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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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CA1 as a communication outlier.Communication metrics (node contents and arrivals) are compared to connectivity metrics, including in-degree (a,b), neighbours' mean in-degree (c,d) and neighbours' mean out-degree (e,f). In panels c-f, “neighbours” refers to nodes that project to CA1.
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pcbi-1003982-g004: CA1 as a communication outlier.Communication metrics (node contents and arrivals) are compared to connectivity metrics, including in-degree (a,b), neighbours' mean in-degree (c,d) and neighbours' mean out-degree (e,f). In panels c-f, “neighbours” refers to nodes that project to CA1.

Mentions: Thus, comparisons with models confirm that the convergence of signal traffic at CA1 is not due to its degree, but some other higher-level feature of macaque connectivity. Specifically, the convergence of signal traffic appears to be related to both the topology and the directionality of the network. Figs. 4A and B confirm this, showing that CA1 behaves in a unique way. While greater in-degree (i.e. number of afferent projections) is associated with greater signal traffic, CA1 is a clear outlier. Namely, CA1 attracts signal traffic to an extent that is above and beyond what would be expected on the basis of its in-degree alone.


A network convergence zone in the hippocampus.

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

CA1 as a communication outlier.Communication metrics (node contents and arrivals) are compared to connectivity metrics, including in-degree (a,b), neighbours' mean in-degree (c,d) and neighbours' mean out-degree (e,f). In panels c-f, “neighbours” refers to nodes that project to CA1.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1003982-g004: CA1 as a communication outlier.Communication metrics (node contents and arrivals) are compared to connectivity metrics, including in-degree (a,b), neighbours' mean in-degree (c,d) and neighbours' mean out-degree (e,f). In panels c-f, “neighbours” refers to nodes that project to CA1.
Mentions: Thus, comparisons with models confirm that the convergence of signal traffic at CA1 is not due to its degree, but some other higher-level feature of macaque connectivity. Specifically, the convergence of signal traffic appears to be related to both the topology and the directionality of the network. Figs. 4A and B confirm this, showing that CA1 behaves in a unique way. While greater in-degree (i.e. number of afferent projections) is associated with greater signal traffic, CA1 is a clear outlier. Namely, CA1 attracts signal traffic to an extent that is above and beyond what would be expected on the basis of its in-degree alone.

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