Self-organizing small-world networks are most robust against local disturbances
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1
VU University Amsterdam, Netherlands
Small-world networks display enhanced signal-propagation speed, computational power, and synchronizability. Neuronal networks in the brain share properties of small-world networks and, in addition, dynamically rewire their connectivity by forming and deleting synapses. It is unclear whether small world networks are best in repairing damages caused by loss of connections and input. Neuronal networks show a reciprocal interaction between topology and the flow of neuronal (electrical) activity they generate. Topology determines the activity flow through the network, whereas on a longer timescale, the flow of activity requires new connections to be formed or existing ones to be removed. Importantly, neurons try to maintain their electrical activity at a certain setpoint (homeostasis of electrical activity). That is if neurons loose synaptic input due to a lesion, they respond with a local change in connectivity to obtain more activity from different sources. Here we investigate by a computational modelling study based on a model for activity-dependent structural plasticity [1,2], first, how local changes in synaptic connectivity alter global network topology after a circumscribed loss of input; and second, which topologies best support network repair re-establishing homeostasis in electrictal activity of all neurons. We found that reorganizing networks become more random as they form more long-range connections after a loss of input and those neurons loosing their input increase their centrality inbetweenness. Interestingly, an increased randomness and centrality inbetweenness has been recently found in functional connectivity of ipsilateral cortical and contralateral cerebellar networks following subcortical stroke [3]. As a second important result we found that small-world networks recover fastest (Fig.1) compared to regular and random networks from a loss of input in terms that all neurons return to homeostasis in electrical activity. The small-worldness of brain networks may therefore have an evolutionary advantage since those networks are more robust against lesions than regular (and random) networks.
Figure 1: Number of connectivity updates needed to completely repair the network as dependent on a small-world parameter γ of the network. Small-world networks go fastest back into homeostasis.
Acknowledgements
This work was supported by a NOW Computational Life Sciences grant (635.100.017) awarded to Arjen van Ooyen.
References
1. Butz , Teuchert-Noodt G, Grafen K, van Ooyen A (2008) Inverse relationship between adult hippocampal cell proliferation and synaptic rewiring in the dentate gyrus. Hippocampus. 2008;18(9):879-98.
2. Butz M, van Ooyen A, Wörgötter F (2009) A model for cortical rewiring following deafferentation and focal stroke. Front Comput Neurosci. 2009;3:10.
3. Wang L, Yu C, Chen H, Qin W, He Y, Fan F, Zhang Y, Wang M, Li K, Zang Y, Woodward TS, Zhu C (2010) Dynamic functional reorganization of the motor execution network after stroke. Brain. 2010 Apr;133(Pt 4):1224-38.
Keywords:
brain lesions,
Homeostasis,
self-organizing networks,
structural plasticity,
topology
Conference:
BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011.
Presentation Type:
Abstract
Topic:
neurons, networks and dynamical systems (please use "neurons, networks and dynamical systems" as keywords)
Citation:
Steenbuck
I,
Van Ooyen
A and
Butz
M
(2011). Self-organizing small-world networks are most robust against local disturbances.
Front. Comput. Neurosci.
Conference Abstract:
BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011.
doi: 10.3389/conf.fncom.2011.53.00034
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Received:
09 Sep 2011;
Published Online:
04 Oct 2011.
*
Correspondence:
Dr. Markus Butz, VU University Amsterdam, Amsterdam, 1081HV, Netherlands, mbutz@falw.vu.nl