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https://github.com/NikVard/memstim-hh
03 January 2024, 01:25:48 UTC
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Tip revision: 563f808f6c4f40630f5b8876cc0b440cdf4159e8 authored by NikVard on 22 September 2023, 08:19:24 UTC
[UPDATE] Updated default figure names in scripts
Tip revision: 563f808
Phase_reset_Onslow_v2.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4d34446c-252a-42f0-a6f9-264bb68d899b",
   "metadata": {},
   "source": [
    "# Onslow et al. 2014\n",
    "\n",
    "### A Canonical Circuit for Generating Phase-Amplitude Coupling\n",
    "\n",
    "Replicating the Onslow model, consisting of a set of coupled E-I populations generating theta-nested gamma oscillations. The authors used the Wilson-Cowan formalism. Equations and parameters are given in the paper (Methods, _Description of the model_). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0c26e8b1-2785-42a6-967a-fdbd1d988791",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "from brian2 import *\n",
    "\n",
    "from tqdm.notebook import tqdm\n",
    "from scipy.signal import welch\n",
    "from matplotlib import ticker\n",
    "\n",
    "from ModelFiles.equations import *\n",
    "from ModelFiles.functions import *\n",
    "from ModelFiles.global_parameters import *\n",
    "\n",
    "# Suppress code generation messages on the console\n",
    "BrianLogger.suppress_name('resolution_conflict')\n",
    "BrianLogger.suppress_hierarchy('brian2.codegen')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "abd2b0ad-c7dd-4ae8-b932-b5723c166ff6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mplb\n",
    "\n",
    "# Text parameters\n",
    "fsize_ticks = fsize_legends = 8\n",
    "fsize_xylabels = 9\n",
    "fsize_titles = 10\n",
    "fsize_figtitles = 11\n",
    "sizebar_off = 50 # sizebar offset\n",
    "\n",
    "# Color selection\n",
    "c_inh = '#bf616a'\n",
    "c_exc = '#5e81ac'\n",
    "\n",
    "# ILLUSTRATOR STUFF\n",
    "mplb.rcParams['pdf.fonttype'] = 42\n",
    "mplb.rcParams['ps.fonttype'] = 42\n",
    "mplb.rcParams['axes.titlesize'] = 11\n",
    "mplb.rcParams['axes.labelsize'] = 9\n",
    "\n",
    "# Arial font everywhere\n",
    "# ILLUSTRATOR STUFF\n",
    "plt.rcParams['pdf.fonttype'] = 42\n",
    "plt.rcParams['ps.fonttype'] = 42\n",
    "\n",
    "plt.rcParams.update({\n",
    "    \"text.usetex\": False,\n",
    "    \"font.family\": \"sans-serif\",\n",
    "    \"font.sans-serif\": \"Arial\",\n",
    "})\n",
    "\n",
    "plt.rcParams['font.family'] = 'sans-serif'\n",
    "plt.rcParams['font.sans-serif'] = 'Arial'\n",
    "plt.rcParams['mathtext.fontset'] = 'custom'\n",
    "plt.rcParams['mathtext.rm'] = 'Arial'\n",
    "plt.rcParams['mathtext.it'] = 'Arial:italic'\n",
    "plt.rcParams['mathtext.bf'] = 'Arial:bold'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ee9bc3bb-977f-438e-9c6c-19909c70a75d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Onslow equations\n",
    "eqs_onslow = '''\n",
    "    dE/dt = 1/tau_E * (-E + 1 / (1 + exp(-beta*(gain_E*theta_E + W_EE*E - W_IE*I + g_stim_E*stim_E(t-delay) - xm)))) + sigma_E*sqrt(2/tau_E)*xi_E : 1\n",
    "    dI/dt = 1/tau_I * (-I + 1 / (1 + exp(-beta*(gain_I*theta_I + W_EI*E - W_II*I + g_stim_I*stim_I(t-delay) - xm)))) + sigma_I*sqrt(2/tau_I)*xi_I : 1\n",
    "    \n",
    "    theta_E : 1 (linked)\n",
    "    theta_I : 1 (linked)\n",
    "    \n",
    "    g_stim_E : 1\n",
    "    g_stim_I : 1\n",
    "    \n",
    "    delay : second\n",
    "'''\n",
    "\n",
    "# Kuramoto oscillators\n",
    "eqs_kuramoto = '''\n",
    "    dTheta/dt = ((omega + (kN * PIF) - gain*X*sin(Theta - pi/2 + offset)) * second**-1) : 1\n",
    "    PIF = .5 * (sin(ThetaPreInput - Theta)) : 1\n",
    "    ThetaPreInput : 1\n",
    "    omega : 1 (constant)\n",
    "    kN : 1 (shared)         # k/N ratio, affects sync.\n",
    "    gain : 1 (shared)       # this is the input gain, affects the phase reset aggressiveness\n",
    "    offset : 1 (shared)     # range [0, 2*pi], controls phase reset PRC\n",
    "    X : 1 (linked)          # this is linked to the firing rates\n",
    "'''\n",
    "\n",
    "# synapses\n",
    "syn_kuramoto_eqs = '''\n",
    "    ThetaPreInput_post = Theta_pre\n",
    "'''\n",
    "\n",
    "# Order parameter group calculation equations\n",
    "pop_avg_eqs = '''\n",
    "    x : 1\n",
    "    y : 1\n",
    "    coherence = sqrt(x**2 + y**2) : 1\n",
    "    phase = arctan(y/x) + int(x<0 and y>0)*pi - int(x<0 and y<0)*pi: 1\n",
    "    rhythm = coherence * sin(phase) : 1\n",
    "    rhythm_pos = coherence * (sin(phase)+1)/2 : 1\n",
    "    rhythm_simple = rhythm : 1\n",
    "    rhythm_abs = abs(rhythm) : 1\n",
    "    rhythm_rect = rhythm_pos : 1\n",
    "    rhythm_zero = 0*rhythm_rect : 1   # for debugging\n",
    "'''\n",
    "\n",
    "syn_avg_eqs = '''\n",
    "    x_post = cos(Theta_pre)/N_incoming : 1 (summed)\n",
    "    y_post = sin(Theta_pre)/N_incoming : 1 (summed)\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "783b7f1b-9585-4c74-b251-77a72894ab87",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fixed parameters\n",
    "seed_val = 42\n",
    "seed(seed_val)\n",
    "\n",
    "duration = 3*second\n",
    "sim_dt = 0.1*ms\n",
    "stim_dt = 1*ms\n",
    "\n",
    "# Default simulation dt\n",
    "defaultclock.dt = sim_dt\n",
    "\n",
    "# Weights\n",
    "W_EE = 2*2.4\n",
    "W_EI = 2*2.\n",
    "W_IE = 2*2.\n",
    "W_II = 2*0.\n",
    "\n",
    "# Gains of inputs\n",
    "gain_E = 0.7\n",
    "gain_I = 0.\n",
    "\n",
    "tau_E = 3.2*ms\n",
    "tau_I = 3.2*ms\n",
    "\n",
    "sigma_E = 0.\n",
    "sigma_I = 0.\n",
    "\n",
    "xm = 1.\n",
    "beta = 4.\n",
    "\n",
    "# Kuramoto oscillators\n",
    "N_K = 100\n",
    "sync_K = 25\n",
    "gain_K = 0\n",
    "offset_K = 0. #+pi/2.\n",
    "f0 = 4.\n",
    "sigma_K = 0.5\n",
    "\n",
    "# stimulation\n",
    "S0 = 1\n",
    "theta_deg = 75\n",
    "theta = theta_deg*pi/180\n",
    "tau_stim = 6*ms\n",
    "t_stim_on = 900*ms\n",
    "t_stim_off = t_stim_on + 20*stim_dt\n",
    "\n",
    "# stimulation\n",
    "#stim_dt = defaultclock.dt\n",
    "tv = linspace(0, int(duration/ms), int(duration/stim_dt+1))\n",
    "stim_E_tv = S0*(tv>t_stim_on/ms) - S0*(tv>t_stim_off/ms)\n",
    "stim_I_tv = S0*(tv>t_stim_on/ms) - S0*(tv>t_stim_off/ms)\n",
    "stim_E = TimedArray(stim_E_tv, dt=stim_dt)\n",
    "stim_I = TimedArray(stim_I_tv, dt=stim_dt)\n",
    "\n",
    "# PR Gain (def. 90)\n",
    "pr_gain = 90\n",
    "\n",
    "# PRC calculations\n",
    "N_sims = 32\n",
    "delays = linspace(0, 1/f0, N_sims+1)*second"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bb3daa1b-3dee-4e55-9fba-aef973ebc2f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make coupled E-I group\n",
    "G_pop = NeuronGroup(N=1, model=eqs_onslow, method='euler', name='Population')\n",
    "G_pop.g_stim_E = 1.\n",
    "G_pop.g_stim_I = 1.\n",
    "\n",
    "# Make Kuramoto oscillators group\n",
    "G_kur = NeuronGroup(N=N_K,\n",
    "                model=eqs_kuramoto,\n",
    "                threshold='True',\n",
    "                method='euler',\n",
    "                name='Kuramoto_oscillators_N_%d' % N_K)\n",
    "theta0 = 2*pi*rand(N_K) # uniform U~[0,2π]\n",
    "omega0 = 2*pi*(f0 + sigma_K*randn(N_K)) # ~N(2πf0,σ)\n",
    "G_kur.Theta = theta0\n",
    "G_kur.omega = omega0\n",
    "G_kur.kN = sync_K\n",
    "G_kur.gain = gain_K\n",
    "G_kur.offset = offset_K\n",
    "\n",
    "# Add synapses\n",
    "syn_kur =  Synapses(G_kur, G_kur, on_pre=syn_kuramoto_eqs, method='euler', name='Kuramoto_intra')\n",
    "syn_kur.connect(condition='i!=j')\n",
    "\n",
    "# Kuramoto order parameter group\n",
    "G_pop_avg = NeuronGroup(1,\n",
    "                model=pop_avg_eqs,\n",
    "                #method='euler',\n",
    "                name='Kuramoto_averaging')\n",
    "r0 = 1/N_K * sum(exp(1j*G_kur.Theta))\n",
    "G_pop_avg.x = real(r0)  # avoid division by zero\n",
    "G_pop_avg.y = imag(r0)\n",
    "syn_avg = Synapses(G_kur, G_pop_avg, syn_avg_eqs, name='Kuramoto_avg')\n",
    "syn_avg.connect()\n",
    "\n",
    "# Link inputs / outputs\n",
    "G_kur.X = linked_var(G_pop, 'E')\n",
    "G_pop.theta_E = linked_var(G_pop_avg, 'rhythm_rect') # theta input to E\n",
    "G_pop.theta_I = linked_var(G_pop_avg, 'rhythm_zero') # no input to I\n",
    "\n",
    "# Make the state monitors\n",
    "mon = StateMonitor(G_pop, ['E', 'I'], record=True)\n",
    "mon_kur = StateMonitor(G_kur, ['Theta'], record=True)\n",
    "mon_order_param = StateMonitor(G_pop_avg, ['coherence', 'phase', 'rhythm', 'rhythm_rect'], record=True)\n",
    "monitors_list = [mon, mon_kur, mon_order_param]\n",
    "\n",
    "# Make a net and store it's state\n",
    "net = Network()\n",
    "net.add(G_pop, G_kur, G_pop_avg)\n",
    "net.add(syn_kur, syn_avg)\n",
    "net.add(monitors_list)\n",
    "net.store('initialized')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b1bf0787-32f3-4ce0-8feb-119cb6b17760",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Restore network state\n",
    "net.restore('initialized')\n",
    "\n",
    "# Set the gain variable on the Kuramoto group\n",
    "G_kur.gain = pr_gain\n",
    "\n",
    "# Run a simulation with E-stimulation\n",
    "G_pop.g_stim_E = 1.\n",
    "G_pop.g_stim_I = 0.\n",
    "G_pop.delay = 0*second\n",
    "\n",
    "# Run a simulation\n",
    "net.run(duration)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3c0db9a9-7dc9-4cdb-b39d-d6b4e098c9f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xlims_rhythm = [0.4, 1.9]\n",
    "\n",
    "# Make a figure\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "\n",
    "# Use gridspec\n",
    "gs = fig.add_gridspec(2,1, height_ratios=(1,3),\n",
    "                      left=0.1, right=0.9, bottom=0.1, top=0.9,\n",
    "                      hspace=0.25)\n",
    "\n",
    "# Create the axes\n",
    "ax_rhythm = fig.add_subplot(gs[0])\n",
    "ax_onslow = fig.add_subplot(gs[1])\n",
    "\n",
    "# Plot the subplot figure\n",
    "ax_rhythm.plot(mon_order_param.t/second, mon_order_param.rhythm_rect[0], color='k', label='Theta rhythm')\n",
    "ax_onslow.plot(mon.t/second, mon.E[0], color='g', linewidth=1, label='Exc')\n",
    "ax_onslow.plot(mon.t/second, mon.I[0], color='r', linewidth=1, label='Inh')\n",
    "\n",
    "# Indicate stimulation\n",
    "# ax_rhythm.axvline(x=t_stim_on/second, ymin=-1, ymax=3, c=\"red\", linewidth=1, zorder=-1)\n",
    "# ax_onslow.axvline(x=t_stim_on/second, ymin=-1, ymax=3, c=\"red\", linewidth=1, zorder=-1)\n",
    "ax_rhythm.scatter(t_stim_on/second, 1.1, c='red', marker='v', clip_on=False, s=50)\n",
    "\n",
    "\n",
    "# Add the labels\n",
    "# ax_onslow.set_ylabel('Gain = {0}'.format(pr_gain), fontsize=10)\n",
    "# ax_onslow.set_xlabel('Time [s]', fontsize=10)\n",
    "\n",
    "# Fixed tick locators\n",
    "ax_onslow.set_xticks(np.arange(0, 2.5, 0.5))\n",
    "\n",
    "# Set the xlims/ylims\n",
    "ax_rhythm.set_xlim(xlims_rhythm)\n",
    "ax_onslow.set_xlim(xlims_rhythm)\n",
    "ax_rhythm.set_ylim([0, 1])\n",
    "ax_onslow.set_ylim([0, 1])\n",
    "\n",
    "\n",
    "# Remove the box borders\n",
    "ax_rhythm.spines['top'].set_visible(False)\n",
    "ax_rhythm.spines['right'].set_visible(False)\n",
    "ax_rhythm.spines['bottom'].set_visible(False)\n",
    "ax_rhythm.spines['left'].set_visible(False)\n",
    "\n",
    "ax_onslow.spines['top'].set_visible(False)\n",
    "ax_onslow.spines['right'].set_visible(False)\n",
    "ax_onslow.spines['bottom'].set_visible(False)\n",
    "ax_onslow.spines['left'].set_visible(False)\n",
    "\n",
    "# Remove ticks\n",
    "ax_rhythm.get_xaxis().set_ticks([])\n",
    "ax_rhythm.get_yaxis().set_ticks([])\n",
    "ax_onslow.get_xaxis().set_ticks([])\n",
    "ax_onslow.get_yaxis().set_ticks([])\n",
    "\n",
    "# Titles\n",
    "ax_rhythm.set_title('Theta rhythm', loc='left', fontsize=fsize_titles)\n",
    "ax_onslow.set_title('Population Rates', loc='left', fontsize=fsize_titles)\n",
    "\n",
    "# Add sizebars\n",
    "add_sizebar(ax_rhythm, [xlims_rhythm[1]+0.03, xlims_rhythm[1]+0.03], [0, 1], 'black', ['0', '1'], fsize=9, rot=[0, 0], \n",
    "            textx=[xlims_rhythm[1]+0.05]*2, texty=[0, 1], \n",
    "            ha='left', va='center')\n",
    "\n",
    "add_sizebar(ax_onslow, [xlims_rhythm[1]-0.25, xlims_rhythm[1]-0.], [-0.1, -0.1], 'black', '250ms', fsize=9, rot=0, \n",
    "            textx=np.mean([xlims_rhythm[1]-0.25, xlims_rhythm[1]-0.]), texty=-0.13, \n",
    "            ha='center', va='top')\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Add the legends\n",
    "ax_onslow.legend()\n",
    "\n",
    "# lines_labels = [ax.get_legend_handles_labels() for ax in fig.axes]\n",
    "# lines, labels = [sum(lol, []) for lol in zip(*lines_labels)]\n",
    "# fig.legend(lines, labels)\n",
    "\n",
    "\n",
    "# Show the figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "197597cb-562a-4d40-b982-9c042ecb847b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import ConnectionPatch\n",
    "\n",
    "\"\"\" Fixed parameters to affect fontsizes \"\"\"\n",
    "fsize_ticks = fsize_legends = 8\n",
    "fsize_xylabels = 9\n",
    "fsize_misc = 10\n",
    "fsize_titles = 11\n",
    "fsize_panels = 12\n",
    "\n",
    "\n",
    "xlims_rhythm = [0.43, 1.86]\n",
    "ylims_all = [-0.1, 1.1]\n",
    "\n",
    "# Make a figure\n",
    "fig = plt.figure(figsize=(8,5))\n",
    "\n",
    "# Use gridspec\n",
    "gs = fig.add_gridspec(3,2, height_ratios=(1,2,2),\n",
    "                      left=0.15, right=0.975, bottom=0.01, top=0.99,\n",
    "                      width_ratios=(0.2, 0.8),\n",
    "                      # hspace=0.15,\n",
    "                      wspace=0.2)\n",
    "\n",
    "# Create the axes\n",
    "ax_placeholder = fig.add_subplot(gs[:,0])\n",
    "ax_rhythm = fig.add_subplot(gs[0,1])\n",
    "ax_onslow_I = fig.add_subplot(gs[1,1])\n",
    "ax_onslow_E = fig.add_subplot(gs[2,1])\n",
    "\n",
    "# Plot the subplot figure\n",
    "ax_rhythm.plot(mon_order_param.t/second, mon_order_param.rhythm_rect[0], color='k', label='Theta rhythm')\n",
    "ax_onslow_E.plot(mon.t/second, mon.E[0], color=c_exc, linewidth=1, label='Exc')\n",
    "ax_onslow_I.plot(mon.t/second, mon.I[0], color=c_inh, linewidth=1, label='Inh')\n",
    "\n",
    "# Indicate stimulation\n",
    "# ax_rhythm.axvline(x=t_stim_on/second, ymin=-1, ymax=3, c=\"red\", linewidth=1, zorder=-1)\n",
    "# ax_onslow.axvline(x=t_stim_on/second, ymin=-1, ymax=3, c=\"red\", linewidth=1, zorder=-1)\n",
    "ax_rhythm.scatter(t_stim_on/second, 1.1, c='red', marker='v', clip_on=False, s=50)\n",
    "# ax_rhythm.vlines(x=t_stim_on/second, ymin=-19.6, ymax=1., color='gray', alpha=0.75, ls='--', linewidth=1.5, zorder=101, rasterized=False, clip_on=False)\n",
    "con = ConnectionPatch(xyA=(t_stim_on/second, 1.1), xyB=(t_stim_on/second, -0.05), coordsA=\"data\", coordsB=\"data\",\n",
    "                      axesA=ax_rhythm, axesB=ax_onslow_E, linestyle='--', linewidth=1.5, color='gray', alpha=0.75)\n",
    "ax_onslow_E.add_artist(con)\n",
    "\n",
    "# Add the labels\n",
    "# ax_onslow.set_ylabel('Gain = {0}'.format(pr_gain), fontsize=10)\n",
    "# ax_onslow.set_xlabel('Time [s]', fontsize=10)\n",
    "\n",
    "# Fixed tick locators\n",
    "ax_onslow.set_xticks(np.arange(0, 2.5, 0.5))\n",
    "\n",
    "# Set the xlims/ylims\n",
    "ax_rhythm.set_xlim(xlims_rhythm)\n",
    "ax_rhythm.set_ylim(ylims_all)\n",
    "ax_onslow_E.set_xlim(xlims_rhythm)\n",
    "ax_onslow_E.set_ylim(ylims_all)\n",
    "ax_onslow_I.set_xlim(xlims_rhythm)\n",
    "ax_onslow_I.set_ylim(ylims_all)\n",
    "\n",
    "# Remove the box borders\n",
    "ax_placeholder.spines['top'].set_visible(False)\n",
    "ax_placeholder.spines['right'].set_visible(False)\n",
    "ax_placeholder.spines['bottom'].set_visible(False)\n",
    "ax_placeholder.spines['left'].set_visible(False)\n",
    "\n",
    "ax_rhythm.spines['top'].set_visible(False)\n",
    "ax_rhythm.spines['right'].set_visible(False)\n",
    "ax_rhythm.spines['bottom'].set_visible(False)\n",
    "ax_rhythm.spines['left'].set_visible(False)\n",
    "\n",
    "ax_onslow_E.spines['top'].set_visible(False)\n",
    "ax_onslow_E.spines['right'].set_visible(False)\n",
    "ax_onslow_E.spines['bottom'].set_visible(False)\n",
    "ax_onslow_E.spines['left'].set_visible(False)\n",
    "\n",
    "ax_onslow_I.spines['top'].set_visible(False)\n",
    "ax_onslow_I.spines['right'].set_visible(False)\n",
    "ax_onslow_I.spines['bottom'].set_visible(False)\n",
    "ax_onslow_I.spines['left'].set_visible(False)\n",
    "\n",
    "# Remove ticks\n",
    "ax_placeholder.get_xaxis().set_ticks([])\n",
    "ax_placeholder.get_yaxis().set_ticks([])\n",
    "ax_rhythm.get_xaxis().set_ticks([])\n",
    "ax_rhythm.get_yaxis().set_ticks([])\n",
    "ax_onslow_E.get_xaxis().set_ticks([])\n",
    "ax_onslow_E.get_yaxis().set_ticks([])\n",
    "ax_onslow_I.get_xaxis().set_ticks([])\n",
    "ax_onslow_I.get_yaxis().set_ticks([])\n",
    "\n",
    "# Titles\n",
    "ax_placeholder.set_title('Network Schematic', loc='center', fontsize=fsize_titles)\n",
    "ax_rhythm.set_title('Theta rhythm', loc='center', fontsize=fsize_titles)\n",
    "ax_onslow_I.set_title('Population Rates', loc='center', fontsize=fsize_titles)\n",
    "\n",
    "# Add sizebars\n",
    "add_sizebar(ax_onslow_E, [xlims_rhythm[1]+0.03, xlims_rhythm[1]+0.03], [0, 0.5], 'black', ['0', '0.5'], fsize=9, rot=[0, 0], \n",
    "            textx=[xlims_rhythm[1]+0.05]*2, texty=[0, 0.5], \n",
    "            ha='left', va='center')\n",
    "\n",
    "add_sizebar(ax_onslow_E, [xlims_rhythm[1]-0.25, xlims_rhythm[1]-0.], [-0.1, -0.1], 'black', '250ms', fsize=9, rot=0, \n",
    "            textx=np.mean([xlims_rhythm[1]-0.25, xlims_rhythm[1]-0.]), texty=-0.13, \n",
    "            ha='center', va='top')\n",
    "\n",
    "# Panels text\n",
    "fig.text(0.0, 0.946, 'A.', weight='bold', fontsize=fsize_panels)\n",
    "fig.text(0.26, 0.946, 'B.', weight='bold', fontsize=fsize_panels)\n",
    "\n",
    "# Add the legend\n",
    "handles_all = []\n",
    "labels_all = []\n",
    "for ax in [ax_onslow_E, ax_onslow_I]:\n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    handles_all += handles\n",
    "    labels_all += labels\n",
    "# ax_onslow_I.legend(handles_all, labels_all, loc='best')\n",
    "fig.legend(handles_all, labels_all, loc=[0.9, 0.55], fontsize=fsize_legends)\n",
    "\n",
    "# Tight layout\n",
    "gs.tight_layout(fig)\n",
    "\n",
    "# Save the figure\n",
    "fig.savefig(\"PR_Onslow_rev_eLife.png\")\n",
    "fig.savefig(\"PR_Onslow_rev_eLife.pdf\")\n",
    "\n",
    "# Show the figure\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aee557ff-8aad-4be7-9a15-8f26f0aacd6f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}

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