Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural
network in which neurons are randomly connected. Once initialized, the connection …

Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most
cortical activity is internally generated by recurrence. Both theoretical and experimental …

Generation of complex patterns at a specific timing is crucial to most forms of learning and
behavior, which are acquired through dopamine-modulated plasticity in the striatum …

Chinese mitten crab has unique limb structures composed of a hard exoskeleton and
flexible muscles. They enable the crab to locomote adaptively and safely on various terrains …

Reservoir Computing is a relatively new framework created to allow the usage of powerful
but complex systems as computational mediums. The basic approach consists in training …

As one of the most complex systems known to science, modeling brain behavior and
function is both fascinating and extremely difficult. Empirical data is increasingly available …

This paper presents a method for reproducing a simple central pattern generator (CPG)
using a modified Echo State Network (ESN). Conventionally, the dynamical reservoir needs …

Due to the complexity of neuronal networks and the nonlinear dynamics of individual
neurons, it is challenging to develop a systems-level model which is accurate enough to be …

Echo state network (ESN), a kind of recurrent neural networks, consists of a fixed reservoir in
which neurons are connected randomly and recursively and obtains the desired output only …

Reservoir computing (RC) is a unique machine learning framework based on a recurrent
neural network, which is currently involved in numerous research fields. RC systems are …