{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains\n", "\n", "The tutorial is based on the paper \\[[1](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004939)\\] and demonstrates a method of finding patterns of synchronous spike times (synfire chains) which cannot be revealed by measuring neuronal firing rates only.\n", "\n", "In this tutorial, we use 50 neurons per group in 10 successive groups of a synfire chain embedded in a balanced network simulation. For more information about the data and ASSET algorithm, refer to \\[[1](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004939)\\].\n", "\n", "#### References\n", "\n", " [1] Torre E, Canova C, Denker M, Gerstein G, Helias M, GrĂ¼n S (2016) ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains. PLoS Comput Biol 12(7): e1004939. https://doi.org/10.1371/journal.pcbi.1004939" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Explore the data and postulate the problem\n", "\n", "We start by importing the required packages, setting up matplotlib and loading the data." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:10:41.726957Z", "start_time": "2020-03-25T14:10:40.432907Z" } }, "outputs": [], "source": [ "import os\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import quantities as pq\n", "import neo\n", "import elephant\n", "from elephant import asset" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:10:41.778627Z", "start_time": "2020-03-25T14:10:41.729668Z" } }, "outputs": [], "source": [ "%load_ext autoreload\n", "\n", "plt.style.use('dark_background')\n", "\n", "plt.rcParams['figure.autolayout'] = False\n", "plt.rcParams['figure.figsize'] = 20, 12\n", "plt.rcParams['axes.labelsize'] = 18\n", "plt.rcParams['axes.titlesize'] = 20\n", "plt.rcParams['font.size'] = 14\n", "plt.rcParams['lines.linewidth'] = 1.0\n", "plt.rcParams['lines.markersize'] = 8\n", "plt.rcParams['legend.fontsize'] = 14\n", "\n", "plt.rcParams['text.latex.preamble'] = r\"\\usepackage{subdepth}, \\usepackage{type1cm}\"\n", "plt.rcParams['mathtext.fontset'] = 'cm'\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we download the data, packed in NixIO structure, from https://gin.g-node.org/INM-6/elephant-data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "!curl https://web.gin.g-node.org/INM-6/elephant-data/raw/master/dataset-2/asset_showcase_500.nix --output asset_showcase_500.nix --location" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data is represented as a `neo.Block` with one `neo.Segment` inside, which contains raw `neo.SpikeTrain`s. For more information on `neo.Block`, `neo.Segment`, and `neo.SpikeTrain` refer to https://neo.readthedocs.io/en/stable/core.html" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:10:46.775022Z", "start_time": "2020-03-25T14:10:41.781858Z" } }, "outputs": [], "source": [ "with neo.NixIO('asset_showcase_500.nix', 'ro') as f:\n", " block = f.read_block()\n", "segment = block.segments[0]\n", "spiketrains = segment.spiketrains" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:10:47.861748Z", "start_time": "2020-03-25T14:10:46.776687Z" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.eventplot([st.magnitude for st in spiketrains], linewidths=5, linelengths=5)\n", "plt.xlabel('time [ms]')\n", "plt.ylabel('neuron id')\n", "plt.title('Raw spikes')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Even though we see an increase of the firing rate, we cannot find a propagating activity just by looking at the raster plot above.\n", "\n", "We want to find a permuation of rows (neurons) in `spiketrains` such that a pattern (synfire chain) appears.\n", "The true unknown permutation is stored in the `segment.annotations['spiketrain_ordering']`. **The goal is to recreate this permutation from raw data with the statistical method ASSET.**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Applying ASSET\n", "\n", "### 2.1. Intersection matrix\n", "\n", "The first step is to compute the intersection matrix `imat`, the `(i,j)` entry of which represents the number of neurons spiking both at bins `i` and `j` after the binning is applied. The resultant symmetric matrix `imat` shows one off-diagonal synfire chain pattern (see the picture below)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:10:48.810547Z", "start_time": "2020-03-25T14:10:47.863279Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 2.1.1) create ASSET analysis object\n", "# hint: try different bin sizes, e.g. bin_size=2.5, 3.5, 4.0 ms\n", "asset_obj = asset.ASSET(spiketrains, bin_size=3*pq.ms)\n", "\n", "# 2.1.2) compute the intersection matrix\n", "imat = asset_obj.intersection_matrix()\n", "plt.matshow(imat)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.2. Analytical probability matrix\n", "\n", "The second step is to estimate the probability $P_{null}$ that non-zero entries in `imat` occurred by chance. The resultant `pmat` matrix is defined as the probability of having strictly fewer coincident spikes at bins `i` and `j` strictly than the observed overlap (`imat`) under the null hypothesis of independence of the input spike trains." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:10:52.180959Z", "start_time": "2020-03-25T14:10:48.812449Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "compute rates by boxcar-kernel convolution...\n", "compute the prob. that each neuron fires in each pair of bins...\n", "compute the probability matrix by Le Cam's approximation...\n", "substitute 0.5 to elements along the main diagonal...\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pmat = asset_obj.probability_matrix_analytical(imat, kernel_width=50*pq.ms)\n", "plt.matshow(pmat)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.3. Joint probability matrix\n", "\n", "The third step is postprocessing of the analytical probability matrix `pmat`, obtained from the previous step. Centered at each (i,j) entry of `pmat` matrix, we apply a diagonal kernel with shape `filter_shape` and select the top `nr_largest` probabilities of (i,j) neighborhood (defined by `filter_shape`), and compute the significance of these `nr_largest` joint neighbor probabilities. The resultant `jmat` matrix is a \"dilated\" version of `imat`.\n", "\n", "This step is most time consuming. If you have PyCUDA or PyOpenCL installed, set `ELEPHANT_USE_CUDA` or `ELEPHANT_USE_OPENCL` environment flag to `1`." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:02.280463Z", "start_time": "2020-03-25T14:10:52.182029Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Joint survival function: 100%|██████████| 47838/47838 [00:06<00:00, 7400.11it/s]\n" ] } ], "source": [ "os.environ['ELEPHANT_USE_OPENCL'] = '0'\n", "# try different filter_shapes, e.g. filter_shape=(7,3)\n", "jmat = asset_obj.joint_probability_matrix(pmat, filter_shape=(11, 3), n_largest=3)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:02.637610Z", "start_time": "2020-03-25T14:11:02.283118Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.matshow(jmat)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.4. Mask matrix\n", "\n", "After setting significance thresholds $\\alpha_P$ and $\\alpha_J$ for the corresponding matrices $P$ (probability matrix `pmat`) and $J$ (joint probability matrix `jmat`), we check the entries for significance. The resultant boolean mask matrix `mmat` is then defined as\n", "\n", "$$\n", "M_{ij} = 1_{P_{ij} > \\alpha_P} \\cdot 1_{J_{ij} > \\alpha_J}\n", "$$\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:02.938666Z", "start_time": "2020-03-25T14:11:02.639331Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# hint: try different alphas for pmat and jmat\n", "# hint: try alphas in range [0.99, 1-1e-6]\n", "# hint: you can call 'asset.ASSET.mask_matrices(...)' without creating the asset_obj\n", "alpha = .99\n", "mmat = asset_obj.mask_matrices([pmat, jmat], [alpha, alpha])\n", "plt.matshow(mmat);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.5. Find clusters in the mask matrix\n", "\n", "Each entry (i,j) of the mask matrix $M$ from the previous step is assigned to a cluster id. A cluster is constrained to have at least `min_neighbors` number of associated elements with at most `eps` intra-distance (within the group). The cluster index, or the (i,j) entry of the resultant `cmat` matrix, is:\n", "\n", "1. a positive int (cluster id), if (i,j) is part of a cluster;\n", "2. `0`, if $M_{ij}$ is non-positive;\n", "3. `-1`, if the element (i,j) does not belong to any cluster.\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:03.303188Z", "start_time": "2020-03-25T14:11:02.940034Z" }, "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# hint: you can call asset.ASSET.cluster_matrix_entries(...) without creating the asset_obj\n", "cmat = asset_obj.cluster_matrix_entries(mmat, max_distance=11, min_neighbors=10, stretch=5)\n", "plt.matshow(cmat)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.6. Sequences of synchronous events\n", "\n", "Given the input spike trains, two arrays of bin edges from step 2.2 and the clustered intersection matrix `cmat` from step 2.5, extract the sequences of synchronous events (synfire chains).\n" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:04.675545Z", "start_time": "2020-03-25T14:11:03.304508Z" } }, "outputs": [ { "data": { "text/plain": [ "dict_keys([1])" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sses = asset_obj.extract_synchronous_events(cmat)\n", "sses.keys()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:04.685097Z", "start_time": "2020-03-25T14:11:04.677381Z" } }, "outputs": [], "source": [ "cluster_id = 1\n", "cluster_chain = []\n", "for chain in sses[cluster_id].values():\n", " cluster_chain.extend(chain)\n", "\n", "_, st_indices = np.unique(cluster_chain, return_index=True)\n", "st_indices = np.take(cluster_chain, np.sort(st_indices))\n", "\n", "reordered_sts = [spiketrains[idx] for idx in st_indices]\n", "spiketrains_not_a_pattern = [spiketrains[idx] for idx in range(len(spiketrains))\n", " if idx not in st_indices]\n", "reordered_sts.extend(spiketrains_not_a_pattern)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:05.868308Z", "start_time": "2020-03-25T14:11:04.686689Z" }, "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.eventplot([st.magnitude for st in reordered_sts], linewidths=5, linelengths=5)\n", "plt.xlabel('time [ms]')\n", "plt.ylabel('reordered neuron id')\n", "plt.title('Reconstructed ordering of the neurons (y-axis) with synfire chains');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### With the sequences of synchronous events `sses` we found a permutation of the spiketrains that reveals the synfire chain as in the ground truth ordering in the last Figure, shown below.." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2020-03-25T14:11:07.018185Z", "start_time": "2020-03-25T14:11:05.869587Z" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ordering_true = segment.annotations['spiketrain_ordering']\n", "spiketrains_ordered = [spiketrains[idx] for idx in ordering_true]\n", "\n", "plt.figure()\n", "plt.eventplot([st.magnitude for st in spiketrains_ordered], linewidths=5, linelengths=5)\n", "plt.xlabel('time [ms]')\n", "plt.ylabel('neuron id')\n", "plt.title('True (unknown) ordering of the neurons (y-axis)')\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.3" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false }, "toc": { "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }