VF Population Model - Afferent Response Simulation

📌 Project Overview

The VF Population Model is a Python-based simulation framework designed to model the firing responses of afferents (SA & RA) to vibratory force (VF) stimuli. The model integrates spatial and radial stress distributions to compute afferent recruitment, firing patterns, and response dynamics.

This tool provides a structured approach to understanding afferent population coding, helping to analyze how mechanoreceptors respond to varying levels of tactile stress in the skin.

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🛠 Features

• Spatial Stress Modeling 🗺️

  • Simulates afferent activation based on stress data at different spatial coordinates.
  • Computes spike timing, mean firing frequency, and peak firing frequency.
  • Visualizes firing locations and intensity using spatial plots.

• Radial Stress Modeling 🎯

  • Examines afferent response at increasing radial distances from a stimulus center.
  • Extracts spike trains and calculates firing frequency based on stress propagation.
  • Analyzes how afferent response changes with distance from the stimulation site.

• Cumulative Firing & Recruitment Analysis 📊

  • Tracks how afferents are recruited over time.
  • Compares firing frequency across different VF tip sizes.
  • Generates cumulative firing and afferent recruitment plots.

• Sensitivity Analysis 🔍

  • Tests how different model parameters (e.g., τ-values, k-values, scaling factors) impact afferent firing.
  • Helps in optimizing and refining the model for realistic tactile response simulations.

• Visualization Tools 🎨

  • Generates heatmaps, scatter plots, radial plots, and grid-based representations of afferent activity.
  • Allows comparative analysis of different VF tip sizes and afferent types.

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📂 Project Structure

├── data/ # Contains stress data for different VF sizes and densities │ ├── P2/ # Processed stress data categorized by VF size and density │ ├── spatial/ # Spatial stress data │ ├── radial/ # Radial stress data │ ├── vf_popul_model.py # Main class for simulating afferent population responses ├── readme.md # Project documentation ├── requirements.txt # Dependencies required for running the model └── vf_graphs/ # Output directory for visualizations

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🚀 Getting Started

1️⃣ Installation

Clone this repository and install the required dependencies:

git clone https://github.com/your-repo/VF_Population_Model.git
cd VF_Population_Model
pip install -r requirements.txt
from vf_popul_model import VF_Population_Model

# Initialize the model with VF tip size, afferent type, and scaling factor
vf_model = VF_Population_Model(vf_tip_size=3.61, aff_type="SA", scaling_factor=1.0)

# Run radial stress model
vf_model.radial_stress_vf_model()

# Run spatial stress model
vf_results = vf_model.spatial_stress_vf_model()

# Visualize spatial afferent activity
vf_model.plot_spatial_coords()

# Perform cumulative afferent recruitment analysis
VF_Population_Model.cumulative_afferent_over_time("SA")