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Titlebook: Computation in Neurons and Neural Systems; Frank H. Eeckman Book 1994 Springer Science+Business Media New York 1994 Motor.Sensor.cognition

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Solutions to Hodgkin-Huxley Equations: Functional Analysis of a Molluscan Neuroneations could be obtained. This paper illustrates that approximate solutions to these equations do exist. These solutions are in the form of Volterra functional expansions of the state equations of the differential model.
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The Effect of ,, Currents on Bursting Patterns of Pairs of Coupled Neuronshe excitable neuron allows that neuron to fire once for every several bursts of the oscillator, depending on the amount of hyperpolarizing current injected into that neuron. This contrasts with the activity of the same network without . where the excitable neuron fires after every burst of the oscillator or fails to fire completely.
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A Multi-Conditional Correlation Statistics for Detecting Spatio-Temporally Correlated Firing Patternrains. It detects the conditions under which firing in neurons occur in recorded spike trains. Once the multi-conditional probability density function (c.p.d.f.) is established, the probability of which of the . recorded neurons contributes to the combinatorical firing of a neuron can be determined.
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Activity-Dependent Distributions of Neuronal Conductancess to self-assemble their membrane currents. In a spatially extended model neuron, the dynamic regulatory mechanism causes a non-uniform distribution of currents to develop in response to both the morphology and the activity of the neuron.
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Simulating the foveal cone receptive fieldtions to the receptive field, we constructed a compartmental model of the primate foveal outer plexiform layer based on the known anatomy and physiology. The similarity between the computed cone receptive field and the measured midget cell receptive field suggest that much of the retina’s spatial filtering occurs at the very first synapse.
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Inward Rectifying Conductances in Inhibitory Neurons of Turtle Visual Cortex components: a larger, rapidly-activating conductance, and a smaller, slower conductance. The estimated kinetic parameters are sufficient to completely specify the conductances in a compartmental model of the inhibitory neurons.
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