Version 2.7.1

This is a feature release that introduces new neuron and synapse models in the state-based API (brainpy.state) and enhances the Dynamics base class with improved input handling.

Major Changes

New Neuron Models (brainpy.state)

• LIF (Leaky Integrate-and-Fire) Variants: Added comprehensive set of LIF neuron models

  • LIF: Basic LIF neuron with exponential synaptic input
  • LifRef: LIF with refractory period
  • ExpIF: Exponential Integrate-and-Fire neuron
  • ExpIFRef: ExpIF with refractory period
  • AdExIF: Adaptive Exponential Integrate-and-Fire neuron
  • AdExIFRef: AdExIF with refractory period
  • QuaIF: Quadratic Integrate-and-Fire neuron
  • QuaIFRef: QuaIF with refractory period
  • AdQuaIF: Adaptive Quadratic Integrate-and-Fire neuron
  • AdQuaIFRef: AdQuaIF with refractory period
  • GifRef: Generalized Integrate-and-Fire with refractory period

• Izhikevich Neuron Models: Added new Izhikevich neuron implementations

  • Izhikevich: Basic Izhikevich neuron model
  • IzhikevichRef: Izhikevich with refractory period

• Hodgkin-Huxley Model: Added classic biophysical neuron model

  • HH: Classic Hodgkin-Huxley model with Na+ and K+ channels

New Synapse Models (brainpy.state)

• BioNMDA: Biological NMDA receptor with second-order kinetics
  • Implements two-state cascade dynamics (x and g variables)
  • Slower rise time compared to AMPA (biologically realistic)
  • Comprehensive documentation with mathematical formulation

Features

Model Implementation

• All new models use the brainstate ecosystem (HiddenState, ShortTermState, LongTermState)
• Proper unit support with brainunit integration
• Exponential Euler integration for numerical stability
• Batch processing support across all models
• Consistent API design following BrainPy v2.7+ architecture

Dynamics Class Enhancements

• Enhanced input handling capabilities in the Dynamics base class
• Added new properties for better state management
• Improved integration with brainstate framework
• Refactored to use public methods instead of private counterparts for clarity

Documentation

• Added comprehensive Examples sections to all neuron classes in _lif.py
• Each example includes:
  • Import statements for required modules
  • Basic usage with parameter specifications
  • State initialization examples
  • Update and spike generation examples
  • Network integration with brainstate.nn.Sequential
  • Notes highlighting key features
• All 13 neuron classes in _lif.py now have complete documentation
• Simplified documentation paths by removing 'core-concepts' and 'quickstart' prefixes in index.rst

Bug Fixes

• Fixed import paths in _base.py: changed references from brainstate to brainpy for consistency (057b872)
• Fixed test suite issues (95ec203)
• Fixed test suite for proper unit handling in synapse models

Code Quality

• Refactored module assignments to brainpy.state for consistency across files (06b2bf4)
• Refactored method calls in _base.py: replaced private methods with public counterparts (210426a)

Testing

• Added comprehensive test suites for all new neuron models
• Added AMPA and GABAa synapse tests
• Added tests for Izhikevich neuron variants
• Added tests for Hodgkin-Huxley model
• All tests passing with proper unit handling

Files Modified

• brainpy/__init__.py: Updated version to 2.7.1
• brainpy/state/_base.py: Enhanced Dynamics class with improved input handling (447 lines added)
• brainpy/state/_lif.py: Added extensive LIF neuron variants (1862 lines total)
• brainpy/state/_izhikevich.py: New file with Izhikevich models (407 lines)
• brainpy/state/_hh.py: New file with Hodgkin-Huxley model (666 lines)
• brainpy/state/_synapse.py: Added BioNMDA model (158 lines)
• brainpy/state/_projection.py: Updated for consistency (43 lines modified)
• brainpy/state/__init__.py: Updated exports for new models
• Test files added: _lif_test.py, _izhikevich_test.py, _hh_test.py, _synapse_test.py, _base_test.py
• Documentation updates in docs_state/index.rst

Removed

• Removed outdated documentation notebooks from docs_state/:
  • checkpointing-en.ipynb and checkpointing-zh.ipynb
  • snn_simulation-en.ipynb and snn_simulation-zh.ipynb
  • snn_training-en.ipynb and snn_training-zh.ipynb

Notes

• This release significantly expands the brainpy.state module with biologically realistic neuron and synapse models
• All new models are fully compatible with the brainstate ecosystem
• Enhanced documentation provides clear usage examples for all models
• The Dynamics class refactoring improves the foundation for future state-based model development

What's Changed

• Update version to 2.7.1 and refactor Dynamics class: enhance input ha… by @chaoming0625 in #793
• update state neuron and synapse by @932179209 in #794

New Contributors

• @932179209 made their first contribution in #794

Full Changelog: V2.7.0...V2.7.1