Limits...
Non-uniformity of cell density and networks in the monkey brain.

Shimono M - Sci Rep (2013)

Bottom Line: Wide comparisons between 27 graph theoretical measures and cell densities revealed that only participation coefficients (PCs) significantly correlated with cell densities.Interestingly, PCs did not show a significant correlation with spatial coordinates.Taken together, these results suggested the presence of a combinatorial effect of modular architectures in the network organization related to the non-uniformity of cell densities additional to the spatially monotonic change.

View Article: PubMed Central - PubMed

Affiliation: Dept. of Physics, Indiana University, Swain Hall West, 727 E. 3rd St., Bloomington, IN, 47405-7105, U.S.A.

ABSTRACT
The brain is a very complex structure. Over the past several decades, many studies have aimed to understand how various non-uniform variables relate to each other. The current study compared the whole-brain network organization and global spatial distribution of cell densities in the monkey brain. Wide comparisons between 27 graph theoretical measures and cell densities revealed that only participation coefficients (PCs) significantly correlated with cell densities. Interestingly, PCs did not show a significant correlation with spatial coordinates. Furthermore, the significance of the correlation between cell densities and spatial coordinates disappeared only with the removal of the visual module, while the significance of the correlation between cell densities and PCs disappeared with the removal of any one module. Taken together, these results suggested the presence of a combinatorial effect of modular architectures in the network organization related to the non-uniformity of cell densities additional to the spatially monotonic change.

Show MeSH
Comparison between adjacent and non-adjacent connections.In Figure A, the thick lines indicate the connections between adjacent pairs of brain regions, and the remaining thin lines indicate the non-adjacent pairs. In Figure B, the columns with two panels show the correlations and p values between the neuron-per-nonneuron ratios and participant coefficients. The three bars in the left panel are, from top to bottom, the participation coefficient given for all networks, networks only between non-adjacent brain regions, and networks only between adjacent brain regions. Three bars in the right panel show p values corresponding to correlations in the left panel. The correlations and p values between the anterior–posterior coordinates and participation coefficients are shown in Figure C. The meanings of the three bars are the same as in Figure B.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3756338&req=5

f7: Comparison between adjacent and non-adjacent connections.In Figure A, the thick lines indicate the connections between adjacent pairs of brain regions, and the remaining thin lines indicate the non-adjacent pairs. In Figure B, the columns with two panels show the correlations and p values between the neuron-per-nonneuron ratios and participant coefficients. The three bars in the left panel are, from top to bottom, the participation coefficient given for all networks, networks only between non-adjacent brain regions, and networks only between adjacent brain regions. Three bars in the right panel show p values corresponding to correlations in the left panel. The correlations and p values between the anterior–posterior coordinates and participation coefficients are shown in Figure C. The meanings of the three bars are the same as in Figure B.

Mentions: In addition, because adjacent pairs of brain regions have a higher connectivity probability compared to non-adjacent pairs, I examined the extent to which adjacent pairs of brain regions affected the significant correlation. Adjacency was defined using a spatial map of brain regions previously described in Felleman and Van Essen (1991). The connections between the adjacent pairs are shown as thick lines in Figure 7-A. Indirect observations of the correlations for adjacent pairs or non-adjacent pairs has been supported with results demonstrating that the significant correlation was mainly caused by pairs of non-adjacent brain regions (Figure 7-B and C).


Non-uniformity of cell density and networks in the monkey brain.

Shimono M - Sci Rep (2013)

Comparison between adjacent and non-adjacent connections.In Figure A, the thick lines indicate the connections between adjacent pairs of brain regions, and the remaining thin lines indicate the non-adjacent pairs. In Figure B, the columns with two panels show the correlations and p values between the neuron-per-nonneuron ratios and participant coefficients. The three bars in the left panel are, from top to bottom, the participation coefficient given for all networks, networks only between non-adjacent brain regions, and networks only between adjacent brain regions. Three bars in the right panel show p values corresponding to correlations in the left panel. The correlations and p values between the anterior–posterior coordinates and participation coefficients are shown in Figure C. The meanings of the three bars are the same as in Figure B.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3756338&req=5

f7: Comparison between adjacent and non-adjacent connections.In Figure A, the thick lines indicate the connections between adjacent pairs of brain regions, and the remaining thin lines indicate the non-adjacent pairs. In Figure B, the columns with two panels show the correlations and p values between the neuron-per-nonneuron ratios and participant coefficients. The three bars in the left panel are, from top to bottom, the participation coefficient given for all networks, networks only between non-adjacent brain regions, and networks only between adjacent brain regions. Three bars in the right panel show p values corresponding to correlations in the left panel. The correlations and p values between the anterior–posterior coordinates and participation coefficients are shown in Figure C. The meanings of the three bars are the same as in Figure B.
Mentions: In addition, because adjacent pairs of brain regions have a higher connectivity probability compared to non-adjacent pairs, I examined the extent to which adjacent pairs of brain regions affected the significant correlation. Adjacency was defined using a spatial map of brain regions previously described in Felleman and Van Essen (1991). The connections between the adjacent pairs are shown as thick lines in Figure 7-A. Indirect observations of the correlations for adjacent pairs or non-adjacent pairs has been supported with results demonstrating that the significant correlation was mainly caused by pairs of non-adjacent brain regions (Figure 7-B and C).

Bottom Line: Wide comparisons between 27 graph theoretical measures and cell densities revealed that only participation coefficients (PCs) significantly correlated with cell densities.Interestingly, PCs did not show a significant correlation with spatial coordinates.Taken together, these results suggested the presence of a combinatorial effect of modular architectures in the network organization related to the non-uniformity of cell densities additional to the spatially monotonic change.

View Article: PubMed Central - PubMed

Affiliation: Dept. of Physics, Indiana University, Swain Hall West, 727 E. 3rd St., Bloomington, IN, 47405-7105, U.S.A.

ABSTRACT
The brain is a very complex structure. Over the past several decades, many studies have aimed to understand how various non-uniform variables relate to each other. The current study compared the whole-brain network organization and global spatial distribution of cell densities in the monkey brain. Wide comparisons between 27 graph theoretical measures and cell densities revealed that only participation coefficients (PCs) significantly correlated with cell densities. Interestingly, PCs did not show a significant correlation with spatial coordinates. Furthermore, the significance of the correlation between cell densities and spatial coordinates disappeared only with the removal of the visual module, while the significance of the correlation between cell densities and PCs disappeared with the removal of any one module. Taken together, these results suggested the presence of a combinatorial effect of modular architectures in the network organization related to the non-uniformity of cell densities additional to the spatially monotonic change.

Show MeSH