Pages that link to "Item:Q3101415"

The following pages link to Modeling Single-Neuron Dynamics and Computations: A Balance of Detail and Abstraction (Q3101415):

Displaying 41 items.

• Dynamics of a neuron model in different two-dimensional parameter-spaces (Q432928) (← links)
• Energy consumption and information transmission in model neurons (Q602114) (← links)
• Modeling convergent ON and OFF pathways in the early visual system (Q999383) (← links)
• Physiological constraints on the formal representation of neurons (Q1200646) (← links)
• Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise (Q1620361) (← links)
• A single retinal circuit model for multiple computations (Q1627028) (← links)
• How does transient signaling input affect the spike timing of postsynaptic neuron near the threshold regime: an analytical study (Q1628229) (← links)
• Algorithmic analysis of irrational rotations in a single neuron model (Q1869962) (← links)
• Formation of autapse connected to neuron and its biological function (Q2012806) (← links)
• Mean-field limits for non-linear Hawkes processes with excitation and inhibition (Q2080269) (← links)
• A simple one-dimensional map-based model of spiking neurons with wide ranges of firing rates and complexities (Q2116015) (← links)
• The dynamical analysis of modified two-compartment neuron model and FPGA implementation (Q2147748) (← links)
• Multi-channels coupling-induced pattern transition in a tri-layer neuronal network (Q2148357) (← links)
• The case for emulating insect brains using anatomical ``wiring diagrams'' equipped with biophysical models of neuronal activity (Q2278553) (← links)
• Biophysically interpretable inference of single neuron dynamics (Q2281001) (← links)
• Capacitor coupling induces synchronization between neural circuits (Q2297028) (← links)
• Gamma oscillations as a mechanism for selective information transmission (Q2376491) (← links)
• Synapse fits neuron: joint reduction by model inversion (Q2403826) (← links)
• Parallel computation in spiking neural nets (Q2455594) (← links)
• Modeling neuronal assemblies: Theory and implementation (Q2784802) (← links)
• Optimal sequential detection of stimuli from multiunit recordings taken in densely populated brain regions (Q2919399) (← links)
• Stochastic Properties of Coincidence-Detector Neural Cells (Q3182482) (← links)
• Multiscale modeling, stochastic and asymptotic approaches for analyzing neural networks based on synaptic dynamics (Q3467500) (← links)
• Multilayer Processing of Spatiotemporal Spike Patterns in a Neuron with Active Dendrites (Q3583497) (← links)
• A Gradient Learning Rule for the Tempotron (Q3612122) (← links)
• Computation in a Single Neuron: Hodgkin and Huxley Revisited (Q4814194) (← links)
• The Refractory Period Matters: Unifying Mechanisms of Macroscopic Brain Waves (Q5004347) (← links)
• Derivation of a Cell-Based Mathematical Model of Excitable Cells (Q5011329) (← links)
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• (Q5134799) (← links)
• Controlling Complexity of Cerebral Cortex Simulations—II: Streamlined Microcircuits (Q5154164) (← links)
• Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data (Q5157143) (← links)
• Omitted variable bias in GLMs of neural spiking activity (Q5157275) (← links)
• MULTISCALE COMPUTATIONS ON NEURAL NETWORKS: FROM THE INDIVIDUAL NEURON INTERACTIONS TO THE MACROSCOPIC-LEVEL ANALYSIS (Q5306419) (← links)
• Capturing the Dynamical Repertoire of Single Neurons with Generalized Linear Models (Q5380878) (← links)
• Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback (Q5383804) (← links)
• Two Computational Regimes of a Single-Compartment Neuron Separated by a Planar Boundary in Conductance Space (Q5387447) (← links)
• Single Neuron Computation: From Dynamical System to Feature Detector (Q5441729) (← links)
• A fundamental inequality governing the rate coding response of sensory neurons (Q6549424) (← links)
• Mathematical generation of data-driven hippocampal CA1 pyramidal neurons and interneurons copies via A-GLIF models for large-scale networks covering the experimental variability range (Q6566653) (← links)
• A computational neural model that incorporates both intrinsic dynamics and sensory feedback in the \textit{Aplysia} feeding network (Q6611532) (← links)