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Mendeley readers
Attention Score in Context
| Title |
Classification of Single Normal and Alzheimer's Disease Individuals from Cortical Sources of Resting State EEG Rhythms
|
|---|---|
| Published in |
Frontiers in Neuroscience, February 2016
|
| DOI | 10.3389/fnins.2016.00047 |
| Pubmed ID | |
| Authors |
Claudio Babiloni, Antonio I. Triggiani, Roberta Lizio, Susanna Cordone, Giacomo Tattoli, Vitoantonio Bevilacqua, Andrea Soricelli, Raffaele Ferri, Flavio Nobili, Loreto Gesualdo, José C. Millán-Calenti, Ana Buján, Rosanna Tortelli, Valentina Cardinali, Maria Rosaria Barulli, Antonio Giannini, Pantaleo Spagnolo, Silvia Armenise, Grazia Buenza, Gaetano Scianatico, Giancarlo Logroscino, Giovanni B. Frisoni, Claudio del Percio |
| Abstract |
Previous studies have shown abnormal power and functional connectivity of resting state electroencephalographic (EEG) rhythms in groups of Alzheimer's disease (AD) compared to healthy elderly (Nold) subjects. Here we tested the best classification rate of 120 AD patients and 100 matched Nold subjects using EEG markers based on cortical sources of power and functional connectivity of these rhythms. EEG data were recorded during resting state eyes-closed condition. Exact low-resolution brain electromagnetic tomography (eLORETA) estimated the power and functional connectivity of cortical sources in frontal, central, parietal, occipital, temporal, and limbic regions. Delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz) were the frequency bands of interest. The classification rates of interest were those with an area under the receiver operating characteristic curve (AUROC) higher than 0.7 as a threshold for a moderate classification rate (i.e., 70%). Results showed that the following EEG markers overcame this threshold: (i) central, parietal, occipital, temporal, and limbic delta/alpha 1 current density; (ii) central, parietal, occipital temporal, and limbic delta/alpha 2 current density; (iii) frontal theta/alpha 1 current density; (iv) occipital delta/alpha 1 inter-hemispherical connectivity; (v) occipital-temporal theta/alpha 1 right and left intra-hemispherical connectivity; and (vi) parietal-limbic alpha 1 right intra-hemispherical connectivity. Occipital delta/alpha 1 current density showed the best classification rate (sensitivity of 73.3%, specificity of 78%, accuracy of 75.5%, and AUROC of 82%). These results suggest that EEG source markers can classify Nold and AD individuals with a moderate classification rate higher than 80%. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Chile | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Italy | 1 | <1% |
| Unknown | 162 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 22% |
| Researcher | 31 | 19% |
| Student > Bachelor | 16 | 10% |
| Student > Master | 13 | 8% |
| Student > Doctoral Student | 11 | 7% |
| Other | 21 | 13% |
| Unknown | 36 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 31 | 19% |
| Medicine and Dentistry | 22 | 13% |
| Engineering | 17 | 10% |
| Psychology | 15 | 9% |
| Computer Science | 13 | 8% |
| Other | 20 | 12% |
| Unknown | 46 | 28% |
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 11 March 2016.
All research outputs
#3,561,046
of 25,371,288 outputs
Outputs from Frontiers in Neuroscience
#2,873
of 11,538 outputs
Outputs of similar age
#53,746
of 313,045 outputs
Outputs of similar age from Frontiers in Neuroscience
#40
of 179 outputs
Altmetric has tracked 25,371,288 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 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 73% 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 313,045 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 82% of its contemporaries.
We're also able to compare this research output to 179 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.