Experiments showed that a neuron can fire when its membrane potential (an intrinsic quality related to electrical charge) reaches specific threshold. On theoretical studies, there are two crucial issues in exploring cortical neuronal dynamics: (i) what model describes spiking dynamics of each neuron, and (ii) how the neurons connected [E. M. Izhikevich, IEEE Trans. Neural Networks, 15 (2004)]. ...

We study the performance of a spiking network model based on Integrate-andFire neurons when performing a benchmark discrimination task. The task consists of determining the direction of moving dots in a noisy context. By varying the synaptic parameters of the Integrate-and-Fire neurons, we illustrate the counter-intuitive importance of the second order statistics (input noise) in improving the ...

We consider a wide class of spiking neuron models, defined by rather general set of conditions typical for basic models like leaky integrate and fire, or binding neuron model. A neuron is fed with a point renewal process. A relation between the three probability density functions (pdf): (i) pdf of input interspike intervals, (ii) pdf of output interspike intervals of a neuron with instantaneous...

Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-...

Objective(s): Cell therapy has provided clinical applications to the treatment of motor neuron diseases. The current obstacle in stem cell therapy is to direct differentiation of stem cells into neurons in the neurodegenerative disorders. Biomaterial scaffolds can improve cell differentiation and are widely used in translational medicine and tissue engineering. The aim...

Artificial neural networks have achieved a great success in simulating the information processing mechanism and process of neuron supervised learning, such as classification. However, traditional artificial neurons still many problems slow difficult training. This paper proposes new dendrite model (DNM), which combines metaheuristic algorithm effectively. Eight learning algorithms including bac...

The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008) in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neuro...

We interpret biological motion trajectories as composed of sequences of sub-blocks or motion primitives. Such primitives, together with the information, when they occur during a motion, provide a compact representation of movement. We present a two-layer model for movement generation, where the higher level consists of a number of spiking neurons that trigger motion primitives in the lower leve...

The human brain is able to perform a number feats that researchers have not been able to replicate in artificial systems. Unsolved questions include: Why are we conscious and how do we process visual information from the input stimulus right down to the individual action. We have created a computational model of visual information processing. A network of spiking neurons, a single layer, is sim...