Abstract
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.
Highlights
Network physiology reveals how organ systems dynamically interact (Bartsch et al, 2015)
Our results show that the delayed conductance in both excitatory and inhibitory connections play an important role in the neuronal synchronization
We find that a small change of the delayed conductance value can improve or suppress synchronous behavior
Summary
Network physiology reveals how organ systems dynamically interact (Bartsch et al, 2015). Brain-brain and brain-organ networks have been considered to study integrated physiological systems under neuronal control (Ivanov et al, 2009). Network models have been used to study the effects of time delay in synchronized neuronal activities (Stepan, 2009). The dynamics of coupled neurons was investigated in networks with random connections (Brunel, 2000), small-world (Tang et al, 2011), and scale-free (Batista et al, 2007, 2010) topologies were used to study neuronal synchronization. Pérez et al (2011) studied the influence of conduction delays on spike synchronization in Hodgkin-Huxley neuronal networks. Our results show that the delayed conductance in both excitatory and inhibitory connections play an important role in the neuronal synchronization.
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