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Ongoing behavior predicts perceptual report of interval duration

Overview of attention for article published in Frontiers in Neurorobotics, March 2014
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Title
Ongoing behavior predicts perceptual report of interval duration
Published in
Frontiers in Neurorobotics, March 2014
DOI 10.3389/fnbot.2014.00010
Pubmed ID
Authors

Thiago S. Gouvêa, Tiago Monteiro, Sofia Soares, Bassam V. Atallah, Joseph J. Paton

Abstract

The ability to estimate the passage of time is essential for adaptive behavior in complex environments. Yet, it is not known how the brain encodes time over the durations necessary to explain animal behavior. Under temporally structured reinforcement schedules, animals tend to develop temporally structured behavior, and interval timing has been suggested to be accomplished by learning sequences of behavioral states. If this is true, trial to trial fluctuations in behavioral sequences should be predictive of fluctuations in time estimation. We trained rodents in an duration categorization task while continuously monitoring their behavior with a high speed camera. Animals developed highly reproducible behavioral sequences during the interval being timed. Moreover, those sequences were often predictive of perceptual report from early in the trial, providing support to the idea that animals may use learned behavioral patterns to estimate the duration of time intervals. To better resolve the issue, we propose that continuous and simultaneous behavioral and neural monitoring will enable identification of neural activity related to time perception that is not explained by ongoing behavior.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 5 7%
Chile 2 3%
United States 2 3%
Brazil 1 1%
Germany 1 1%
Spain 1 1%
India 1 1%
Unknown 61 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 35%
Researcher 11 15%
Student > Master 9 12%
Student > Bachelor 6 8%
Professor > Associate Professor 4 5%
Other 12 16%
Unknown 6 8%
Readers by discipline Count As %
Neuroscience 23 31%
Agricultural and Biological Sciences 21 28%
Psychology 13 18%
Computer Science 2 3%
Arts and Humanities 2 3%
Other 6 8%
Unknown 7 9%
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 27 May 2015.
All research outputs
#14,773,697
of 22,743,667 outputs
Outputs from Frontiers in Neurorobotics
#398
of 853 outputs
Outputs of similar age
#125,439
of 220,816 outputs
Outputs of similar age from Frontiers in Neurorobotics
#5
of 7 outputs
Altmetric has tracked 22,743,667 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 853 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 48th percentile – i.e., 48% 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 220,816 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 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.