A large body of experimental and theoretical work on neural coding suggests that the information stored in brain circuits is represented by time-varying patterns of neural activity. Reservoir computing, where the activity of a recurrently connected p...
International journal of neural systems
Sep 1, 2016
This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timi...
Neural networks : the official journal of the International Neural Network Society
Jul 18, 2016
The role of sensory inputs in the modelling of synchrony regimes is exhibited by means of networks of spiking cells where the relative strength of the inhibitory interaction is controlled by the activation of a linear unit working as a gating variabl...
Cortex; a journal devoted to the study of the nervous system and behavior
Jul 15, 2016
Single neurons in the primate orbitofrontal cortex respond when an expected reward is not obtained, and behaviour must change. The human lateral orbitofrontal cortex is activated when non-reward, or loss occurs. The neuronal computation of this negat...
Computational intelligence and neuroscience
Jun 29, 2016
A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To ...
IEEE transactions on neural networks and learning systems
Jun 24, 2016
In this paper, we have introduced a general modeling approach for dynamic nonlinear systems that utilizes a variant of the simulated annealing algorithm for training the Laguerre-Volterra network (LVN) to overcome the local minima and convergence pro...
The spiking neural P systems (SN P systems, for short) refer to the parallel-distributed biocomputing models, which have currently become research hotspots in the biocomputing field. In computing systems, logical operations and arithmetic operations ...
BACKGROUND: Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (I...
Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic fee...
In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration dep...