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Effects of Accuracy Feedback on Fractal Characteristics of Time Estimation

Overview of attention for article published in Frontiers in Integrative Neuroscience, January 2011
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Title
Effects of Accuracy Feedback on Fractal Characteristics of Time Estimation
Published in
Frontiers in Integrative Neuroscience, January 2011
DOI 10.3389/fnint.2011.00062
Pubmed ID
Authors

Nikita A. Kuznetsov, Sebastian Wallot

Abstract

The current experiment investigated the effect of visual accuracy feedback on the structure of variability of time interval estimates in the continuation tapping paradigm. Participants were asked to repeatedly estimate a 1-s interval for a prolonged period of time by tapping their index finger. In some conditions, participants received accuracy feedback after every estimate, whereas in other conditions, no feedback was given. Also, the likelihood of receiving visual feedback was manipulated by adjusting the tolerance band around the 1-s target interval so that feedback was displayed only if the temporal estimate deviated from the target interval by more than 50, 100, or 200 ms respectively. We analyzed the structure of variability of the inter-tap intervals with fractal and multifractal methods that allow for a quantification of complex long-range correlation patterns in the timing performance. Our results indicate that feedback changes the long-range correlation structure of time estimates: Increased amounts of feedback lead to a decrease in fractal long-range correlations, as well to a decrease in the magnitude of local fluctuations in the performance. The multifractal characteristics of the time estimates were not impacted by the presence of accuracy feedback. Nevertheless, most of the data sets show significant multifractal signatures. We interpret these findings as showing that feedback acts to constrain and possibly reorganize timing performance. Implications for mechanistic and complex systems-based theories of timing behavior are discussed.

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Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 49 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 8 16%
Student > Doctoral Student 6 12%
Student > Bachelor 4 8%
Lecturer 4 8%
Other 12 24%
Unknown 6 12%
Readers by discipline Count As %
Psychology 24 48%
Neuroscience 5 10%
Computer Science 2 4%
Economics, Econometrics and Finance 2 4%
Agricultural and Biological Sciences 2 4%
Other 8 16%
Unknown 7 14%
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 29 March 2013.
All research outputs
#15,267,294
of 22,703,044 outputs
Outputs from Frontiers in Integrative Neuroscience
#595
of 853 outputs
Outputs of similar age
#140,145
of 180,401 outputs
Outputs of similar age from Frontiers in Integrative Neuroscience
#26
of 34 outputs
Altmetric has tracked 22,703,044 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.