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Articles 1 - 4 of 4
Full-Text Articles in Computational Neuroscience
A Model Of Intracellular Θ Phase Precession Dependent On Intrinsic Subthreshold Membrane Currents., L Stan Leung
A Model Of Intracellular Θ Phase Precession Dependent On Intrinsic Subthreshold Membrane Currents., L Stan Leung
Physiology and Pharmacology Publications
A hippocampal place cell fires at an increasingly earlier phase in relation to the extracellular theta rhythm as a rodent moves through the place field. The present report presents a compartment model of a CA1 pyramidal cell that explains the increase in amplitude and the phase precession of intracellular theta oscillations, with the assumption that the cell receives an asymmetric ramp depolarization (<10 >mV) in the place field and rhythmic inhibitory and/or excitatory synaptic driving. Intracellular subthreshold membrane potential oscillations (MPOs) increase in amplitude and frequency, and show phase precession within the place field. Theta phase precession and MPO power …
Fuzzy Logic: A “Simple” Solution For Complexities In Neurosciences?, Saniya Siraj Godil, Muhammad Shahzad Shamim, Ather Enam, Uvais Qidwai
Fuzzy Logic: A “Simple” Solution For Complexities In Neurosciences?, Saniya Siraj Godil, Muhammad Shahzad Shamim, Ather Enam, Uvais Qidwai
Medical College Documents
Background: Fuzzy logic is a multi-valued logic which is similar to human thinking and interpretation. It has the potential of combining human heuristics into computer-assisted decision making, which is applicable to individual patients as it takes into account all the factors and complexities of individuals. Fuzzy logic has been applied in all disciplines of medicine in some form and recently its applicability in neurosciences has also gained momentum.
Methods: This review focuses on the use of this concept in various branches of neurosciences including basic neuroscience, neurology, neurosurgery, psychiatry and psychology.
Results: The applicability of fuzzy logic is not limited …
Neural Spike Renormalization. Part I — Universal Number 1, Bo Deng
Neural Spike Renormalization. Part I — Universal Number 1, Bo Deng
Department of Mathematics: Faculty Publications
For a class of circuit models for neurons, it has been shown that the transmembrane electrical potentials in spike bursts have an inverse correlation with the intra-cellular energy conversion: the fewer spikes per burst the more energetic each spike is. Here we demonstrate that as the per-spike energy goes down to zero, a universal constant to the bifurcation of spike-bursts emerges in a similar way as Feigenbaum’s constant does to the period-doubling bifurcation to chaos generation, and the new universal constant is the first natural number 1.
Neural Spike Renormalization. Part Ii — Multiversal Chaos, Bo Deng
Neural Spike Renormalization. Part Ii — Multiversal Chaos, Bo Deng
Department of Mathematics: Faculty Publications
Reported here for the first time is a chaotic infinite-dimensional system which contains infinitely many copies of every deterministic and stochastic dynamical system of all finite dimensions. The system is the renormalizing operator of spike maps that was used in a previous paper to show that the first natural number 1 is a universal constant in the generation of metastable and plastic spike-bursts of a class of circuit models of neurons.