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Mendeley readers
Attention Score in Context
| Title |
Neuroimaging and genetic risk for Alzheimer’s disease and addiction-related degenerative brain disorders
|
|---|---|
| Published in |
Brain Imaging and Behavior, October 2013
|
| DOI | 10.1007/s11682-013-9263-y |
| Pubmed ID | |
| Authors |
Florence F. Roussotte, Madelaine Daianu, Neda Jahanshad, Cassandra D. Leonardo, Paul M. Thompson |
| Abstract |
Neuroimaging offers a powerful means to assess the trajectory of brain degeneration in a variety of disorders, including Alzheimer's disease (AD). Here we describe how multi-modal imaging can be used to study the changing brain during the different stages of AD. We integrate findings from a range of studies using magnetic resonance imaging (MRI), positron emission tomography (PET), functional MRI (fMRI) and diffusion weighted imaging (DWI). Neuroimaging reveals how risk genes for degenerative disorders affect the brain, including several recently discovered genetic variants that may disrupt brain connectivity. We review some recent neuroimaging studies of genetic polymorphisms associated with increased risk for late-onset Alzheimer's disease (LOAD). Some genetic variants that increase risk for drug addiction may overlap with those associated with degenerative brain disorders. These common associations offer new insight into mechanisms underlying neurodegeneration and addictive behaviors, and may offer new leads for treating them before severe and irreversible neurological symptoms appear. |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 26% |
| Student > Master | 7 | 13% |
| Student > Bachelor | 6 | 11% |
| Researcher | 6 | 11% |
| Professor > Associate Professor | 4 | 7% |
| Other | 8 | 15% |
| Unknown | 9 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 10 | 19% |
| Medicine and Dentistry | 10 | 19% |
| Agricultural and Biological Sciences | 9 | 17% |
| Neuroscience | 7 | 13% |
| Computer Science | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 9 | 17% |
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 10 March 2015.
All research outputs
#20,264,045
of 22,794,367 outputs
Outputs from Brain Imaging and Behavior
#1,008
of 1,155 outputs
Outputs of similar age
#184,884
of 211,771 outputs
Outputs of similar age from Brain Imaging and Behavior
#21
of 22 outputs
Altmetric has tracked 22,794,367 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,155 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 1st percentile – i.e., 1% 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 211,771 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.