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BRAPH: A graph theory software for the analysis of brain connectivity
Mijalkov M, Kakaei E, Pereira JB, Westman E, Volpe G, Alzheimer's Disease Neuroimaging Initiative.. PloS one, 2017-08-01
Topic: Risk, prevention and care in population studies
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.
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APA 7th
Mijalkov, M., Kakaei, E., Pereira, J. B., Westman, E., Volpe, G., & Alzheimer's Disease Neuroimaging Initiative. (2017). BRAPH: A graph theory software for the analysis of brain connectivity. PloS one. https://doi.org/10.1371/journal.pone.0178798
Vancouver
Mijalkov M, Kakaei E, Pereira JB, Westman E, Volpe G, Alzheimer's Disease Neuroimaging Initiative. BRAPH: A graph theory software for the analysis of brain connectivity. PloS one. 2017. doi:10.1371/journal.pone.0178798. PMID: 28763447.
BibTeX
@article{mijalkov2017-28763447,
author = {Mijalkov, M. and Kakaei, E. and Pereira, J. B. and Westman, E. and Volpe, G. and {Alzheimer's Disease Neuroimaging Initiative}},
title = {{BRAPH: A graph theory software for the analysis of brain connectivity}},
journal = {PloS one},
year = {2017},
doi = {10.1371/journal.pone.0178798},
pmid = {28763447},
url = {https://doi.org/10.1371/journal.pone.0178798}
}
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Key findings
- BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks.
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Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 57/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 33 of the 58 points we could judge it on, which is 57 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (PloS one) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2017 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 28763447) |
| Free to read | 2 / 2 | Free to read |
| Points | 33 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 33 of the 58 points we could judge it on is 57 out of 100. |
| Total | 57 / 100 | — |
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