An electrophysiological experiment showed that spike timing was precise to less than one millisecond. This result indicates the possibility in the precise time codings. For a high accurate time coding, reconsideration of a neural mechanism which decides firing time is required. From such viewpoint, we quantitatively examined change in firing time with interference between two synaptic inputs th...

A variety of (dis)similarity measures for one-dimensional point processes (e.g., spike trains) are investigated, including the Victor-Purpura distance metric, the van Rossum distance metric, the Schreiber et al. similarity measure, the Hunter-Milton similarity measure, the event synchronization proposed by Quiroga, and the stochastic event synchrony measures (SES) recently proposed by Dauwels e...

The ability to move in complex environments is one of the most important features of human beings and animals. In this work, we exploit a bio-inspired method to generate different gaits in a bipedal locomotion system. We used the 4-cell CPG model developed by Pinto [21]. This model has been established on symmetric coupling between the cells which are responsible for generating oscillatory sign...

In recent neuroscience, many researchers have claimed that synchronization of coupled neurons plays a very important role to code information in the brain. Neurons are classified into two types, class I and class II, by the difference of the onsets of the firing. These two types are confirmed by the physiologic experiments and it is very important to know how these differences affect synchroniz...

Parameter estimation in two-dimensional diffusion models with only one coordinate observed is highly relevant in many biological applications, but a statistically difficult problem. In neuroscience, the membrane potential evolution in single neurons can be measured at high frequency, but biophysical realistic models have to include the unobserved dynamics of ion channels. One such model is the ...

Different from classical artificial neural network which processes digital data, the spiking (SNN) spike trains. Indeed, its event-driven property helps to capture rich dynamics neurons have within brain, and sparsity of collected spikes reducing computational power. Novel synthesis framework is proposed an algorithm detailed guide designers into deep learning energy-efficient analog SNN using ...

Phase and frequency locking are generic phenomena among coupled limit cycles. As yet, it has been shown that simple models of the neurons (such as the Hodgkin-Huxley and Morris-Lecar) are on limit-cycle solutions. The same holds for in vitro pyramidal neurons, if they are driven by constant currents. It is, however, unknown whether this also holds for detailed neuronal compartment models. In th...

We examine a generalized FitzHugh-Nagumo (FHN) type model with modified excitability derived from the diffusive Morris-Lecar equations for neuronal activity. We obtain exact analytic solutions in the form of traveling waves using a piecewise linear approximation for the activator and inhibitor reaction terms. We study the existence and stability of waves and find that the inhibitor species exhi...