Action potentials (APs) and sodium current from the slowly and the rapidly adapting stretch receptor neurons in the crayfish (Astacus astacus) were recorded with a two microelectrode voltage- and current-clamp technique. In the rapidly adapting neuron the APs had a duration of 3.2 +/- 0.2 ms (means +/- SE) and an amplitude of 55.2 +/- 1.5 mV. In the slowly adapting receptor neuron APs had a dur...

This paper presents an alternative approach for the control of an antagonistic muscle actuated manipulator. The proposed method uses a neuronal network called NeuraBase to learn the sensor events obtained via a rotary encoder and to control the motor events of two DC motors, to rotate the manipulator. A neuron layer called the controller network links the sensor neuron events to the motor neuro...

Abstract: The long term objective of our research is to use the knowledge from biological studies on animal locomotion and establish a new paradigm for control design that realizes robust, adaptive, and autonomous systems. As a very first step, this paper proposes a new dynamical model of a single neuron, given by a specific class of the Lur’e systems, and show that the model makes a good trade...

In many real-world applications, the amount of data available for training is often limited, and thus inductive bias auxiliary knowledge are much needed regularizing model training. One popular regularization method to impose prior distribution assumptions on parameters, recent works also attempt regularize by integrating external into specific neurons. However, existing methods did not take ac...

Neural networks traditionally produce a scalar value for an activated neuron. Capsules, on the other hand, vector of values, which has been shown to correspond single, composite feature wherein values components vectors indicate properties such as transformation or contrast. We present new way parameterizing and training capsules that we refer homogeneous (HVCs). demonstrate, experimentally, al...

Many physiological events require an accurate timing signal, usually generated by neural networks called central pattern generators (CPGs). On the other hand, properties of neurons and neural networks (e.g. time constants of neurons and weights of network connections) alter with time, resulting in gradual changes in timing of such networks. Recently, a synaptic weight adjustment mechanism has b...

In this study, we propose an advanced category of a fuzzy adaptive neural network (FANN) based on feature self-enhancement unit (FSU) and statistical selection methods (SSMs). Undoubtedly, the raw data contain large amount information with varying importance. One most important tasks for regression model design is to avoid losing these details. However, cannot participate in whole training proc...

Objective(s): Cell therapy has provided clinical applications to the treatment of motor neuron diseases. The current obstacle in stem cell therapy is to direct differentiation of stem cells into neurons in the neurodegenerative disorders. Biomaterial scaffolds can improve cell differentiation and are widely used in translational medicine and tissue engineering. The aim...

Because microglial cells, the resident macrophages of the CNS, react to any lesion of the nervous system, they have for long been regarded as potential players in the pathogenesis of several neurodegenerative disorders including Amyotrophic Lateral Sclerosis, the most common motor neuron disease in the adult. In recent years, this microglial reaction to motor neuron injury, in particular, and t...

Multiple pages have been removed from this document in order to comply with copyright law. In this article, we describe an adaptive controller for an autonomous mobile robot with a simple structure. Sensorimotor connections were made using a three-layered spiking neural network (SNN) with only one hidden-layer neuron and synapses with spike timing-dependent plasticity (STDP). In the SNN control...