Conductance-Based Neuron Models and the Slow Dynamics of Excitability
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Summary
A general scheme is proposed, that closely describes the response of deterministic conductance-based neuron models under pulse stimulation, using a discrete time piecewise linear mapping, which is amenable to detailed mathematical analysis.
- Type
- article
- Published
- 2012-02-16
- Cited by
- 18
- References
- 96
- Access
- Open access
- OpenAlex
- https://openalex.org/W2020596453
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9265332
Keywords
Dynamics (music), Biological neuron model, Neuroscience, Conductance, Neuron
References
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Cited by
- Experimentally verified reduced models of neocortical pyramidal cells
- The neuronal response at extended timescales: long-term correlations without long-term memory
- A computational paradigm for dynamic logic-gates in neuronal activity
- Self-organized criticality in single-neuron excitability.
- The neuronal response at extended timescales: a linearized spiking input–output relation
- Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model
- Multiple modes of electrical activities in a new neuron model under electromagnetic radiation
- Dynamical Timescale Explains Marginal Stability in Excitability Dynamics
- Feedback Identification of conductance-based models
- Virtual reality validation of naturalistic modulation strategies to counteract fading in retinal stimulation
- Dynamics and synchronization control of fractional conformable neuron system
- Compact seizure detection based on spiking neural network and support vector machine for efficient neuromorphic implementation
- NMDA receptor kinetics drive distinct routes to chaotic firing in pyramidal neurons
- Single‐Neuron Critical Intermittency in a Stochastic Hodgkin–Huxley Model
- MODELING SUBFORNICAL ORGAN NEURONS
- Single Neuron Response Fluctuations: A Self‐Organized Criticality Point of View
- Dynamics, variability and adaptation of single neuron response over extended timescales
- Failure of Averaging
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