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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, August 2018
|
| DOI | 10.3389/fninf.2018.00055 |
| Pubmed ID | |
| Authors |
Harshvardhan Gazula, Bradley T. Baker, Eswar Damaraju, Sergey M. Plis, Sandeep R. Panta, Rogers F. Silva, Vince D. Calhoun |
| Abstract |
In the field of neuroimaging, there is a growing interest in developing collaborative frameworks that enable researchers to address challenging questions about the human brain by leveraging data across multiple sites all over the world. Additionally, efforts are also being directed at developing algorithms that enable collaborative analysis and feature learning from multiple sites without requiring the often large data to be centrally located. In this paper, we propose two new decentralized algorithms: (1) A decentralized regression algorithm for performing a voxel-based morphometry analysis on structural magnetic resonance imaging (MRI) data and, (2) A decentralized dynamic functional network connectivity algorithm which includes decentralized group ICA and sliding-window analysis of functional MRI data. We compare results against those obtained from their pooled (or centralized) counterparts on the same data i.e., as if they are at one site. Results produced by the decentralized algorithms are similar to the pooled-case and showcase the potential of performing multi-voxel and multivariate analyses of data located at multiple sites. Such approaches enable many more collaborative and comparative analysis in the context of large-scale neuroimaging studies. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 17% |
| United States | 2 | 17% |
| Finland | 1 | 8% |
| Switzerland | 1 | 8% |
| Unknown | 6 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 67% |
| Scientists | 4 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 20% |
| Researcher | 2 | 13% |
| Lecturer > Senior Lecturer | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Other | 1 | 7% |
| Other | 2 | 13% |
| Unknown | 5 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 3 | 20% |
| Mathematics | 1 | 7% |
| Computer Science | 1 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Social Sciences | 1 | 7% |
| Other | 3 | 20% |
| Unknown | 5 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 02 October 2020.
All research outputs
#4,551,181
of 23,102,082 outputs
Outputs from Frontiers in Neuroinformatics
#240
of 758 outputs
Outputs of similar age
#88,254
of 334,958 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#7
of 22 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 758 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 68% 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 334,958 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
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 has gotten more attention than average, scoring higher than 68% of its contemporaries.