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A Cortical Folding Pattern-Guided Model of Intrinsic Functional Brain Networks in Emotion Processing

Overview of attention for article published in Frontiers in Neuroscience, August 2018
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Title
A Cortical Folding Pattern-Guided Model of Intrinsic Functional Brain Networks in Emotion Processing
Published in
Frontiers in Neuroscience, August 2018
DOI 10.3389/fnins.2018.00575
Pubmed ID
Authors

Xi Jiang, Lin Zhao, Huan Liu, Lei Guo, Keith M. Kendrick, Tianming Liu

Abstract

There have been increasing studies demonstrating that emotion processing in humans is realized by the interaction within or among the large-scale intrinsic functional brain networks. Identifying those meaningful intrinsic functional networks based on task-based functional magnetic resonance imaging (task fMRI) with specific emotional stimuli and responses, and exploring the underlying functional working mechanisms of interregional neural communication within the intrinsic functional networks are thus of great importance to understand the neural basis of emotion processing. In this paper, we propose a novel cortical folding pattern-guided model of intrinsic networks in emotion processing: gyri serve as global functional connection centers that perform interregional neural communication among distinct regions via long distance dense axonal fibers, and sulci serve as local functional units that directly communicate with neighboring gyri via short distance fibers and indirectly communicate with other distinct regions via the neighboring gyri. We test the proposed model by adopting a computational framework of dictionary learning and sparse representation of emotion task fMRI data of 68 subjects in the publicly released Human Connectome Project. The proposed model provides novel insights of functional mechanisms in emotion processing.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 21%
Student > Ph. D. Student 2 14%
Researcher 2 14%
Student > Master 2 14%
Lecturer 1 7%
Other 0 0%
Unknown 4 29%
Readers by discipline Count As %
Neuroscience 3 21%
Social Sciences 2 14%
Computer Science 2 14%
Philosophy 1 7%
Agricultural and Biological Sciences 1 7%
Other 1 7%
Unknown 4 29%
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 04 September 2018.
All research outputs
#19,954,338
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#8,672
of 11,542 outputs
Outputs of similar age
#250,532
of 342,201 outputs
Outputs of similar age from Frontiers in Neuroscience
#196
of 232 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 232 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.