Membrane - Overdrive77/BioSynapStudio-Public GitHub Wiki

Membrane Class

Abstract base class that simulates the dynamic electrophysiological properties of a biological membrane using ion channels, potentials, and capacitance.

Namespace

BioSynapStudio.Net.Core

Assembly

BioSynapStudio.Net.Core.dll

Summary

The Membrane class models a biologically inspired neural membrane capable of integrating ionic currents, maintaining capacitance, and updating its potential state. It supports simulation of action potentials through customizable thresholds and ionic dynamics.

Inheritance

Identity  
  ↳ Membrane

Constructors

Membrane()

Initializes the membrane with an empty list of ion channels and default simulation parameters.

Public Properties

Name Type Description
IonChannels List<IonChannel> Collection of all ion channels associated with the membrane.
Potential PotentialType Current state of the membrane (e.g., Resting, Graded, Action, Reset).
Capacitance double Membrane capacitance in microfarads (µF). (Persisted with [HippocampalMemory])
DeltaT double Simulation timestep in milliseconds.
ResetPotential short Membrane voltage after spike (e.g., -90 mV). (Persisted)
RestingPotential short Membrane voltage at rest (e.g., -70 mV). (Persisted)
ThresholdPotential short Voltage threshold for triggering spikes. (Persisted)
ActionPotential short Peak voltage during an action potential.
MembranePotential double Current voltage across the membrane.
CurrentTick double Current simulation time in ticks.

Public Methods

void Add(IonChannel channel)

Adds an ion channel to the membrane.

membrane.Add(new SodiumChannel());

void Remove(IonChannel channel)

Removes an ion channel from the membrane.

membrane.Remove(kChannel);

virtual void Tick()

Performs a simulation step, calculating the net ionic current and updating membrane voltage accordingly.

membrane.Tick();

Remarks

This class provides core simulation functionality for realistic neuron modeling. It integrates channel behavior, biophysical properties, and membrane dynamics. Internal potential updates and voltage clamping ensure biologically meaningful results.

See Also

Legal Notice This software constitutes original intellectual property of the author, protected under international copyright and patent law. Patent: GB2506327.2 – Synthesized Emotional Cognition (SEC) DOI: 10.17605/OSF.IO/XERKF

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