We have located links that may give you full text access.
Acoustic and higher-level representations of naturalistic auditory scenes in human auditory and frontal cortex.
NeuroImage 2018 June
Often, in everyday life, we encounter auditory scenes comprising multiple simultaneous sounds and succeed to selectively attend to only one sound, typically the most relevant for ongoing behavior. Studies using basic sounds and two-talker stimuli have shown that auditory selective attention aids this by enhancing the neural representations of the attended sound in auditory cortex. It remains unknown, however, whether and how this selective attention mechanism operates on representations of auditory scenes containing natural sounds of different categories. In this high-field fMRI study we presented participants with simultaneous voices and musical instruments while manipulating their focus of attention. We found an attentional enhancement of neural sound representations in temporal cortex - as defined by spatial activation patterns - at locations that depended on the attended category (i.e., voices or instruments). In contrast, we found that in frontal cortex the site of enhancement was independent of the attended category and the same regions could flexibly represent any attended sound regardless of its category. These results are relevant to elucidate the interacting mechanisms of bottom-up and top-down processing when listening to real-life scenes comprised of multiple sound categories.
Full text links
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app