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The effect of target and non-target similarity on neural classification performance: a boost from confidence

Overview of attention for article published in Frontiers in Neuroscience, August 2015
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Title
The effect of target and non-target similarity on neural classification performance: a boost from confidence
Published in
Frontiers in Neuroscience, August 2015
DOI 10.3389/fnins.2015.00270
Pubmed ID
Authors

Amar R. Marathe, Anthony J. Ries, Vernon J. Lawhern, Brent J. Lance, Jonathan Touryan, Kaleb McDowell, Hubert Cecotti

Abstract

Brain computer interaction (BCI) technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in similar neural activity between the two classes. It is unknown how current neural-based target classification algorithms perform when qualitatively similar target and non-target images are presented. This study address this question by comparing behavioral and neural classification performance across two conditions: first, when targets were the only infrequent stimulus presented amongst frequent background distracters; and second when targets were presented together with infrequent non-targets containing similar visual features to the targets. The resulting findings show that behavior is slower and less accurate when targets are presented together with similar non-targets; moreover, single-trial classification yielded high levels of misclassification when infrequent non-targets are included. Furthermore, we present an approach to mitigate the image misclassification. We use confidence measures to assess the quality of single-trial classification, and demonstrate that a system in which low confidence trials are reclassified through a secondary process can result in improved performance.

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The data shown below were collected from the profiles of 2 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
New Zealand 1 3%
United States 1 3%
Unknown 26 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 34%
Student > Bachelor 4 14%
Student > Master 3 10%
Researcher 3 10%
Lecturer 2 7%
Other 3 10%
Unknown 4 14%
Readers by discipline Count As %
Computer Science 7 24%
Engineering 7 24%
Agricultural and Biological Sciences 2 7%
Neuroscience 2 7%
Psychology 2 7%
Other 3 10%
Unknown 6 21%
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 06 September 2015.
All research outputs
#17,235,172
of 25,371,288 outputs
Outputs from Frontiers in Neuroscience
#7,944
of 11,538 outputs
Outputs of similar age
#164,188
of 275,650 outputs
Outputs of similar age from Frontiers in Neuroscience
#63
of 94 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 30th percentile – i.e., 30% 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 275,650 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.