4.7 Article

Effects of short-term plasticity in UP-DOWN cortical dynamics

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DOI: 10.1016/j.cnsns.2023.107207

Keywords

Synaptic inhibition and excitation; Short-term plasticity; Neuronal network; Simulations; Facilitation

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Neuronal dynamics are influenced by short-term plasticity (STP), which can be dominated by short-term depression (STD), short-term facilitation (STF), or both. This study develops a network model with excitatory and inhibitory neurons endowed with STD and STF, mimicking the connectivity circuitry in the visual cortex. The results suggest that depression and facilitation are involved in switching between different activity patterns, and critical levels of depression and facilitation determine the network's behavior.
Neuronal dynamics are strongly influenced by short-term plasticity (STP), that is, changes in synaptic efficacy that occur on a short (from milliseconds to seconds) time scale. Depending on the brain areas considered, STP can be dominated by short-term depression (STD), short-term facilitation (STF), or both mechanisms can coexist simultaneously. These two plasticity mechanisms modulate particular patterns of elec-trophysiological activity characterized by alternating UP and DOWN states. In this work, we develop a network model made up of excitatory and inhibitory multi-compartment neurons endowed with both mechanisms (STD and STF), spatially arranged to emulate the connectivity circuitry observed experimentally in the visual cortex. Our results reveal that both depression and facilitation can be involved in the switching process between different activity patterns, from an alternation of UP and DOWN states (for relatively low levels of depression and high levels of facilitation) to an asynchronous firing regime (for relatively high levels of depression and low levels of facilitation). For STD and STF, we identify the critical levels of depression and facilitation that push the network into the different regimes. Furthermore, we also find that these critical levels separate different growth rates of the mean synaptic conductances of the whole network with respect to the depression levels. This latter data is paramount to understanding how excitation and inhibition are organized to generate different brain activity regimes. Finally, after observing the changes in the trajectories of excitatory and inhibitory instantaneous firing rates near these critical boundaries, we identify dynamic patterns that shed light on the type of bifurcations that should arise in a rate model for this complex network.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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