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Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation

Overview of attention for article published in Frontiers in Human Neuroscience, January 2018
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Title
Positive Classification Advantage: Tracing the Time Course Based on Brain Oscillation
Published in
Frontiers in Human Neuroscience, January 2018
DOI 10.3389/fnhum.2017.00659
Pubmed ID
Authors

Tianyi Yan, Xiaonan Dong, Nan Mu, Tiantian Liu, Duanduan Chen, Li Deng, Changming Wang, Lun Zhao

Abstract

The present study aimed to explore the modulation of frequency bands (alpha, beta, theta) underlying the positive facial expressions classification advantage within different post-stimulus time intervals (100-200 ms, 200-300 ms, 300-400 ms). For this purpose, we recorded electroencephalogram (EEG) activity during an emotion discrimination task for happy, sad and neutral faces. The correlation between the non-phase-locked power of frequency bands and reaction times (RTs) was assessed. The results revealed that beta played a major role in positive classification advantage (PCA) within the 100-200 and 300-400 ms intervals, whereas theta was important within the 200-300 ms interval. We propose that the beta band modulated the neutral and emotional face classification process, and that the theta band modulated for happy and sad face classification.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 14%
Student > Ph. D. Student 4 14%
Student > Doctoral Student 2 7%
Lecturer 2 7%
Student > Bachelor 1 3%
Other 4 14%
Unknown 12 41%
Readers by discipline Count As %
Neuroscience 6 21%
Psychology 3 10%
Computer Science 3 10%
Unspecified 1 3%
Business, Management and Accounting 1 3%
Other 1 3%
Unknown 14 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 18 January 2018.
All research outputs
#13,576,042
of 23,012,811 outputs
Outputs from Frontiers in Human Neuroscience
#4,080
of 7,191 outputs
Outputs of similar age
#220,833
of 443,293 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#102
of 160 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,191 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 443,293 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 160 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.