{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a0a5769e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T08:12:52.328266Z",
     "iopub.status.busy": "2026-06-19T08:12:52.327976Z",
     "iopub.status.idle": "2026-06-19T08:12:57.705834Z",
     "shell.execute_reply": "2026-06-19T08:12:57.704863Z"
    },
    "tags": [
     "remove-cell"
    ]
   },
   "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"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import brainmass\n",
    "import brainstate\n",
    "import brainunit as u\n",
    "import jax.numpy as jnp\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "brainstate.random.seed(0)\n",
    "brainstate.environ.set(dt=0.1 * u.ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ea48120",
   "metadata": {},
   "source": [
    "# Coombes-Byrne (Next-Generation Neural Mass)\n",
    "\n",
    "The **Coombes-Byrne model** is a next-generation neural-mass model: an *exact* mean field of a network of theta/QIF neurons with **synaptic conductance** coupling, derived from the Ott-Antonsen reduction. Its macroscopic variables are the firing rate $r$ and mean potential $v$, with a synaptic conductance $g = k\\pi r$:\n",
    "\n",
    "$$\\dot r = \\tfrac{\\Delta}{\\pi} + 2 r v - g r,\\qquad \\dot v = v^2 - (\\pi r)^2 + \\eta + (v_{syn} - v)\\,g.$$\n",
    "\n",
    "Setting the conductance scale $k = 0$ recovers the Montbrio-Pazo-Roxin model (with $J=0$); the conductance term is what distinguishes the two synapse models.\n",
    "\n",
    "**Reference:** Coombes & Byrne (2019), *Next generation neural mass models*, in Nonlinear Dynamics in Computational Neuroscience, Springer, pp. 1-16."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7160ee4c",
   "metadata": {},
   "source": [
    "## Build the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "38a35aa9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T08:12:57.709243Z",
     "iopub.status.busy": "2026-06-19T08:12:57.708518Z",
     "iopub.status.idle": "2026-06-19T08:12:57.730497Z",
     "shell.execute_reply": "2026-06-19T08:12:57.729374Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CoombesByrneStep(\n",
       "  in_size=(1,),\n",
       "  out_size=(1,),\n",
       "  Delta=Const(\n",
       "    fit=False,\n",
       "    t=IdentityT(),\n",
       "    reg=None,\n",
       "    val=Array(1., dtype=float32)\n",
       "  ),\n",
       "  eta=Const(\n",
       "    fit=False,\n",
       "    t=IdentityT(),\n",
       "    reg=None,\n",
       "    val=Array(2., dtype=float32)\n",
       "  ),\n",
       "  k=Const(\n",
       "    fit=False,\n",
       "    t=IdentityT(),\n",
       "    reg=None,\n",
       "    val=Array(1., dtype=float32)\n",
       "  ),\n",
       "  v_syn=Const(\n",
       "    fit=False,\n",
       "    t=IdentityT(),\n",
       "    reg=None,\n",
       "    val=Array(-4., dtype=float32)\n",
       "  ),\n",
       "  init_r=Constant(value=0.1),\n",
       "  init_v=Constant(value=0.0),\n",
       "  method=exp_euler\n",
       ")"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "node = brainmass.CoombesByrneStep(in_size=1, Delta=1.0, eta=2.0, k=1.0, v_syn=-4.0)\n",
    "node"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcecbd44",
   "metadata": {},
   "source": [
    "## Run a simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1467f45f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T08:12:57.732966Z",
     "iopub.status.busy": "2026-06-19T08:12:57.732680Z",
     "iopub.status.idle": "2026-06-19T08:12:57.886594Z",
     "shell.execute_reply": "2026-06-19T08:12:57.885842Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(800, 1)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim = brainmass.Simulator(node, dt=0.1 * u.ms)\n",
    "res = sim.run(80. * u.ms, monitors=['r', 'v'])\n",
    "res['r'].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "507e4cb3",
   "metadata": {},
   "source": [
    "## Visualize\n",
    "\n",
    "The rate `r` and potential `v` relax toward the fixed point of the conductance-coupled mean field."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "76db74de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T08:12:57.889087Z",
     "iopub.status.busy": "2026-06-19T08:12:57.888887Z",
     "iopub.status.idle": "2026-06-19T08:12:58.110614Z",
     "shell.execute_reply": "2026-06-19T08:12:58.108982Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1, 2, figsize=(10, 4))\n",
    "brainmass.viz.plot_timeseries(res['r'], ts=res['ts'], ax=axes[0])\n",
    "axes[0].set_title('Coombes-Byrne firing rate r')\n",
    "brainmass.viz.plot_phase_portrait(res['r'], res['v'], ax=axes[1])\n",
    "axes[1].set_xlabel('r'); axes[1].set_ylabel('v')\n",
    "axes[1].set_title('Phase portrait')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69765899",
   "metadata": {},
   "source": [
    "## Try it: vary the conductance scale `k`\n",
    "\n",
    "The synaptic conductance scale `k` is the knob that separates this model from MPR. `k = 0` removes the conductance term entirely (recovering the QIF mean field with `J = 0`); larger `k` strengthens the self-conductance and shifts the steady rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "93b2aa57",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-19T08:12:58.113714Z",
     "iopub.status.busy": "2026-06-19T08:12:58.113408Z",
     "iopub.status.idle": "2026-06-19T08:12:58.551163Z",
     "shell.execute_reply": "2026-06-19T08:12:58.550463Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 4))\n",
    "for k in [0.0, 1.0, 2.0]:\n",
    "    m = brainmass.CoombesByrneStep(in_size=1, Delta=1.0, eta=2.0, k=k, v_syn=-4.0)\n",
    "    r = brainmass.Simulator(m, dt=0.1 * u.ms).run(80. * u.ms, monitors=['r'])\n",
    "    ax.plot(u.get_magnitude(r['ts']), u.get_magnitude(r['r'])[:, 0], label=f'k = {k}')\n",
    "ax.set_xlabel('time (ms)'); ax.set_ylabel('r'); ax.legend()\n",
    "ax.set_title('Conductance-scale sweep (k = 0 -> MPR limit)')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
