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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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Role of network topology and directionality.The mean and standard deviation of CA1 node metrics: (a) arrivals, (b) utilization and (c) node contents. Data represent 100 simulations on the original macaque brain network (red), a single simulation for 100 randomized surrogate networks (green) and a single simulation for 100 surrogate networks with randomly reversed directions (blue).
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pcbi-1003982-g003: Role of network topology and directionality.The mean and standard deviation of CA1 node metrics: (a) arrivals, (b) utilization and (c) node contents. Data represent 100 simulations on the original macaque brain network (red), a single simulation for 100 randomized surrogate networks (green) and a single simulation for 100 surrogate networks with randomly reversed directions (blue).

Mentions: To determine whether the high ranking of CA1 is due to its degree or due to its embedding in the global topology, the data from the macaque network were compared against a “” model, comprised of randomized surrogate networks. In these surrogate networks the degree sequence is preserved but the global topology is destroyed by randomization. Critically, when the network is randomized, information flow through CA1 is greatly reduced (Fig. 3). The extent to which the role of CA1 differs when embedded in a randomized network versus the macaque network can be quantified and statistically assessed by expressing the mean of the macaque network distribution (red) as a -score relative to the randomized distribution (blue). In the present case, the scores for the node contents, arrivals and utilization were and respectively, corresponding to .


A network convergence zone in the hippocampus.

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

Role of network topology and directionality.The mean and standard deviation of CA1 node metrics: (a) arrivals, (b) utilization and (c) node contents. Data represent 100 simulations on the original macaque brain network (red), a single simulation for 100 randomized surrogate networks (green) and a single simulation for 100 surrogate networks with randomly reversed directions (blue).
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1003982-g003: Role of network topology and directionality.The mean and standard deviation of CA1 node metrics: (a) arrivals, (b) utilization and (c) node contents. Data represent 100 simulations on the original macaque brain network (red), a single simulation for 100 randomized surrogate networks (green) and a single simulation for 100 surrogate networks with randomly reversed directions (blue).
Mentions: To determine whether the high ranking of CA1 is due to its degree or due to its embedding in the global topology, the data from the macaque network were compared against a “” model, comprised of randomized surrogate networks. In these surrogate networks the degree sequence is preserved but the global topology is destroyed by randomization. Critically, when the network is randomized, information flow through CA1 is greatly reduced (Fig. 3). The extent to which the role of CA1 differs when embedded in a randomized network versus the macaque network can be quantified and statistically assessed by expressing the mean of the macaque network distribution (red) as a -score relative to the randomized distribution (blue). In the present case, the scores for the node contents, arrivals and utilization were and respectively, corresponding to .

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