{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Simulating multivariate effects with intersubject variability\n", "\n", "In the previous examples, we set the size of the effect to 0.5. The effect size modulates the decoding accuracy, by taking into account the noise present at teh single subject level. Importantly, the amplitude of the effect was assumed to be fixed across participants. However, in most data sets, that will not be the case, as the **true** decoding accuracy surely varies between participants.\n", "\n", "In order to simulate between participants variability, you can specify a between subjects noise parameter. Specifically, instead of simulating multivariate effect of the same strength across participants, we draw the effect strength from a normal distribution with a given mean and standard deviation. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Setting up the simulation\n", "\n", "We will stick to the same parameters as before, with the kernel and everything, just adding the noise parameter." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "from scipy.stats import gamma as gamma_dist\n", "import matplotlib.pyplot as plt\n", "\n", "# Creating the design matrix of our 2 by two balanced design:\n", "X = np.array([[1, 1, -1, -1] * 40, [1, -1] * 80]).T\n", "\n", "# Add descriptors:\n", "cond_names = [\"category\", \"attention\"]\n", "X = pd.DataFrame(X, columns=cond_names) # Add a column for the interaction between category and attention\n", "mapping = {\n", " \"category\": {1: \"face\", -1: \"object\"},\n", " \"attention\": {1: \"attended\", -1: \"unattended\"},\n", "}\n", "\n", "# Specifying the effects:\n", "effects = [\n", " {\"condition\": 'category', \"windows\": [0.1, 0.2], \"effect_size\": 0.5}, \n", " {\"condition\": 'attention', \"windows\": [0.3, 0.4], \"effect_size\": 0.5}\n", " ] # Packaging them in a list to pass to the simulator class\n", "\n", "# Data parameters:\n", "n_channels = 32 # EEG system with 32 electrodes\n", "n_subjects = 20 # Recording from 20 subjects\n", "noise_std = 1 / 2 # Variance of the data\n", "ch_cov = None # Assuming that the data of each sensor are independent\n", "sfreq = 50 # Simulating data at 50Hz\n", "tmin = -0.25\n", "tmax = 1.0\n", "\n", "# Generate our kernel:\n", "t = np.arange(0, 1, 1 / sfreq) # time vector (in seconds)\n", "kernel = gamma_dist(a=2, scale=0.08).pdf(t)\n", "kernel /= kernel.max() * 5 # Normalize peak to 0.25\n", "\n", "# Between subject noise:\n", "intersub_noise_std = 1 / 8" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Simulating the data\n", "\n", "The simulation of the data is exactly the same as before, except with the addition of intersubjects noise:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from multisim import Simulator\n", "\n", "sims = Simulator(\n", " X, # Design matrix\n", " effects, # Effects to simulate\n", " noise_std, # Observation noise\n", " n_channels, # Number of channelss\n", " n_subjects, # Number of subjects\n", " tmin,\n", " tmax, # Start and end of epochs\n", " sfreq, # Sampling frequency of the data\n", " ch_cov=ch_cov, # Spatial covariance of the data\n", " kern=kernel, # Temporal kernel,\n", " intersub_noise_std=intersub_noise_std, # Intersubject variability\n", ")\n", "epochs = sims.export_to_mne(X=X.copy(), mapping=mapping)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Decoding analysis and plotting\n", "\n", "We will perform the analysis on all subjects and show how the added between subject noise changes the results" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using a threshold of 1.729133\n", "stat_fun(H1): min=-2.7821216769418657 max=4.770225544943381\n", "Running initial clustering …\n", "Found 4 clusters\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2c0ca1611fb847a498e1a6ecfbbf0e14", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | Permuting : 0/1023 [00:00" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot the results\n", "fig, ax = plt.subplots(2, 1)\n", "\n", "# Plot the results of category decoding:\n", "ax[0].plot(epochs[0].times, np.mean(scores_category, axis=0), color=\"r\")\n", "ax[0].plot(epochs[0].times, scores_category.T, color=\"k\", alpha=0.5, linewidth=0.5)\n", "\n", "ax[0].plot(\n", " epochs[0].times[sig_mask_cate],\n", " np.ones(np.sum(sig_mask_cate)) * 0.4,\n", " marker=\"o\",\n", " linestyle=\"None\",\n", " color=\"b\",\n", ")\n", "ax[0].set_title(\"Category decoding\")\n", "ax[0].axhline(0.5, color=\"k\", linestyle=\"--\", label=\"chance\")\n", "ax[0].set_ylim([0.3, 1.0])\n", "# Plot the results of attention condition:\n", "ax[1].plot(epochs[0].times, np.mean(scores_attention, axis=0), color=\"r\")\n", "ax[1].plot(epochs[0].times, scores_attention.T, color=\"k\", alpha=0.5, linewidth=0.5)\n", "ax[1].plot(\n", " epochs[0].times[sig_mask_att],\n", " np.ones(np.sum(sig_mask_att)) * 0.4,\n", " marker=\"o\",\n", " linestyle=\"None\",\n", " color=\"g\",\n", ")\n", "ax[1].set_title(\"Attention decoding\")\n", "ax[1].axhline(0.5, color=\"k\", linestyle=\"--\", label=\"chance\")\n", "ax[1].set_xlim([epochs[0].times[0], epochs[0].times[-1]])\n", "ax[1].set_xlabel(\"Times\")\n", "ax[1].set_ylabel(\"Decoding accuracy\")\n", "ax[1].set_ylim([0.3, 1.0])\n", "ax[1].legend()\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The results seem similar to what we had before, though the variance of each subjects decoding is quite high. By comparison, here is what the results look like if we fix the intersubject variance: " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sims = Simulator(\n", " X, # Design matrix\n", " effects, # Effects to simulate\n", " noise_std, # Observation noise\n", " n_channels, # Number of channelss\n", " n_subjects, # Number of subjects\n", " tmin,\n", " tmax, # Start and end of epochs\n", " sfreq, # Sampling frequency of the data\n", " ch_cov=ch_cov, # Spatial covariance of the data\n", " kern=kernel, # Temporal kernel,\n", " intersub_noise_std=0, # Intersubject variability\n", ")\n", "epochs = sims.export_to_mne(X=X.copy(), mapping=mapping)\n", "\n", "# Apply decoding:\n", "scores_category = []\n", "scores_attention = []\n", "\n", "# Loop through each subject:\n", "for epo in epochs:\n", " # Extract the data:\n", " data = epo.get_data()\n", " # Classification of category\n", " scores_category.append(\n", " np.mean(\n", " cross_val_multiscore(\n", " time_decod, data, cate_lbl, cv=5, n_jobs=-1, verbose=\"WARNING\"\n", " ),\n", " axis=0,\n", " )\n", " )\n", " # Classification of attention:\n", " scores_attention.append(\n", " np.mean(\n", " cross_val_multiscore(\n", " time_decod, data, att_lbl, cv=5, n_jobs=-1, verbose=\"WARNING\"\n", " ),\n", " axis=0,\n", " )\n", " )\n", "\n", "scores_category = np.array(scores_category)\n", "scores_attention = np.array(scores_attention)\n", "\n", "# Plot the results:\n", "fig, ax = plt.subplots(2, 1)\n", "\n", "# Plot the results of category decoding:\n", "ax[0].plot(epochs[0].times, np.mean(scores_category, axis=0), color=\"r\")\n", "ax[0].plot(epochs[0].times, scores_category.T, color=\"k\", alpha=0.5, linewidth=0.5)\n", "ax[0].set_title(\"Category decoding\")\n", "ax[0].axhline(0.5, color=\"k\", linestyle=\"--\", label=\"chance\")\n", "ax[0].set_ylim([0.3, 1.0])\n", "# Plot the results of attention condition:\n", "ax[1].plot(epochs[0].times, np.mean(scores_attention, axis=0), color=\"r\")\n", "ax[1].plot(epochs[0].times, scores_attention.T, color=\"k\", alpha=0.5, linewidth=0.5)\n", "ax[1].set_title(\"Attention decoding\")\n", "ax[1].axhline(0.5, color=\"k\", linestyle=\"--\", label=\"chance\")\n", "ax[1].set_xlim([epochs[0].times[0], epochs[0].times[-1]])\n", "ax[1].set_xlabel(\"Times\")\n", "ax[1].set_ylabel(\"Decoding accuracy\")\n", "ax[1].set_ylim([0.3, 1.0])\n", "ax[1].legend()\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you can see, when no between subject variance is specified, the decoding accuracy is more concentrated around the mean, which makes sense. Adding a between subject variance term make the data more realistic, as you will typically have subjects for which the decoding accuracy is really high, and others not so much.\n", "\n", "In the next tutorial, we will explore how to specify various temporal generalization patterns of the simulated data." ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.13.0" } }, "nbformat": 4, "nbformat_minor": 2 }