Limits...
A network convergence zone in the hippocampus.

Mišić B, Goñi J, Betzel RF, Sporns O, McIntosh AR - PLoS Comput. Biol. (2014)

Bottom Line: However, recent quantitative graph-theoretic analyses of the static large-scale connectome have failed to demonstrate the centrality of the hippocampus; in the context of the whole brain, the hippocampus is not among the most connected or reachable nodes.Using a novel computational model, we demonstrate that large-scale brain network topology is organized to funnel and concentrate information flow in the hippocampus, supporting the long-standing hypothesis that this region acts as a critical convergence zone.Our results indicate that the functional capacity of the hippocampus is shaped by its embedding in the large-scale connectome.

View Article: PubMed Central - PubMed

Affiliation: Rotman Research Institute, Baycrest Centre, Toronto, Canada; Department of Psychology, University of Toronto, Toronto, Canada; Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.

ABSTRACT
The hippocampal formation is a key structure for memory function in the brain. The functional anatomy of the brain suggests that the hippocampus may be a convergence zone, as it receives polysensory input from distributed association areas throughout the neocortex. However, recent quantitative graph-theoretic analyses of the static large-scale connectome have failed to demonstrate the centrality of the hippocampus; in the context of the whole brain, the hippocampus is not among the most connected or reachable nodes. Here we show that when communication dynamics are taken into account, the hippocampus is a key hub in the connectome. Using a novel computational model, we demonstrate that large-scale brain network topology is organized to funnel and concentrate information flow in the hippocampus, supporting the long-standing hypothesis that this region acts as a critical convergence zone. Our results indicate that the functional capacity of the hippocampus is shaped by its embedding in the large-scale connectome.

Show MeSH
Neighbourhood of CA1.Nodes TFM and TFL have large in-degrees and low out-degrees, causing traffic to be funneled towards CA1. The nodes are spatially positioned in a way that coincides with the directionality of edges, i.e. information is projected from top to bottom.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4256084&req=5

pcbi-1003982-g007: Neighbourhood of CA1.Nodes TFM and TFL have large in-degrees and low out-degrees, causing traffic to be funneled towards CA1. The nodes are spatially positioned in a way that coincides with the directionality of edges, i.e. information is projected from top to bottom.

Mentions: The most plausible reason why these two projections carry so much signal traffic is because of a severe degree imbalance. Namely, both TFM and TFL have relatively large in-degrees (34 and 41, respectively), and relatively low out-degrees (1 and 2, respectively) (Fig. 6D). Thus, TFM and TFL absorb high levels of signal traffic but - as they project only to CA1 and one other node (prosubiculum) - create a funneling effect, resulting in a convergence of signal units at CA1. This degree imbalance is illustrated in Fig. 7, which shows the connectivity between TFM/TFL and CA1. Both TFM and TFL have very large in-degrees but very low out-degrees, causing traffic to be funneled towards CA1.


A network convergence zone in the hippocampus.

Mišić B, Goñi J, Betzel RF, Sporns O, McIntosh AR - PLoS Comput. Biol. (2014)

Neighbourhood of CA1.Nodes TFM and TFL have large in-degrees and low out-degrees, causing traffic to be funneled towards CA1. The nodes are spatially positioned in a way that coincides with the directionality of edges, i.e. information is projected from top to bottom.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256084&req=5

pcbi-1003982-g007: Neighbourhood of CA1.Nodes TFM and TFL have large in-degrees and low out-degrees, causing traffic to be funneled towards CA1. The nodes are spatially positioned in a way that coincides with the directionality of edges, i.e. information is projected from top to bottom.
Mentions: The most plausible reason why these two projections carry so much signal traffic is because of a severe degree imbalance. Namely, both TFM and TFL have relatively large in-degrees (34 and 41, respectively), and relatively low out-degrees (1 and 2, respectively) (Fig. 6D). Thus, TFM and TFL absorb high levels of signal traffic but - as they project only to CA1 and one other node (prosubiculum) - create a funneling effect, resulting in a convergence of signal units at CA1. This degree imbalance is illustrated in Fig. 7, which shows the connectivity between TFM/TFL and CA1. Both TFM and TFL have very large in-degrees but very low out-degrees, causing traffic to be funneled towards CA1.

Bottom Line: However, recent quantitative graph-theoretic analyses of the static large-scale connectome have failed to demonstrate the centrality of the hippocampus; in the context of the whole brain, the hippocampus is not among the most connected or reachable nodes.Using a novel computational model, we demonstrate that large-scale brain network topology is organized to funnel and concentrate information flow in the hippocampus, supporting the long-standing hypothesis that this region acts as a critical convergence zone.Our results indicate that the functional capacity of the hippocampus is shaped by its embedding in the large-scale connectome.

View Article: PubMed Central - PubMed

Affiliation: Rotman Research Institute, Baycrest Centre, Toronto, Canada; Department of Psychology, University of Toronto, Toronto, Canada; Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.

ABSTRACT
The hippocampal formation is a key structure for memory function in the brain. The functional anatomy of the brain suggests that the hippocampus may be a convergence zone, as it receives polysensory input from distributed association areas throughout the neocortex. However, recent quantitative graph-theoretic analyses of the static large-scale connectome have failed to demonstrate the centrality of the hippocampus; in the context of the whole brain, the hippocampus is not among the most connected or reachable nodes. Here we show that when communication dynamics are taken into account, the hippocampus is a key hub in the connectome. Using a novel computational model, we demonstrate that large-scale brain network topology is organized to funnel and concentrate information flow in the hippocampus, supporting the long-standing hypothesis that this region acts as a critical convergence zone. Our results indicate that the functional capacity of the hippocampus is shaped by its embedding in the large-scale connectome.

Show MeSH