{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "# Overview\n",
    "\n",
    "Welcome to the world of `braincell`!\n",
    "\n",
    "This section provides a brief introduction to some of the key concepts and modeling features of the `braincell` framework.\n",
    "\n",
    "`braincell` is a high-performance computing framework specifically designed for neuron modeling, built on top of [JAX](https://github.com/jax-ml/jax) and [brainstate](https://brainstate.readthedocs.io/). It offers a comprehensive toolchain for neuroscientists, computational neuroscientists, and neuromorphic computing engineers to construct, simulate, and optimize electrophysiologically precise models ranging from ion channels to multi-scale neural networks. The framework integrates advanced features such as modern hardware acceleration and automatic differentiation. The following tutorials will walk you through its layered architecture and core functionalities, helping you quickly understand the design logic behind `braincell`."
   ],
   "id": "e571568bcb9e1b01"
  },
  {
   "metadata": {
    "ExecuteTime": {
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     "start_time": "2025-10-13T08:02:51.193841Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import brainunit as u\n",
    "import brainpy\n",
    "import braincell\n",
    "import brainstate\n",
    "import matplotlib.pyplot as plt"
   ],
   "id": "87d352fb92e4aeb6",
   "outputs": [],
   "execution_count": 19
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Hierarchical Architecture\n",
    "\n",
    "In neuron modeling, models are typically divided into the following major levels based on structural complexity and functional hierarchy:\n",
    "\n",
    "- `Channel`\n",
    "- `Ion`\n",
    "- `Cell`\n",
    "\n",
    "`braincell` focuses on precise neuronal dynamics modeling at these three levels.\n",
    "- `Channel`: Ion channels on the membrane, controlling the permeability of specific ions and determining the flow of ionic currents.\n",
    "- `Ion`: The fundamental charged particles, such as Na⁺, K⁺, and Ca²⁺, that drive changes in membrane potential.\n",
    "- `Cell`: The basic modeling unit of a single neuron, integrating multiple channels to produce membrane potential dynamics.\n",
    "\n",
    "Taking the Hodgkin–Huxley (HH) neuron as an example, the relationship among these three levels can be illustrated as follows:\n",
    "\n",
    "![Hierarchical Structure](../_static/structure-en.png)\n",
    "\n",
    "From this diagram, it is clear that `Channel`, `Ion`, and `Cell` are tightly interconnected. Biologically, these three levels form the fundamental mechanisms underlying neuronal electrical activity:\n",
    "- A neuron `Cell` is surrounded by a cell membrane populated with various ion `Channel`s.\n",
    "- Ion `Channel`s regulate the flow of different `Ion`s across the membrane.\n",
    "- The movement of `Ion`s changes the potential difference across the membrane, thereby driving neuronal electrical activity.\n",
    "\n",
    "Together, these levels provide a complete modeling pathway from microscopic mechanisms to macroscopic dynamics of neurons.\n",
    "\n",
    "## Core Features\n",
    "\n",
    "The main features of `braincell` include:\n",
    "- Ion channel modeling: Support for constructing electrophysiologically precise ion channel models using modular components.\n",
    "- Ion modeling: Support for modular construction of ion dynamics models.\n",
    "- Neuron modeling: Support for single-compartment and multi-compartment neuron models based on the HH framework.\n",
    "- Differential equation solvers: High-performance solvers built on [JAX](https://github.com/jax-ml/jax).\n",
    "\n",
    "In the following sections, we will explore how to use and optimize these features, helping you build models ranging from complete neurons down to fine-grained ion mechanisms, and fully leverage the modeling capabilities of `braincell`.\n",
    "\n",
    "## Single-Compartment Neuron Modeling\n",
    "\n",
    "We now turn to how `braincell` can be used to construct neuron models.\n",
    "\n",
    "Below is an example of building an HH neuron using `braincell`:"
   ],
   "id": "142813589187e43f"
  },
  {
   "metadata": {
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   },
   "cell_type": "code",
   "source": [
    "class HH(braincell.SingleCompartment):\n",
    "    def __init__(self, in_size):\n",
    "        super().__init__(in_size, C=Cm, solver='ind_exp_euler')\n",
    "\n",
    "        self.na = braincell.ion.SodiumFixed(in_size, E=50. * u.mV)\n",
    "        self.na.add(\n",
    "            INa=braincell.channel.INa_TM1991(in_size, g_max=(100. * u.mS * u.cm **-2) * area, V_sh=-63. * u.mV)\n",
    "        )\n",
    "\n",
    "        self.k = braincell.ion.PotassiumFixed(in_size, E=-90 * u.mV)\n",
    "        self.k.add(\n",
    "            IK=braincell.channel.IK_TM1991(in_size, g_max=(30. * u.mS * u.cm** -2) * area, V_sh=-63. * u.mV)\n",
    "        )\n",
    "\n",
    "        self.IL = braincell.channel.IL(\n",
    "            in_size,\n",
    "            E=-60. * u.mV,\n",
    "            g_max=(5. * u.nS * u.cm **-2) * area\n",
    "        )"
   ],
   "id": "53b36fddde644d3d",
   "outputs": [],
   "execution_count": 20
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "We construct the `HH` neuron model by inheriting from `SingleCompartment`, which represents a single-compartment neuron.\n",
    "`SingleCompartment` itself is the base class for all single-compartment neurons and is derived from `HHTypedNeuron`.\n",
    "Through `HHTypedNeuron`, both single-compartment neurons (`SingleCompartment`) and multi-compartment neurons (`MultiCompartment`) can be modeled.\n",
    "\n",
    "`SingleCompartment` provides built-in interfaces for membrane potential while supporting the integration of multiple `Channel`s.\n",
    "For example, `INa_TM1991`, `IK_TM1991`, and `IL` are concrete subclasses of the `Channel` class.\n",
    "Taking `INa_TM1991` as an example, it inherits from the sodium channel base class `SodiumChannel`, and thus provides the relevant interfaces.\n",
    "\n",
    "From this example, we can see that modeling a neuron with `braincell` requires only the composition of the relevant classes at the three levels: `Cell`, `Channel`, and `Ion`.\n",
    "The inheritance relationships within these three levels are deliberately kept simple in `braincell`.\n",
    "\n",
    "The neuron `Cell` regulates the flow of different `Ion`s, and each `Ion` is controlled by its corresponding `Channel`.\n",
    "In the `HH` neuron model above:\n",
    "- The neuron includes sodium ions (implemented as `SodiumFixed`) and potassium ions (implemented as `PotassiumFixed`).\n",
    "- Sodium ions determine the behavior of the sodium channel `INa_TM1991`.\n",
    "- Potassium ions determine the behavior of the potassium channel `IK_TM1991`.\n",
    "- In addition, `IL` represents a leakage channel, which is not associated with any ion.\n",
    "\n",
    "This design makes neuron model construction both flexible and modular, facilitating extension and modification.\n",
    "\n",
    "## Neural Network Modeling\n",
    "\n",
    "Building upon single-neuron modeling in `braincell`, we can further construct neural network models, seamlessly integrating with the network modeling capabilities of [BrainState](https://brainstate.readthedocs.io/).\n",
    "\n",
    "Returning to our example, we can use the constructed HH neuron model to build networks for practical applications, such as an excitatory–inhibitory (E–I) network:\n"
   ],
   "id": "43cae7b266df0eb2"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-13T08:02:52.067833Z",
     "start_time": "2025-10-13T08:02:52.059604Z"
    }
   },
   "cell_type": "code",
   "source": [
    "V_th = -20. * u.mV\n",
    "area = 20000 * u.um ** 2\n",
    "area = area.in_unit(u.cm ** 2)\n",
    "Cm = (1 * u.uF * u.cm ** -2) * area  # Membrane Capacitance [pF]\n",
    "\n",
    "class EINet(brainstate.nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.n_exc = 3200\n",
    "        self.n_inh = 800\n",
    "        self.num = self.n_exc + self.n_inh\n",
    "        self.N = HH(self.num)\n",
    "\n",
    "        self.E = brainpy.state.AlignPostProj(\n",
    "            comm=brainstate.nn.EventFixedProb(self.n_exc, self.num, conn_num=0.02, conn_weight=6. * u.nS),\n",
    "            syn=brainpy.state.Expon(self.num, tau=5. * u.ms),\n",
    "            out=brainpy.state.COBA(E=0. * u.mV),\n",
    "            post=self.N\n",
    "        )\n",
    "        self.I = brainpy.state.AlignPostProj(\n",
    "            comm=brainstate.nn.EventFixedProb(self.n_inh, self.num, conn_num=0.02, conn_weight=67. * u.nS),\n",
    "            syn=brainpy.state.Expon(self.num, tau=10. * u.ms),\n",
    "            out=brainpy.state.COBA(E=-80. * u.mV),\n",
    "            post=self.N\n",
    "        )\n",
    "\n",
    "    def update(self, t):\n",
    "        with brainstate.environ.context(t=t):\n",
    "            spk = self.N.spike.value\n",
    "            self.E(spk[:self.n_exc])\n",
    "            self.I(spk[self.n_exc:])\n",
    "            spk = self.N(0. * u.nA)\n",
    "            return spk"
   ],
   "id": "dfbc478f9a7c516f",
   "outputs": [],
   "execution_count": 21
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-13T08:02:52.517940Z",
     "start_time": "2025-10-13T08:02:52.495914Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# network\n",
    "net = EINet()\n",
    "_ = brainstate.nn.init_all_states(net)"
   ],
   "id": "d023c88e6c96bbaf",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Document\\PyCharm\\Project\\braincell(collaborator)\\.venv\\Lib\\site-packages\\braintools\\surrogate.py:72: UserWarning: Explicitly requested dtype float64 requested in asarray is not available, and will be truncated to dtype float32. To enable more dtypes, set the jax_enable_x64 configuration option or the JAX_ENABLE_X64 shell environment variable. See https://github.com/jax-ml/jax#current-gotchas for more.\n",
      "  z = jnp.asarray(x >= 0, dtype=x.dtype)\n"
     ]
    }
   ],
   "execution_count": 22
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-13T08:02:54.133738Z",
     "start_time": "2025-10-13T08:02:52.892772Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# simulation\n",
    "with brainstate.environ.context(dt=0.1 * u.ms):\n",
    "    times = u.math.arange(0. * u.ms, 100. * u.ms, brainstate.environ.get_dt())\n",
    "    spikes = brainstate.transform.for_loop(net.update, times, pbar=brainstate.transform.ProgressBar(10))"
   ],
   "id": "84ec536e1f3b4544",
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Running for 1,000 iterations: 100%|██████████| 1000/1000 [00:00<00:00, 9927.91it/s]\n"
     ]
    }
   ],
   "execution_count": 23
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-13T08:02:55.384922Z",
     "start_time": "2025-10-13T08:02:54.907230Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# visualization\n",
    "t_indices, n_indices = u.math.where(spikes)\n",
    "plt.scatter(times[t_indices], n_indices, s=1)\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Neuron index')\n",
    "plt.show()"
   ],
   "id": "ae366911755b05bc",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 24
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "In this way, we have used `braincell` to model the HH neuron and implemented a complete E–I network!",
   "id": "d9ab009f271530ea"
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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    "version": 2
   },
   "file_extension": ".py",
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