AIMC Topic: Neurons

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A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

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...
Action Potentials Epilepsy Supervised Machine Learning Neural Networks, Computer Humans Time Factors Cerebral Cortex Wavelet Analysis Neurons Neural Inhibition Synapses
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Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

Neural networks : the official journal of the International Neural Network Society Aug 31, 2016
In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means o...
Neural Networks, Computer Algorithms Neurons Linear Models Computer Simulation Time Factors
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The effect of the neural activity on topological properties of growing neural networks.

Journal of integrative neuroscience Aug 10, 2016
The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is conti...
Animals Neurons Neural Networks, Computer Synaptic Transmission Neural Pathways
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Stability analysis of switched cellular neural networks: A mode-dependent average dwell time approach.

Neural networks : the official journal of the International Neural Network Society Jul 26, 2016
This paper addresses the exponential stability of switched cellular neural networks by using the mode-dependent average dwell time (MDADT) approach. This method is quite different from the traditional average dwell time (ADT) method in permitting eac...
Neurons Algorithms Computer Simulation Neural Networks, Computer
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Global oscillation regime change by gated inhibition.

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...
Neurons Attention Biological Clocks Neural Inhibition Animals Action Potentials Neural Networks, Computer
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Non-reward neural mechanisms in the orbitofrontal cortex.

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...
Prefrontal Cortex Emotions Action Potentials Neural Networks, Computer Computer Simulation Nerve Net Neurons Reward Humans
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Audiovisual integration in hemianopia: A neurocomputational account based on cortico-collicular interaction.

Neuropsychologia Jul 15, 2016
Hemianopic patients retain some abilities to integrate audiovisual stimuli in the blind hemifield, showing both modulation of visual perception by auditory stimuli and modulation of auditory perception by visual stimuli. Indeed, conscious detection o...
Humans Neural Networks, Computer Models, Neurological Neurons Computer Simulation Hemianopsia Superior Colliculi Neural Pathways Visual Perception Auditory Perception Synapses Cerebral Cortex
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Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation.

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 ...
Locomotion Neuronal Plasticity Artificial Intelligence Models, Neurological Computer Simulation Humans Action Potentials Robotics Neural Networks, Computer Neurons
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Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.

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...
Neural Networks, Computer Algorithms Computer Simulation Animals Action Potentials Neurons Models, Neurological Humans Nonlinear Dynamics
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Decoder Design Based on Spiking Neural P Systems.

IEEE transactions on nanobioscience Jun 23, 2016
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 ...
Models, Neurological Action Potentials Neurons Neural Networks, Computer Computer Simulation
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