University of Hertfordshire

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Growth rules for repair of asynchronous irregular network models following peripheral lesions

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Original languageEnglish
Article number56
Pages (from-to)157-157
Number of pages1
JournalBMC Neuroscience
Issue(Supple 1)
Publication statusPublished - 14 Nov 2019
Event28th Annual Computational Neuroscience Meeting - Barcelona, Spain
Duration: 13 Jul 201917 Jul 2019


Several homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity after disruptive changes to synaptic inputs. One of these homeostatic mechanisms, structural plasticity, can restore activity levels after peripheral lesions and deafferentation by altering neuronal connectivity over extended time periods [2]. Several experimental lesion studies have investigated the temporal evolution of network rewiring by structural plasticity in detail. However, the underlying mechanisms and growth rules that underlie these homeostatic rewiring processes are still not known [3].

We have used computer simulations of a network model that exhibits biologically realistic Asynchronous Irregular (AI) activity [1] in order to study the growth rules and processes that could explain homeostatic rewiring based on structural plasticity after peripheral lesions. In our simulations, we observe network rewiring after loss of peripheral input to a localised part of the network, the Lesion Projection Zone (LPZ).

Our simulation results indicate that the homeostatic re-establishment of activity in neurons both within and outside the LPZ requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. As a consequence, the reduction of activity in the LPZ results in ingrowth of novel excitatory inputs and a retraction of inhibitory input connections, whilst an increase in activity due to the loss of inhibition outside the LPZ causes a retraction of excitatory input connections and an increase in inhibitory ones. Our growth rules maintain desired activity levels in the network as well as in individual neurons.

Furthermore, we show that these growth rules replicate the directional formation of connections that is observed in lesion experiments. After deafferentation of the LPZ, the simulated network exhibits the sprouting of excitatory axons from areas next to the LPZ into the LPZ that has been reported in experiments, and the outgrowth of inhibitory axons from the LPZ into neighbouring areas that has been found experimentally. Further predictions of our model that could be tested experimentally are (1) that the ingrowth of excitatory axons into the LPZ requires that the growth of excitatory axons is triggered by an increase in neuronal activity, and (2) that the sprouting of inhibitory axons needs to be caused by a decrease in neuronal activity.


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