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Entraining IDyOT: Timing in the Information Dynamics of Thinking

Overview of attention for article published in Frontiers in Psychology, October 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Entraining IDyOT: Timing in the Information Dynamics of Thinking
Published in
Frontiers in Psychology, October 2016
DOI 10.3389/fpsyg.2016.01575
Pubmed ID
Authors

Jamie Forth, Kat Agres, Matthew Purver, Geraint A. Wiggins

Abstract

We present a novel hypothetical account of entrainment in music and language, in context of the Information Dynamics of Thinking model, IDyOT. The extended model affords an alternative view of entrainment, and its companion term, pulse, from earlier accounts. The model is based on hierarchical, statistical prediction, modeling expectations of both what an event will be and when it will happen. As such, it constitutes a kind of predictive coding, with a particular novel hypothetical implementation. Here, we focus on the model's mechanism for predicting when a perceptual event will happen, given an existing sequence of past events, which may be musical or linguistic. We propose a range of tests to validate or falsify the model, at various different levels of abstraction, and argue that computational modeling in general, and this model in particular, can offer a means of providing limited but useful evidence for evolutionary hypotheses.

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The data shown below were collected from the profiles of 11 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 61 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 19%
Student > Ph. D. Student 10 16%
Researcher 8 13%
Student > Doctoral Student 5 8%
Student > Bachelor 4 6%
Other 13 21%
Unknown 10 16%
Readers by discipline Count As %
Psychology 13 21%
Computer Science 13 21%
Neuroscience 8 13%
Arts and Humanities 4 6%
Linguistics 3 5%
Other 9 15%
Unknown 12 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 15 November 2016.
All research outputs
#5,075,059
of 25,196,456 outputs
Outputs from Frontiers in Psychology
#8,204
of 34,034 outputs
Outputs of similar age
#78,148
of 323,960 outputs
Outputs of similar age from Frontiers in Psychology
#158
of 451 outputs
Altmetric has tracked 25,196,456 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 34,034 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has done well, scoring higher than 75% of its peers.
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 323,960 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 451 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.