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Multiscale modeling in the clinic: diseases of the brain and nervous system

Overview of attention for article published in Brain Informatics, May 2017
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Title
Multiscale modeling in the clinic: diseases of the brain and nervous system
Published in
Brain Informatics, May 2017
DOI 10.1007/s40708-017-0067-5
Pubmed ID
Authors

William W. Lytton, Jeff Arle, Georgiy Bobashev, Songbai Ji, Tara L. Klassen, Vasilis Z. Marmarelis, James Schwaber, Mohamed A. Sherif, Terence D. Sanger

Abstract

Computational neuroscience is a field that traces its origins to the efforts of Hodgkin and Huxley, who pioneered quantitative analysis of electrical activity in the nervous system. While also continuing as an independent field, computational neuroscience has combined with computational systems biology, and neural multiscale modeling arose as one offshoot. This consolidation has added electrical, graphical, dynamical system, learning theory, artificial intelligence and neural network viewpoints with the microscale of cellular biology (neuronal and glial), mesoscales of vascular, immunological and neuronal networks, on up to macroscales of cognition and behavior. The complexity of linkages that produces pathophysiology in neurological, neurosurgical and psychiatric disease will require multiscale modeling to provide understanding that exceeds what is possible with statistical analysis or highly simplified models: how to bring together pharmacotherapeutics with neurostimulation, how to personalize therapies, how to combine novel therapies with neurorehabilitation, how to interlace periodic diagnostic updates with frequent reevaluation of therapy, how to understand a physical disease that manifests as a disease of the mind. Multiscale modeling will also help to extend the usefulness of animal models of human diseases in neuroscience, where the disconnects between clinical and animal phenomenology are particularly pronounced. Here we cover areas of particular interest for clinical application of these new modeling neurotechnologies, including epilepsy, traumatic brain injury, ischemic disease, neurorehabilitation, drug addiction, schizophrenia and neurostimulation.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 113 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 18%
Student > Ph. D. Student 16 14%
Student > Master 16 14%
Other 10 9%
Student > Bachelor 9 8%
Other 25 22%
Unknown 17 15%
Readers by discipline Count As %
Engineering 18 16%
Neuroscience 18 16%
Medicine and Dentistry 16 14%
Computer Science 10 9%
Psychology 7 6%
Other 19 17%
Unknown 26 23%
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 30 May 2017.
All research outputs
#18,547,867
of 22,971,207 outputs
Outputs from Brain Informatics
#82
of 103 outputs
Outputs of similar age
#236,741
of 310,725 outputs
Outputs of similar age from Brain Informatics
#3
of 4 outputs
Altmetric has tracked 22,971,207 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 103 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 310,725 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.