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Spectral-temporal EEG dynamics of speech discrimination processing in infants during sleep

Overview of attention for article published in BMC Neuroscience, March 2017
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  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Title
Spectral-temporal EEG dynamics of speech discrimination processing in infants during sleep
Published in
BMC Neuroscience, March 2017
DOI 10.1186/s12868-017-0353-4
Pubmed ID
Authors

Phillip M. Gilley, Kristin Uhler, Kaylee Watson, Christine Yoshinaga-Itano

Abstract

Oddball paradigms are frequently used to study auditory discrimination by comparing event-related potential (ERP) responses from a standard, high probability sound and to a deviant, low probability sound. Previous research has established that such paradigms, such as the mismatch response or mismatch negativity, are useful for examining auditory processes in young children and infants across various sleep and attention states. The extent to which oddball ERP responses may reflect subtle discrimination effects, such as speech discrimination, is largely unknown, especially in infants that have not yet acquired speech and language. Mismatch responses for three contrasts (non-speech, vowel, and consonant) were computed as a spectral-temporal probability function in 24 infants, and analyzed at the group level by a modified multidimensional scaling. Immediately following an onset gamma response (30-50 Hz), the emergence of a beta oscillation (12-30 Hz) was temporally coupled with a lower frequency theta oscillation (2-8 Hz). The spectral-temporal probability of this coupling effect relative to a subsequent theta modulation corresponds with discrimination difficulty for non-speech, vowel, and consonant contrast features. The theta modulation effect suggests that unexpected sounds are encoded as a probabilistic measure of surprise. These results support the notion that auditory discrimination is driven by the development of brain networks for predictive processing, and can be measured in infants during sleep. The results presented here have implications for the interpretation of discrimination as a probabilistic process, and may provide a basis for the development of single-subject and single-trial classification in a clinically useful context. An infant's brain is processing information about the environment and performing computations, even during sleep. These computations reflect subtle differences in acoustic feature processing that are necessary for language-learning. Results from this study suggest that brain responses to deviant sounds in an oddball paradigm follow a cascade of oscillatory modulations. This cascade begins with a gamma response that later emerges as a beta synchronization, which is temporally coupled with a theta modulation, and followed by a second, subsequent theta modulation. The difference in frequency and timing of the theta modulations appears to reflect a measure of surprise. These insights into the neurophysiological mechanisms of auditory discrimination provide a basis for exploring the clinically utility of the MMR TF and other auditory oddball responses.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 22%
Researcher 11 14%
Student > Bachelor 9 11%
Student > Master 6 8%
Student > Doctoral Student 6 8%
Other 14 18%
Unknown 16 20%
Readers by discipline Count As %
Psychology 23 29%
Neuroscience 18 23%
Medicine and Dentistry 5 6%
Agricultural and Biological Sciences 2 3%
Nursing and Health Professions 2 3%
Other 7 9%
Unknown 22 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 17 April 2017.
All research outputs
#6,548,934
of 23,344,526 outputs
Outputs from BMC Neuroscience
#314
of 1,260 outputs
Outputs of similar age
#104,819
of 310,179 outputs
Outputs of similar age from BMC Neuroscience
#3
of 16 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,260 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 75% 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 310,179 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 66% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.