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Attention Score in Context
| Title |
Correspondence between structure and function in the human brain at rest
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, January 2012
|
| DOI | 10.3389/fninf.2012.00010 |
| Pubmed ID | |
| Authors |
Judith M. Segall, Elena A. Allen, Rex E. Jung, Erik B. Erhardt, Sunil K. Arja, Kent Kiehl, Vince D. Calhoun |
| Abstract |
To further understanding of basic and complex cognitive functions, previous connectome research has identified functional and structural connections of the human brain. Functional connectivity is often measured by using resting-state functional magnetic resonance imaging (rs-fMRI) and is generally interpreted as an indirect measure of neuronal activity. Gray matter (GM) primarily consists of neuronal and glia cell bodies; therefore, it is surprising that the majority of connectome research has excluded GM measures. Therefore, we propose that by exploring where GM corresponds to function would aid in the understanding of both structural and functional connectivity and in turn the human connectome. A cohort of 603 healthy participants underwent structural and functional scanning on the same 3 T scanner at the Mind Research Network. To investigate the spatial correspondence between structure and function, spatial independent component analysis (ICA) was applied separately to both GM density (GMD) maps and to rs-fMRI data. ICA of GM delineates structural components based on the covariation of GMD regions among subjects. For the rs-fMRI data, ICA identified spatial patterns with common temporal features. These decomposed structural and functional components were then compared by spatial correlation. Basal ganglia components exhibited the highest structural to resting-state functional spatial correlation (r = 0.59). Cortical components generally show correspondence between a single structural component and several resting-state functional components. We also studied relationships between the weights of different structural components and identified the precuneus as a hub in GMD structural network correlations. In addition, we analyzed relationships between component weights, age, and gender; concluding that age has a significant effect on structural components. |
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 % |
|---|---|---|
| Switzerland | 1 | 25% |
| Belgium | 1 | 25% |
| Unknown | 2 | 50% |
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 246 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 2% |
| Spain | 3 | 1% |
| Italy | 2 | <1% |
| Netherlands | 2 | <1% |
| Germany | 2 | <1% |
| Japan | 2 | <1% |
| Russia | 1 | <1% |
| Finland | 1 | <1% |
| Czechia | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 228 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 57 | 23% |
| Researcher | 48 | 20% |
| Student > Master | 30 | 12% |
| Professor > Associate Professor | 17 | 7% |
| Student > Bachelor | 16 | 7% |
| Other | 49 | 20% |
| Unknown | 29 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 41 | 17% |
| Psychology | 37 | 15% |
| Medicine and Dentistry | 33 | 13% |
| Agricultural and Biological Sciences | 28 | 11% |
| Engineering | 28 | 11% |
| Other | 32 | 13% |
| Unknown | 47 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 03 May 2018.
All research outputs
#15,424,518
of 25,759,158 outputs
Outputs from Frontiers in Neuroinformatics
#483
of 848 outputs
Outputs of similar age
#158,845
of 251,832 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#14
of 25 outputs
Altmetric has tracked 25,759,158 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 848 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 251,832 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.