Toggle Main Menu Toggle Search

Open Access padlockePrints

The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

Multivoxel codes for representing and integrating acoustic features in human cortex

Lookup NU author(s): Dr Sukhbinder Kumar, Professor Tim GriffithsORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2020 The AuthorsUsing fMRI and multivariate pattern analysis, we determined whether spectral and temporal acoustic features are represented by independent or integrated multivoxel codes in human cortex. Listeners heard band-pass noise varying in frequency (spectral) and amplitude-modulation (AM) rate (temporal) features. In the superior temporal plane, changes in multivoxel activity due to frequency were largely invariant with respect to AM rate (and vice versa), consistent with an independent representation. In contrast, in posterior parietal cortex, multivoxel representation was exclusively integrated and tuned to specific conjunctions of frequency and AM features (albeit weakly). Direct between-region comparisons show that whereas independent coding of frequency weakened with increasing levels of the hierarchy, such a progression for AM and integrated coding was less fine-grained and only evident in the higher hierarchical levels from non-core to parietal cortex (with AM coding weakening and integrated coding strengthening). Our findings support the notion that primary auditory cortex can represent spectral and temporal acoustic features in an independent fashion and suggest a role for parietal cortex in feature integration and the structuring of sensory input.


Publication metadata

Author(s): Sohoglu E, Kumar S, Chait M, Griffiths TD

Publication type: Article

Publication status: Published

Journal: NeuroImage

Year: 2020

Volume: 217

Online publication date: 17/02/2020

Acceptance date: 15/02/2020

Date deposited: 08/06/2020

ISSN (print): 1053-8119

ISSN (electronic): 1095-9572

Publisher: Elsevier

URL: https://doi.org/10.1016/j.neuroimage.2020.116661

DOI: 10.1016/j.neuroimage.2020.116661

PubMed id: 32081785


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
Wellcome Trust grant WT106964MA

Share