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Molecular and Functional Models in Neuropsychiatry

Overview of attention for book
Attention for Chapter 108: Animal Models of Depression: Molecular Perspectives
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

blogs
1 blog
twitter
3 X users
patent
2 patents
facebook
1 Facebook page
wikipedia
6 Wikipedia pages
q&a
1 Q&A thread

Readers on

mendeley
670 Mendeley
citeulike
1 CiteULike
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Chapter title
Animal Models of Depression: Molecular Perspectives
Chapter number 108
Book title
Molecular and Functional Models in Neuropsychiatry
Published in
Current topics in behavioral neurosciences, July 2013
DOI 10.1007/7854_2010_108
Pubmed ID
Book ISBNs
978-3-64-219702-4, 978-3-64-219703-1
Authors

Vaishnav Krishnan, Eric J. Nestler, Krishnan, Vaishnav, Nestler, Eric J.

Abstract

Much of the current understanding about the pathogenesis of altered mood, impaired concentration and neurovegetative symptoms in major depression has come from animal models. However, because of the unique and complex features of human depression, the generation of valid and insightful depression models has been less straightforward than modeling other disabling diseases like cancer or autoimmune conditions. Today's popular depression models creatively merge ethologically valid behavioral assays with the latest technological advances in molecular biology and automated video-tracking. This chapter reviews depression assays involving acute stress (e.g., forced swim test), models consisting of prolonged physical or social stress (e.g., social defeat), models of secondary depression, genetic models, and experiments designed to elucidate the mechanisms of antidepressant action. These paradigms are critically evaluated in relation to their ease, validity and replicability, the molecular insights that they have provided, and their capacity to offer the next generation of therapeutics for depression.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 670 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Japan 3 <1%
Norway 1 <1%
Austria 1 <1%
Australia 1 <1%
Portugal 1 <1%
Canada 1 <1%
Malaysia 1 <1%
United Kingdom 1 <1%
Other 1 <1%
Unknown 655 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 132 20%
Student > Ph. D. Student 108 16%
Researcher 73 11%
Student > Master 69 10%
Student > Doctoral Student 37 6%
Other 68 10%
Unknown 183 27%
Readers by discipline Count As %
Neuroscience 142 21%
Agricultural and Biological Sciences 86 13%
Pharmacology, Toxicology and Pharmaceutical Science 51 8%
Biochemistry, Genetics and Molecular Biology 49 7%
Medicine and Dentistry 47 7%
Other 89 13%
Unknown 206 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 16 March 2024.
All research outputs
#1,520,716
of 24,205,409 outputs
Outputs from Current topics in behavioral neurosciences
#54
of 505 outputs
Outputs of similar age
#12,942
of 198,264 outputs
Outputs of similar age from Current topics in behavioral neurosciences
#1
of 1 outputs
Altmetric has tracked 24,205,409 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 505 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done well, scoring higher than 89% 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 198,264 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 93% of its contemporaries.
We're also able to compare this research output to 1 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