ArticlePLoS computational biology2014
Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Fractional-Order Spiking Bayesian Neural Model for Cognitive Computations.Neuroinformatics · 2026Article
- BioMem-FWK4α: A Fractional Windkessel-Constant Phase Framework for Analog Simulation and Frequency-Domain Interpretation of Biological Ion Channels.Biomedical engineering and computational biology · 2026Article
- Spike Timing-Dependent Plasticity and Random Inputs Shape Interspike Interval Regularity of Model STN Neurons.Biomedicines · 2025Article
- Imperfect chimera and synchronization in a hybrid adaptive conductance based exponential integrate and fire neuron model.Cognitive neurodynamics · 2024Article
- Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function.Scientific reports · 2024Article
- Dynamics and synchronization control of fractional conformable neuron system.Cognitive neurodynamics · 2024Article
- Diverse electrical responses in a network of fractional-order conductance-based excitable Morris-Lecar systems.Scientific reports · 2023Article
- A directionally selective collision-sensing visual neural network based on fractional-order differential operator.Frontiers in neurorobotics · 2023Article
- Memristive LIF Spiking Neuron Model and Its Application in Morse Code.Frontiers in neuroscience · 2022Article
- Dendritic Organic Electrochemical Transistors Grown by Electropolymerization for 3D Neuromorphic Engineering.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Article
- Possibility of information encoding/decoding using the memory effect in fractional-order capacitive devices.Scientific reports · 2021Article
- NEO: NEuro-Inspired Optimization-A Fractional Time Series Approach.Frontiers in physiology · 2021Article
- Fractional Lotka-Volterra-Type Cooperation Models: Impulsive Control on Their Stability Behavior.Entropy (Basel, Switzerland) · 2020Article
- Emergence of bursting in a network of memory dependent excitable and spiking leech-heart neurons.Journal of the Royal Society, Interface · 2020Article
- A New Spiking Convolutional Recurrent Neural Network (SCRNN) With Applications to Event-Based Hand Gesture Recognition.Frontiers in neuroscience · 2020Article
- Firing activities of a fractional-order FitzHugh-Rinzel bursting neuron model and its coupled dynamics.Scientific reports · 2019Article
- An integrate-and-fire model to generate spike trains with long-range dependence.Journal of computational neuroscience · 2018Article
- Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow.Neuroinformatics · 2017Article
- SK channel subtypes enable parallel optimized coding of behaviorally relevant stimulus attributes: A review.Channels (Austin, Tex.) · 2017Review
- Modulation of neuronal dynamic range using two different adaptation mechanisms.Neural regeneration research · 2017Article
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3 authors.
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Abstract
The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation.
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