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Tracking cortical entrainment in neural activity: auditory processes in human temporal cortex

Overview of attention for article published in Frontiers in Computational Neuroscience, February 2015
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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Title
Tracking cortical entrainment in neural activity: auditory processes in human temporal cortex
Published in
Frontiers in Computational Neuroscience, February 2015
DOI 10.3389/fncom.2015.00005
Pubmed ID
Authors

Andrew Thwaites, Ian Nimmo-Smith, Elisabeth Fonteneau, Roy D. Patterson, Paula Buttery, William D. Marslen-Wilson

Abstract

A primary objective for cognitive neuroscience is to identify how features of the sensory environment are encoded in neural activity. Current auditory models of loudness perception can be used to make detailed predictions about the neural activity of the cortex as an individual listens to speech. We used two such models (loudness-sones and loudness-phons), varying in their psychophysiological realism, to predict the instantaneous loudness contours produced by 480 isolated words. These two sets of 480 contours were used to search for electrophysiological evidence of loudness processing in whole-brain recordings of electro- and magneto-encephalographic (EMEG) activity, recorded while subjects listened to the words. The technique identified a bilateral sequence of loudness processes, predicted by the more realistic loudness-sones model, that begin in auditory cortex at ~80 ms and subsequently reappear, tracking progressively down the superior temporal sulcus (STS) at lags from 230 to 330 ms. The technique was then extended to search for regions sensitive to the fundamental frequency (F0) of the voiced parts of the speech. It identified a bilateral F0 process in auditory cortex at a lag of ~90 ms, which was not followed by activity in STS. The results suggest that loudness information is being used to guide the analysis of the speech stream as it proceeds beyond auditory cortex down STS toward the temporal pole.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
United Kingdom 2 3%
France 1 1%
Belgium 1 1%
Unknown 61 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 26%
Student > Ph. D. Student 16 24%
Student > Master 6 9%
Student > Postgraduate 5 7%
Professor 4 6%
Other 11 16%
Unknown 8 12%
Readers by discipline Count As %
Neuroscience 14 21%
Psychology 10 15%
Linguistics 5 7%
Agricultural and Biological Sciences 5 7%
Computer Science 4 6%
Other 14 21%
Unknown 16 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 July 2015.
All research outputs
#13,079,409
of 22,793,427 outputs
Outputs from Frontiers in Computational Neuroscience
#509
of 1,341 outputs
Outputs of similar age
#170,098
of 357,447 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#13
of 33 outputs
Altmetric has tracked 22,793,427 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,341 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 357,447 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.