AIMC Topic: Models, Neurological

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Selection-for-action emerges in neural networks trained to learn spatial associations between stimuli and actions.

Cognitive processing Sep 1, 2015
The objects present in our environment evoke multiple conflicting actions at every moment. Thus, a mechanism that resolves this conflict is needed in order to avoid the production of chaotic ineffective behaviours. A plausible candidate for such role...
Reaction Time Attention Physical Stimulation Spatial Learning Humans Neural Networks, Computer Computer Simulation Models, Neurological
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Emotion recognition from sound stimuli based on back-propagation neural networks and electroencephalograms.

The Journal of the Acoustical Society of America Aug 1, 2015
This research aims to explore the feasibility of using back-propagation (BP) neural networks and electroencephalograms (EEGs) to recognize the emotional reactions induced by sound stimuli in the dimensions of pleasure and arousal, as well as compare ...
Humans Neural Networks, Computer Adolescent Emotions Models, Neurological Electroencephalography Female Young Adult Adult Male Self-Assessment Pattern Recognition, Automated Personal Satisfaction Acoustic Stimulation Feasibility Studies Models, Psychological Pleasure Arousal
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Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.

Chaos (Woodbury, N.Y.) Aug 1, 2015
In this paper, experimental neurophysiologic recording and statistical analysis are combined to investigate the nonlinear characteristic and the cognitive function of the brain. Fuzzy approximate entropy and fuzzy sample entropy are applied to charac...
Humans Brain Female Aged Male Case-Control Studies Fuzzy Logic Models, Neurological Electroencephalography Signal Processing, Computer-Assisted Electrodes Alzheimer Disease Entropy Alpha Rhythm
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Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jul 15, 2015
UNLABELLED: While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates....
Nerve Net Biophysics Neurons Synapses Biophysical Phenomena Neural Networks, Computer Computer Simulation Animals Models, Neurological Action Potentials
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Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition.

IEEE transactions on pattern analysis and machine intelligence Jul 1, 2015
Systems based on bag-of-words models from image features collected at maxima of sparse interest point operators have been used successfully for both computer visual object and action recognition tasks. While the sparse, interest-point based approach ...
Human Activities Pattern Recognition, Visual Male Eye Movements Models, Neurological Video Recording Female Young Adult Adult Humans Artificial Intelligence
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Training and operation of an integrated neuromorphic network based on metal-oxide memristors.

Nature May 7, 2015
Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 10(14) synapses, makes the hardware implementation of neuromorphic networks with a comparable number of ...
Humans Neural Networks, Computer Algorithms Metals Models, Neurological Oxides Equipment Design Biomimetics Semiconductors Synapses Electronics Transistors, Electronic Nanotechnology Engineering
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Variable neural adaptive robust control: a switched system approach.

IEEE transactions on neural networks and learning systems May 1, 2015
Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multiinput multioutput uncertain systems. The controllers incorporate a novel variable-structure radial basis function (RBF) network as the ...
Humans Neural Networks, Computer Computer Simulation Feedback Models, Neurological Nonlinear Dynamics
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Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks.

Chaos (Woodbury, N.Y.) Apr 1, 2015
Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is s...
Models, Theoretical Models, Neurological Humans Synaptic Transmission Action Potentials Neural Networks, Computer Computer Simulation Algorithms Signal Processing, Computer-Assisted Animals Neurons Brain Cognition Signal-To-Noise Ratio Nerve Net Normal Distribution
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A universal concept based on cellular neural networks for ultrafast and flexible solving of differential equations.

IEEE transactions on neural networks and learning systems Apr 1, 2015
This paper develops and validates a comprehensive and universally applicable computational concept for solving nonlinear differential equations (NDEs) through a neurocomputing concept based on cellular neural networks (CNNs). High-precision, stabilit...
Models, Neurological Neurons Nonlinear Dynamics Problem Solving Algorithms Computer Simulation Time Factors Humans Neural Networks, Computer Software
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Synchronization, non-linear dynamics and low-frequency fluctuations: analogy between spontaneous brain activity and networked single-transistor chaotic oscillators.

Chaos (Woodbury, N.Y.) Mar 1, 2015
In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functi...
Transistors, Electronic Nerve Net Cortical Synchronization Animals Models, Neurological Biomimetics Nonlinear Dynamics Humans Neural Networks, Computer Computer Simulation
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