{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"execution": {},
"id": "view-in-github"
},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"# Example Data Project: the Train Illusion\n",
"\n",
"Marius 't Hart, Megan Peters, Paul Schrater, Jean Laurens, Gunnar Blohm\n",
"\n",
"**Disclaimer**: this is a \"toy\" data neuroscience project used to demonstrate the [10 step procedure of how-to-model](https://doi.org/10.1523/ENEURO.0352-19.2019). It is not meant to be state of the art research."
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"---\n",
"# Setup"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Install dependencies\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cellView": "form",
"execution": {},
"tags": [
"hide-input"
]
},
"outputs": [],
"source": [
"# @title Install dependencies\n",
"!pip install tqdm --quiet"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"execution": {}
},
"outputs": [],
"source": [
"# Imports\n",
"\n",
"# for matrices and plotting\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# for random distributions\n",
"from scipy.stats import norm, poisson\n",
"\n",
"# for logistic regression\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.model_selection import cross_val_score"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Helper functions\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" Generate the Data\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cellView": "form",
"execution": {},
"tags": [
"hide-input"
]
},
"outputs": [],
"source": [
"# @title Helper functions\n",
"# @markdown Generate the Data\n",
"\n",
"\n",
"def generateSpikeTrains():\n",
"\n",
" gain = 2\n",
" neurons = 50\n",
" movements = [0, 1, 2]\n",
" repetitions = 800\n",
"\n",
" np.random.seed(37)\n",
"\n",
" # set up the basic parameters:\n",
" dt = 1/100\n",
" start, stop = -1.5, 1.5\n",
" t = np.arange(start, stop + dt, dt) # a time interval\n",
" Velocity_sigma = 0.5 # std dev of the velocity profile\n",
" Velocity_Profile = norm.pdf(t, 0, Velocity_sigma)/norm.pdf(0, 0, Velocity_sigma) # The Gaussian velocity profile, normalized to a peak of 1\n",
"\n",
" # set up the neuron properties:\n",
" Gains = np.random.rand(neurons) * gain # random sensitivity between 0 and `gain`\n",
" FRs = (np.random.rand(neurons) * 60 ) - 10 # random base firing rate between -10 and 50\n",
"\n",
" # output matrix will have this shape:\n",
" target_shape = [len(movements), repetitions, neurons, len(Velocity_Profile)]\n",
"\n",
" # build matrix for spikes, first, they depend on the velocity profile:\n",
" Spikes = np.repeat(Velocity_Profile.reshape([1, 1, 1, len(Velocity_Profile)]),\n",
" len(movements)*repetitions*neurons, axis=2).reshape(target_shape)\n",
"\n",
" # multiplied by gains:\n",
" S_gains = np.repeat(np.repeat(Gains.reshape([1, 1, neurons]),\n",
" len(movements)*repetitions, axis=1).reshape(target_shape[:3]),\n",
" len(Velocity_Profile)).reshape(target_shape)\n",
" Spikes = Spikes * S_gains\n",
"\n",
" # and multiplied by the movement:\n",
" S_moves = np.repeat( np.array(movements).reshape([len(movements), 1, 1, 1]),\n",
" repetitions*neurons*len(Velocity_Profile), axis=3 ).reshape(target_shape)\n",
" Spikes = Spikes * S_moves\n",
"\n",
" # on top of a baseline firing rate:\n",
" S_FR = np.repeat(np.repeat(FRs.reshape([1, 1, neurons]), len(movements)*repetitions, axis=1).reshape(target_shape[:3]),\n",
" len(Velocity_Profile)).reshape(target_shape)\n",
" Spikes = Spikes + S_FR\n",
"\n",
" # can not run the poisson random number generator on input lower than 0:\n",
" Spikes = np.where(Spikes < 0, 0, Spikes)\n",
"\n",
" # so far, these were expected firing rates per second, correct for dt:\n",
" Spikes = poisson.rvs(Spikes * dt)\n",
"\n",
" return Spikes\n",
"\n",
"\n",
"def subsetPerception(spikes):\n",
"\n",
" movements = [0, 1, 2]\n",
" split = 400\n",
" subset = 40\n",
" hwin = 3\n",
"\n",
" [num_movements, repetitions, neurons, timepoints] = np.shape(spikes)\n",
"\n",
" decision = np.zeros([num_movements, repetitions])\n",
"\n",
" # ground truth for logistic regression:\n",
" y_train = np.repeat([0, 1, 1], split)\n",
" y_test = np.repeat([0, 1, 1], repetitions - split)\n",
"\n",
" m_train = np.repeat(movements, split)\n",
" m_test = np.repeat(movements, split)\n",
"\n",
" # reproduce the time points:\n",
" dt = 1/100\n",
" start, stop = -1.5, 1.5\n",
" t = np.arange(start, stop + dt, dt)\n",
"\n",
" w_idx = list((abs(t) < (hwin*dt)).nonzero()[0])\n",
" w_0 = min(w_idx)\n",
" w_1 = max(w_idx) + 1 # python...\n",
"\n",
" # get the total spike counts from stationary and movement trials:\n",
" spikes_stat = np.sum( spikes[0, :, :, :], axis=2)\n",
" spikes_move = np.sum( spikes[1:, :, :, :], axis=3)\n",
"\n",
" train_spikes_stat = spikes_stat[:split, :]\n",
" train_spikes_move = spikes_move[:, :split, :].reshape([-1, neurons])\n",
"\n",
" test_spikes_stat = spikes_stat[split:, :]\n",
" test_spikes_move = spikes_move[:, split:, :].reshape([-1, neurons])\n",
"\n",
" # data to use to predict y:\n",
" x_train = np.concatenate((train_spikes_stat, train_spikes_move))\n",
" x_test = np.concatenate((test_spikes_stat, test_spikes_move))\n",
"\n",
" # this line creates a logistics regression model object, and immediately fits it:\n",
" population_model = LogisticRegression(solver='liblinear',\n",
" random_state=0).fit(x_train, y_train)\n",
"\n",
" # solver, one of: 'liblinear', 'newton-cg', 'lbfgs', 'sag', and 'saga'\n",
" # some of those require certain other options\n",
" #print(population_model.coef_) # slope\n",
" #print(population_model.intercept_) # intercept\n",
"\n",
" ground_truth = np.array(population_model.predict(x_test))\n",
" ground_truth = ground_truth.reshape([3, -1])\n",
"\n",
" output = {}\n",
" output['perception'] = ground_truth\n",
" output['spikes'] = spikes[:, split:, :subset, :]\n",
"\n",
" return output\n",
"\n",
"\n",
"def getData():\n",
"\n",
" spikes = generateSpikeTrains()\n",
"\n",
" dataset = subsetPerception(spikes=spikes)\n",
"\n",
" return dataset\n",
"\n",
"\n",
"dataset = getData()\n",
"perception = dataset['perception']\n",
"spikes = dataset['spikes']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot Functions\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"cellView": "form",
"execution": {},
"tags": [
"hide-input"
]
},
"outputs": [],
"source": [
"# @title Plot Functions\n",
"\n",
"def rasterplot(spikes,movement,trial):\n",
"\n",
" [movements, trials, neurons, timepoints] = np.shape(spikes)\n",
" trial_spikes = spikes[movement,trial, :, :]\n",
" trial_events = [((trial_spikes[x, :] > 0).nonzero()[0] - 150)/100 for x in range(neurons)]\n",
" dt = 1/100\n",
"\n",
" plt.figure()\n",
" plt.eventplot(trial_events, linewidths=1);\n",
" plt.title('movement: %d - trial: %d'%(movement, trial))\n",
" plt.ylabel('neuron')\n",
" plt.xlabel('time [s]')\n",
"\n",
"\n",
"def plotCrossValAccuracies(accuracies):\n",
" f, ax = plt.subplots(figsize=(8, 3))\n",
" ax.boxplot(accuracies, vert=False, widths=.7)\n",
" ax.scatter(accuracies, np.ones(8))\n",
" ax.set(\n",
" xlabel=\"Accuracy\",\n",
" yticks=[],\n",
" title=f\"Average test accuracy: {accuracies.mean():.2%}\"\n",
" )\n",
" ax.spines[\"left\"].set_visible(False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"----\n",
"# Phenomenon\n",
"*Part of Steps 1-2*\n",
"\n",
"The train illusion occurs when sitting on a train and viewing another train outside the window. Suddenly, the other train *seems* to move, i.e. you experience visual motion of the other train relative to your train. But which train is actually moving?\n",
"\n",
"Often people mix this up. In particular, they think their own train might be moving when it's the other train that moves; or vice versa. The illusion is usually resolved once you gain vision of the surroundings that lets you disambiguate the relative motion; or if you experience strong vibrations indicating that it is indeed your own train that is in motion."
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"----\n",
"# Question\n",
"\n",
"*Part of Step 1*\n",
"\n",
"We assume that we have build the train illusion model (see the other example project colab). That model predicts that accumulated sensory evidence from vestibular signals determines the decision of whether self-motion is experienced or not. We now have vestibular neuron data (simulated in our case, but let's pretend) and would like to see if that prediction holds true.\n",
"\n",
"The data contains $N$ neurons and $M$ trials for each of 3 motion conditions: no self-motion, slowly accelerating self-motion and faster accelerating self-motion.\n",
"\n",
"\\begin{align}\n",
"N &= 40\\\\\n",
"M &= 400\\\\\n",
"\\end{align}\n",
"\n",
"**So we can ask the following question**: \"Does accumulated vestibular neuron activity correlate with self-motion judgements?\""
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"# Background\n",
"\n",
"_Part of step 2_"
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"While it seems a well-known fact that vestibular signals are noisy, we should check if we can also find this in the literature."
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"Let's also see what's in our data, there should be a 4d array called `spikes` that has spike counts (positive integers), a 2d array called `perception` with self-motion judgements (0=no motion or 1=motion). Let's see what this data looks like:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"execution": {}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(3, 400, 40, 301)\n",
"(3, 400)\n",
"[0.355 0.7575 0.975 ]\n"
]
}
],
"source": [
"print(np.shape(spikes))\n",
"print(np.shape(perception))\n",
"print(np.mean(perception, axis=1))"
]
},
{
"cell_type": "markdown",
"metadata": {
"execution": {}
},
"source": [
"In the `spikes` array, we see our 3 acceleration conditions (first dimension), with 400 trials each (second dimensions) and simultaneous recordings from 40 neurons (third dimension), across 3 seconds in 10 ms bins (fourth dimension). The first two dimensions are also there in the `perception` array.\n",
"\n",
"Perfect perception would have looked like [0, 1, 1]. The average judgements are far from correct (lots of self-motion illusions) but they do make some sense: it's closer to 0 in the no-motion condition and closer to 1 in both of the real-motion conditions.\n",
"\n",
"The idea of our project is that the vestibular signals are noisy so that they might be mis-interpreted by the brain. Let's see if we can reproduce the stimuli from the data:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"execution": {}
},
"outputs": [
{
"data": {
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",
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