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Updated: Jun 30, 2026
08:08
Real-time Electrophysiology: Using Closed-loop Protocols to Probe Neuronal Dynamics and Beyond
Published on: June 24, 2015
Spiking without Resets: Continuous Integrate-and-Fire Dynamics in Neuronal Circuits
Roberto Fenollosa1, Juan Bisquert1
1Instituto de Tecnología Química (ITQ), Consejo Superior de Investigaciones Científicas-Universitat Politècnica de València, 46022, València, Spain.
The Journal of Physical Chemistry Letters
|June 29, 2026
Summary
Spiking behavior in artificial neurons can emerge from a continuous dynamical system without explicit reset rules. This novel approach utilizes a memristor
Area of Science:
- Neuroscience
- Computational Neuroscience
- Artificial Intelligence
Background:
- The leaky integrate-and-fire (LIF) model is a standard for neuronal spiking dynamics.
- LIF models typically require explicit reset mechanisms or negative differential resistance.
- Alternative mechanisms for spike generation are actively sought.
Purpose of the Study:
- To investigate if spike-like behavior can arise in a continuous dynamical system.
- To explore a novel mechanism for spike generation without traditional reset rules.
- To analyze the role of nonlinear coupling in emergent spiking.
Main Methods:
- Studied a minimal resistive-capacitive circuit.
- Coupled the circuit to a conductance-activated quasi-linear memristor.
- Analyzed the system's dynamics using an internal state variable.
Main Results:
- Demonstrated that spiking emerges from nonlinear coupling between the state variable and its voltage-dependent equilibrium.
- Showed that spiking onset is not governed by static current-voltage characteristics.
- Found that the emergence of spiking is sensitive to excitation frequency, not sharp thresholds.
Conclusions:
- Spike-like dynamics can be generated within a fully continuous framework.
- Nonlinear coupling in memristive circuits offers a new paradigm for artificial neuron design.
- This approach bypasses the need for explicit reset mechanisms in neuronal modeling.
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