2020, Protachevicz, Paulo R., Iarosz, Kelly C., Caldas, Iberê L., Antonopoulos, Chris G., Batista, Antonio M., Kurths, Jürgen

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.

2020, Protachevicz, Paulo R., Borges, Fernando S., Iarosz, Kelly C., Baptista, Murilo S., Lameu, Ewandson L., Hansen, Matheus, Caldas, Iberê L., Szezech Jr., José D., Batista, Antonio M., Kurths, Jürgen

In the brain, the excitation-inhibition balance prevents abnormal synchronous behavior. However, known synaptic conductance intensity can be insufficient to account for the undesired synchronization. Due to this fact, we consider time delay in excitatory and inhibitory conductances and study its effect on the neuronal synchronization. In this work, we build a neuronal network composed of adaptive integrate-and-fire neurons coupled by means of delayed conductances. We observe that the time delay in the excitatory and inhibitory conductivities can alter both the state of the collective behavior (synchronous or desynchronous) and its type (spike or burst). For the weak coupling regime, we find that synchronization appears associated with neurons behaving with extremes highest and lowest mean firing frequency, in contrast to when desynchronization is present when neurons do not exhibit extreme values for the firing frequency. Synchronization can also be characterized by neurons presenting either the highest or the lowest levels in the mean synaptic current. For the strong coupling, synchronous burst activities can occur for delays in the inhibitory conductivity. For approximately equal-length delays in the excitatory and inhibitory conductances, desynchronous spikes activities are identified for both weak and strong coupling regimes. Therefore, our results show that not only the conductance intensity, but also short delays in the inhibitory conductance are relevant to avoid abnormal neuronal synchronization. © Copyright © 2020 Protachevicz, Borges, Iarosz, Baptista, Lameu, Hansen, Caldas, Szezech, Batista and Kurths.

2019, Protachevicz, Paulo R., Borges, Fernando S., Lameu, Ewandson L., Ji, Peng, Iarosz, Kelly C., Kihara, Alexandre H., Caldas, Ibere L., Szezech Jr., Jose D., Baptista, Murilo S., Macau, Elbert E.N., Antonopoulos, Chris G., Batista, Antonio M., Kurths, Jürgen

Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronization originating from a pattern of desynchronized spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures. © 2019 Protachevicz, Borges, Lameu, Ji, Iarosz, Kihara, Caldas, Szezech, Baptista, Macau, Antonopoulos, Batista and Kurths.