A simple analog circuit is presented which can play a neuron role in static-model-based neural networks implemented in the form of an integrated circuit. Operating in a transresistance mode it is suited to cooperate with transconductance synapses. As a result, its input signal is a current which is a sum of currents coming from the synapses. Summation of the currents is realized in a node at th...

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...

We present a low-power analog circuit for implementing a model of a leaky integrate and fire neuron. Next to being optimized for low-power consumption, the proposed circuit includes elements for implementing spike frequency adaptation, for setting an arbitrary refractory period and for modulating the neuron’s threshold voltage. We present experimental data from a prototype chip, implemented usi...

ThèBussgang' algorithm is one among the most known blind deconvo-lution techniques in the adaptive signal processing literature. It relies on a Bayesian estimator of the source signal that requires the prior knowledge of the source statistics as well as the deconvolution noise characteristics. In this paper we propose to implement the estimator with a simple adap-tive activation function neuron...

We present a new algorithm for automatic and interactive segmentation of neuron structures from electron microscopy (EM) images. Our method selects a collection of nodes from the watershed mergng tree as the proposed segmentation. This is achieved by building a onditional random field (CRF) whose underlying graph is the merging tree. The maximum a posteriori (MAP) prediction of the CRF is the o...

objective(s):silver nanoparticles (ag-nps) are used widely in bedding, water purification, tooth paste and toys. these nanoparticles can enter into the body and move into the hippocampus. the aim of this study was to investigate the neurotoxicity of silver nanoparticles in the adult rat hippocampus. materials and methods:12 male wistar rats were randomly divided into two experimental and contro...

We describe the response properties of a compact, low power, analog circuit that implements a model of a leaky–Integrate & Fire (I&F) neuron, with spike-frequency adaptation, refractory period and voltage threshold modulation properties. We investigate the statistics of the circuit’s output response by modulating its operating parameters, like refractory period and adaptation level and by chang...

Recognizing that Internet congestion control is a complex nonlinear system, we propose here to use an intelligent controller to improve its stability and performance. In particular, we propose here a new, powerful, easy-to-configure and robust active queue management (AQM) scheme called adaptive neuron AQM (AN-AQM). We present extensive simulation results for AN-AQM, over a wide range of networ...

Neurophysiology is largely the study of spike rates of single neurons, under controlled conditions, with the hope that these results reflect how populations of neurons compute. However, the population response differs radically from the single-neuron response if the membrane voltage's rate of change drops dramatically when it is close to the spike-firing threshold. By delaying spiking, this sle...

In the paper, a new optimal learning algorithm for a neo-fuzzy neuron (NFN) is proposed. The algorithm is characteristic in that it provides online tuning of not only the synaptic weights, but also the membership functions parameters. The proposed algorithm has both the tracking and filtering properties, so the NFN can be effectively used for prediction, filtering, and restoration of non-statio...