NeunCgcForRtxi

NeunCgcForRtxi is a real-time neuron model module for RTXI, based on a Q10 temperature-sensitive conductance-based model of a central ganglion cell (CGC). It uses the Neun neuron simulation library for defining and simulating intrinsic ionic conductances.

---

Features

• Real-time CGC neuron simulation with biologically realistic currents.
• Q10-based temperature scaling of conductances.
• GUI-based interaction for all key model parameters.
• Control buttons for resetting and printing parameters.
• Integration with RTXI for real-time experiments.

---

Requirements

• RTXI
• Qt5 (for GUI widgets)
• Neun library

---

Neun Dependency

This module depends on the Neun library. Clone and build it before compiling this module

Ensure the Neun headers and libraries are accessible when compiling.

---

Build Instructions

Option 1: Manual Compile

g++ -std=c++11 -fPIC \
    -I/path/to/Neun/include \
    -I$RTXI_INCLUDE -I$QT_INCLUDE \
    -L/path/to/Neun/lib -lneun \
    -shared -o neun_cgc_for_rtxi.so neun_cgc_for_rtxi.cpp

Replace /path/to/Neun, $RTXI_INCLUDE, and $QT_INCLUDE with appropriate paths.

---

Using in RTXI

1. Launch RTXI.

2. Load neun_cgc_for_rtxi.so through RTXI’s module loader.

3. The GUI lets you adjust:

   • Temperature (°C)
   • External current (I_ext)
   • Maximal conductances (e.g. gna, gnaP, gK, gh)
   • Q10 parameters
   • Initial conditions
   • Activation variables in channels

4. Use the GUI buttons:

   • Reset initial: Reinitialize state variables and parameters.
   • Print Parameters: Dump current parameter set to console.

5. Outputs include:

   • Membrane voltage
   • Ionic currents (Ia, Id, Ihva, Ilva, Inap, Inat)
   • Synaptic input current

---

Notes

• Parameter saving/loading from YAML is stubbed (currently inactive).
• Model equations and gating are implemented via Neun's ConductanceBasedNeuron.
• Initial gating values are calculated via Boltzmann functions.

---

📄 License

MIT License. For full model framework and licensing, see the Neun GitHub repository.

---

🙏 Acknowledgments

• RTXI: Real-Time eXperiment Interface
• Neun: Neuron Modeling Framework