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Attention Score in Context
| Title |
Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, July 2018
|
| DOI | 10.3389/fnagi.2018.00212 |
| Pubmed ID | |
| Authors |
Hongyoon Choi, Hyejin Kang, Dong Soo Lee, The Alzheimer's Disease Neuroimaging Initiative |
| Abstract |
Predicting future brain topography can give insight into neural correlates of aging and neurodegeneration. Due to variability in the aging process, it has been challenging to precisely estimate brain topographical change according to aging. Here, we predict age-related brain metabolic change by generating future brain 18F-Fluorodeoxyglucose PET. A cross-sectional PET dataset of cognitively normal subjects with different age was used to develop a generative model. The model generated PET images using age information and characteristic individual features. Predicted regional metabolic changes were correlated with the real changes obtained by follow-up data. This model was applied to produce a brain metabolism aging movie by generating PET at different ages. Normal population distribution of brain metabolic topography at each age was estimated as well. In addition, a generative model using APOE4 status as well as age as inputs revealed a significant effect of APOE4 status on age-related metabolic changes particularly in the calcarine, lingual cortex, hippocampus, and amygdala. It suggested APOE4 could be a factor affecting individual variability in age-related metabolic degeneration in normal elderly. This predictive model may not only be extended to understanding the cognitive aging process, but apply to the development of a preclinical biomarker for various brain disorders. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 65 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 17% |
| Researcher | 9 | 14% |
| Student > Bachelor | 6 | 9% |
| Student > Master | 6 | 9% |
| Student > Doctoral Student | 4 | 6% |
| Other | 10 | 15% |
| Unknown | 19 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 15% |
| Engineering | 7 | 11% |
| Neuroscience | 7 | 11% |
| Psychology | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 5% |
| Other | 9 | 14% |
| Unknown | 25 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 03 August 2018.
All research outputs
#3,248,200
of 23,096,849 outputs
Outputs from Frontiers in Aging Neuroscience
#1,755
of 4,871 outputs
Outputs of similar age
#66,670
of 326,949 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#52
of 98 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,871 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has gotten more attention than average, scoring higher than 60% 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 326,949 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.