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Low-Level Contrast Statistics of Natural Images Can Modulate the Frequency of Event-Related Potentials (ERP) in Humans

Overview of attention for article published in Frontiers in Human Neuroscience, December 2016
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Title
Low-Level Contrast Statistics of Natural Images Can Modulate the Frequency of Event-Related Potentials (ERP) in Humans
Published in
Frontiers in Human Neuroscience, December 2016
DOI 10.3389/fnhum.2016.00630
Pubmed ID
Authors

Masoud Ghodrati, Mahrad Ghodousi, Ali Yoonessi

Abstract

Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP) in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs' power within theta frequency band (~3-7 Hz). This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 20%
Student > Ph. D. Student 5 20%
Student > Bachelor 4 16%
Professor > Associate Professor 3 12%
Student > Master 3 12%
Other 2 8%
Unknown 3 12%
Readers by discipline Count As %
Psychology 9 36%
Neuroscience 9 36%
Engineering 2 8%
Physics and Astronomy 1 4%
Unknown 4 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 20 December 2016.
All research outputs
#17,285,036
of 25,373,627 outputs
Outputs from Frontiers in Human Neuroscience
#5,579
of 7,685 outputs
Outputs of similar age
#265,307
of 420,110 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#139
of 170 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,685 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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