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Framework for single input single output nanonetwork-based realistic molecular communication.

IET nanobiotechnology
Mobile ad hoc molecular nanonetwork (MAMNET) is a new paradigm for the realisation of future nanonetworks. In MAMNET, transmission of nanoscale information from nanomachine to infostation is based on collision and adhesion. In this study, the authors...

A Lognormal Recurrent Network Model for Burst Generation during Hippocampal Sharp Waves.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The strength of cortical synapses distributes lognormally, with a long tail of strong synapses. Various properties of neuronal activity, such as the average firing rates of neurons, the rate and magnitude of spike bursts, the magnitude of population ...

HFirst: A Temporal Approach to Object Recognition.

IEEE transactions on pattern analysis and machine intelligence
This paper introduces a spiking hierarchical model for object recognition which utilizes the precise timing information inherently present in the output of biologically inspired asynchronous address event representation (AER) vision sensors. The asyn...

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience
UNLABELLED: Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in ...

Implementation of Arithmetic Operations With Time-Free Spiking Neural P Systems.

IEEE transactions on nanobioscience
Spiking neural P systems (SN P systems) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. In most applications of SN P systems, synchronization plays a key role which means the executi...

Passivity and Synchronization of Linearly Coupled Reaction-Diffusion Neural Networks With Adaptive Coupling.

IEEE transactions on cybernetics
In this paper, we study a general array model of coupled reaction-diffusion neural networks (NNs) with adaptive coupling. In order to ensure the passivity of the coupled reaction-diffusion neural networks, some adaptive strategies to tune the couplin...

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

Cognitive processing
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...

Emotion recognition from sound stimuli based on back-propagation neural networks and electroencephalograms.

The Journal of the Acoustical Society of America
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 ...

Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.

Chaos (Woodbury, N.Y.)
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...

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

The Journal of neuroscience : the official journal of the Society for Neuroscience
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....