Tracking the Effects of Top-Down Attention on Word Discrimination Using Frequency-tagged Neuromagnetic Responses.

Tracking the Effects of Top-Down Attention on Word Discrimination Using Frequency-tagged Neuromagnetic Responses.

Niesen, Maxime;Vander Ghinst, Marc;Bourguignon, Mathieu;Wens, Vincent;Bertels, Julie;Goldman, Serge;Choufani, Georges;Hassid, Sergio;De Tiege, Xavier;
journal of cognitive neuroscience 2020 pp. 1-12
247
niesen2020trackingjournal

Abstract

Discrimination of words from nonspeech sounds is essential in communication. Still, how selective attention can influence this early step of speech processing remains elusive. To answer that question, brain activity was recorded with magnetoencephalography in 12 healthy adults while they listened to two sequences of auditory stimuli presented at 2.17 Hz, consisting of successions of one randomized (tagging frequency = 0.54 Hz) and three acoustically matched stimuli. Participants were instructed to focus their attention on the occurrence of a predefined in the verbal attention condition and on a stimulus in the nonverbal attention condition. Steady-state neuromagnetic responses were identified with spectral analysis at sensor and source levels. Significant sensor responses peaked at 0.54 and 2.17 Hz in both conditions. Sources at 0.54 Hz were reconstructed in supratemporal auditory cortex, left superior temporal gyrus (STG), left middle temporal gyrus, and left inferior frontal gyrus. Sources at 2.17 Hz were reconstructed in supratemporal auditory cortex and STG. Crucially, source strength in the left STG at 0.54 Hz was significantly higher in verbal attention than in nonverbal attention condition. This study demonstrates speech-sensitive responses at primary auditory and speech-related neocortical areas. Critically, it highlights that, during word discrimination, top-down attention modulates activity within the left STG. This area therefore appears to play a crucial role in selective verbal attentional processes for this early step of speech processing.

Citation

ID: 80744
Ref Key: niesen2020trackingjournal
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
80744
Unique Identifier:
10.1162/jocn_a_01522
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet