Version 2.7.7

Release Date: March 12, 2026

This release migrates to the new brainevent binary backend API, fixes numerous bugs across neuron models, synapse dynamics, ODE integrators, and object transforms, and raises the minimum Python version to 3.11.

Breaking Changes

Python Version Requirement

• Raised: Minimum Python version from 3.10 to 3.11
  • Dropped Python 3.10 support from classifiers and build metadata

brainevent API Migration (#817)

• Updated: Event-driven operations to use the new brainevent binary backend
  • EventArray replaced by BinaryArray in all event CSR and jitconn operations
  • JITCHomoR replaced by JITCScalarR for homogeneous JIT connectivity
  • STDP weight update functions renamed:
    • dense_on_pre / dense_on_post → update_dense_on_binary_pre / update_dense_on_binary_post
    • csr_on_pre / csr2csc_on_post → update_csr_on_binary_pre / update_csr_on_binary_post
  • Affected layers: Dense, AllToAll, MaskedLinear, and all CSR-based layers

Bug Fixes

Neuron Models

• Fixed: All LIF-family neuron models (LifLTC, LifRefLTC, ExpIFLTC, ExpIFRefLTC, AdExIFLTC, AdExIFRefLTC, QuaIFLTC, QuaIFRefLTC, AdQuaIFLTC, AdQuaIFRefLTC, GifLTC, GifRefLTC) now raise descriptive ValueError messages for invalid spk_reset modes instead of bare ValueError

Synapse Models

• Fixed: Synaptic variable updates in DualExpon, Alpha, and NMDA models
  • Replaced in-place += operator with explicit .value assignment to prevent tracing issues under JAX transformations

ODE Integrators

• Fixed: BogackiShampine adaptive Runge-Kutta coefficient typo — corrected '4/0' to '4/9' in the Butcher tableau
• Fixed: set_default_odeint was incorrectly assigning to _DEFAULT_ODE_METHOD instead of _DEFAULT_DDE_METHOD

Object Transforms

• Fixed: Variable.varshape used self.batch_size instead of self.batch_axis when computing non-batch shape dimensions
• Fixed: NodeDict.update() and VarDict.update() referenced args[1] instead of arg[1] when updating from tuple arguments
• Fixed: NodeDict.__setitem__ duplicate key error message incorrectly displayed the new value instead of the existing one

Training

• Fixed: BPTrainer did not raise NoLongerSupportError when seed parameter was passed (missing raise keyword)
• Fixed: BPTrainer metric aggregation switched from jnp.mean(bm.as_jax(...)) to np.mean(np.asarray(...)) to avoid unnecessary JAX tracing overhead

Core

• Fixed: ShardedArray.value setter used _check_tracer() instead of direct _value access
• Fixed: _slice_to_num did not handle negative step values and raised no error on zero step
• Fixed: load_state crashed with KeyError when state dict contained missing keys; now correctly reports them as missing

Code Quality

• Improved: Narrowed bare except clauses to specific exception types (ValueError, TypeError, ImportError, ModuleNotFoundError) in convolution layers and Flax interoperation module

Dependencies

• Updated: brainevent from >=0.0.4 to >=0.0.7
• Updated: braintools version spec corrected to >=0.0.9
• Updated: numpy minimum version set to >=1.15
• Updated: brainpy_state from >=0.0.2 to >=0.0.3

CI/CD

• Updated: actions/upload-artifact from v6 to v7 (#815)
• Updated: actions/download-artifact from v7 to v8 (#816)

What's Changed

• chore(ci)(deps): bump actions/upload-artifact from 6 to 7 by @dependabot[bot] in #815
• chore(ci)(deps): bump actions/download-artifact from 7 to 8 by @dependabot[bot] in #816
• Refactor STDP and event ops for new brainevent binary backend by @chaoming0625 in #817

Full Changelog: V2.7.6...V2.7.7