{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dynamics and Integration\n",
    "\n",
    "Brain models are dynamical systems: state variables that evolve over time according to update\n",
    "rules. This tutorial introduces how BrainState represents such dynamics \u2014 the update mechanism,\n",
    "input/output sizing, and delay support \u2014 and how a model integrates its state step by step. It is\n",
    "the entry point to the brain-dynamics track; later notebooks build synapses, event-driven\n",
    "operators, and full spiking networks on top of it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2fb1495702e12179",
   "metadata": {
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    },
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   "outputs": [],
   "source": [
    "import brainunit as u\n",
    "import jax.numpy as jnp\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import brainstate\n",
    "\n",
    "# Set simulation time step\n",
    "brainstate.environ.set(dt=0.1 * u.ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e6a846f6127af4c",
   "metadata": {},
   "source": [
    "## Part 1: What is Dynamics?\n",
    "\n",
    "### Core Concept\n",
    "\n",
    "`Dynamics` is a module that defines how **state variables evolve over time** in neural or other dynamical systems. All Dynamics models follow the **element-wise computation principle**: state updates only affect local variables and do not include cross-unit interactions.\n",
    "\n",
    "### Element-Wise Principle\n",
    "\n",
    "Consider the **Leaky Integrate-and-Fire (LIF)** neuron model:\n",
    "\n",
    "$$\n",
    "\\tau \\frac{dV}{dt} = -(V - V_{rest}) + R I\n",
    "$$\n",
    "\n",
    "Each neuron's voltage $V$ evolves **independently** based only on its own state and input current $I$. This is element-wise dynamics.\n",
    "\n",
    "### What Dynamics is NOT\n",
    "\n",
    "Dynamics does **NOT** include:\n",
    "- Synaptic connections between neurons\n",
    "- Network connectivity\n",
    "- Inter-neuron interactions\n",
    "\n",
    "These are handled by separate modules like `Linear`, `Sparse`, or `Convolution` connection operators.\n",
    "\n",
    "### Architecture Overview\n",
    "\n",
    "```\n",
    "Input (External Drive)\n",
    "    \u2193\n",
    "[Connection Modules]  \u2190 (Linear, Conv, Sparse)\n",
    "    \u2193\n",
    "[Dynamics Modules]    \u2190 (LIF, HH, Izhikevich)\n",
    "    \u2193\n",
    "Output (Spikes/Voltages)\n",
    "```\n",
    "\n",
    "See [BrainScale documentation](https://brainscale.readthedocs.io) for visual reference.\n",
    "\n",
    "![](https://brainscale.readthedocs.io/_images/model-dynamics-supported.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce89f37e1374b0a4",
   "metadata": {},
   "source": [
    "### Example: Simple Exponential Decay\n",
    "\n",
    "Let's implement a simple dynamics model that demonstrates the element-wise principle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dbf2b2094c7a8b5f",
   "metadata": {
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    "execution": {
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     "shell.execute_reply": "2026-05-30T16:44:09.775619Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dynamics module: ExponentialDecay(\n",
      "  in_size=(5,),\n",
      "  out_size=(5,),\n",
      "  v=State(\n",
      "    value=ShapedArray(float32[5])\n",
      "  ),\n",
      "  tau=Quantity(5., \"ms\")\n",
      ")\n",
      "Input size:  (5,)\n",
      "Output size: (5,)\n",
      "Variable shape (varshape): (5,)\n",
      "\n",
      "Initial state: [0. 0. 0. 0. 0.]\n",
      "\n",
      "After one step with input [ 1.   0.5  0.  -0.5 -1. ]:\n",
      "Output: [ 1.   0.5  0.  -0.5 -1. ]\n"
     ]
    }
   ],
   "source": [
    "class ExponentialDecay(brainstate.nn.Dynamics):\n",
    "    \"\"\"Simple exponential decay dynamics: \u03c4 dv/dt = -v\"\"\"\n",
    "\n",
    "    def __init__(self, size, tau=10.0 * u.ms):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # State variable\n",
    "        self.v = brainstate.State(jnp.zeros(size))\n",
    "\n",
    "        # Parameter (constant, not a State)\n",
    "        self.tau = tau\n",
    "\n",
    "    def update(self, inp):\n",
    "        \"\"\"Element-wise update: each element evolves independently\"\"\"\n",
    "        # Exponential Euler integration\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "\n",
    "        # Update state (element-wise operation)\n",
    "        self.v.value = self.v.value * alpha + inp\n",
    "\n",
    "        # Return current state\n",
    "        return self.v.value\n",
    "\n",
    "\n",
    "# Create dynamics module with 5 independent elements\n",
    "dynamics = ExponentialDecay(size=(5,), tau=5.0 * u.ms)\n",
    "\n",
    "print(f\"Dynamics module: {dynamics}\")\n",
    "print(f\"Input size:  {dynamics.in_size}\")\n",
    "print(f\"Output size: {dynamics.out_size}\")\n",
    "print(f\"Variable shape (varshape): {dynamics.varshape}\")\n",
    "print(f\"\\nInitial state: {dynamics.v.value}\")\n",
    "\n",
    "# Apply input to all 5 elements\n",
    "inp = jnp.array([1.0, 0.5, 0.0, -0.5, -1.0])\n",
    "output = dynamics(inp)\n",
    "print(f\"\\nAfter one step with input {inp}:\")\n",
    "print(f\"Output: {output}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50688b07f04b9e4e",
   "metadata": {},
   "source": [
    "### Visualizing Element-Wise Dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dc73792114f18aa2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:58.861687Z",
     "start_time": "2025-10-11T09:48:58.539647Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:09.778948Z",
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     "shell.execute_reply": "2026-05-30T16:44:10.098879Z"
    }
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u2705 Each element decays independently (element-wise dynamics)\n",
      "\u2705 No interaction between elements (pure dynamics, no connectivity)\n"
     ]
    }
   ],
   "source": [
    "# Reset dynamics\n",
    "dynamics.v.value = jnp.zeros(5)\n",
    "\n",
    "# Simulate with step input\n",
    "n_steps = 100\n",
    "history = []\n",
    "\n",
    "for i in range(n_steps):\n",
    "    # Step input at t=20ms\n",
    "    if i == 20:\n",
    "        inp = jnp.array([1.0, 0.8, 0.6, 0.4, 0.2])\n",
    "    else:\n",
    "        inp = jnp.zeros(5)\n",
    "\n",
    "    output = dynamics(inp)\n",
    "    history.append(output)\n",
    "\n",
    "history = jnp.array(history)\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Plot\n",
    "plt.figure(figsize=(12, 6))\n",
    "for i in range(5):\n",
    "    plt.plot(times.to_decimal(u.ms), history[:, i], label=f'Element {i}')\n",
    "\n",
    "plt.axvline(20 * 0.1, color='red', linestyle='--', alpha=0.5, label='Input applied')\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('State value')\n",
    "plt.title('Element-Wise Exponential Decay Dynamics')\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()\n",
    "\n",
    "print(\"\u2705 Each element decays independently (element-wise dynamics)\")\n",
    "print(\"\u2705 No interaction between elements (pure dynamics, no connectivity)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ed3564a7e53d03f",
   "metadata": {},
   "source": [
    "## Part 2: Basic Dynamics Structure\n",
    "\n",
    "### The Core: `update()` Function\n",
    "\n",
    "Every Dynamics module must implement the `update()` method, which defines how state variables evolve in time:\n",
    "\n",
    "```python\n",
    "class MyDynamics(brainstate.nn.Dynamics):\n",
    "    def __init__(self, in_size):\n",
    "        super().__init__(in_size=in_size)\n",
    "        # Define state variables with brainstate.State\n",
    "        self.state_var = brainstate.State(initial_value)\n",
    "        # Define parameters as regular Python variables (constants)\n",
    "        self.param = value\n",
    "    \n",
    "    def update(self, inp):\n",
    "        # 1. Compute state evolution\n",
    "        # 2. Update internal states\n",
    "        # 3. Return output\n",
    "        return output\n",
    "```\n",
    "\n",
    "### Key Points\n",
    "\n",
    "- **Input**: External drive (current, synaptic input, etc.)\n",
    "- **Output**: Observable quantity (voltage, firing rate, spikes, etc.)\n",
    "- **States**: Dynamic variables that change over time (`brainstate.State`)\n",
    "- **Parameters**: Constants that don't change during simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea0b243d62489fdd",
   "metadata": {},
   "source": [
    "### Example: Leaky Integrate-and-Fire Neuron"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5f4d9d5f3445900",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:58.978533Z",
     "start_time": "2025-10-11T09:48:58.873919Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:10.101387Z",
     "iopub.status.busy": "2026-05-30T16:44:10.101137Z",
     "iopub.status.idle": "2026-05-30T16:44:10.240107Z",
     "shell.execute_reply": "2026-05-30T16:44:10.239473Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LIF Neuron Population:\n",
      "  Size: (3,)\n",
      "  Initial V: [-65. -65. -65.] mV\n",
      "  Threshold: -50. mV\n",
      "  Time constant: 10. ms\n"
     ]
    }
   ],
   "source": [
    "class SimpleLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"Leaky Integrate-and-Fire neuron dynamics.\n",
    "    \n",
    "    Equation: \u03c4 dV/dt = -(V - V_rest) + R*I\n",
    "    Spike when V >= V_th, then reset to V_reset\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, size, tau=10.0 * u.ms, V_rest=-65.0 * u.mV,\n",
    "                 V_th=-50.0 * u.mV, V_reset=-65.0 * u.mV, R=1.0 * u.ohm):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # State variables (dynamic)\n",
    "        self.V = brainstate.State(jnp.ones(size) * V_rest)\n",
    "        self.spike = brainstate.State(jnp.zeros(size, dtype=bool))\n",
    "\n",
    "        # Parameters (constants)\n",
    "        self.tau = tau\n",
    "        self.V_rest = V_rest\n",
    "        self.V_th = V_th\n",
    "        self.V_reset = V_reset\n",
    "        self.R = R\n",
    "\n",
    "    def update(self, I):\n",
    "        \"\"\"Update membrane potential and detect spikes.\n",
    "        \n",
    "        Args:\n",
    "            I: Input current\n",
    "            \n",
    "        Returns:\n",
    "            Spike events (boolean array)\n",
    "        \"\"\"\n",
    "        # Exponential Euler integration for V\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "\n",
    "        # Update voltage\n",
    "        V_inf = self.V_rest + self.R * I  # Steady state\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "\n",
    "        # Spike detection\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "\n",
    "        # Reset voltage for spiking neurons\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "\n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "# Create a population of 3 LIF neurons\n",
    "lif = SimpleLIF(size=(3,))\n",
    "\n",
    "print(\"LIF Neuron Population:\")\n",
    "print(f\"  Size: {lif.in_size}\")\n",
    "print(f\"  Initial V: {lif.V.value}\")\n",
    "print(f\"  Threshold: {lif.V_th}\")\n",
    "print(f\"  Time constant: {lif.tau}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed43aebeadf0eab6",
   "metadata": {},
   "source": [
    "### Simulating the LIF Dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f1bc101789484373",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:59.888973Z",
     "start_time": "2025-10-11T09:48:58.987600Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:10.242930Z",
     "iopub.status.busy": "2026-05-30T16:44:10.242665Z",
     "iopub.status.idle": "2026-05-30T16:44:11.185100Z",
     "shell.execute_reply": "2026-05-30T16:44:11.184281Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Neuron 0: 7 spikes, rate = 70.00 Hz * kHz\n",
      "Neuron 1: 14 spikes, rate = 140.00 Hz * kHz\n",
      "Neuron 2: 20 spikes, rate = 200.00 Hz * kHz\n",
      "\n",
      "\u2705 Each neuron evolves independently (element-wise)\n",
      "\u2705 Different inputs lead to different firing rates\n"
     ]
    }
   ],
   "source": [
    "# Reset neuron states\n",
    "lif.V.value = jnp.ones(3) * lif.V_rest\n",
    "lif.spike.value = jnp.zeros(3, dtype=bool)\n",
    "\n",
    "# Simulation parameters\n",
    "duration = 100 * u.ms\n",
    "n_steps = int(duration / brainstate.environ.get_dt())\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Different input currents for each neuron\n",
    "I_inputs = jnp.array([20.0, 30.0, 40.0]) * u.mA\n",
    "\n",
    "\n",
    "def step_run(t):\n",
    "    with brainstate.environ.context(t=t):\n",
    "        spikes = lif(I_inputs)\n",
    "        return lif.V.value, spikes\n",
    "\n",
    "\n",
    "# Run simulation\n",
    "V_history, spike_history = brainstate.transform.for_loop(step_run, times)\n",
    "\n",
    "# Visualization\n",
    "fig, axes = plt.subplots(2, 1, figsize=(14, 8), sharex=True)\n",
    "\n",
    "# Membrane potentials\n",
    "for i in range(3):\n",
    "    axes[0].plot(times.to_decimal(u.ms), V_history[:, i].to_decimal(u.mV),\n",
    "                 label=f'Neuron {i} (I={I_inputs[i]})', linewidth=1.5)\n",
    "\n",
    "axes[0].axhline(lif.V_th.to_decimal(u.mV), color='red', linestyle='--',\n",
    "                alpha=0.5, label='Threshold')\n",
    "axes[0].set_ylabel('Membrane Potential (mV)')\n",
    "axes[0].set_title('LIF Dynamics: Element-Wise Computation', fontweight='bold')\n",
    "axes[0].legend()\n",
    "axes[0].grid(alpha=0.3)\n",
    "\n",
    "# Spike rasters\n",
    "for i in range(3):\n",
    "    spike_times = times[spike_history[:, i]]\n",
    "    if len(spike_times) > 0:\n",
    "        axes[1].eventplot([spike_times.to_decimal(u.ms)], lineoffsets=[i],\n",
    "                          colors=[f'C{i}'], linewidths=2)\n",
    "\n",
    "axes[1].set_ylabel('Neuron Index')\n",
    "axes[1].set_xlabel('Time (ms)')\n",
    "axes[1].set_yticks(range(3))\n",
    "axes[1].set_ylim([-0.5, 2.5])\n",
    "axes[1].grid(alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Statistics\n",
    "for i in range(3):\n",
    "    n_spikes = jnp.sum(spike_history[:, i])\n",
    "    rate = n_spikes / duration * 1000 * u.Hz\n",
    "    print(f\"Neuron {i}: {n_spikes} spikes, rate = {rate:.2f}\")\n",
    "\n",
    "print(\"\\n\u2705 Each neuron evolves independently (element-wise)\")\n",
    "print(\"\u2705 Different inputs lead to different firing rates\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d233fec548fc9eea",
   "metadata": {},
   "source": [
    "## Part 3: Before/After Update Mechanism\n",
    "\n",
    "Dynamics supports flexible control flow through **before-update** and **after-update** hooks. These allow you to insert custom logic at specific points in the update cycle.\n",
    "\n",
    "### Basic Usage\n",
    "\n",
    "```python\n",
    "# Add functions to execute before/after update\n",
    "dynamics.add_before_update(key, function)\n",
    "dynamics.add_after_update(key, function)\n",
    "```\n",
    "\n",
    "### Default Behavior\n",
    "\n",
    "- **before_update**: Does NOT receive `update()` input parameters\n",
    "- **after_update**: DOES receive `update()` return value\n",
    "\n",
    "```python\n",
    "# Execution flow:\n",
    "for fn in before_updates:\n",
    "    fn()  # No parameters\n",
    "\n",
    "output = dynamics.update(inp)  # Main update\n",
    "\n",
    "for fn in after_updates:\n",
    "    fn(output)  # Receives output\n",
    "```\n",
    "\n",
    "### Custom Control\n",
    "\n",
    "You can modify this behavior using decorators:\n",
    "\n",
    "- `brainstate.nn.receive_update_input(fn)`: Make before_update receive input\n",
    "- `brainstate.nn.not_receive_update_output(fn)`: Make after_update NOT receive output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a279fb222572705d",
   "metadata": {},
   "source": [
    "### Example: Monitoring with Before/After Updates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3d88f6cf3011e7f6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:02.197336Z",
     "start_time": "2025-10-11T09:49:01.947513Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:11.186846Z",
     "iopub.status.busy": "2026-05-30T16:44:11.186663Z",
     "iopub.status.idle": "2026-05-30T16:44:11.583738Z",
     "shell.execute_reply": "2026-05-30T16:44:11.582577Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running simulation with after-update monitoring...\n",
      "\n",
      "Step 1:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 2:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 3:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 4:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 5:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Final statistics:\n",
      "  Min V: [-65. -65.] mV\n",
      "  Max V: [-65. -65.] mV\n",
      "  Total spikes: [0 0]\n",
      "\n",
      "\u2705 After-update hooks receive the output\n",
      "\u2705 Useful for monitoring, logging, and statistics\n"
     ]
    }
   ],
   "source": [
    "class MonitoredLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"LIF with monitoring hooks.\"\"\"\n",
    "\n",
    "    def __init__(self, size):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # States\n",
    "        self.V = brainstate.State(jnp.ones(size) * -65.0 * u.mV)\n",
    "        self.spike = brainstate.State(jnp.zeros(size, dtype=bool))\n",
    "\n",
    "        # Monitoring statistics\n",
    "        self.min_V = brainstate.State(jnp.ones(size) * jnp.inf * u.mV)\n",
    "        self.max_V = brainstate.State(jnp.ones(size) * -jnp.inf * u.mV)\n",
    "        self.total_spikes = brainstate.State(jnp.zeros(size, dtype=int))\n",
    "\n",
    "        # Parameters\n",
    "        self.tau = 10.0 * u.ms\n",
    "        self.V_rest = -65.0 * u.mV\n",
    "        self.V_th = -50.0 * u.mV\n",
    "        self.V_reset = -65.0 * u.mV\n",
    "\n",
    "    def update(self, I):\n",
    "        # Update voltage\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "        V_inf = self.V_rest + I * 1.0 * u.ohm\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "\n",
    "        # Detect spikes\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "# Create neuron\n",
    "neuron = MonitoredLIF(size=(2,))\n",
    "\n",
    "\n",
    "# Define monitoring functions\n",
    "def before_check():\n",
    "    \"\"\"Check state before update (no parameters).\"\"\"\n",
    "    print(f\"  [Before] V = {neuron.V.value}\")\n",
    "\n",
    "\n",
    "def after_statistics(spikes):\n",
    "    \"\"\"Update statistics after update (receives output).\"\"\"\n",
    "    # Update min/max voltage\n",
    "    neuron.min_V.value = u.math.minimum(neuron.min_V.value, neuron.V.value)\n",
    "    neuron.max_V.value = u.math.maximum(neuron.max_V.value, neuron.V.value)\n",
    "    # Count spikes\n",
    "    neuron.total_spikes.value += spikes\n",
    "\n",
    "\n",
    "def after_log(spikes):\n",
    "    \"\"\"Log output after update (receives output).\"\"\"\n",
    "    if jnp.any(spikes):\n",
    "        print(f\"  [After] Spike detected! Neurons: {jnp.where(spikes)[0]}\")\n",
    "\n",
    "\n",
    "# Add hooks (only for demonstration, normally not called every step)\n",
    "neuron.add_after_update('statistics', after_statistics)\n",
    "\n",
    "print(\"Running simulation with after-update monitoring...\\n\")\n",
    "\n",
    "# Simulate for a few steps\n",
    "for i in range(5):\n",
    "    print(f\"Step {i + 1}:\")\n",
    "    I = jnp.array([3.0, 4.0]) * u.nA\n",
    "    spikes = neuron(I)\n",
    "    print(f\"  Spikes: {spikes}\")\n",
    "    print(f\"  Total spikes so far: {neuron.total_spikes.value}\\n\")\n",
    "\n",
    "print(\"Final statistics:\")\n",
    "print(f\"  Min V: {neuron.min_V.value}\")\n",
    "print(f\"  Max V: {neuron.max_V.value}\")\n",
    "print(f\"  Total spikes: {neuron.total_spikes.value}\")\n",
    "\n",
    "print(\"\\n\"\n",
    "      \"\u2705 After-update hooks receive the output\")\n",
    "print(\"\u2705 Useful for monitoring, logging, and statistics\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52fbcd7eebdbd64",
   "metadata": {},
   "source": [
    "### Example: Custom Input/Output Control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "177f8088a19c0e20",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:02.360505Z",
     "start_time": "2025-10-11T09:49:02.207279Z"
    },
    "execution": {
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     "shell.execute_reply": "2026-05-30T16:44:11.790789Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running with custom input/output control:\n",
      "\n",
      "Step 1:\n",
      "  [Before with input] Received I = [3.5] nA\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  [After without output] Current V = -65. mV\n",
      "\n",
      "Step 2:\n",
      "  [Before with input] Received I = [3.5] nA\n",
      "  [After without output] Current V = -65. mV\n",
      "\n",
      "Step 3:\n",
      "  [Before with input] Received I = [3.5] nA\n",
      "  [After without output] Current V = -65. mV\n",
      "\n",
      "\u2705 receive_update_input: before-update receives input\n",
      "\u2705 not_receive_update_output: after-update doesn't receive output\n"
     ]
    }
   ],
   "source": [
    "# Create a new neuron for this example\n",
    "neuron2 = MonitoredLIF(size=(1,))\n",
    "\n",
    "\n",
    "# Before-update that RECEIVES input\n",
    "@brainstate.nn.receive_update_input\n",
    "class InputLogger:\n",
    "    def __call__(self, I):\n",
    "        print(f\"  [Before with input] Received I = {I}\")\n",
    "\n",
    "\n",
    "# After-update that DOES NOT receive output\n",
    "@brainstate.nn.not_receive_update_output\n",
    "class StateLogger:\n",
    "    def __init__(self, neuron):\n",
    "        self.neuron = neuron\n",
    "\n",
    "    def __call__(self):\n",
    "        print(f\"  [After without output] Current V = {self.neuron.V.value[0]}\")\n",
    "\n",
    "\n",
    "# Add custom hooks\n",
    "neuron2.add_before_update('input_log', InputLogger())\n",
    "neuron2.add_after_update('state_log', StateLogger(neuron2))\n",
    "\n",
    "print(\"Running with custom input/output control:\\n\")\n",
    "for i in range(3):\n",
    "    print(f\"Step {i + 1}:\")\n",
    "    neuron2(jnp.array([3.5]) * u.nA)\n",
    "    print()\n",
    "\n",
    "print(\"\u2705 receive_update_input: before-update receives input\")\n",
    "print(\"\u2705 not_receive_update_output: after-update doesn't receive output\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3074c73826d2d20",
   "metadata": {},
   "source": [
    "## Part 4: Input/Output Size Definition\n",
    "\n",
    "### Size Management\n",
    "\n",
    "Dynamics modules use `in_size` to define the geometry of the neuron population:\n",
    "\n",
    "```python\n",
    "# 1D population\n",
    "dynamics = MyDynamics(in_size=10)  # or in_size=(10,)\n",
    "\n",
    "# 2D population\n",
    "dynamics = MyDynamics(in_size=(10, 20))\n",
    "\n",
    "# 3D population\n",
    "dynamics = MyDynamics(in_size=(10, 20, 5))\n",
    "```\n",
    "\n",
    "### Key Attributes\n",
    "\n",
    "- **`in_size`**: Input shape (tuple)\n",
    "- **`out_size`**: Output shape (default: same as `in_size`)\n",
    "- **`varshape`**: Alias for `in_size` (variable shape)\n",
    "\n",
    "### Size Consistency\n",
    "\n",
    "This design ensures consistency with the `Module` class and enables seamless integration into larger network architectures."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "add245a0ccac9a40",
   "metadata": {},
   "source": [
    "### Example: Multi-Dimensional Populations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "891faca8c41b39da",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:02.941254Z",
     "start_time": "2025-10-11T09:49:02.367511Z"
    },
    "execution": {
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     "shell.execute_reply": "2026-05-30T16:44:12.637163Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1D Population:\n",
      "  in_size:  (10,)\n",
      "  out_size: (10,)\n",
      "  varshape: (10,)\n",
      "  V shape:  (10,)\n",
      "\n",
      "2D Population (8x8 grid):\n",
      "  in_size:  (8, 8)\n",
      "  out_size: (8, 8)\n",
      "  varshape: (8, 8)\n",
      "  V shape:  (8, 8)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3D Population (4x4x4 volume):\n",
      "  in_size:  (4, 4, 4)\n",
      "  out_size: (4, 4, 4)\n",
      "  varshape: (4, 4, 4)\n",
      "  V shape:  (4, 4, 4)\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied 2D input with shape (8, 8)\n",
      "Got 2D output with shape (8, 8)\n",
      "Number of spikes: 0\n",
      "\n",
      "\u2705 Dynamics supports arbitrary dimensional populations\n",
      "\u2705 in_size defines the geometry of the population\n",
      "\u2705 Element-wise operations preserve dimensionality\n"
     ]
    }
   ],
   "source": [
    "# 1D population (line of neurons)\n",
    "pop_1d = SimpleLIF(size=10)\n",
    "print(\"1D Population:\")\n",
    "print(f\"  in_size:  {pop_1d.in_size}\")\n",
    "print(f\"  out_size: {pop_1d.out_size}\")\n",
    "print(f\"  varshape: {pop_1d.varshape}\")\n",
    "print(f\"  V shape:  {pop_1d.V.value.shape}\\n\")\n",
    "\n",
    "# 2D population (grid of neurons)\n",
    "pop_2d = SimpleLIF(size=(8, 8))\n",
    "print(\"2D Population (8x8 grid):\")\n",
    "print(f\"  in_size:  {pop_2d.in_size}\")\n",
    "print(f\"  out_size: {pop_2d.out_size}\")\n",
    "print(f\"  varshape: {pop_2d.varshape}\")\n",
    "print(f\"  V shape:  {pop_2d.V.value.shape}\\n\")\n",
    "\n",
    "# 3D population (volume of neurons)\n",
    "pop_3d = SimpleLIF(size=(4, 4, 4))\n",
    "print(\"3D Population (4x4x4 volume):\")\n",
    "print(f\"  in_size:  {pop_3d.in_size}\")\n",
    "print(f\"  out_size: {pop_3d.out_size}\")\n",
    "print(f\"  varshape: {pop_3d.varshape}\")\n",
    "print(f\"  V shape:  {pop_3d.V.value.shape}\\n\")\n",
    "\n",
    "# Demonstrate element-wise operation with 2D input\n",
    "I_2d = brainstate.random.randn(8, 8) * u.nA\n",
    "spikes_2d = pop_2d(I_2d)\n",
    "\n",
    "print(f\"Applied 2D input with shape {I_2d.shape}\")\n",
    "print(f\"Got 2D output with shape {spikes_2d.shape}\")\n",
    "print(f\"Number of spikes: {jnp.sum(spikes_2d)}\")\n",
    "\n",
    "print(\"\\n\u2705 Dynamics supports arbitrary dimensional populations\")\n",
    "print(\"\u2705 in_size defines the geometry of the population\")\n",
    "print(\"\u2705 Element-wise operations preserve dimensionality\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37c786a93c8b6658",
   "metadata": {},
   "source": [
    "## Part 5: Delay Support Mechanism\n",
    "\n",
    "Dynamics naturally supports **temporal delays** through the after-update mechanism, which is crucial for neural dynamics modeling.\n",
    "\n",
    "### Two Types of Delays\n",
    "\n",
    "#### 1. Output Delay\n",
    "\n",
    "Delay the output of `update()` for downstream modules:\n",
    "\n",
    "```python\n",
    "# Create delayed output reference\n",
    "delayed_output = dynamics.output_delay(5.0 * u.ms)\n",
    "\n",
    "# Access delayed value\n",
    "value = delayed_output()\n",
    "```\n",
    "\n",
    "#### 2. State Delay (Prefetch Delay)\n",
    "\n",
    "Delay a specific state variable:\n",
    "\n",
    "```python\n",
    "# Prefetch delayed state (before init_state is called)\n",
    "delayed_V = dynamics.prefetch_delay('V', delay_time=5.0 * u.ms)\n",
    "\n",
    "# Access delayed voltage\n",
    "v_delayed = delayed_V()\n",
    "```\n",
    "\n",
    "### Automatic Synchronization\n",
    "\n",
    "After each `update()`, the delay buffer is automatically updated through the after-update hook. No manual management required!\n",
    "\n",
    "### Use Cases\n",
    "\n",
    "- Axonal delays\n",
    "- Synaptic delays\n",
    "- Feedback connections\n",
    "- Time-delayed systems"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d03b5f1de8cccead",
   "metadata": {},
   "source": [
    "### Example: Output Delay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "be45b27be04b3d4e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:04.319908Z",
     "start_time": "2025-10-11T09:49:02.947260Z"
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    "execution": {
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     "shell.execute_reply": "2026-05-30T16:44:14.723536Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulating with output delays...\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u2705 Output delay shifts spikes in time\n",
      "\u2705 Multiple delays can coexist\n",
      "\u2705 Delays are automatically managed\n"
     ]
    }
   ],
   "source": [
    "# Create neuron\n",
    "neuron = SimpleLIF(size=(1,))\n",
    "\n",
    "# Create delayed output references\n",
    "output_now = neuron  # No delay\n",
    "output_delayed_2ms = neuron.output_delay(2.0 * u.ms)\n",
    "output_delayed_5ms = neuron.output_delay(5.0 * u.ms)\n",
    "\n",
    "brainstate.nn.init_all_states(neuron)\n",
    "print(\"Simulating with output delays...\\n\")\n",
    "\n",
    "# Simulate\n",
    "n_steps = 200\n",
    "history_now = []\n",
    "history_2ms = []\n",
    "history_5ms = []\n",
    "\n",
    "for i in range(n_steps):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    with brainstate.environ.context(t=t, i=i):\n",
    "        # Update neuron (immediate output)\n",
    "        spike_now = neuron(30.0 * u.mA)\n",
    "\n",
    "        # Access delayed outputs\n",
    "        spike_2ms = output_delayed_2ms()\n",
    "        spike_5ms = output_delayed_5ms()\n",
    "\n",
    "        history_now.append(spike_now[0])\n",
    "        history_2ms.append(spike_2ms[0])\n",
    "        history_5ms.append(spike_5ms[0])\n",
    "\n",
    "history_now = jnp.where(jnp.array(history_now))[0]\n",
    "history_2ms = jnp.where(jnp.array(history_2ms))[0]\n",
    "history_5ms = jnp.where(jnp.array(history_5ms))[0]\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Visualize\n",
    "plt.figure(figsize=(14, 6))\n",
    "\n",
    "# Find spike times\n",
    "spikes_now = times[history_now]\n",
    "spikes_2ms = times[history_2ms]\n",
    "spikes_5ms = times[history_5ms]\n",
    "\n",
    "if len(spikes_now) > 0:\n",
    "    plt.eventplot(\n",
    "        [spikes_now.to_decimal(u.ms)],\n",
    "        lineoffsets=[0],\n",
    "        colors='blue',\n",
    "        linewidths=2,\n",
    "        label='No delay'\n",
    "    )\n",
    "if len(spikes_2ms) > 0:\n",
    "    plt.eventplot(\n",
    "        [spikes_2ms.to_decimal(u.ms)],\n",
    "        lineoffsets=[1],\n",
    "        colors='orange',\n",
    "        linewidths=2,\n",
    "        label='2ms delay'\n",
    "    )\n",
    "if len(spikes_5ms) > 0:\n",
    "    plt.eventplot(\n",
    "        [spikes_5ms.to_decimal(u.ms)],\n",
    "        lineoffsets=[2],\n",
    "        colors='red',\n",
    "        linewidths=2,\n",
    "        label='5ms delay'\n",
    "    )\n",
    "\n",
    "plt.yticks([0, 1, 2], ['Now', '2ms', '5ms'])\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Delay')\n",
    "plt.title('Output Delay Mechanism', fontweight='bold')\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()\n",
    "\n",
    "print(\"\u2705 Output delay shifts spikes in time\")\n",
    "print(\"\u2705 Multiple delays can coexist\")\n",
    "print(\"\u2705 Delays are automatically managed\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e73f875251734a6",
   "metadata": {},
   "source": [
    "### Example: State Delay (Prefetch Delay)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9678f9b8a392febb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:05.305541Z",
     "start_time": "2025-10-11T09:49:04.466890Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:14.728120Z",
     "iopub.status.busy": "2026-05-30T16:44:14.727787Z",
     "iopub.status.idle": "2026-05-30T16:44:13.252630Z",
     "shell.execute_reply": "2026-05-30T16:44:13.251872Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u2705 prefetch_delay accesses delayed state variables\n",
      "\u2705 Delayed feedback creates oscillatory dynamics\n",
      "\u2705 Delay buffer is automatically synchronized after update()\n"
     ]
    }
   ],
   "source": [
    "class DelayedFeedbackLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"LIF with delayed self-feedback.\"\"\"\n",
    "\n",
    "    def __init__(self, size, feedback_delay=3.0 * u.ms, feedback_strength=0.5):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # Create delayed voltage reference\n",
    "        self.V_delayed = self.prefetch_delay('V', feedback_delay)\n",
    "\n",
    "        # Parameters\n",
    "        self.tau = 10.0 * u.ms\n",
    "        self.V_rest = -65.0 * u.mV\n",
    "        self.V_th = -50.0 * u.mV\n",
    "        self.V_reset = -65.0 * u.mV\n",
    "        self.feedback_strength = feedback_strength\n",
    "\n",
    "    def init_state(self, *args, **kwargs):\n",
    "        self.V = brainstate.State(jnp.ones(self.varshape) * -65.0 * u.mV)\n",
    "        self.spike = brainstate.State(jnp.zeros(self.varshape, dtype=bool))\n",
    "\n",
    "    def update(self, I):\n",
    "        # Get delayed voltage for feedback\n",
    "        V_delayed = self.V_delayed()\n",
    "\n",
    "        # Add delayed feedback to input\n",
    "        feedback_current = (V_delayed - self.V_rest) * self.feedback_strength / (1.0 * u.ohm)\n",
    "        I_total = I + feedback_current\n",
    "\n",
    "        # Update voltage\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "        V_inf = self.V_rest + I_total * 1.0 * u.ohm\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "\n",
    "        # Spike\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "\n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "# Create neurons: one with feedback, one without\n",
    "neuron_no_fb = SimpleLIF(size=(1,))\n",
    "neuron_fb = DelayedFeedbackLIF(size=(1,), feedback_delay=3.0 * u.ms, feedback_strength=0.3)\n",
    "\n",
    "brainstate.nn.init_all_states(neuron_no_fb)\n",
    "brainstate.nn.init_all_states(neuron_fb)\n",
    "\n",
    "# Simulate both\n",
    "n_steps = 150\n",
    "V_no_fb = []\n",
    "V_fb = []\n",
    "\n",
    "for i in range(n_steps):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    with brainstate.environ.context(t=t, i=i):\n",
    "        neuron_no_fb(28.0 * u.mA)\n",
    "        neuron_fb(28.0 * u.mA)\n",
    "        V_no_fb.append(neuron_no_fb.V.value[0])\n",
    "        V_fb.append(neuron_fb.V.value[0])\n",
    "\n",
    "V_no_fb = u.math.array(V_no_fb)\n",
    "V_fb = u.math.array(V_fb)\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Plot\n",
    "plt.figure(figsize=(14, 6))\n",
    "plt.plot(\n",
    "    times.to_decimal(u.ms),\n",
    "    V_no_fb.to_decimal(u.mV),\n",
    "    label='No feedback',\n",
    "    linewidth=1.5,\n",
    "    alpha=0.8\n",
    ")\n",
    "plt.plot(\n",
    "    times.to_decimal(u.ms),\n",
    "    V_fb.to_decimal(u.mV),\n",
    "    label='With delayed feedback (3ms)',\n",
    "    linewidth=1.5,\n",
    "    alpha=0.8\n",
    ")\n",
    "plt.axhline(-50, color='red', linestyle='--', alpha=0.5, label='Threshold')\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Membrane Potential (mV)')\n",
    "plt.title('State Delay: Delayed Self-Feedback', fontweight='bold')\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()\n",
    "\n",
    "print(\"\u2705 prefetch_delay accesses delayed state variables\")\n",
    "print(\"\u2705 Delayed feedback creates oscillatory dynamics\")\n",
    "print(\"\u2705 Delay buffer is automatically synchronized after update()\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "428bb19dcc3fef2a",
   "metadata": {},
   "source": [
    "## Part 6: Ecosystem Integration\n",
    "\n",
    "The Dynamics protocol is the foundation of the BrainPy ecosystem, providing a unified interface across multiple systems:\n",
    "\n",
    "### **brainpy.state** - General Dynamical Systems\n",
    "\n",
    "Implements common neuron models (LIF, HH, Izhikevich) and synapse models (Exponential, Alpha, NMDA)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f71f7681d67df776",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:07.764615Z",
     "start_time": "2025-10-11T09:49:05.478944Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:13.254701Z",
     "iopub.status.busy": "2026-05-30T16:44:13.254475Z",
     "iopub.status.idle": "2026-05-30T16:44:15.888627Z",
     "shell.execute_reply": "2026-05-30T16:44:15.887557Z"
    }
   },
   "outputs": [],
   "source": [
    "import brainpy\n",
    "\n",
    "# All follow the Dynamics protocol\n",
    "lif = brainpy.state.LIF(100)\n",
    "hh = brainpy.state.ALIF(50)\n",
    "syn = brainpy.state.Expon(100, tau=5.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9c76960c989ed0",
   "metadata": {},
   "source": [
    "\n",
    "### **brainmass** - Neural Mass Models\n",
    "\n",
    "Large-scale brain modeling with population dynamics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "96a54b90cb598ad4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:07.987082Z",
     "start_time": "2025-10-11T09:49:07.904940Z"
    },
    "execution": {
     "iopub.execute_input": "2026-05-30T16:44:15.891274Z",
     "iopub.status.busy": "2026-05-30T16:44:15.890804Z",
     "iopub.status.idle": "2026-05-30T16:44:15.907589Z",
     "shell.execute_reply": "2026-05-30T16:44:15.906683Z"
    }
   },
   "outputs": [],
   "source": [
    "import brainmass\n",
    "wilson_cowan = brainmass.WilsonCowanModel((10, 10))\n",
    "jansen_rit = brainmass.JansenRitModel(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb93666039c8aa0",
   "metadata": {},
   "source": [
    "\n",
    "### Unified Benefits\n",
    "\n",
    "\u2705 **Same API** - All use `update()`, before/after updates, delays\n",
    "\u2705 **Composable** - Mix and match across systems\n",
    "\u2705 **Consistent** - Learn once, use everywhere\n",
    "\u2705 **Scalable** - From single neurons to whole brain models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23a45d683608e7df",
   "metadata": {},
   "source": [
    "## Exercise: Implement Your Own Dynamics\n",
    "\n",
    "### Task\n",
    "\n",
    "Implement a simplified **Izhikevich neuron** model:\n",
    "\n",
    "$$\n",
    "\\frac{dv}{dt} = 0.04v^2 + 5v + 140 - u + I\n",
    "$$\n",
    "$$\n",
    "\\frac{du}{dt} = a(bv - u)\n",
    "$$\n",
    "\n",
    "When $v \\geq 30$: spike, then $v \\leftarrow c$, $u \\leftarrow u + d$\n",
    "\n",
    "### Requirements\n",
    "\n",
    "1. Inherit from `brainstate.nn.Dynamics`\n",
    "2. Define states `v` and `u`\n",
    "3. Define parameters `a`, `b`, `c`, `d`\n",
    "4. Implement `update(I)` with Euler integration\n",
    "5. Return spike events\n",
    "\n",
    "### Starter Code"
   ]
  },
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   "source": [
    "class Izhikevich(brainstate.nn.Dynamics):\n",
    "    \"\"\"Izhikevich neuron model.\"\"\"\n",
    "\n",
    "    def __init__(self, size, a=0.02, b=0.2, c=-65.0, d=8.0):\n",
    "        # TODO: Initialize parent class\n",
    "        # TODO: Create states v and u\n",
    "        # TODO: Store parameters a, b, c, d\n",
    "        pass\n",
    "\n",
    "    def update(self, I):\n",
    "        # TODO: Implement Euler integration\n",
    "        # TODO: Detect spikes (v >= 30)\n",
    "        # TODO: Reset v and u when spike occurs\n",
    "        # TODO: Return spike events\n",
    "        pass\n",
    "\n",
    "# Test your implementation\n",
    "# izh = Izhikevich(size=1)\n",
    "# for i in range(100):\n",
    "#     spike = izh(jnp.array([10.0]))\n",
    "#     if spike[0]:\n",
    "#         print(f\"Spike at step {i}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9e0adebf175d9a1",
   "metadata": {},
   "source": [
    "### Solution Hints\n",
    "\n",
    "<details>\n",
    "<summary>Click to show hints</summary>\n",
    "\n",
    "1. **Initialization**:\n",
    "   ```python\n",
    "   super().__init__(in_size=size)\n",
    "   self.v = brainstate.State(jnp.ones(size) * -65.0)\n",
    "   self.u = brainstate.State(jnp.ones(size) * b * -65.0)\n",
    "   ```\n",
    "\n",
    "2. **Euler integration**:\n",
    "   ```python\n",
    "   dt = brainstate.environ.get_dt().to_decimal(u.ms)\n",
    "   dv = (0.04 * v**2 + 5*v + 140 - u + I) * dt\n",
    "   du = a * (b*v - u) * dt\n",
    "   ```\n",
    "\n",
    "3. **Spike detection and reset**:\n",
    "   ```python\n",
    "   spike = v >= 30\n",
    "   v = jnp.where(spike, c, v)\n",
    "   u = jnp.where(spike, u + d, u)\n",
    "   ```\n",
    "\n",
    "</details>\n",
    "\n",
    "### Further Exploration\n",
    "\n",
    "- Add delayed self-feedback using `prefetch_delay`\n",
    "- Add monitoring using before/after updates\n",
    "- Implement different Izhikevich neuron types (RS, IB, CH, FS)\n",
    "- Combine with synaptic models from brainpy.state"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "resources",
   "metadata": {},
   "source": [
    "## Additional Resources\n",
    "\n",
    "### Documentation\n",
    "- [BrainState API Reference](https://brainx.chaobrain.com/brainstate/)\n",
    "- [BrainPy Documentation](https://brainpy.readthedocs.io/)\n",
    "- [BrainScale Documentation](https://brainscale.readthedocs.io/)\n",
    "\n",
    "### Related Tutorials\n",
    "- `06_delay_basics.ipynb` - Detailed delay mechanisms\n",
    "- `01_module_basics.ipynb` - Module system fundamentals\n",
    "- `02_state_management.ipynb` - State management in depth\n",
    "\n",
    "### Papers\n",
    "- Izhikevich, E. M. (2003). Simple model of spiking neurons. IEEE Transactions on neural networks.\n",
    "- Brette, R., & Gerstner, W. (2005). Adaptive exponential integrate-and-fire model.\n",
    "- Gerstner, W., et al. (2014). Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition."
   ]
  }
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