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Effects of short-term plasticity in UP-DOWN cortical dynamics
被引:2
|作者:
Vich, C.
[1
]
Giossi, C.
[1
]
Massobrio, P.
[2
]
Guillamon, A.
[3
,4
,5
]
机构:
[1] Univ Illes Balears, Inst Appl Comp & Community Code IAC3, Dept Matemat & Informat, Palma De Mallorca, Spain
[2] Univ Genoa, Dept Informat Bioegineering Robot Syst Engn DIBRIS, Genoa, Italy
[3] Univ Politecn Catalunya UPC, Dept Matemat, Barcelona, Spain
[4] Univ Politecn Catalunya UPC, Inst Matemat UPC BarcelonaTech IMTech, Barcelona, Spain
[5] Ctr Recerca Matemat, Barcelona, Spain
来源:
关键词:
Synaptic inhibition and excitation;
Short-term plasticity;
Neuronal network;
Simulations;
Facilitation;
SYNAPTIC DEPRESSION;
NETWORK MECHANISMS;
SLOW OSCILLATIONS;
NEURAL-NETWORKS;
LESS-THAN-1;
HZ;
SPIKING;
SLEEP;
STATE;
FACILITATION;
NEURONS;
D O I:
10.1016/j.cnsns.2023.107207
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
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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