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Beyond the evoked/intrinsic neural process dichotomy

Overview of attention for article published in Network Neuroscience, March 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#35 of 385)
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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30 X users
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1 Redditor
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4 Bluesky users

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57 Mendeley
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Article details
Title
Beyond the evoked/intrinsic neural process dichotomy
Published in
Network Neuroscience, March 2018
DOI 10.1162/netn_a_00028
Pubmed ID
Authors
Abstract

Contemporary functional neuroimaging research has increasingly focused on characterization of intrinsic or "spontaneous" brain activity. Analysis of intrinsic activity is often contrasted with analysis of task-evoked activity that has traditionally been the focus of cognitive neuroscience. But does this evoked/intrinsic dichotomy adequately characterize human brain function? Based on empirical data demonstrating a close functional interdependence between intrinsic and task-evoked activity, we argue that the dichotomy between intrinsic and task-evoked activity as unobserved contributions to brain activity is artificial. We present an alternative picture of brain function in which the brain's spatiotemporal dynamics do not consist of separable intrinsic and task-evoked components, but reflect the enaction of a system of mutual constraints to move the brain into and out of task-appropriate functional configurations. According to this alternative picture, cognitive neuroscientists are tasked with describing both the temporal trajectory of brain activity patterns across time, and the modulation of this trajectory by task states, without separating this process into intrinsic and task-evoked components. We argue that this alternative picture of brain function is best captured in a novel explanatory framework called enabling constraint. Overall, these insights call for a reconceptualization of functional brain activity, and should drive future methodological and empirical efforts.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 30 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 17 30%
Researcher 10 18%
Student > Master 7 12%
Other 3 5%
Student > Doctoral Student 3 5%
Other 6 11%
Unknown 11 19%
Readers by discipline
Readers by discipline Count As %
Neuroscience 15 26%
Psychology 9 16%
Agricultural and Biological Sciences 6 11%
Engineering 5 9%
Computer Science 2 4%
Other 4 7%
Unknown 16 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 24 February 2025.
All research outputs
#2,235,275
of 34,601,261 outputs
Outputs from Network Neuroscience
#35
of 385 outputs
Outputs of similar age
#36,273
of 374,355 outputs
Outputs of similar age from Network Neuroscience
#1
of 6 outputs
Altmetric has tracked 34,601,261 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 385 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. This one has done particularly well, scoring higher than 90% 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 374,355 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them