Results 231 to 240 of about 176,597 (260)
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Dynamics of stochastic artificial neurons

Neurocomputing, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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NEURONAL DYNAMICS UNDER PERIODIC STIMULI

International Journal of Neural Systems, 2002
The convergence characteristics of a single dissipative Hopfield-type neuron with self-interaction under periodic external stimuli are considered. Sufficient conditions are established for associative encoding and recall of the periodic patterns associated with the external stimuli.
K. Gopalsamy, S. Mohamad
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INFORMATION MODELING OF NEURONAL DYNAMICS

Journal of Biological Systems, 2003
The information transformation of neuronal dynamics into a human's built information network that structures and assembles an incoming information is introduced, based on Information Macrodynamics. Formalized functions of this mechanism represent a general attribute of a system's cognition, which is useful in understanding brain functions and ...
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Dynamic Self-Organizing Neurons

IEEE Transactions on Neural Networks and Learning Systems
Many currently available deep neural network (DNN) accelerators are highly application specific and have focused on supervised learning. In addition, many accelerators have rigid architectures and algorithms that prevent adapting to dynamic environments.
Siddharth Barve, Rashmi Jha
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ANALYTICAL DYNAMICS OF NEURON PULSE PROPAGATION

International Journal of Bifurcation and Chaos, 2006
The four-dimensional Hodgkin–Huxley equations describe the propagation in space and time of the action potential v(z) along a neural axon with z = x + ct and c being the pulse speed. The potential v(z), which is parameterized by the temperature, is driven by three gating functions, m(z), n(z) and h(z), each of which obeys formal first order kinetics ...
Phillipson, Paul E., Schuster, Peter
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Neuronal Dynamics of Predictive Coding

The Neuroscientist, 2001
A critical task of the central nervous system is to learn causal relationships between stimuli to anticipate events in the future, such as the position of a moving prey or predator. What are the neuronal phenomena underlying anticipation? In this article, I review recent results in hippocampal electrophysiology that shed light on this issue.
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Dynamics of golgi impregnation in neurons

Microscopy Research and Technique, 1992
AbstractThis paper describes the early stages of impregnation by the Golgi rapid method in sections and blocks of brain tissue. Aldehyde‐fixed and potassium dichromate–treated sections of cerebral cortex were placed on glass slides and coverslipped. The dichromate solution was then replaced by a silver nitrate solution, and events taking place in the ...
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Calcium Dynamics and Compartmentalization in Leech Neurons

Journal of Neurophysiology, 2005
Calcium dynamics in leech neurons were studied using a fast CCD camera. Fluorescence changes (Δ F/ F) of the membrane impermeable calcium indicator Oregon Green were measured. The dye was pressure injected into the soma of neurons under investigation. Δ F/ F caused by a single action potential (AP) in mechanosensory neurons had approximately the same ...
Andjelic, S., Torre, V.
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Dynamics of Neuronal Populations: The Equilibrium Solution

SIAM Journal on Applied Mathematics, 2000
Summary: The behavior of an aggregate of neurons is followed by means of a population equation which describes the probability density of neurons as a function of membrane potentials. The model is based on integrate-and-fire membrane dynamics and a synaptic dynamics which produce a fixed potential jump in response to stimulation.
Ahmet Omurtag   +2 more
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On the Dynamics of a Couple of Mutually Interacting Neurons

2013
A model for describing the dynamics of two mutually interacting neurons is considered. In such a context, maintaining statements of the Leaky Integrate-and-Fire framework, we include a random component in the synaptic current, whose role is to modify the equilibrium point of the membrane potential of one of the two neurons when a spike of the other one
BUONOCORE, ANIELLO   +3 more
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