{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "header",
   "metadata": {},
   "source": [
    "# The Wong-Wang Decision-Making Model\n",
    "\n",
    "A biophysically-inspired neural mass model for perceptual decision-making and evidence integration."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "learning-objectives",
   "metadata": {},
   "source": [
    "## Learning Objectives\n",
    "\n",
    "By the end of this tutorial, you will be able to:\n",
    "\n",
    "- Understand the biophysical basis of the Wong-Wang model (NMDA synaptic dynamics)\n",
    "- Simulate two-choice decision-making with varying stimulus coherence\n",
    "- Analyze decision accuracy, reaction time, and choice probability\n",
    "- Explain the attractor dynamics underlying perceptual decisions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "background",
   "metadata": {},
   "source": [
    "## Background / Theory\n",
    "\n",
    "### The Decision-Making Problem\n",
    "\n",
    "When you see dots moving on a screen, how does your brain decide whether they're moving left or right? This is the classic **random dot motion task** studied extensively in neuroscience.\n",
    "\n",
    "Key experimental findings:\n",
    "- Decision accuracy increases with stimulus strength (coherence)\n",
    "- Reaction time decreases with stimulus strength\n",
    "- Neural activity in parietal cortex ramps up during decision formation\n",
    "\n",
    "### The Wong-Wang Model\n",
    "\n",
    "Wong & Wang (2006) developed a reduced neural mass model that captures these phenomena. The model describes two competing neural populations:\n",
    "\n",
    "- **Population 1**: Prefers leftward motion\n",
    "- **Population 2**: Prefers rightward motion\n",
    "\n",
    "### Mathematical Formulation\n",
    "\n",
    "The synaptic gating variables $S_1$ and $S_2$ evolve according to:\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\frac{dS_1}{dt} &= -\\frac{S_1}{\\tau_S} + (1-S_1)\\gamma r_1 \\\\\n",
    "\\frac{dS_2}{dt} &= -\\frac{S_2}{\\tau_S} + (1-S_2)\\gamma r_2\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "Where firing rates are computed from input currents via threshold-linear function:\n",
    "\n",
    "$$\n",
    "r_i = \\phi(I_i) = \\alpha(I_i - \\theta)^+ \n",
    "$$\n",
    "\n",
    "Input currents include:\n",
    "- **Recurrent excitation**: $J_{N,11}S_1$ or $J_{N,22}S_2$\n",
    "- **Cross-inhibition**: $-J_{N,12}S_2$ or $-J_{N,21}S_1$\n",
    "- **Stimulus**: $J_{A,ext}\\mu_0(1 \\pm c)$ where $c$ is coherence\n",
    "\n",
    "### Key Parameters\n",
    "\n",
    "| Parameter | Value | Description |\n",
    "|-----------|-------|-------------|\n",
    "| $\\tau_S$ | 100 ms | NMDA time constant (slow integration) |\n",
    "| $\\gamma$ | 0.641 | Saturation factor |\n",
    "| $\\alpha$ | 270 Hz/nA | Gain |\n",
    "| $\\theta$ | 0.31 nA | Firing threshold |\n",
    "| $c$ | [-1, 1] | Motion coherence |"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "implementation",
   "metadata": {},
   "source": [
    "## Implementation\n",
    "\n",
    "### Step 1: Setup and Imports"
   ]
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:26.511004700Z",
     "start_time": "2026-03-21T13:55:21.666936200Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import brainmass\n",
    "import brainstate\n",
    "import brainunit as u\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Set simulation time step (finer for accurate dynamics)\n",
    "brainstate.environ.set(dt=0.5 * u.ms)"
   ],
   "id": "27fafa26bcc7756c",
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Step 2: Single Decision Trial\n",
    "\n",
    "Let's simulate a single trial with moderate coherence:"
   ],
   "id": "6df172c76c0304fa"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:26.599286400Z",
     "start_time": "2026-03-21T13:55:26.513011700Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# Create Wong-Wang model\n",
    "model = brainmass.WongWangStep(\n",
    "    in_size=1,  # single decision unit\n",
    "    # Add noise for realistic variability\n",
    "    noise_s1=brainmass.OUProcess(1, sigma=0.02 * u.nA, tau=2.0 * u.ms),\n",
    "    noise_s2=brainmass.OUProcess(1, sigma=0.02 * u.nA, tau=2.0 * u.ms),\n",
    ")\n",
    "\n",
    "# Initialize states\n",
    "model.init_all_states()\n",
    "\n",
    "print(f\"NMDA time constant: {model.tau_S.value()}\")\n",
    "print(f\"Firing threshold: {model.theta.value()}\")"
   ],
   "id": "2467349904ee6f65",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NMDA time constant: 0.1 s\n",
      "Firing threshold: 0.31 nA\n"
     ]
    }
   ],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:27.611829700Z",
     "start_time": "2026-03-21T13:55:26.601728300Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# Simulate a trial with positive coherence (favoring population 1)\n",
    "coherence = 0.25  # 25% motion coherence\n",
    "\n",
    "\n",
    "def step_run(i):\n",
    "    r1, r2 = model.update(coherence=coherence)\n",
    "    return model.S1.value, model.S2.value, r1, r2\n",
    "\n",
    "\n",
    "# Run for 2 seconds (typical decision time)\n",
    "n_steps = int(2.0 * u.second / brainstate.environ.get_dt())\n",
    "indices = np.arange(n_steps)\n",
    "S1_trace, S2_trace, r1_trace, r2_trace = brainstate.transform.for_loop(step_run, indices)"
   ],
   "id": "854b49fdeae9c3a6",
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:28.664122100Z",
     "start_time": "2026-03-21T13:55:27.833968Z"
    }
   },
   "cell_type": "code",
   "source": [
    "t_ms = indices * brainstate.environ.get_dt()\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
    "\n",
    "# Synaptic gating variables\n",
    "axes[0].plot(t_ms, S1_trace[:, 0], 'b-', label='S1 (favored)', linewidth=1.5)\n",
    "axes[0].plot(t_ms, S2_trace[:, 0], 'r-', label='S2', linewidth=1.5)\n",
    "axes[0].set_xlabel('Time (ms)')\n",
    "axes[0].set_ylabel('Synaptic gating (S)')\n",
    "axes[0].set_title(f'Decision Dynamics (coherence = {coherence})')\n",
    "axes[0].legend()\n",
    "axes[0].set_xlim([0, 2000])\n",
    "\n",
    "# Firing rates\n",
    "axes[1].plot(t_ms, r1_trace[:, 0], 'b-', label='r1 (favored)', linewidth=1.5)\n",
    "axes[1].plot(t_ms, r2_trace[:, 0], 'r-', label='r2', linewidth=1.5)\n",
    "axes[1].axhline(15, color='gray', linestyle='--', label='Decision threshold')\n",
    "axes[1].set_xlabel('Time (ms)')\n",
    "axes[1].set_ylabel('Firing rate (Hz)')\n",
    "axes[1].set_title('Population Firing Rates')\n",
    "axes[1].legend()\n",
    "axes[1].set_xlim([0, 2000])\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "110a00580fe12593",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Step 3: Effect of Stimulus Coherence\n",
    "\n",
    "Coherence determines stimulus strength - let's see how it affects the decision:"
   ],
   "id": "3eb7f017324ba072"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:31.929761100Z",
     "start_time": "2026-03-21T13:55:28.687675400Z"
    }
   },
   "cell_type": "code",
   "source": [
    "coherence_values = [0.0, 0.1, 0.25, 0.5]\n",
    "\n",
    "fig, axes = plt.subplots(2, len(coherence_values), figsize=(14, 6))\n",
    "\n",
    "for idx, coh in enumerate(coherence_values):\n",
    "    # Create fresh model\n",
    "    model = brainmass.WongWangStep(\n",
    "        in_size=1,\n",
    "        noise_s1=brainmass.OUProcess(1, sigma=0.02 * u.nA, tau=2.0 * u.ms),\n",
    "        noise_s2=brainmass.OUProcess(1, sigma=0.02 * u.nA, tau=2.0 * u.ms),\n",
    "    )\n",
    "    model.init_all_states()\n",
    "\n",
    "\n",
    "    # Simulate\n",
    "    def step(i):\n",
    "        r1, r2 = model.update(coherence=coh)\n",
    "        return model.S1.value, model.S2.value\n",
    "\n",
    "\n",
    "    S1, S2 = brainstate.transform.for_loop(step, indices)\n",
    "\n",
    "    # Plot S dynamics (top row)\n",
    "    axes[0, idx].plot(t_ms, S1[:, 0], 'b-', label='S1', linewidth=1)\n",
    "    axes[0, idx].plot(t_ms, S2[:, 0], 'r-', label='S2', linewidth=1)\n",
    "    axes[0, idx].set_title(f'c = {coh}')\n",
    "    axes[0, idx].set_xlabel('Time (ms)')\n",
    "    if idx == 0:\n",
    "        axes[0, idx].set_ylabel('S')\n",
    "        axes[0, idx].legend()\n",
    "\n",
    "    # Phase portrait (bottom row)\n",
    "    axes[1, idx].plot(S1[:, 0], S2[:, 0], 'k-', linewidth=0.5, alpha=0.7)\n",
    "    axes[1, idx].plot(S1[0, 0], S2[0, 0], 'go', markersize=8, label='Start')\n",
    "    axes[1, idx].plot(S1[-1, 0], S2[-1, 0], 'r*', markersize=12, label='End')\n",
    "    axes[1, idx].set_xlabel('S1')\n",
    "    if idx == 0:\n",
    "        axes[1, idx].set_ylabel('S2')\n",
    "        axes[1, idx].legend()\n",
    "    axes[1, idx].set_xlim([0, 1])\n",
    "    axes[1, idx].set_ylim([0, 1])\n",
    "    axes[1, idx].set_aspect('equal')\n",
    "\n",
    "plt.suptitle('Decision Dynamics Across Coherence Levels', y=1.02, fontsize=14)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "3605b5e2bc41121a",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x600 with 8 Axes>"
      ],
      "image/png": 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qevXq5CwAKPsDrPnz52vTpk0aOnSo1eXAQTEMAlDEZs+era5du1pdBgBA0q+//qrSpUtzphcA2NmFCxf05ptvqmHDhmrfvr3V5QCA5Y4dO6Z///vf8vb2VlRUlEqUKGF1SXBQnFkLFKH169erVKlSqlSpktWlAIDbO3jwoBYvXqxRo0ZZXQoAuJTU1FS98cYbuv/++/mKLwBI2rVrl6ZMmaInnniCfgCuyaXPrM3Kyrri9H379hVxNXB3e/bs0WeffaaePXtaXQoAuD1jjKZOnaonn3xSXl58dg0A9mKM0fjx4/Xggw/SqAUASX/88YemTp2qyMhIGrXIF5ds1qakpKhbt24qUaKEgoODNWbMGGVmZubcf/ToUVWrVs3CCuFuduzYoSlTpmjEiBF81QEAHMCaNWsUFhamcuXKWV0KALiUr7/+WjVr1lTDhg2tLgUALHf48GFNnTpVI0aM4GK2yDeXbNaOHj1av//+uz755BP9+9//1owZM9SpUyelp6fnzGOMsbBCuJPNmzfr008/VWRkpAICAqwuBwDcXmZmpubNm6eHH37Y6lIAwKUcPHhQGzZs0IMPPmh1KQBguYyMDE2cOFHDhg2Tv7+/1eXAibhkszY2NlYffPCBHnnkEQ0cOFCrVq3S0aNH1bFjR6WlpUmSbDabxVXCHaxfv15z585VZGQkZ9QCgIOIi4vTbbfdpmLFilldCgC4lE8++USDBg3iby0AkPTll1/q3nvvVdmyZa0uBU7GJZu1R48eVdWqVXN+L1u2rL777judPn1a7du317lz5yysDu7iwIED+uKLLxQZGSk/Pz+rywEAKPuiNz/++KPuvfdeq0sBAJeyd+9elShRQuXLl7e6FACw3MGDB/XHH3+oTZs2VpcCJ+SSzdoqVapoy5YtuaaVLFlS3377rc6fP68uXbpYVBncxenTp/X+++9r6NCh8vHxsbocAMCfvvjiC3Xu3Fmenp5WlwIALuXzzz9Xt27drC4DACxnjNFHH32kgQMH8k0DFIhLNmvvvfdeTZ069bLp/v7+Wrx4MWc5olDt2LFDr732mgYOHKjSpUtbXQ4A4E8HDhzQrl271KxZM6tLAQCXsn//fhUrVkzBwcFWlwIAlps7d65atGjBhWxRYF5WF1AY/vWvf+nQoUN53hcQEKClS5dqzZo1RVwVXN3Zs2c1c+ZMpaamasSIEVxMDAAcyLZt2zRz5kw9++yznOEAAHa2aNEitW/f3uoyAMByv/76q/bv369nn33W6lLgxFzyzNqtW7dq9+7duabNmDFD1apVU/ny5fXcc8+pRYsWFlUHV7Rx40a9+uqratWqlYYOHUqjFgAcyJEjRzRz5kxFRUXxjQcAsLOjR4/qxIkTql69utWlAIClvv76a61cuVLPPPMMJwfghrhks/Zf//qXNm3alPP7hg0bNGDAALVt21aRkZH6+uuvNW7cOAsrhCv57bfftGjRIo0aNUoNGjSwuhwAwCUuXLig8ePH68knn1Tx4sWtLgcAXE5MTIx69OhhdRkAYJkzZ87orbfe0vnz5/X000/Ly8slv8SOIuSSr6B169Zp7NixOb/HxMQoPDxckydPliSFhoYqOjpaL7/8skUVwlVcuHBBsbGxio6O5kJiAOCApkyZogceeEAhISFWlwIALmfnzp3KyspStWrVrC4FACyxbt06zZkzR3369FHt2rWtLgcuwiWbtSdPnsw1uP2PP/6o+++/P+f3W2+9Vfv377eiNLiYBQsWKCIigkYtADigH3/8UcWKFVPz5s2tLgUAXE5mZqamT5+u559/3upSAKDIHTt2TJ988olKlCih0aNHcyF72JVLDoMQHBycM2Ztenq61qxZk2uM2tOnT8vb29uq8uAiUlJStG7dOrVp08bqUgAAf7N//379+OOP6tWrl9WlAIBLWrBggW6//XYFBgZaXQoAFKnt27frnXfeUZcuXfT444/TqIXduWSztn379oqMjNRPP/2kqKgoFS9ePFdDbf369apRo4aFFcIVzJ49Wz169GDgcABwMKmpqZo0aZKefvppeXp6Wl0OALicQ4cOad26dWrbtq3VpQBAkVq3bp1iYmIUFRWlsLAwq8uBi3LJYRDGjh2rhx56SHfccYf8/f01ffr0XF9T//jjj3XfffdZWCGc3erVq5Wenq66detaXQoA4BLnz5/Xf//7X/Xq1UulSpWyuhwAcDlbtmzRp59+qmHDhnHSAgC3snHjRi1YsECRkZEMhYhC5ZLN2rJly2rZsmVKTk6Wv7//ZWfVzJkzR/7+/hZVB2e3fft2LViwQFFRUVaXAgC4RGpqql5//XV169aND9MAoBDEx8crISFBL730kooVK2Z1OQBQZJKTkxUTE6PRo0fTqEWhc8lm7UVXGj+pdOnSRVwJXMWBAwf0ySef8EkaADiYi43arl270qgFgEIwd+5cnTx5UiNGjJCHh0uOpgcAV/TFF1+oW7du8vX1tboUuAH+lwXy6dixY3r//fc1fPhwlShRwupyAAB/Sk9P1xtvvKGHHnpI9erVs7ocAHA5P/74o06ePKlBgwbRqAXgdnbs2KFTp06pYcOGVpcCN8H/tEA+nD59Wm+//baeeuopxkAEAAeSkZGht99+W+3bt1f9+vWtLgcAXM7mzZu1fPlyDRgwwOpSAKDIpaena9q0aRo0aJDVpcCN0KwFruHEiRP6z3/+o4EDB6pChQpWlwMA+FNWVpbee+89tWnTRk2aNLG6HABwOTt37tTnn3+uYcOGcUYtALc0c+ZMderUSSVLlrS6FLgRlx6zFrhRR44c0bvvvqsnnnhClSpVsrocAMAlFi1apFq1aqlVq1ZWlwIALic5OVlTp05VVFQUFxMD4Ja2bNmiM2fOqHnz5laXAjfDx6PAFRw4cEDvvvuuhg4dSqMWABzMkSNH9Ntvv6l9+/ZWlwIALmfLli16/fXX9c9//lP+/v5WlwMARc4Yo08//ZQhYGAJmrXXYcKECQoLC5Ofn5/Cw8O1cuXKfC0XExMjm82mzp07F26BsJs//vhDkyZN0vPPP6/y5ctbXQ7gkshUFJQxRh988IGeeOIJ2Ww2q8sBHAa5CntYtWqVvvjiC40aNUpVqlSxuhzAMmSqe/vll1906623cnFxWIJmbT599tlnGj58uKKjo7VmzRo1atRIEREROnLkyFWX27Nnj55//nm1adOmiCrFjcjKytKSJUv06aefKjIykouJAYWETMWN+Pnnn1WrVi0FBwdbXQrgMMhV2MP69esVFxenESNGMPQB3BqZ6t6MMVqyZInatWtndSlwUzRr8+mtt97SoEGD1L9/f9WrV0+TJk1S8eLF9fHHH19xmczMTD366KN65ZVXVL169SKsFgWxYcMGRUdHKyMjQ6NGjeIrX0AhIlNRUEePHtXSpUv18MMPW10K4FDIVdyo/fv367PPPtMzzzwjb29vq8sBLEWmurdffvlFjRs3lq+vr9WlwE3RrM2H9PR0rV69Wm3bts2Z5uHhobZt2yohIeGKy/3rX/9S+fLl8z3GSVpamlJSUnLdUDS+++47LV26VFFRUerQoQNXuwUKEZmKgsrKytLEiRM1ZMgQeXlxjVTgoqLIVTLVtX377beaMWOGhg8fzhm1cHu8V3Vv27Zt05IlS9SxY0erS4EboyOVD8eOHVNmZuZlX7cMDg5WYmJinsv8/PPPmjJliiZPnpzv9YwbN06BgYE5t9DQ0BuqG/mzadMmrV27Vs8++6yKFy9udTmAyyNTUVCff/65WrVqpQoVKlhdCuBQiiJXyVTXlJaWpvfee09Hjx7VyJEjVaZMGatLAizHe1X3tWzZMs2dO1eRkZHy8fGxuhy4MZq1heD06dPq3bu3Jk+erLJly+Z7uaioKCUnJ+fc9u/fX4hVQpKOHz+u2bNn6+mnn+YiNYCDIlMhSUuWLNHp06dzneUCoGAKkqtkqutJS0vTuHHj1KZNGz366KO8FwYKiPeqzi8rK0szZ87U9u3bFRkZyUXFYDm+Q5gPZcuWlaenp5KSknJNT0pKUkhIyGXz//HHH9qzZ0+u0+azsrIkSV5eXtq2bZtq1Khx2XK+vr6MiVKELly4oP/973964okn5OfnZ3U5gNsgU3G9VqxYoS1btmjo0KE0E4A8FEWukqmuJSsrS++8844eeughNWzY0OpyAIfCe1X3kp6errfeekvNmjXjpAA4DM6szQcfHx81bdpUcXFxOdOysrIUFxenli1bXjZ/nTp1tGHDBq1bty7n9uCDD+quu+7SunXr+HqDAzDG6P3339cDDzygihUrWl0O4FbIVFyP7du369tvv9VTTz1Foxa4AnIV1+Ps2bP6z3/+o9atW9OoBfJAprqPjIwMvfnmm2rXrh2NWjgUzqzNp+HDh6tv375q1qyZmjdvrnfeeUdnz55V//79JUl9+vRRpUqVNG7cOPn5+al+/fq5lg8KCpKky6bDGnPmzFFYWJhuvfVWq0sB3BKZivxITEzUjBkzFBUVxQXFgGsgV5Efhw8f1vjx49WnTx/Vrl3b6nIAh0Wmuj5jjN59913dfffdaty4sdXlALnwl08+de/eXUePHtWYMWOUmJioxo0ba/HixTmDju/bt08eHpyo7Aw2btyow4cP65lnnrG6FMBtkam4lpMnT+q9997Ts88+y7hhQD6Qq7iWDRs26PPPP9ezzz57XeNqAu6ITHV9y5cvV9WqVRUeHm51KcBlbMYYY3URyFtKSooCAwOVnJysgIAAq8txCUePHtU777yjUaNGqVixYlaXAzvhWEF+8DpxHmfPntVrr72mf/7zn6pcubLV5bgdjhXkB68T57JhwwbNnz9fzz33HNdqsADHC/KD10nRycrK0pgxYzR69GjGDXZC7nCs8FEQ3EZycrLeeecdDR06lEYtADio1NRUvfHGG+rTpw+NWgCwg/3792vu3Ll6/vnnadQCgKTFixerZcuWNGrhsGjWwi0YYzRx4kQNGjRI5cuXt7ocAEAeLp5R27VrV9WsWdPqcgDA6aWmpmrSpEkaOnQoTQkAkLRixQpt2bJF999/v9WlAFfEmLVwC/Pnz1e9evUUFhZmdSkAgDxs27ZNM2bMUN++fVWrVi2rywEAp3fkyBFNnDhRPXr0UOnSpa0uBwAst2HDBsXFxenFF19kzGE4NJq1cHkbN27U9u3b9fzzz1tdCgAgDytXrtS3336rkSNHcjExALCD5cuXa8mSJRo8eLAqVKhgdTkAYLldu3bpyy+/VGRkpLy8aIXBsfEKhUs7ePCgPvvsM7300kuy2WxWlwMA+JvvvvtO69ev540zANhJQkKCVqxYodGjR5OrACDp5MmTmjJliiIjIxkSBk6B/73hsk6fPq2JEydy1VsAcEDGGM2dO1fJycl69tln+UANAOzg999/V3x8vF544QUatQAgKT09Xe+++66GDBmikiVLWl0OkC8M0gGXNXXqVPXt25cxugDAwaSlpWnSpEmy2WwaMGAAjVoAsIMdO3YoNjZWzz33HI1aAJCUkZGhd999Vx07dlTlypWtLgfIN/4Xh0vasGGDfH19uUgNADiY3377TbGxserSpYuaNWtmdTkA4BJOnjypadOmaeTIkfLx8bG6HACw3LFjxzRhwgS1a9dOTZs2tboc4LrQrIXLuXDhgmJiYjRy5EirSwEA/OnEiROaPHmyKlasqDFjxjBeGADYycUzxwYPHsxFGgFA2WN3L1q0SEOGDFHFihWtLge4bjRr4XK++OILtWvXjjerAOAAjDFavHixEhISNGDAAFWtWtXqkgDAZaSnp+udd95R+/btFRoaanU5AGCp1NRUTZ06Vb6+voqOjmZIGDgtXrlwKQcPHtTu3bvVvXt3q0sBALe3a9cuTZ8+XeHh4Xr55Zfl4cFQ+QBgL+fPn9cbb7yh9u3b8xVfAG5v27ZtmjFjhrp27arGjRtbXQ5wQ2jWwmUcOXJEEydO1LBhw7hYDQBYKD09XZ988omSk5M1bNgwlSpVyuqSAMClJCYmasKECfrHP/6hunXrWl0OAFgmNTVVs2bNUkpKiqKiouTv7291ScANo1kLl7B//35NmjRJQ4cOVbly5awuBwDc1uHDhzVx4kR17tyZM70AwM4OHTqkuXPnKj09XYMHD1alSpWsLgkALJOYmKjx48erS5cuvO+ES6FZC6d35MgRTZo0SS+++KICAwOtLgcA3NbKlSu1cOFCPfPMM3xwBgB2lJGRoY8//lhnzpxR165dGZ8WgNs7ePCgJk6cqGeffVZly5a1uhzArmjWwqklJyfr3Xff1dChQ2nUAoBFtm3bpi+//FLly5fXqFGj5O3tbXVJAOAyUlJS9M477ygiIkLh4eFWlwMAlrv4zdrnnntOpUuXtrocwO5o1sJpnT9/Xm+++aYef/xxlS9f3upyAMCtZGRkaN26dfrmm29UoUIFPf744ypTpozVZQGAS9m3b58++OADDRw4UNWqVbO6HACw3J49e/TRRx/xzVq4NJq1cEoXLlzQm2++qZ49e6pq1apWlwMAbmXTpk2aNWuWmjZtqmeeeYY3ygBgZ8YYffPNN1q1apVeeOEFBQUFWV0SAFjujz/+0LRp0zRixAiVLFnS6nKAQkOzFk4nKytL7777riIiIrj6LQAUsZ9++kk///yzRo8eLT8/P6vLAQCXc/jwYU2ePFlNmjTR6NGjZbPZrC4JACy3bds2ffrppxoxYoT8/f2tLgcoVDRr4XRmzpypW265RbfeeqvVpQCAW/nxxx+1bt06vfjii/L09LS6HABwKVlZWfrqq6+0adMmDR48mGG+AEDZ3zRYsGCBNm7cqBEjRqhEiRJWlwQUOg+rCwCux86dO3XixAndc889VpcCAG7lm2++0e+//66nn36aRi0A2FlKSor+/e9/y9/fXy+99BKNWgBQ9oXEXn31VdlsNkVGRtKohdvgzFo4jaysLH3yyScaNmyY1aUAgNvIzMzU7NmzlZ6erqeffpqv4wKAne3evVuTJ0/WwIEDVb16davLAQDLpaWl6auvvtLevXs1YMAAhYSEWF0SUKRo1sJpfP3112rdurVKlSpldSkA4BaOHj2qiRMnqk2bNrr77rutLgcAXM5PP/2kH374QZGRkQoICLC6HACw1MmTJzVv3jzt3btXbdu2VdeuXTlRAG6JZi2cwuHDh7Vhwwa99NJLVpcCAG7hl19+0ZIlSzRkyBBVqFDB6nIAwOXMnz9fBw8e1EsvvcTwMgDcWmZmphYtWqTVq1erZ8+eeuyxx6wuCbAUzVo4vFOnTmn8+PEaOnQon6oBQCFLTU3VlClT5O/vrzFjxsjLi7cKAGBPe/fuVUxMjMLCwjR48GDe3wJwazt37tT06dN1++23Kzo6mkwERLMWDi49PV1vvvkmV8QFgCKwY8cOTZs2Td27d1fDhg2tLgcAXMrhw4c1Y8YMlSxZUr1791bFihWtLgkALGOM0dKlS7Vy5Uq98MILDAUDXIJmLRzajBkz1KFDB4WGhlpdCgC4rKysLM2dO1d79+5VZGSkSpYsaXVJAOAy0tPT9fnnn+vAgQPq06cPTVoAbu/s2bN699131aBBA0VFRTEUDPA3NGvhsBYuXKhixYqpRYsWVpcCAC7ryJEjev/993XbbbdxEQcAsKOMjAytXLlSCxcuVMeOHdWrVy+rSwIAy1389mz37t1Vu3Ztq8sBHBLNWjik3377TTt27NDQoUOtLgUAXNayZcsUFxenwYMHcxExALCT1NRULVmyRL/99puaN2+ukSNHqkSJElaXBQCWM8bof//7nzp06ECjFrgKmrVwODt37tQ333yjkSNHcoYXABSCtLQ0ffjhhwoKCtLo0aO5iBgA3CBjjHbu3Klvv/1Wx48f15133qmxY8fyXhYALjFlyhTdcsstatq0qdWlAA6Nv87gUNauXau5c+cqKiqK5gEAFILdu3drypQpeuSRR9S4cWOrywEAp2aM0fLly7VkyRKFhYWpU6dOqly5stVlAYBDOX/+vCZPnqzQ0FDdc889VpcDODwPqwtwJhMmTFBYWJj8/PwUHh6ulStXXnHeyZMnq02bNipVqpRKlSqltm3bXnV+d2eM0ezZs7VixQq99NJL8vf3t7okAIWMTC1a6enpiomJ0Zw5c/T888/TqAVcELlatDIzM/W///1PBw4c0KhRo/TYY4/RqAVcCJlqHwcPHtT//d//6e6771aXLl2sLgdwCjRr8+mzzz7T8OHDFR0drTVr1qhRo0aKiIjQkSNH8pw/Pj5ePXv21A8//KCEhASFhobqvvvu08GDB4u4cseXmpqqd999VyVLltTgwYNVvHhxq0sCUMjI1KJz9uxZzZ07V//6178UGhqqF154QUFBQVaXBcDOyNWiN2PGDDVo0EDdu3eXj4+P1eUAsCMy1T5+++03ffjhh3ruuedUv359q8sBnIbNGGOsLsIZhIeH69Zbb9X48eMlSVlZWQoNDdXTTz+tyMjIay6fmZmpUqVKafz48erTp0++1pmSkqLAwEAlJycrICDghup3RKmpqfr+++/1yy+/qFu3bmrUqJHVJcFJufqx4orI1MJnjNH333+v+Ph4PfDAA2revDljJyJf3O1YcRVFnavu/jqZO3euUlNT1atXL6tLgRNw9+PFGfFe9cakp6fr888/18mTJzV48GB5e3tbXRJciCsdK1fCoKD5kJ6ertWrVysqKipnmoeHh9q2bauEhIR8Pca5c+d04cIFlS5d+orzpKWlKS0tLef3lJSUghftwA4dOqQFCxbo0KFDuvPOO/XKK68wPi3gRsjUwpecnKxJkyapRo0aeuWVV+ThwRdpAFdWFLnqzpl6qYtDd9lsNj366KNWlwOgEPBeteCMMVq9erXmzZunBx54QC1atOBkAaAA6JDlw7Fjx5SZmang4OBc04ODg7V169Z8PcaIESNUsWJFtW3b9orzjBs3Tq+88soN1ero5s+fr82bN6t79+6qVq2a1eUAsACZWrh+/fVXLViwQAMGDCBnATdRFLnqrpl6KWOMpk+fLn9/fz3yyCNWlwOgkPBe9frt2bNHcXFx2rNnj+rUqaPRo0fLz8/P6rIAp0Wztgi89tpriomJUXx8/FUDKyoqSsOHD8/5PSUlRaGhoUVRYqFLS0vTxx9/rFKlSmnEiBF8ugagwMjUvJ09e1ZTpkxRQECAoqOj+boZgHzLT666W6b+XXJysj788EPdfPPNat++vdXlAHBg7vRe9cSJE5o2bZp8fX11//33q1q1avytD9gBzdp8KFu2rDw9PZWUlJRrelJSkkJCQq667BtvvKHXXntN3333nRo2bHjVeX19feXr63vD9TqaLVu2aObMmXrooYfUtGlTq8sBYDEy1f7279+vSZMm6dFHH1W9evWsLgdAESuKXHWnTL1UZmamFi1apFWrVqlXr16qWbOm1SUBKGS8V722vXv3KiYmRpLUvXt3hYWFWVsQ4GIYxC4ffHx81LRpU8XFxeVMy8rKUlxcnFq2bHnF5V5//XWNHTtWixcvVrNmzYqiVIdijNGiRYu0YMECjRw5kkYtAElkqr0dOnRIkyZN0gsvvECjFnBT5Kr9GWO0bNkyRUdHq1ixYnr55Zdp1AJugky9MmOM5s2bp5iYGA0YMEAjRoygUQsUAs6szafhw4erb9++atasmZo3b6533nlHZ8+eVf/+/SVJffr0UaVKlTRu3DhJ0n/+8x+NGTNGs2bNUlhYmBITEyVJ/v7+8vf3t2w7isrp06c1ZcoUhYSE6Pnnn+erEAByIVPtIykpSRMmTNBzzz2noKAgq8sBYCFy1T6Sk5P19ddfa9u2bbrllls0evRopz3zDUDBkamXO3jwoD7++GM1b95cL774In/jA4WIZm0+de/eXUePHtWYMWOUmJioxo0ba/HixTmDju/bty/X1bbff/99paenX3bxgejoaL388stFWXqRW7FihebPn68+ffqodu3aVpcDwAGRqTdu7969+vDDDzVs2LCrXmkYgHsgV2/MhQsX9PXXX2v9+vV65JFH1KNHD3l58acS4K7I1L8sX75c3333nQIDAzVgwABVrFjR6pIAl2czxhiri0DeUlJSFBgYqOTkZAUEBFhdzjUlJydrypQpKlu2rHr06CEfHx+rS4KbcLZjBdZwldfJhQsXNGfOHO3fv1+DBg2iUQu7c5VjBYXLVV4nxhglJCRo4cKFioiIUJs2bThbDHbnKscLCpejvU6MMZo1a5bOnz+v3r178y0DOAxHO1YKAx8X44alp6frq6++0qZNm9SrVy/ddNNNVpcEAC4nKytLv/32m77++mvdf//96tmzJw0FALgB+/fv19SpU1WnTh1FR0dzogEA/OnChQuaMGGCatasqUcffdTqcgC3Q7MWN2TlypX66quv1KFDBz3yyCM0DgCgEGzYsEExMTFq1qyZoqKiVKJECatLAgCnFhcXp+XLl+vJJ59UmTJlrC4HABzG6tWr9eWXX6pLly4ue6E0wNHRrEWBbN26VbGxsQoODuZMBAAoROvXr9eCBQs0evRo+fn5WV0OADit1NRUrV27Vt99951q1aqll156KdeYkwDgzo4dO6aPPvpIFStW1KhRo1SsWDGrSwLcFs1aXJeNGzfqyy+/VOXKlTVo0CDORACAQhQfH6+EhAQNHz6cRi0AFFBqamrOxcOaN2+uZ5991mWuzg4AN2L79u367bfftGPHDvn7+6tnz56qWrWq1WUBbo9mLfLlxIkTmj59uvz9/fXss8+qZMmSVpcEAC7LGKOYmBidPXtWI0aM4MwvACiA9PR0ffPNN/rtt9/0wAMPMGQXACj7feaKFSu0ePFiValSRa1bt1bPnj15vwk4EJq1uCpjjBYuXKjVq1erT58+qlatmtUlAYDLmzNnjnx9fdWzZ0+rSwEAp7R27VrNnTtXERERGjt2LE1aAG7v7NmzWr16tZYtW6YaNWooKipKvr6+VpcFIA80a3FFxhjNmDFDxYoV05gxY3iTCwBFYOXKlTp06JCGDRtmdSkA4HROnDih8ePHq0qVKhozZgyNCABu79y5c4qJidGBAwfUqlUrPfnkkypVqpTVZQG4Cpq1yNOpU6f0wQcfqF69eurYsaPV5QCAy8vIyNDHH3+szMxMPfXUU1aXAwBO5cKFCznfBhs8eLAqVapkdUkAYLlNmzZp1qxZ6t69ux577DGrywGQTzRrkYsxRsuWLdN3332nAQMGKCwszOqSAMDlZWZm6u2331br1q3VqlUrq8sBAKeyc+dOTZ06Vffdd5/+9a9/8W0wAJA0d+5cHTx4UKNGjVKxYsWsLgfAdaBZC0nZF2BYs2aNFi5cqMaNGys6OlpeXrw8AKCwHTt2TO+//77uuusuGrUAcB2MMfr222+1Zs0aRUZGcgFcAPjTsmXLdPLkSQ0dOtTqUgAUAN04N5SVlaXdu3dr586d2rp1q+Li4hQeHq6bb75ZI0eO5FM3AChEp0+fVkJCgtasWaP09HR5e3vrscce4yu7AHAd0tLS9MEHHygkJESRkZGcTQsAf1q5cqVWrlyp4cOHW10KgAKiWetmtm/frhkzZqhWrVq66aab1KdPHz3zzDO8wQWAQpaRkaEPP/xQp0+fVnh4uIYOHcqHYwBQAElJSRo/frwefvhhNW7c2OpyAMBhzJ8/X9u3b9ewYcPk4eFhdTkACohmrRtJTEzUrFmzFBUVpRIlSlhdDgC4DWOMJk2apKZNm6ply5ZWlwMATmvTpk2aPXu2nnnmGZUvX97qcgDAYaxatUqHDx/Wc889x8lYgJOjWesmjDH65JNP1LdvXxq1AFBEDh06pGXLlmnTpk267bbbaNQCwA1YsmSJ1q1bp5deeolvJgDAJU6cOKHY2FiNGTOGRi3gAmjWuolvv/1W1atXV7Vq1awuBQBc2tGjR7V582atW7dOGRkZioiIULdu3fgqGgAUUEZGhiZPnqzAwEC9+OKLNCIA4G/Gjx+vIUOGyMfHx+pSANgBzVo3cOLECS1fvlzR0dFWlwIALskYozVr1ujrr79W2bJldfPNN6tHjx4KDg62ujQAcGqnTp3Su+++q/vuu49vJwBAHnbs2KHKlStzsVrAhdCsdXHGGE2ePFn9+/fnrC4AKATr16/X3LlzVa9ePb3wwgsMNQMAdnLo0CFNmDBB//znP1WlShWrywEAh3PixAlNmzZNw4YNs7oUAHZEs9aFZWVl6cMPP1T9+vUVFhZmdTkA4FJSU1M1ceJEBQQEaMSIETRpAcAOMjIytHr1an3//ffy9vbW0KFDuZAYAFxBbGys+vTpo3LlylldCgA7olnroowxev/991WvXj3dddddVpcDAC7lzJkzeuutt/TQQw+pfv36VpcDAE7PGKMFCxZoxYoVatq0qZ555hk+BAOAq0hPT9eePXv02GOPWV0KADujWeuiZsyYoapVq9KoBYBC8P7776tnz56qWbOm1aUAgNNLTEzURx99pMaNG2vs2LFcQAwA8mH27Nnq0KGD1WUAKAQ0a13Qnj17lJKSor59+1pdCgC4nD179shms9GoBYAbdO7cOX399dfasWOHBgwYoAoVKlhdEgA4ha+++kqZmZkKDw+3uhQAhYBmrYvJyMhQbGysIiIirC4FAFzO/v37NXnyZL344otWlwIATm3FihWaP3++HnzwQXXr1o2zaQEgnzZv3qzdu3dr6NChVpcCoJDQrHUxU6ZM0c0336w6depYXQoAuIz09HT9+OOP+umnn/TCCy8oMDDQ6pIAwCmlpqZqypQpKlasmF5++WV5e3tbXRIAOI1Tp05p5syZGjlyJB9yAS6MZq2LyMzM1MyZM1WmTBnde++9VpcDAC5j27ZtmjFjhtq0aaMxY8bIy4v/OgHgemVkZGjjxo2aM2eOunXrpkaNGlldEgA4lXXr1mnOnDkaMmSI/P39rS4HQCHiL04XsHnzZs2aNUv33HMPFxQDADvau3evZs2apZEjR3JVcgAogHPnzmn27Nnat2+f6tatq8jISJUsWdLqsgDAaVy4cEEzZsxQenq6Ro8eLT8/P6tLAlDIaNY6ufT0dH366ac0EgDAzi4dn5Z8BYDrt3//fk2aNEk9evTQgAEDrC4HAJzS9OnTVatWLd1+++1WlwKgiNCsdXJTpkxR586daSQAgB3t2bNHkydP1gsvvKCAgACrywEAp7N161Z9+umnev7551WqVCmrywEAp3PhwgXNnTtXmZmZNGoBN0Oz1gn0+rKXut7SVV1v7io/r+yvPGRlZemTTz5RuXLldOutt1pcIQA4j7wy9aJz585p5syZOn36tJ5//nkFBQVZUyQAOIn2n7ZXcJlgda7dWV1v7iqPLA/NmjVLiYmJioqKUvHixa0uEQCcSq8ve+nBeg9qzzd7FHF3hG677TarSwJQxGzGGGN1EchbSkqKAgMDZYuyyfgalfIrpemdp+vOinfq7bffVuvWrXXPPfdYXSZguYvHSnJyMmdB4oqulKkda3fMmScmJoYLNcLtkanIj4uvE0VKHsU8lGWy5O/pr/vT7tcLD77AyQTAJchV5Mff36sGeAdo5sMzc71XBeAemephdQHOZMKECQoLC5Ofn5/Cw8O1cuXKq84/Z84c1alTR35+fmrQoIEWLVpUoPVe7KefSj2lTjGdNPC/A/Xoo4/SqAXg1BwlU+dvmy9JOnLkiLZv36677767QI8LAFazKlezTJYk6WzmWc31mqvDAYcL9DgA4Eisfq96+sLpXO9VAbgPmrX59Nlnn2n48OGKjo7WmjVr1KhRI0VEROjIkSN5zr98+XL17NlTAwYM0Nq1a9W5c2d17txZGzduLHANRkbGGC0utliVqlYq8OMAgNUcJVMlqV9sP+3cs1Off/652rRpI09PzwI/JgBYxdFyNTUjtcCPAwBWI1MBWIlhEPIpPDxct956q8aPHy8pe8zY0NBQPf3004qMjLxs/u7du+vs2bNasGBBzrQWLVqocePGmjRpUr7WeenXy5R7WEV90uUT9WrYq8DbA7gSd/gahKtxtEx9SA9pdKfRql+/vry8GM4d7o1MdU5FnatXy1SJ96rApchV5+No71XJVOAv7pCpnFmbD+np6Vq9erXatm2bM83Dw0Nt27ZVQkJCnsskJCTkml+SIiIirjj/9fCweWje1nk3/DgAYAWHy1R5SHWkxo0b06gF4JQcLld5rwrAiZGpAKzGX6X5cOzYMWVmZio4ODjX9ODgYG3dujXPZRITE/OcPzEx8YrrSUtLU1paWs7vycnJf96Re74sZenI8SNKSUm5jq0AXNfFY4EvCjgHh8zUE2QqcBGZ6nyKIlfzm6kS71WBvyNXnYtDvlclU4Ec7pCpNGsdyLhx4/TKK69cfsfbl0/6WT8r8InAwi8KcCLHjx/P/uoQIDIVuFFkKi51PZkqkatAXshVXIr3qsCNceVMpVmbD2XLlpWnp6eSkpJyTU9KSlJISEiey4SEhFzX/JIUFRWl4cOH5/x+6tQpVa1aVfv27XPqF2BKSopCQ0O1f/9+px9PhG1xTMnJyapSpYpKly5tdSnIBzL1xrnS8esq2+Iq2yGRqc6oKHKVTHUObItjIledC+9Vb4wrHbtsi2Nyh0ylWZsPPj4+atq0qeLi4tS5c2dJ2QOMx8XF6amnnspzmZYtWyouLk7Dhg3LmbZ06VK1bNnyiuvx9fWVr6/vZdMDAwOd/mCSpICAAJfYDoltcVQeHgzD7QzIVPtxpePXVbbFVbZDIlOdSVHkKpnqXNgWx0SuOgfeq9qHKx27bItjcuVMpVmbT8OHD1ffvn3VrFkzNW/eXO+8847Onj2r/v37S5L69OmjSpUqady4cZKkoUOH6o477tCbb76pDh06KCYmRqtWrdKHH35o5WYAgEMgUwHAvshVALAfMhWAlWjW5lP37t119OhRjRkzRomJiWrcuLEWL16cM4j4vn37cnX1W7VqpVmzZmnUqFEaOXKkatasqdjYWNWvX9+qTQAAh0GmAoB9kasAYD9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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Step 4: Psychometric Function\n",
    "\n",
    "Run multiple trials to measure choice accuracy as a function of coherence:"
   ],
   "id": "7bfb87939521e440"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:33.062520600Z",
     "start_time": "2026-03-21T13:55:31.969476300Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# Parameters\n",
    "coherence_levels = np.array([-0.5, -0.25, -0.1, 0.0, 0.1, 0.25, 0.5])\n",
    "n_trials = 20  # trials per coherence\n",
    "decision_threshold = 0.5  # S value threshold\n",
    "\n",
    "\n",
    "def single_trial(coh):\n",
    "    # Fresh model each trial\n",
    "    model = brainmass.WongWangStep(\n",
    "        in_size=1,\n",
    "        noise_s1=brainmass.OUProcess(1, sigma=0.02 * u.nA, tau=2.0 * u.ms),\n",
    "        noise_s2=brainmass.OUProcess(1, sigma=0.02 * u.nA, tau=2.0 * u.ms),\n",
    "    )\n",
    "    model.init_all_states()\n",
    "\n",
    "    # Simulate\n",
    "    def step(i):\n",
    "        with brainstate.environ.context(i=i, t=i * brainstate.environ.get_dt()):\n",
    "            model.update(coherence=coh)\n",
    "            return model.S1.value, model.S2.value\n",
    "\n",
    "    brainstate.transform.for_loop(step, np.arange(int(1.5 * u.second / brainstate.environ.get_dt())))\n",
    "\n",
    "    # Decision: which population won?\n",
    "    choice = u.math.where(model.S1.value > model.S2.value, 1, 0)\n",
    "    return choice\n",
    "\n",
    "\n",
    "def multi_trials(coh):\n",
    "    choices = brainstate.transform.vmap2(lambda: single_trial(coh), axis_size=n_trials)()\n",
    "    return choices.mean()\n",
    "\n",
    "\n",
    "@brainstate.transform.jit\n",
    "def multi_coherences():\n",
    "    return brainstate.transform.vmap2(multi_trials)(coherence_levels)\n",
    "\n",
    "\n",
    "choice_prob = multi_coherences()"
   ],
   "id": "72bc7c014de904e",
   "outputs": [],
   "execution_count": 6
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-21T13:55:33.349754Z",
     "start_time": "2026-03-21T13:55:33.170624800Z"
    }
   },
   "cell_type": "code",
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "plt.plot(coherence_levels * 100, choice_prob * 100, 'bo-', markersize=10, linewidth=2)\n",
    "plt.axhline(50, color='gray', linestyle='--', alpha=0.5)\n",
    "plt.axvline(0, color='gray', linestyle='--', alpha=0.5)\n",
    "\n",
    "plt.xlabel('Motion Coherence (%)', fontsize=12)\n",
    "plt.ylabel('P(Choose Population 1) %', fontsize=12)\n",
    "plt.title('Psychometric Function', fontsize=14)\n",
    "plt.ylim([0, 100])\n",
    "plt.grid(True, alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "1f8964b81442ebe9",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "### Step 5: Attractor Dynamics\n",
    "\n",
    "The Wong-Wang model exhibits bistable attractor dynamics. Let's visualize the attractor landscape:"
   ],
   "id": "b4bb266a13a254b6"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "start_time": "2026-03-21T13:55:33.367473Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# Run many trials with zero coherence to see bistability\n",
    "n_trials_attractor = 30\n",
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "for trial in range(n_trials_attractor):\n",
    "    model = brainmass.WongWangStep(\n",
    "        in_size=1,\n",
    "        noise_s1=brainmass.OUProcess(1, sigma=0.025 * u.nA, tau=2.0 * u.ms),\n",
    "        noise_s2=brainmass.OUProcess(1, sigma=0.025 * u.nA, tau=2.0 * u.ms),\n",
    "    )\n",
    "    model.init_all_states()\n",
    "\n",
    "\n",
    "    def step(i):\n",
    "        with brainstate.environ.context(i=i, t=i * brainstate.environ.get_dt()):\n",
    "            model.update(coherence=0.0)  # Zero coherence\n",
    "            return model.S1.value, model.S2.value\n",
    "\n",
    "\n",
    "    S1, S2 = brainstate.transform.for_loop(step, np.arange(int(2.0 * u.second / brainstate.environ.get_dt())))\n",
    "\n",
    "    # Color by final choice\n",
    "    color = 'blue' if S1[-1, 0] > S2[-1, 0] else 'red'\n",
    "    ax.plot(S1[:, 0], S2[:, 0], color=color, linewidth=0.5, alpha=0.5)\n",
    "\n",
    "# Mark attractors\n",
    "ax.plot([0.8], [0.2], 'b*', markersize=20, label='Attractor 1 (S1 wins)')\n",
    "ax.plot([0.2], [0.8], 'r*', markersize=20, label='Attractor 2 (S2 wins)')\n",
    "ax.plot([0], [0], 'ko', markersize=10, label='Unstable fixed point')\n",
    "\n",
    "# Diagonal\n",
    "ax.plot([0, 1], [0, 1], 'k--', alpha=0.3, label='S1=S2 (indecision)')\n",
    "\n",
    "ax.set_xlabel('S1', fontsize=12)\n",
    "ax.set_ylabel('S2', fontsize=12)\n",
    "ax.set_title('Attractor Landscape (c=0): Bistable Decision States', fontsize=14)\n",
    "ax.legend(loc='upper right')\n",
    "ax.set_xlim([0, 1])\n",
    "ax.set_ylim([0, 1])\n",
    "ax.set_aspect('equal')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "id": "6a1b7ae5d71fc25",
   "outputs": [],
   "execution_count": null
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Exercises\n",
    "\n",
    "### Exercise 1: Reaction Time Analysis\n",
    "\n",
    "Measure how long it takes to reach a decision:\n",
    "\n",
    "```python\n",
    "def measure_reaction_time(S1_trace, S2_trace, threshold=0.5):\n",
    "    \"\"\"Find when |S1 - S2| exceeds threshold.\"\"\"\n",
    "    diff = np.abs(S1_trace - S2_trace)\n",
    "    crossing = np.where(diff > threshold)[0]\n",
    "    return crossing[0] if len(crossing) > 0 else len(S1_trace)\n",
    "```\n",
    "\n",
    "Questions:\n",
    "1. How does reaction time vary with coherence?\n",
    "2. Plot reaction time vs coherence (chronometric function)\n",
    "\n",
    "### Exercise 2: Speed-Accuracy Tradeoff\n",
    "\n",
    "Explore how noise affects decision-making:\n",
    "1. Increase noise sigma from 0.02 to 0.05 nA\n",
    "2. What happens to accuracy? To reaction time?\n",
    "3. Is there a speed-accuracy tradeoff?\n",
    "\n",
    "### Exercise 3: Whole-Brain Decision Network\n",
    "\n",
    "Create multiple interconnected decision units:\n",
    "\n",
    "```python\n",
    "# Multiple decision areas\n",
    "model = brainmass.WongWangStep(in_size=10)  # 10 decision units\n",
    "```\n",
    "\n",
    "Add coupling between units and explore how network structure affects decision-making."
   ],
   "id": "7e4d0be4d519ccbb"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Summary\n",
    "\n",
    "In this tutorial, you learned:\n",
    "\n",
    "1. **Wong-Wang model**: A biophysically-inspired model for perceptual decision-making\n",
    "2. **NMDA dynamics**: Slow synaptic time constants enable temporal integration of evidence\n",
    "3. **Coherence effects**: Stimulus strength determines accuracy and speed\n",
    "4. **Attractor dynamics**: Decisions emerge from competition between bistable states\n",
    "\n",
    "### Key Insights\n",
    "\n",
    "- **Evidence integration**: The slow NMDA time constant ($\\tau_S \\approx$ 100ms) allows accumulation of noisy sensory evidence\n",
    "- **Winner-take-all**: Cross-inhibition creates competition leading to a clear winner\n",
    "- **Bistability**: At zero coherence, the system can settle into either attractor\n",
    "\n",
    "### Neuroscience Connection\n",
    "\n",
    "The model captures key features observed in monkey LIP neurons during random dot motion tasks:\n",
    "- Ramping activity during decision formation\n",
    "- Threshold crossing predicts choice and reaction time\n",
    "- Psychometric and chronometric functions match behavior"
   ],
   "id": "6beee2bdef22eb68"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## References\n",
    "\n",
    "1. Wong, K.-F., & Wang, X.-J. (2006). A recurrent network mechanism of time integration in perceptual decisions. *Journal of Neuroscience*, 26(4), 1314-1328.\n",
    "\n",
    "2. Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. *Annual Review of Neuroscience*, 30, 535-574.\n",
    "\n",
    "3. Shadlen, M. N., & Newsome, W. T. (2001). Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. *Journal of Neurophysiology*, 86(4), 1916-1936.\n"
   ],
   "id": "6bef703672a798cf"
  }
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