Synchronised firing patterns in a random network of adaptive exponential integrate-and-fire neuron model

Acknowledgements This study was possible by partial financial support from the following Brazilian government agencies: CNPq, CAPES, and FAPESP (2011/19296-1 and 2015/07311-7). We also wish thank Newton Fund and COFAP.Peer reviewedPostprin

Analytical solutions for the short-term plasticity

Acknowledgements This study was possible by partial financial support from the following Brazilian government agencies: FAPESP (2020/04624-2, 2022/05153-9, 2022/13761-9).Peer reviewe

Alterations in brain connectivity due to plasticity and synaptic delay

Brain plasticity refers to brain's ability to change neuronal connections, as a result of environmental stimuli, new experiences, or damage. In this work, we study the effects of the synaptic delay on both the coupling strengths and synchronisation in a neuronal network with synaptic plasticity. We build a network of Hodgkin-Huxley neurons, where the plasticity is given by the Hebbian rules. We verify that without time delay the excitatory synapses became stronger from the high frequency to low frequency neurons and the inhibitory synapses increases in the opposite way, when the delay is increased the network presents a non-trivial topology. Regarding the synchronisation, only for small values of the synaptic delay this phenomenon is observed

Influence of Autapses on Synchronization in Neural Networks With Chemical Synapses

A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on neural synchronization. Here, we build a random network with adaptive exponential integrate-and-fire neurons coupled with chemical synapses, equipped with autapses, to study the effect of the latter on synchronous behavior. We consider time delay in the conductance of the pre-synaptic neuron for excitatory and inhibitory connections. Interestingly, in neural networks consisting of both excitatory and inhibitory neurons, we uncover that synchronous behavior depends on their synapse type. Our results provide evidence on the synchronous and desynchronous activities that emerge in random neural networks with chemical, inhibitory and excitatory synapses where neurons are equipped with autapses. © Copyright © 2020 Protachevicz, Iarosz, Caldas, Antonopoulos, Batista and Kurths

Plastic neural network with transmission delays promotes equivalence between function and structure

Acknowledgements The authors acknowledge the financial support from São Paulo Research Foundation (FAPESP, Brazil) (Grants Nos. 2016/23398-8, 2017/13502-5, 2018/03211-6, 2020/04624-2, 2022/05153-9, 2022/13761-9), National Council for Scientific and Technological Development (CNPq), Fundação Araucária and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) .Peer reviewedPublisher PD

Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

We wish to acknowledge the support from Fundação Araucária, CNPq (Grant No. 150701/2018-7), CAPES, and FAPESP (Grant Nos. 2015/07311-7, 2018/03211-6, and 2017/18977-1).Peer reviewedPublisher PD