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Human brain networks in health and disease
Bassett DS, Bullmore ET.. Current opinion in neurology, 2009-08-01
Topic: Brain imaging, connectivity and assessment
Purpose of review Recent developments in the statistical physics of complex networks have been translated to neuroimaging data in an effort to enhance our understanding of human brain structural and functional networks. This review focuses on studies using graph theoretical measures applied to structural MRI, diffusion MRI, functional MRI, electroencephalography, and magnetoencephalography data. Recent findings Complex network properties have been identified with some consistency in all modalities of neuroimaging data and over a range of spatial and time scales. Conserved properties include small worldness, high efficiency of information transfer for low wiring cost, modularity, and the existence of network hubs. Structural and functional network metrics have been found to be heritable and to change with normal aging. Clinical studies, principally in Alzheimer's disease and schizophrenia, have identified abnormalities of network configuration in patients. Future work will likely involve efforts to synthesize structural and functional networks in integrated models and to explore the interdependence of network configuration and cognitive performance. Summary Graph theoretical analysis of neuroimaging data is growing rapidly and could potentially provide a relatively simple but powerful quantitative framework to describe and compare whole human brain structural and functional networks under diverse experimental and clinical conditions.
Key findings
- Conserved properties include small worldness, high efficiency of information transfer for low wiring cost, modularity, and the existence of network hubs.
- Structural and functional network metrics have been found to be heritable and to change with normal aging.
- Clinical studies, principally in Alzheimer's disease and schizophrenia, have identified abnormalities of network configuration in patients.
- Future work will likely involve efforts to synthesize structural and functional networks in integrated models and to explore the interdependence of network configuration and cognitive performance.
- Summary Graph theoretical analysis of neuroimaging data is growing rapidly and could potentially provide a relatively simple but powerful quantitative framework to describe and compare whole human brain structural and functional networks under diverse experimental and clinical conditions.
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Study details
- Evidence strengthLow
How this study scored 36/100
Published in a peer-reviewed journal. Scored zero for study design, 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 21 of the 58 points we could judge it on, which is 36 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Current opinion in neurology) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2009 — within 20 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 19494774) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 21 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 21 of the 58 points we could judge it on is 36 out of 100. |
| Total | 36 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Bassett, D. S., & Bullmore, E. T. (2009). Human brain networks in health and disease. Current opinion in neurology. https://doi.org/10.1097/wco.0b013e32832d93dd
Vancouver
Bassett DS, Bullmore ET. Human brain networks in health and disease. Current opinion in neurology. 2009. doi:10.1097/wco.0b013e32832d93dd. PMID: 19494774.
BibTeX
@article{bassett2009-19494774,
author = {Bassett, D. S. and Bullmore, E. T.},
title = {{Human brain networks in health and disease}},
journal = {Current opinion in neurology},
year = {2009},
doi = {10.1097/wco.0b013e32832d93dd},
pmid = {19494774},
url = {https://doi.org/10.1097/wco.0b013e32832d93dd}
}
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