load_cichy_fMRI_MEG.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "load_cichy_fMRI_MEG.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J8FuAReHVFsX"
      },
      "source": [
        "# Data loader"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CX1lDpbfgyD-"
      },
      "source": [
        "## Summary\n",
        "Here we will load data from Cichy et al. 2014 [1]. The data consist of fMRI responses from early visual cortex (EVC) and inferior temporal (IT) cortex and MEG responses at different timepoints in the form of representational dissimilarity matrices (RDMs) to 92 images. These images belong to different categories as shown in the Figure below. \n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aRhugM2Xf1_a"
      },
      "source": [
        "![Screenshot 2021-06-29 175923.jpg](data:image/jpeg;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8KJPoY_QsJ95"
      },
      "source": [
        "## Representational Similarity Analysis (RSA)\n",
        "RSA is a method to relate signals\n",
        "from different source spaces (such as behavior, neural\n",
        "responses, DNN activations) by abstracting signals from\n",
        "separate source spaces into a common similarity space. For\n",
        "this, in each source space, condition-specific responses are\n",
        "compared to each other for dissimilarity (e.g., by calculating\n",
        "Euclidean distances between signals), and the values are\n",
        "aggregated in so-called representational dissimilarity matrices (RDMs) indexed in rows and columns by the conditions\n",
        "compared. RDMs thus summarize the representational\n",
        "geometry of the source space signals. Different from source\n",
        "space signals themselves, RDMs from different sources\n",
        "spaces are directly comparable to each other for similarity\n",
        "and thus can relate signals from different spaces \n",
        "\n",
        "The figure below illustrates how RSA can be applied to different problems by comparing RDMs of different modalities/species."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y8KJwxw7inxQ"
      },
      "source": [
        "![RSA.jpg](data:image/jpeg;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "o6cT8Swpa0yR"
      },
      "source": [
        "## Data from Cichy et al. 2014\n",
        "\n",
        "In the cells below, we will download and visualize MEG and fMRI RDMs. Please refer Figure 1 in [1] to learn details about the image category order in RDMs "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9kyn7SKaDads"
      },
      "source": [
        "#@title Imports\n",
        "import glob\n",
        "import numpy as np\n",
        "import urllib\n",
        "import torch\n",
        "import cv2\n",
        "import argparse\n",
        "import time\n",
        "import random\n",
        "import matplotlib.pyplot as plt\n",
        "import nibabel as nib\n",
        "import pickle\n",
        "from tqdm import tqdm\n",
        "from PIL import Image\n",
        "from torchvision import transforms as trn\n",
        "import scipy.io as sio\n",
        "import h5py\n",
        "import os\n",
        "from PIL import Image\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from torch.autograd import Variable as V\n",
        "from sklearn.decomposition import PCA, IncrementalPCA\n",
        "import torch.nn as nn\n",
        "import torch.utils.model_zoo as model_zoo\n",
        "\n",
        "def loadmat(matfile):\n",
        "    \"\"\"Function to load .mat files.\n",
        "    Parameters\n",
        "    ----------\n",
        "    matfile : str\n",
        "        path to `matfile` containing fMRI data for a given trial.\n",
        "    Returns\n",
        "    -------\n",
        "    dict\n",
        "        dictionary containing data in key 'vol' for a given trial.\n",
        "    \"\"\"\n",
        "    try:\n",
        "        f = h5py.File(matfile)\n",
        "    except (IOError, OSError):\n",
        "        return sio.loadmat(matfile)\n",
        "    else:\n",
        "        return {name: np.transpose(f.get(name)) for name in f.keys()}"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lZrV3T6f7qdZ"
      },
      "source": [
        "#@title Data download\n",
        "!wget -qO data.zip -c https://osf.io/7vpyh/download\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8amcBA92zd0b"
      },
      "source": [
        "%%capture\n",
        "!unzip -o data.zip #unzip the files"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rZF8xqqkDQCC"
      },
      "source": [
        "## Loading MEG RDMs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w1XJNWMDDVXm"
      },
      "source": [
        "# Load MEG RDMs for each time point for all subjects all sessions\n",
        "MEG_RDMs = loadmat(\"MEG_decoding_RDMs.mat\")['MEG_decoding_RDMs']\n",
        "print(MEG_RDMs.shape)  "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z_8aPio3jwB9"
      },
      "source": [
        "Shape of RDM is num_subjects x num_sessions x num_timepoints x num_stimulus x num_stimulus"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RXI2oMM_jr5_"
      },
      "source": [
        "# average RDM across subjects and sessions\n",
        "MEG_RDM_sub_averaged = np.mean(MEG_RDMs,axis=(0,1))\n",
        "del MEG_RDMs"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BDMxx4ufnx8h"
      },
      "source": [
        "#@title visualize subject averaged MEG RDMs\n",
        "timepoint = 420 #@param {type:\"slider\", min:-100, max:600, step:20}\n",
        "\n",
        "# Load RDM at a given timepoint \n",
        "# +100 as the RDMs provided are from -100ms to 1000ms after the stimulus onset\n",
        "RDM = np.array(MEG_RDM_sub_averaged[timepoint+100])\n",
        "\n",
        "# Since the matrix is symmetric we set upper triangular values to NaN\n",
        "RDM[np.triu_indices(RDM.shape[0], 1)] = np.nan\n",
        "\n",
        "# plot the RDM at given timepoint\n",
        "plt.imshow(RDM,\\\n",
        "           cmap=\"bwr\")\n",
        "plt.title(\"MEG RDM at t = \" + str(timepoint))\n",
        "cbar = plt.colorbar()\n",
        "plt.xlabel(\"Stimuli\")\n",
        "plt.ylabel(\"Stimuli\")\n",
        "cbar.ax.get_yaxis().labelpad = 15\n",
        "cbar.ax.set_ylabel('Decoding Accuracy', rotation=270)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Vsd0IKvVJCEu"
      },
      "source": [
        "##Loading fMRI RDMs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VC4iQd73JGRf"
      },
      "source": [
        "fMRI_file = '92_Image_Set/target_fmri.mat'  # path of fMRI RDM file\n",
        "fMRI_RDMs = loadmat(fMRI_file)  # load the fMRI RDMs\n",
        "print(fMRI_RDMs.keys())\n",
        "print(fMRI_RDMs['EVC_RDMs'].shape)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C1cu5oU7j9Tg"
      },
      "source": [
        "fMRI_RDMs is a dictionary with keys 'EVC_RDMs' and 'IT_RDMs' corresponding to ROIs EVC and IT respectively. The shape of each RDM is num_subjects x num_stimulus x num_stimulus"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8W7f5F3qlpm-"
      },
      "source": [
        "#@title visualize subject averaged fMRI RDMs\n",
        "ROI = 'IT' #@param [\"EVC\", \"IT\"]\n",
        "\n",
        "# Average the ROI RDM across subjects \n",
        "RDM = np.array(fMRI_RDMs[ROI + '_RDMs'].mean(axis=0))\n",
        "\n",
        "# Since the matrix is symmetric we set upper triangular values to NaN\n",
        "RDM[np.triu_indices(RDM.shape[0], 1)] = np.nan\n",
        "\n",
        "# plot the ROI RDM at given timepoint\n",
        "plt.imshow(RDM,\\\n",
        "           cmap=\"bwr\")\n",
        "plt.title(ROI + \" RDM\")\n",
        "cbar = plt.colorbar()\n",
        "plt.xlabel(\"Stimuli\")\n",
        "plt.ylabel(\"Stimuli\")\n",
        "cbar.ax.get_yaxis().labelpad = 15\n",
        "cbar.ax.set_ylabel('1-Correlation', rotation=270)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d8MLJH8cctX7"
      },
      "source": [
        "# Example Analyses\n",
        "\n",
        "Below we will perform two analyses:\n",
        "\n",
        "1.   MEG-fMRI comparison: To find out at which timepoint MEG representation is similar to a given ROI's representation. \n",
        "2.   MEG-Deep Neural Network (DNN) comparison: To find out at which timepoint MEG representation is similar to a given DNN layer's representation. \n",
        "\n",
        "In other words, the comparison will inform us about the sequential order of visual feature processing in the cortex. \n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vt8ai7Mmr9_Q"
      },
      "source": [
        "#@title RDM Comparison functions\n",
        "\n",
        "from scipy.stats import spearmanr\n",
        "\n",
        "def RSA_spearman(rdm1,rdm2):\n",
        "    \"\"\"\n",
        "    computes and returns the spearman correlation between lower triangular \n",
        "    part of the input rdms. We only need to compare either lower or upper \n",
        "    triangular part of the matrix as RDM is symmetric\n",
        "    \"\"\"\n",
        "    # get lower triangular part of the RDM1 \n",
        "    lt_rdm1 = get_lowertriangular(rdm1)\n",
        "    # get lower triangular part of the RDM1 \n",
        "    lt_rdm2 = get_lowertriangular(rdm2)\n",
        "    # return Spearman's correlation between lower triangular part of rdm1 & rdm2\n",
        "    return spearmanr(lt_rdm1, lt_rdm2)[0]\n",
        "\n",
        "def get_lowertriangular(rdm):\n",
        "    \"\"\"\n",
        "    returns lower triangular part of the matrix\n",
        "    \"\"\"\n",
        "    num_conditions = rdm.shape[0]\n",
        "    return rdm[np.tril_indices(num_conditions,-1)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zursdOO3rzm-"
      },
      "source": [
        "##MEG-fMRI Comparison"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RmhU-WgUsX-k"
      },
      "source": [
        "#@title Correlating MEG RDMs with fMRI RDMs\n",
        "num_timepoints = MEG_RDM_sub_averaged.shape[0] #get number of timepoints\n",
        "\n",
        "# initialize a dictionary to store MEG and ROI RDM correlation at each timepoint\n",
        "MEG_correlation = {}\n",
        "ROIs = ['EVC','IT']\n",
        "for ROI in ROIs:\n",
        "  MEG_correlation[ROI] = []\n",
        "\n",
        "# for loop that goes over MEG RDMs at all time points and correlate with ROI RDMs\n",
        "for t in range(num_timepoints):\n",
        "  MEG_RDM_t = MEG_RDM_sub_averaged[t,:,:]\n",
        "  for ROI in ROIs:\n",
        "    ROI_RDM = np.mean(fMRI_RDMs[ROI + '_RDMs'],axis=0)\n",
        "    MEG_correlation[ROI].append(RSA_spearman(ROI_RDM,MEG_RDM_t))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TcU2IrixsZbu"
      },
      "source": [
        "#@title Plotting MEG-fMRI comparison\n",
        "\n",
        "plt.rc('font', size=12)\n",
        "fig, ax = plt.subplots(figsize=(10, 6))\n",
        "\n",
        "time_range = range(-100,1201)\n",
        "ax.plot(time_range, MEG_correlation['IT'], color='tab:orange', label='IT')\n",
        "ax.plot(time_range, MEG_correlation['EVC'], color='tab:blue', label='EVC')\n",
        "\n",
        "# Same as above\n",
        "ax.set_xlabel('Time')\n",
        "ax.set_ylabel('Spearmans Correlation')\n",
        "ax.set_title('MEG-fMRI fusion')\n",
        "ax.grid(True)\n",
        "ax.legend(loc='upper left');"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YzIVj7RBsdas"
      },
      "source": [
        "## MEG-DNN Comparison"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kHUxlD_e321P"
      },
      "source": [
        "### Creating DNN (AlexNet) RDMs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HwEf4Ffm4SV9"
      },
      "source": [
        "#@title AlexNet Definition\n",
        "__all__ = ['AlexNet', 'alexnet']\n",
        "\n",
        "\n",
        "model_urls = {\n",
        "    'alexnet': 'https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth',\n",
        "}\n",
        "\n",
        "# Here we redefine AlexNet differently from torchvision code for better understanding\n",
        "class AlexNet(nn.Module):\n",
        "    def __init__(self, num_classes=1000):\n",
        "        super(AlexNet, self).__init__()\n",
        "        self.conv1 = nn.Sequential(\n",
        "            nn.Conv2d(3, 64, kernel_size=11, stride=4, padding=2),\n",
        "            nn.ReLU(inplace=True),\n",
        "            nn.MaxPool2d(kernel_size=3, stride=2),\n",
        "            )\n",
        "        self.conv2 = nn.Sequential(\n",
        "            nn.Conv2d(64, 192, kernel_size=5, padding=2),\n",
        "            nn.ReLU(inplace=True),\n",
        "            nn.MaxPool2d(kernel_size=3, stride=2),\n",
        "            )\n",
        "        self.conv3 = nn.Sequential(\n",
        "            nn.Conv2d(192, 384, kernel_size=3, padding=1),\n",
        "            nn.ReLU(inplace=True),\n",
        "            )\n",
        "        self.conv4 = nn.Sequential(\n",
        "            nn.Conv2d(384, 256, kernel_size=3, padding=1),\n",
        "            nn.ReLU(inplace=True),\n",
        "            )\n",
        "        self.conv5 = nn.Sequential(\n",
        "            nn.Conv2d(256, 256, kernel_size=3, padding=1),\n",
        "            nn.ReLU(inplace=True),\n",
        "            nn.MaxPool2d(kernel_size=3, stride=2),\n",
        "            )\n",
        "        self.fc6 = nn.Sequential(\n",
        "            nn.Dropout(),\n",
        "            nn.Linear(256 * 6 * 6, 4096),\n",
        "            nn.ReLU(inplace=True),\n",
        "            )\n",
        "        self.fc7 =nn.Sequential(\n",
        "            nn.Dropout(),\n",
        "            nn.Linear(4096, 4096),\n",
        "            )\n",
        "        self.fc8 = nn.Sequential(\n",
        "            nn.ReLU(inplace=True),\n",
        "            nn.Linear(4096, num_classes),\n",
        "            )\n",
        "\n",
        "    def forward(self, x):\n",
        "        out1 = self.conv1(x)\n",
        "        out2 = self.conv2(out1)\n",
        "        out3 = self.conv3(out2)\n",
        "        out4 = self.conv4(out3)\n",
        "        out5 = self.conv5(out4)\n",
        "\n",
        "        out5_reshaped = out5.view(out5.size(0), 256 * 6 * 6)\n",
        "        out6= self.fc6(out5_reshaped)\n",
        "        out7= self.fc7(out6)\n",
        "        out8 = self.fc8(out7)\n",
        "        return out1, out2, out3,out4, out5, out6,out7,out8\n",
        "\n",
        "\n",
        "def alexnet(pretrained=False, **kwargs):\n",
        "    \"\"\"AlexNet model architecture from the\n",
        "    `\"One weird trick...\" <https://arxiv.org/abs/1404.5997>`_ paper.\n",
        "    Args:\n",
        "        pretrained (bool): If True, returns a model pre-trained on ImageNet\n",
        "    \"\"\"\n",
        "    model = AlexNet(**kwargs)\n",
        "    if pretrained:\n",
        "        model.load_state_dict(model_zoo.load_url(model_urls['alexnet']))\n",
        "    return model "
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6GqrOsWn4WBx"
      },
      "source": [
        "#@title Feature extraction code\n",
        "def load_alexnet(model_checkpoints):\n",
        "    \"\"\"This function initializes an Alexnet and load\n",
        "    its weights from a pretrained model. Since we redefined model in a different\n",
        "    way we have to rename the weights that were in the pretrained checkpoint.\n",
        "    ----------\n",
        "    model_checkpoints : str\n",
        "        model checkpoints location.\n",
        "    Returns\n",
        "    -------\n",
        "    model\n",
        "        pytorch model of alexnet\n",
        "    \"\"\"\n",
        "\n",
        "    model = alexnet()\n",
        "    # Load checkpoint\n",
        "    model_file = model_checkpoints\n",
        "    checkpoint = torch.load(model_file, map_location=lambda storage, loc: storage)\n",
        "\n",
        "    # Rename the checkpoint keys according to new definition\n",
        "    model_dict =[\"conv1.0.weight\", \"conv1.0.bias\", \"conv2.0.weight\", \"conv2.0.bias\", \"conv3.0.weight\", \"conv3.0.bias\", \"conv4.0.weight\", \"conv4.0.bias\", \"conv5.0.weight\", \"conv5.0.bias\", \"fc6.1.weight\", \"fc6.1.bias\", \"fc7.1.weight\", \"fc7.1.bias\", \"fc8.1.weight\", \"fc8.1.bias\"]\n",
        "    state_dict={}\n",
        "    i=0\n",
        "    for k,v in checkpoint.items():\n",
        "        state_dict[model_dict[i]] =  v\n",
        "        i+=1\n",
        "\n",
        "    # initialize model with pretrained weights \n",
        "    model.load_state_dict(state_dict)\n",
        "    if torch.cuda.is_available():\n",
        "        model.cuda()\n",
        "    model.eval()\n",
        "    return model\n",
        "\n",
        "\n",
        "def get_activations_and_save(model, image_list, activations_dir):\n",
        "    \"\"\"This function generates Alexnet features and save them in a specified directory.\n",
        "    Parameters\n",
        "    ----------\n",
        "    model :\n",
        "        pytorch model : alexnet.\n",
        "    image_list : list\n",
        "        the list contains path to all images.\n",
        "    activations_dir : str\n",
        "        save path for extracted features.\n",
        "    \"\"\"\n",
        "\n",
        "    resize_normalize = trn.Compose([\n",
        "            trn.Resize((224,224)),\n",
        "            trn.ToTensor(),\n",
        "            trn.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])\n",
        "\n",
        "    # for all images in the list generate and save activations\n",
        "    for image_file in tqdm(image_list):\n",
        "        \n",
        "        # open image\n",
        "        img = Image.open(image_file)\n",
        "        image_file_name = os.path.split(image_file)[-1].split(\".\")[0]\n",
        "\n",
        "        # apply transformations before feeding to model\n",
        "        input_img = V(resize_normalize(img).unsqueeze(0))\n",
        "        if torch.cuda.is_available():\n",
        "            input_img=input_img.cuda()\n",
        "        x = model.forward(input_img)\n",
        "\n",
        "        activations = []\n",
        "        for i,feat in enumerate(x):\n",
        "            activations.append(feat.data.cpu().numpy().ravel())\n",
        "\n",
        "        for layer in range(len(activations)):\n",
        "            save_path = os.path.join(activations_dir, image_file_name+\"_\"+\"layer\" + \"_\" + str(layer+1) + \".npy\")\n",
        "            np.save(save_path,activations[layer])\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tFpNlkrd4atV"
      },
      "source": [
        "# get the paths to all the images in the stimulus set\n",
        "image_dir = '92_Image_Set/92images'\n",
        "image_list = glob.glob(image_dir + '/*.jpg')\n",
        "image_list.sort()\n",
        "print('Total Number of Images: ', len(image_list))\n",
        "save_dir = \"/content/activations_alexnet\"\n",
        "\n",
        "######### load Alexnet initialized with pretrained weights ###################\n",
        "# Download pretrained Alexnet from:\n",
        "# https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth\n",
        "# and save in the current directory\n",
        "checkpoint_path = \"/content/alexnet.pth\"\n",
        "if not os.path.exists(checkpoint_path):\n",
        "    url = \"https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth\"\n",
        "    urllib.request.urlretrieve(url, \"/content/alexnet.pth\")\n",
        "model = load_alexnet(checkpoint_path)\n",
        "\n",
        "##############################################################################\n",
        "\n",
        "######### get and save activations ################################\n",
        "\n",
        "activations_dir = os.path.join(save_dir)\n",
        "if not os.path.exists(activations_dir):\n",
        "    os.makedirs(activations_dir)\n",
        "print(\"-------------Saving activations ----------------------------\")\n",
        "get_activations_and_save(model, image_list, activations_dir)\n",
        "###################################################################"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h9gqjNEw5duf"
      },
      "source": [
        "num_layers = 8  # number of layers in the model\n",
        "layers = []\n",
        "\n",
        "\n",
        "for i in range(num_layers):\n",
        "  layers.append(\"layer\" + \"_\" + str(i+1))\n",
        "\n",
        "model_RDMs = {}\n",
        "# create RDM for each layer from activations\n",
        "for layer in layers:\n",
        "  activation_files =  glob.glob(activations_dir + '/*'+layer + '.npy')\n",
        "  activation_files.sort()\n",
        "  activations = []\n",
        "  # Load all activations\n",
        "  for activation_file  in activation_files:\n",
        "    activations.append(np.load(activation_file))\n",
        "  activations = np.array(activations)\n",
        "\n",
        "  # calculate Pearson's distance for all pairwise comparisons \n",
        "  model_RDMs[layer] = 1-np.corrcoef(activations)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pBlKti2M5hxH"
      },
      "source": [
        "#@title visualize model RDMs\n",
        "layer = 'layer_8' #@param ['layer_1','layer_2','layer_3','layer_4','layer_5','layer_6','layer_7','layer_8']\n",
        "\n",
        "# loading layer RDM\n",
        "RDM = np.array(model_RDMs[layer])\n",
        "\n",
        "# Since the matrix is symmetric we set upper triangular values to NaN\n",
        "RDM[np.triu_indices(RDM.shape[0], 1)] = np.nan\n",
        "\n",
        "# Visualize layer RDM\n",
        "plt.imshow(RDM,\\\n",
        "           cmap=\"bwr\")\n",
        "plt.title(layer + \" RDM\")\n",
        "cbar = plt.colorbar()\n",
        "plt.xlabel(\"Stimuli\")\n",
        "plt.ylabel(\"Stimuli\")\n",
        "cbar.ax.get_yaxis().labelpad = 15\n",
        "cbar.ax.set_ylabel('1-Correlation', rotation=270)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yxszMqem_4eV"
      },
      "source": [
        "### Comparing MEG RDMs with AlexNet RDMs"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rUWBI3Fukj2_"
      },
      "source": [
        "#@title Correlating MEG RDMs with DNN RDMs\n",
        "\n",
        "num_timepoints = MEG_RDM_sub_averaged.shape[0]#get number of timepoints\n",
        "\n",
        "# initialize a dictionary to store MEG and DNN RDM correlation at each timepoint\n",
        "for layer in layers:\n",
        "  MEG_correlation[layer] = []\n",
        "\n",
        "# for loop that goes over MEG RDMs at all time points and correlate with DNN RDMs\n",
        "for t in range(num_timepoints):\n",
        "  MEG_RDM_t = MEG_RDM_sub_averaged[t,:,:]\n",
        "  for layer in layers:\n",
        "    model_RDM = model_RDMs[layer]\n",
        "    MEG_correlation[layer].append(RSA_spearman(model_RDM,MEG_RDM_t))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WfdvhLwnkpbf"
      },
      "source": [
        "#@title Plotting MEG-DNN comparison\n",
        "plt.rc('font', size=12)\n",
        "fig, ax = plt.subplots(figsize=(10, 6))\n",
        "\n",
        "time_range = range(-100,1201)\n",
        "ax.plot(time_range, MEG_correlation['layer_1'], color='tab:orange', label='layer_1')\n",
        "ax.plot(time_range, MEG_correlation['layer_7'], color='tab:blue', label='layer_7')\n",
        "\n",
        "# Same as above\n",
        "ax.set_xlabel('Time')\n",
        "ax.set_ylabel('Spearmans Correlation')\n",
        "ax.set_title('MEG-model comparison')\n",
        "ax.grid(True)\n",
        "ax.legend(loc='upper left');"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uM5mp1kwbJos"
      },
      "source": [
        "#References\n",
        "1.   [Resolving human object recognition in space and time. Cichy et al. Nature Neuroscience 2014](https://www.nature.com/articles/nn.3635)\n",
        "2.   [Representational similarity analysis – connecting the branches of systems neuroscience. Kriegeskorte et al. Front. Syst. Neurosci., 2008](https://www.frontiersin.org/articles/10.3389/neuro.06.004.2008/full?utm_source=FWEB&utm_medium=NBLOG&utm_campaign=ECO_10YA_top-research)\n",
        "\n",
        "\n",
        "\n"
      ]
    }
  ]
}