintelligible syllable sequences. The activity of the brain was registered using magnetoencephalography, a non-invasive technique that measures the magnetic fields generated by the electrical activity of neurons in the brain. The results showed that unattended speech activated brain areas related to both hearing and language. Thus, unattended speech was processed not only at the acoustic level (as any other type of sound would be), but also at the linguistic level. In addition, the brain response to the attended speech in brain regions related to language was stronger when the competing sound was natural speech compared to random syllables. This suggests that the two speech inputs compete for the same processing resources, which may explain why we find it difficult to stay focused in a conversation when there are other people talking in the background. This study contributes to our understanding on how the brain processes multiple auditory inputs at once. In addition, it highlights the fact that selective attention is a dynamic process of balancing the cognitive resources allocated to competing information rather than an all-or-none process. A potential application of these findings could be the design of smart devices to help individuals focus their attention in noisy environments.[Abstract] [Full Text] [Related] [New Search]