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BMTool

Project description

bmtool

A comprehensive toolkit for developing computational neuroscience models with NEURON and BMTK

License: MIT Python 3.8+ PyPI version Documentation Code style: ruff

Documentation | Installation | Features | Contributing


Overview

BMTool is a collection of utilities designed to streamline the development, analysis, and execution of large-scale neural network models using NEURON and the Brain Modeling Toolkit (BMTK). Whether you're building single-cell models, developing synaptic mechanisms, or running parameter sweeps on HPC clusters, BMTool provides the tools you need.

Features

Single Cell Modeling

  • Analyze passive membrane properties
  • Current injection protocols and voltage responses
  • F-I curve generation and analysis
  • Impedance profile calculations

Synapse Development

  • Synaptic property tuning and validation
  • Gap junction modeling and analysis
  • Visualization of synaptic responses
  • Parameter optimization tools

Network Construction

  • Custom connectors for complex network models
  • Distance-dependent connection probabilities
  • Connection matrix visualization
  • Network statistics and validation

Visualization

  • Network position plotting (2D/3D)
  • Connection matrices and weight distributions
  • Raster plots and spike train analysis
  • LFP and ECP visualization
  • Power spectral density analysis

SLURM Cluster Management

  • YAML-based simulation configuration
  • Automated parameter sweeps (value-based and percentage-based)
  • Multi-environment support for different HPC devices
  • Job monitoring and status tracking
  • Microsoft Teams webhook notifications

Analysis Tools

  • Spike rate and population activity analysis
  • Phase locking and spike-phase timing
  • Oscillation detection with FOOOF
  • Power spectral analysis
  • Batch processing capabilities

Installation

Install the latest stable release from PyPI:

pip install bmtool

For development installation, see the Contributing Guide.

Documentation

Comprehensive documentation with examples and tutorials is available at:

https://cyneuro.github.io/bmtool/

Key Documentation Sections

Contributing

We welcome contributions from the community! To get started:

  1. Read the Contributing Guide for setup instructions
  2. Check out open issues or propose new features
  3. Follow our code style guidelines using Ruff and pre-commit hooks

See CONTRIBUTING.md for detailed information on development setup, code standards, and the pull request process.

Requirements

  • Python 3.8+
  • NEURON 8.2.4
  • BMTK
  • See setup.py for complete dependency list

License

BMTool is released under the MIT License.

Support

For questions, bug reports, or feature requests:

Acknowledgments

Developed by the Neural Engineering Laboratory at the University of Missouri.

Project details


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