{
"cells": [
{
"cell_type": "code",
"execution_count": 322,
"metadata": {
"ExecuteTime": {
"end_time": "2020-06-29T11:17:43.231859Z",
"start_time": "2020-06-29T11:17:43.228477Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1.15.2\n"
]
}
],
"source": [
"# %tensorflow_version 1.x\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from time import time\n",
"import tensorflow as tf\n",
"# need tensorflow 1.x version\n",
"# use tensorflow module to improve matrix caclulation speed\n",
"print(tf.__version__)"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {
"ExecuteTime": {
"end_time": "2020-06-29T06:54:53.795343Z",
"start_time": "2020-06-29T06:54:53.792656Z"
}
},
"outputs": [],
"source": [
"plt.rcParams['font.family'] = 'Serif'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2020-06-30T10:30:41.856735Z",
"start_time": "2020-06-30T10:30:41.839763Z"
}
},
"outputs": [],
"source": [
"class KuramotoOsc_tf:\n",
" def __init__(self, k, num_osc, t_max, w0=None, theta=None, ext_A1=0, ext_w1=0, ext_A2=0, ext_w2=0, w_r=0, tau_ext=0, tau_lag=0, noise_std=0, dt=0.001):\n",
" if w0 is None:\n",
" w0 = abs(np.random.normal(loc=1, scale=0, size=[1, num_osc]))\n",
" if theta is None:\n",
" theta = np.random.normal(loc=0, scale=5, size=[1, num_osc])\n",
" self.N = num_osc\n",
" self.k = k\n",
" self.ext_amp1, self.ext_w1 = ext_A1, ext_w1\n",
" self.ext_amp2, self.ext_w2 = ext_A2, ext_w2\n",
" self.tau_ext, self.tau_lag = tau_ext, tau_lag\n",
" self.w_r = w_r\n",
" self.noise_std = noise_std\n",
" self.t_max, self.dt = t_max, dt\n",
" self.itr_all = int(t_max/dt)\n",
" self.w0 = np.array(w0)\n",
" self._init_arrays()\n",
" self.theta_list[0, :] = theta\n",
" self.r_coh[0], self.psi_coh[0] = self.get_coh(0)\n",
" \n",
" def run_model(self):\n",
" # create tensorflow model\n",
" theta_tf = tf.placeholder(tf.float32, shape=(1, self.N))\n",
" F = tf.placeholder(tf.float32, shape=(1, self.N))\n",
" K = tf.placeholder(tf.float32, shape=(1, self.N))\n",
" w0_tf = tf.constant(self.w0, dtype=tf.float32)\n",
" ## use midpoint method to solve ODE\n",
" # Euler 1st\n",
" dsin1 = tf.math.sin(tf.subtract(tf.transpose(theta_tf), theta_tf))\n",
" df1 = tf.add(tf.add(tf.matmul(K, dsin1), w0_tf), F)\n",
" temp_theta = tf.add(theta_tf, tf.multiply(df1, self.dt))\n",
" # Euler 2nd\n",
" dsin2 = tf.math.sin(tf.subtract(tf.transpose(temp_theta), temp_theta))\n",
" df2 = tf.add(tf.add(tf.matmul(K, dsin2), w0_tf), F)\n",
" # update theta\n",
" theta_next = tf.add(theta_tf, tf.multiply(tf.add(df1, df2), self.dt/2))\n",
" \n",
" with tf.Session() as sess:\n",
" for i in range(self.itr_all):\n",
" self.theta_list[i+1, np.newaxis, :] = sess.run(theta_next, feed_dict={theta_tf: self.theta_list[i, np.newaxis, :],\n",
" K: self.get_k(i),\n",
" F: self.external_drive(i)})\n",
" self.theta_list[i+1, :] = np.round(self.theta_list[i+1, :], 10)\n",
" self.r_coh[i+1], self.psi_coh[i+1] = self.get_coh(i+1)\n",
" \n",
" def get_k(self, i):\n",
" # calculate K\n",
" return self.k /(((self.get_freq(i))**2-self.w_r**2)**2+1) / self.N\n",
" \n",
" def external_drive(self, i):\n",
" # AS and OS\n",
" self.phs_as[i, :] = self.ext_w1*self.t[i] + np.random.normal(loc=0, scale=self.noise_std, size=(1, self.N))\n",
" self.phs_os[i] = self.ext_w2*(self.t[i] + self.tau_lag + self.tau_ext)\n",
" return (self.ext_amp1 * np.sin(self.phs_as[i, np.newaxis, :] - self.theta_list[i, np.newaxis, :])\n",
" + self.ext_amp2 * np.sin(self.phs_os[i] - self.theta_list[i, np.newaxis, :]))\n",
" \n",
" def get_freq(self, i):\n",
" return (self.theta_list[i, np.newaxis, :]-self.theta_list[i-1, np.newaxis, :])/self.dt\n",
" \n",
" def get_coh(self, i):\n",
" # calculate r and \\psi\n",
" temp = np.average(np.exp(1j * self.theta_list[i, :]))\n",
" r = abs(temp)\n",
" psi = np.log(temp / r)\n",
" return r, psi.imag\n",
" \n",
" def _init_arrays(self):\n",
" self.t = np.arange(0, self.t_max+self.dt/10, self.dt) # t = [0, self.dt]\n",
" self.theta_list = np.zeros([self.itr_all+1, self.N]) # save theta\n",
" self.phs_as = np.zeros([self.itr_all, self.N])\n",
" self.phs_os = np.zeros(self.itr_all)\n",
" self.r_coh = np.zeros(self.itr_all+1)\n",
" self.psi_coh = np.zeros(self.itr_all+1)\n",
" \n",
"def show_result(model, title, ymax=1):\n",
" # plot result\n",
" plt.figure(dpi=150, figsize=(6, 3))\n",
" # subplot 211\n",
" plt.subplot(211)\n",
" plt.plot(model.t, model.r_coh, 'k', lw=0.8)\n",
" plt.ylabel('r', fontsize=14)\n",
" plt.title(title)\n",
" plt.xlim([0, model.t_max])\n",
" plt.ylim([0, ymax])\n",
" plt.yticks([0, ymax/2, ymax])\n",
" # subplot 212\n",
" plt.subplot(212)\n",
" plt.plot(model.t, model.r_coh * np.sin(model.psi_coh), 'k', lw=0.8)\n",
" plt.xlim([0, model.t_max])\n",
" plt.ylim([-ymax, ymax])\n",
" plt.yticks([-ymax, -ymax/2, 0, ymax/2, ymax])\n",
" plt.xlabel('time t', fontsize=14)\n",
" plt.ylabel(r'r * sin($\\phi$)', fontsize=14)\n",
" # show figure\n",
" plt.tight_layout()\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Results of 'assr', 'out of phase' and 'advanced' condition"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Cortical response"
]
},
{
"cell_type": "markdown",
"metadata": {
"ExecuteTime": {
"end_time": "2020-07-01T02:40:03.916924Z",
"start_time": "2020-07-01T02:40:03.913343Z"
}
},
"source": [
" printf \n"
]
},
{
"cell_type": "code",
"execution_count": 396,
"metadata": {
"ExecuteTime": {
"end_time": "2020-06-30T09:27:04.775487Z",
"start_time": "2020-06-30T09:27:04.771603Z"
}
},
"outputs": [],
"source": [
"# condition\n",
"kmax = 0.8 # k_{max}\n",
"tmax, dt = 100, 0.01 # t_{max}, \\Delta t\n",
"w_r = 2*np.pi/5 # resonance frequency, w_{r}\n",
"num_osc = 1000 # the number of oscillations, N\n",
"# set initial value\n",
"w0 = abs(np.random.normal(loc=w_r, scale=0.5, size=[1, num_osc]))\n",
"theta0 = abs(np.random.normal(loc=0, scale=20, size=[1, num_osc]))"
]
},
{
"cell_type": "code",
"execution_count": 397,
"metadata": {
"ExecuteTime": {
"end_time": "2020-06-30T09:27:18.112097Z",
"start_time": "2020-06-30T09:27:05.240035Z"
}
},
"outputs": [
{
"data": {
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\n",
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