Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions.

Ankur Sinha,Neil Davey,Roderick Adams,Christoph Metzner,Michael Schmuker,Volker Steuber,Abigail Morrison

doi:10.1371/journal.pcbi.1008996

Ankur Sinha, Neil Davey + Show 5 more

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https://doi.org/10.1371/journal.pcbi.1008996

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Abstract

Several homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity. One of these, homeostatic structural plasticity, has been reported to restore activity in networks disrupted by peripheral lesions by altering their neuronal connectivity. While multiple lesion experiments have studied the changes in neurite morphology that underlie modifications of synapses in these networks, the underlying mechanisms that drive these changes are yet to be explained. Evidence suggests that neuronal activity modulates neurite morphology and may stimulate neurites to selective sprout or retract to restore network activity levels. We developed a new spiking network model of peripheral lesioning and accurately reproduced the characteristics of network repair after deafferentation that are reported in experiments to study the activity dependent growth regimes of neurites. To ensure that our simulations closely resemble the behaviour of networks in the brain, we model deafferentation in a biologically realistic balanced network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex. Our simulation results indicate that the re-establishment of activity in neurons both within and outside the deprived region, the Lesion Projection Zone (LPZ), requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. Analysis of these growth regimes indicates that they also contribute to the maintenance of activity levels in individual neurons. Furthermore, in our model, the directional formation of synapses that is observed in experiments requires that pre-synaptic excitatory and inhibitory elements also follow opposite growth rules. Lastly, we observe that our proposed structural plasticity growth rules and the inhibitory synaptic plasticity mechanism that also balances our AI network both contribute to the restoration of the network to pre-deafferentation stable activity levels.

Highlights

Multiple plasticity mechanisms act simultaneously and at differing time scales on neuronal networks in the brain
To ensure that our simulations closely resemble the behaviour of networks in the brain, we model deafferentation in a biologically realistic balanced network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex
An accumulating body of evidence suggests that our brain can compensate for peripheral lesions by adaptive rewiring of its neuronal circuitry

Summary

Introduction

Multiple plasticity mechanisms act simultaneously and at differing time scales on neuronal networks in the brain. Along with confirmation of structural plasticity in the adult brain [1,2,3,4], recent work has shown that axonal boutons and branches [5,6,7,8,9,10], and both inhibitory [11, 12] and excitatory dendritic structures [13, 14] are highly dynamic even in physiological networks. Recent time-lapse imaging studies of neurites in the cortex during the rewiring process show that both axonal [6, 10, 27] and dendritic structures display increased turnover rates [10, 13, 28, 29] in and around the area deafferented by the peripheral lesion, the Lesion Projection Zone (LPZ). Along with an increased excitatory dendritic spine gain [28] and a marked loss of inhibitory shaft synapses [11, 30] in the LPZ, the rewiring of synapses in the network successfully restores activity to deprived LPZ neurons in many cases

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