Neurodegeneration exposes firing rate dependent effects on oscillation dynamics in computational neural networks

Abstract

18Traumatic brain injury (TBI) can lead to neurodegeneration in the injured circuitry, either through primary 19 structural damage to the neuron or secondary effects that disrupt key cellular processes. Moreover, 20 traumatic injuries can preferentially impact subpopulations of neurons, but the functional network effects 21 of these targeted degeneration profiles remain unclear. Although isolating the consequences of complex 22 Author Summary 37In this study, we study the impact of neuronal degeneration -a process that commonly occurs after 38 traumatic injury and neurodegenerative disease -on the neuronal dynamics in a cortical network. We 39 create computational models of neural networks and include spike timing plasticity to alter the synaptic 40 strength among connections as networks remodel after simulated injury. We find that spike-timing 41 dependent plasticity helps recover the neural dynamics of an injured microcircuit, but it frequently 42 cannot recover the original oscillation dynamics in an uninjured network. In addition, we find that 43 selectively injuring excitatory neurons with the highest firing rate reduced the neuronal oscillations in a 44 circuit much more than either random deletion or the removing neurons with the lowest firing rate. In 45 all, these data suggest (a) plasticity reduces the consequences of neurodegeneration and (b) losing the 46 most active neurons in the network has the most adverse effect on neural oscillations. 47

Neuronal Degeneration Impairs Rhythms Between Connected Microcircuits

“…One possibility is that easy-and hardto-reach states are near one another on the energy landscape, so this deletion process would produce indistinguishable results. However, our manipulation also fundamentally differs from previous control studies in macroscale brain networks because deleting neurons effectively subtracts energy from the system as evidenced by deficits in both firing rate (Gabrieli et al, 2019) and frequency power after injury. These changes indicate a global loss of energy after neurodegeneration.…”

“…Neuron activity was modeled via a system of differential equations, which describe the membrane potential and the recovery potential (Izhikevich, 2003;Izhikevich et al, 2004;Izhikevich and Edelman, 2008;Wiles et al, 2017;Gabrieli et al, 2019). The dynamic equations are as follows:…”

“…The model also incorporated primary ionic currents through AMPA and GABA receptors, which drove synaptic-based activity. As in our previous work (Gabrieli et al, 2019), the networks were driven with a contribution of 1 Hz noise according to a gamma distribution (k, θ = 2, 1/2) (Izhikevich and Edelman, 2008;Wiles et al, 2017). When neurons fired, the action potential propagated along synaptic connections with a delay depending on the distance the signal must travel.…”

A multilayer network model of neuron-astrocyte populations in vitro reveals mGluR5inhibition is protective following traumatic injury

“…-21- Conceptually, increased mean nodal strength in the neuronal layer following injury may result from local changes in synaptic strength from plasticity, or may also result from NMDA receptor subtypes influencing the remodeling of synaptic strength. On its own, spike timing dependent plasticity can compensate quickly for reductions in activity that occur when a fraction of the neuronal population is inactivated, leading to a recovery in connectivity within the microcircuit and an increase in remaining synaptic strength (Gabrieli, Schumm, Vigilante, Parvesse, and Meaney (2020); Schumm, Gabrieli, and Meaney ( 2020)), in turn increasing the functional connectivity in the network. Our model of mechanical trauma may lead to local increases in functional connectivity within neurons containing a large fraction of NMDAR receptors containing the GluN 2 A subunit (Patel et al (2014)).…”

A multilayer network model of neuron-astrocyte populations in vitro reveals mGluR5 inhibition is protective following traumatic injury

“…Taken together, these results suggest that multilayer changes in clustering coefficient are mostly mediated by the neuronal layer.Conceptually, increased mean nodal strength in the neuronal layer following injury may result from local changes in synaptic strength from plasticity, or may also result from NMDA receptor subtypes influencing the remodeling of synaptic strength. On its own, spike timing dependent plasticity can compensate quickly for reductions in activity that occur when a fraction of the neuronal population is inactivated, leading to a recovery in connectivity within the microcircuit and an increase in remaining synaptic strength(Gabrieli, Schumm, Vigilante, Parvesse, and Meaney (2020);Schumm, Gabrieli, and Meaney (2020)), in turn increasing the functional connectivity in the network. Our model of mechanical trauma may lead to local increases in functional connectivity within neurons containing a large fraction of NMDAR receptors containing the GluN 2 A subunit(Patel et al (2014)).…”