``brainpy.state`` documentation ===================================== `brainpy.state `_ provides spiking neural network models built on `JAX `_ and the `brainstate `_ state-management system. It is the point-neuron modeling layer of the `BrainX ecosystem `_. .. admonition:: API maturity :class: important ``brainpy.state`` ships two model families with different maturity levels: - **Stable** — Base classes (``Dynamics``, ``Neuron``, ``Synapse``) and **BrainPy-style models** (45+ neurons, synapses, projections, readouts, input generators). Public API is stable for the 0.0.x series and recommended for production use and surrogate-gradient training. - **Experimental — In Development** — **NEST-compatible models** (119+ neurons, synapses, plasticity, devices). These are under active development; parameter names, defaults, and numerical behavior may change without notice. Use them for exploration and validation, but pin your dependency version and expect breaking changes. See the :doc:`NEST-style status page ` for what is currently available and what users should not rely on yet. What's in the library ^^^^^^^^^^^^^^^^^^^^^ - **Base classes** — ``Dynamics``, ``Neuron``, ``Synapse``: the abstract foundation every model inherits from. - **BrainPy-style models** (Stable, 45+) — high-level, composable neurons (LIF, ALIF, AdEx, HH, Izhikevich, ...), synapses (Expon, Alpha, AMPA, GABA, NMDA), projections, readouts, input generators, and short-term plasticity, designed in the tradition of `BrainPy `_. - **NEST-compatible models** (Experimental, 119+) — JAX re-implementations of `NEST simulator `_ neuron, synapse, plasticity (STDP, STP), and device models with NEST-compatible parameter names. - All parameters carry **physical units** via `saiunit `_; BrainPy-style neurons support surrogate-gradient training out of the box. Installation ^^^^^^^^^^^^ .. tab-set:: .. tab-item:: CPU .. code-block:: bash pip install -U brainpy.state[cpu] .. tab-item:: GPU .. code-block:: bash pip install -U brainpy.state[cuda12] pip install -U brainpy.state[cuda13] .. tab-item:: TPU .. code-block:: bash pip install -U brainpy.state[tpu] .. tab-item:: Ecosystem .. code-block:: bash pip install -U BrainX Quick Example ^^^^^^^^^^^^^ A small excitatory–inhibitory balanced network using the Stable BrainPy-style API. See the :doc:`5-minute tutorial ` for the full walkthrough. .. code-block:: python import brainpy.state import brainstate import braintools import saiunit as u class EINet(brainstate.nn.Module): def __init__(self): super().__init__() self.n_exc, self.n_inh = 3200, 800 self.num = self.n_exc + self.n_inh self.N = brainpy.state.LIFRef( self.num, V_rest=-60. * u.mV, V_th=-50. * u.mV, V_reset=-60. * u.mV, tau=20. * u.ms, tau_ref=5. * u.ms, V_initializer=braintools.init.Normal(-55., 2., unit=u.mV), ) self.E = brainpy.state.AlignPostProj( comm=brainstate.nn.EventFixedProb(self.n_exc, self.num, conn_num=0.02, conn_weight=0.6 * u.mS), syn=brainpy.state.Expon.desc(self.num, tau=5. * u.ms), out=brainpy.state.COBA.desc(E=0. * u.mV), post=self.N, ) self.I = brainpy.state.AlignPostProj( comm=brainstate.nn.EventFixedProb(self.n_inh, self.num, conn_num=0.02, conn_weight=6.7 * u.mS), syn=brainpy.state.Expon.desc(self.num, tau=10. * u.ms), out=brainpy.state.COBA.desc(E=-80. * u.mV), post=self.N, ) def update(self, t, inp): with brainstate.environ.context(t=t): spk = self.N.get_spike() != 0. self.E(spk[:self.n_exc]) self.I(spk[self.n_exc:]) self.N(inp) return self.N.get_spike() ---- Learn more ^^^^^^^^^^ .. grid:: .. grid-item:: :columns: 6 6 6 4 .. card:: :material-regular:`rocket_launch;2em` 5-Minute Tutorial :class-card: sd-text-black sd-bg-light :link: quickstart/5min-tutorial.html .. grid-item:: :columns: 6 6 6 4 .. card:: :material-regular:`library_books;2em` BrainPy-style Guide :class-card: sd-text-black sd-bg-light :link: brainpy-guide/index.html .. grid-item:: :columns: 6 6 6 4 .. card:: :material-regular:`explore;2em` Examples Gallery :class-card: sd-text-black sd-bg-light :link: examples/gallery.html .. grid-item:: :columns: 6 6 6 4 .. card:: :material-regular:`data_exploration;2em` API Reference :class-card: sd-text-black sd-bg-light :link: api/index.html .. grid-item:: :columns: 6 6 6 4 .. card:: :material-regular:`science;2em` NEST-style Status :class-card: sd-text-black sd-bg-light :link: nest-status/index.html .. grid-item:: :columns: 6 6 6 4 .. card:: :material-regular:`settings;2em` BrainX Ecosystem :class-card: sd-text-black sd-bg-light :link: https://brainmodeling.readthedocs.io ---- See also the ecosystem ^^^^^^^^^^^^^^^^^^^^^^ ``brainpy.state`` is one part of the `BrainX ecosystem `__: - `brainstate `_ — state management for JAX-based brain modeling - `saiunit `_ — physical units for neuroscience - `brainevent `_ — event-driven sparse operators - `braintools `_ — surrogate gradients, analysis, and utilities .. toctree:: :hidden: :maxdepth: 1 :caption: Tutorials quickstart/index.rst brainpy-guide/index.rst examples/gallery.rst .. toctree:: :hidden: :maxdepth: 2 :caption: API Reference (Stable) api/base api/brainpy-neurons api/brainpy-synapses api/brainpy-projections api/brainpy-synouts api/brainpy-plasticity api/brainpy-readouts api/brainpy-inputs .. toctree:: :hidden: :maxdepth: 2 :caption: Experimental (NEST-Compatible) nest-status/index api/nest-base api/nest-neurons api/nest-synapses api/nest-plasticity api/nest-devices .. toctree:: :hidden: :maxdepth: 1 :caption: Project changelog.md