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Mendeley readers
Attention Score in Context
| Title |
A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD)
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, August 2018
|
| DOI | 10.3389/fncom.2018.00060 |
| Pubmed ID | |
| Authors |
Pravat K. Mandal, Anwesha Banerjee, Manjari Tripathi, Ankita Sharma |
| Abstract |
Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 195 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 195 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 13% |
| Student > Ph. D. Student | 24 | 12% |
| Student > Master | 24 | 12% |
| Student > Bachelor | 23 | 12% |
| Student > Postgraduate | 8 | 4% |
| Other | 27 | 14% |
| Unknown | 64 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 42 | 22% |
| Medicine and Dentistry | 18 | 9% |
| Engineering | 17 | 9% |
| Psychology | 16 | 8% |
| Computer Science | 7 | 4% |
| Other | 28 | 14% |
| Unknown | 67 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 14 September 2018.
All research outputs
#2,944,512
of 23,567,572 outputs
Outputs from Frontiers in Computational Neuroscience
#127
of 1,379 outputs
Outputs of similar age
#60,458
of 335,237 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 30 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,379 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done particularly well, scoring higher than 90% 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 335,237 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 81% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.