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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.

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Degree imbalances.(a) The total number of signal units that traversed a particular connection. (b) The ten most traversed connections. (c) A histogram of all connections in (a), showing the distribution of signal traffic on all connections. (d) The relationship between in-degree and out-degree for all nodes in the network.
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pcbi-1003982-g006: Degree imbalances.(a) The total number of signal units that traversed a particular connection. (b) The ten most traversed connections. (c) A histogram of all connections in (a), showing the distribution of signal traffic on all connections. (d) The relationship between in-degree and out-degree for all nodes in the network.

Mentions: However, it may be possible that the mean connectivity profile of the in-neighbours of CA1 obscures the contribution of individual projections. For instance, it may be the case that there is a small number of projections terminating in CA1 that carry high levels of signal traffic. The total throughput along each directed connection in the macaque network is shown in Fig. 6A, while Fig. 6B shows the top 10 most traversed connections (i.e. highest-valued elements in the matrix). Note that the two most traversed connections in the network are from TFM to CA1 and from TFL to CA1. TFM and TFL represent the medial and lateral portions of parahippocampal area TF, and are known to project directly to CA1 [22]–[24]. The histogram in Fig. 6C helps to get a sense of the contribution of these two projections. The two projections are not only the most traversed; they are far removed from the distribution, representing extreme outliers.


A network convergence zone in the hippocampus.

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

Degree imbalances.(a) The total number of signal units that traversed a particular connection. (b) The ten most traversed connections. (c) A histogram of all connections in (a), showing the distribution of signal traffic on all connections. (d) The relationship between in-degree and out-degree for all nodes in the network.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1003982-g006: Degree imbalances.(a) The total number of signal units that traversed a particular connection. (b) The ten most traversed connections. (c) A histogram of all connections in (a), showing the distribution of signal traffic on all connections. (d) The relationship between in-degree and out-degree for all nodes in the network.
Mentions: However, it may be possible that the mean connectivity profile of the in-neighbours of CA1 obscures the contribution of individual projections. For instance, it may be the case that there is a small number of projections terminating in CA1 that carry high levels of signal traffic. The total throughput along each directed connection in the macaque network is shown in Fig. 6A, while Fig. 6B shows the top 10 most traversed connections (i.e. highest-valued elements in the matrix). Note that the two most traversed connections in the network are from TFM to CA1 and from TFL to CA1. TFM and TFL represent the medial and lateral portions of parahippocampal area TF, and are known to project directly to CA1 [22]–[24]. The histogram in Fig. 6C helps to get a sense of the contribution of these two projections. The two projections are not only the most traversed; they are far removed from the distribution, representing extreme outliers.

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