{ "cells": [ { "cell_type": "markdown", "id": "1d67cd9e", "metadata": {}, "source": [ "## Synaptic Plasticity in Pointnet (STP, Facilitation, Depression, STDP, and Others)\n", "\n", "In the NEST simulator, the available postsynaptic current or conductance waveforms (alpha, exp, or delta) are typically integrated into the _neuron model_. The _synapse model_ allows for more sophisticated and varied built-in models of synapses, such as dynamic synapses or gap junctions.\n", "\n", "A list of available synapse models is provided here:\n", "https://nest-simulator.readthedocs.io/en/v2.18.0/models/synapses.html\n", "\n", "So far, we have been using \"static_synapse\" (which simply stores target, weight, delay and receiver port). In this mini-tutorial, we will show an example of how to implement facilitation and depression using BMTK. This approach can be used to access other synaptic models as well.\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "e16b8b80", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: nest-3.0\n", " Built: Sep 14 2022 22:43:51\n", "\n", " This program is provided AS IS and comes with\n", " NO WARRANTY. See the file LICENSE for details.\n", "\n", " Problems or suggestions?\n", " Visit https://www.nest-simulator.org\n", "\n", " Type 'nest.help()' to find out more about NEST.\n", "\n" ] } ], "source": [ "import matplotlib.pyplot as plt\n", "import nest\n", "import numpy as np\n", "import os\n", "import glob\n", "\n", "from bmtk.builder.networks import NetworkBuilder\n", "from bmtk.simulator import pointnet\n", "from bmtk.analyzer.compartment import plot_traces" ] }, { "cell_type": "markdown", "id": "11b9a0ca", "metadata": {}, "source": [ "First, we will create a two neuron network. The presynaptic neuron is a simple integrate-and-fire neuron. If we open the dynamics_params file ```472363762_point_with_cc.json``` within _/components/point_neuron_models_, we see that the parameter **I_e** has been set to 190.0, which injects a constant background current, triggering regular firing in the presynaptic neuron. \n", "\n", "```json\n", "{\n", " \"I_e\": 190.0,\n", " \"tau_m\": 44.9,\n", " \"C_m\": 239.0,\n", " \"t_ref\": 3.0,\n", " \"E_L\": -78.0,\n", " \"V_th\": -43.0,\n", " \"V_reset\": -55.0\n", "}\n", "```\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "d2a255ec", "metadata": {}, "outputs": [], "source": [ "net = NetworkBuilder('two_cell')\n", "\n", "# Build Nodes\n", "\n", "net.add_nodes(\n", " N=1,\n", " model_type='point_neuron',\n", " model_template= 'nest:iaf_psc_alpha',\n", " dynamics_params='472363762_point_with_cc.json',\n", " ei_type='e',\n", " pop_name='presyn'\n", ")\n", "\n", "net.add_nodes(\n", " N=1,\n", " model_type='point_neuron',\n", " model_template= 'nest:glif_lif_asc_psc',\n", " dynamics_params='Scnn1a_515806250_glif_lif_asc.json',\n", " ei_type='e',\n", " pop_name='postsyn'\n", ")" ] }, { "cell_type": "markdown", "id": "380830e0", "metadata": {}, "source": [ "We will add a 'static_synapse' connection between the neurons so we can first see the baseline behavior of the network with an inhibitory static synapse." ] }, { "cell_type": "code", "execution_count": 3, "id": "3e7c9598", "metadata": {}, "outputs": [], "source": [ "# Build edge\n", "\n", "net.add_edges(\n", " source=net.nodes(pop_name='presyn'),\n", " target=net.nodes(pop_name='postsyn'),\n", " connection_rule = 1,\n", " model_template='static_synapse',\n", " dynamics_params='static_ExcToExc.json', \n", " delay=2.0,\n", " syn_weight=-100\n", ")\n", "\n", "net.build()\n", "net.save(output_dir='sim_dyn_syn/network')" ] }, { "cell_type": "code", "execution_count": 4, "id": "743f3a7a", "metadata": {}, "outputs": [], "source": [ "from bmtk.utils.create_environment import create_environment\n", "\n", "create_environment(\n", " 'pointnet',\n", " base_dir='sim_dyn_syn',\n", " config_file='config.pointnet.json',\n", " components_dir='../sources/pointnet_files/dynamic_synapses',\n", " network_dir='network',\n", " output_dir='output_pointnet',\n", " tstop=3000.0, dt=0.1,\n", " report_vars=['V_m'],\n", " run_script='run_pointnet.py',\n", " overwrite=True,\n", ")\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "c733db2a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:43,972 [INFO] Created log file\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Created log file\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:43,986 [INFO] Batch processing nodes for two_cell/0.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Batch processing nodes for two_cell/0.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:43,998 [INFO] Setting up output directory\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Setting up output directory\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:44,000 [INFO] Building cells.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Building cells.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:44,006 [INFO] Building recurrent connections\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Building recurrent connections\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:44,012 [INFO] Network created.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Network created.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:44,018 [INFO] Starting Simulation\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Starting Simulation\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:44,159 [INFO] Simulation finished, finalizing results.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Simulation finished, finalizing results.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:26:44,217 [INFO] Done.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Done.\n" ] } ], "source": [ "configure = pointnet.Config.from_json('sim_dyn_syn/config.pointnet.json')\n", "configure.build_env()\n", "\n", "network = pointnet.PointNetwork.from_config(configure)\n", "sim = pointnet.PointSimulator.from_config(configure, network)\n", "sim.run()\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "f40c67ba", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Presynaptic cell\n", "_ = plot_traces(config_file='sim_dyn_syn/config.pointnet.json', report_name='V_m_report', node_ids = [0])" ] }, { "cell_type": "markdown", "id": "27935b5f", "metadata": {}, "source": [ "Our background current produces regular firing in the presynaptic cell. Note that for LIF models the spike itself is not shown and just produces a reset of the membrane potential." ] }, { "cell_type": "code", "execution_count": 7, "id": "a4a3f4e4", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Postsynaptic cell\n", "_ = plot_traces(config_file='sim_dyn_syn/config.pointnet.json', report_name='V_m_report', node_ids = [1])" ] }, { "cell_type": "markdown", "id": "241e7b2c", "metadata": {}, "source": [ "In the postsynaptic cell, we can see the summation of a series of IPSPs triggered by each presynaptic spike (note that the postsynaptic effect is modeled as a current but produces the voltage effect seen here).\n", "\n", "Next, we'll try rebuilding the network, this time with a facilitating synapse based on the \"tsodyks2_synapse\" model. This model is described in more detail at:\n", "\n", "https://nest-simulator.readthedocs.io/en/stable/auto_examples/evaluate_tsodyks2_synapse.html\n", "\n", "as well as on the synapses documentation page linked at the top. " ] }, { "cell_type": "code", "execution_count": 9, "id": "e7a51682", "metadata": {}, "outputs": [], "source": [ "# Clear the network folder\n", "\n", "for f in glob.glob('sim_dyn_syn/network/*'):\n", " try:\n", " os.remove(f)\n", " except FileNotFoundError as fnfe:\n", " pass" ] }, { "cell_type": "code", "execution_count": 10, "id": "08ca43e4", "metadata": {}, "outputs": [], "source": [ "net2 = NetworkBuilder('two_cell_fac')\n", "\n", "# Build Nodes\n", "\n", "net2.add_nodes(\n", " N=1,\n", " model_type='point_neuron',\n", " model_template= 'nest:iaf_psc_alpha',\n", " dynamics_params='472363762_point_with_cc.json',\n", " ei_type='e',\n", " pop_name='presyn'\n", ")\n", "\n", "net2.add_nodes(\n", " N=1,\n", " model_type='point_neuron',\n", " model_template= 'nest:glif_lif_asc_psc',\n", " dynamics_params='Scnn1a_515806250_glif_lif_asc.json',\n", " ei_type='e',\n", " pop_name='postsyn'\n", ")" ] }, { "cell_type": "code", "execution_count": 11, "id": "b2d2e599", "metadata": {}, "outputs": [], "source": [ "net2.add_edges(\n", " source=net2.nodes(pop_name='presyn'),\n", " target=net2.nodes(pop_name='postsyn'),\n", " connection_rule = 1, \n", " model_template='tsodyks2_synapse',\n", " dynamics_params='TsodyksFac_glif.json', \n", " delay=2.0,\n", " syn_weight=-100\n", ")\n", "\n", "net2.build()\n", "net2.save(output_dir='sim_dyn_syn/network')" ] }, { "cell_type": "markdown", "id": "68ee86d8", "metadata": {}, "source": [ "We have created a new dynamics_params file ```tsodyksFac_glif.json``` based on the dynamic_params file for the static synapse and have added to it the following params for the tsodyks2 synapse:\n", "\n", "```json\n", "{\n", " \"U\": 0.1, \n", " \"u\": 0.1, \n", " \"x\": 1.0,\n", " \"tau_rec\": 100.0,\n", " \"tau_fac\": 1000.0, \n", " \"weight\": 250.0,\n", "}\n", "```" ] }, { "cell_type": "code", "execution_count": 12, "id": "170db049", "metadata": {}, "outputs": [], "source": [ "create_environment(\n", " 'pointnet',\n", " base_dir='sim_dyn_syn',\n", " config_file='config.pointnet.json',\n", " components_dir='../sources/pointnet_files/dynamic_synapses',\n", " network_dir='network',\n", " output_dir='output_pointnet',\n", " tstop=3000.0, dt=0.1,\n", " report_vars=['V_m'],\n", " run_script='run_pointnet.py',\n", " overwrite=True,\n", ")" ] }, { "cell_type": "code", "execution_count": 13, "id": "6d33e5c3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,710 [INFO] Created log file\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Created log file\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,728 [INFO] Batch processing nodes for two_cell_fac/0.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Batch processing nodes for two_cell_fac/0.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,739 [INFO] Setting up output directory\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Setting up output directory\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,740 [INFO] Building cells.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Building cells.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,746 [INFO] Building recurrent connections\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Building recurrent connections\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,756 [INFO] Network created.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Network created.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,763 [INFO] Starting Simulation\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Starting Simulation\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,878 [INFO] Simulation finished, finalizing results.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Simulation finished, finalizing results.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:28,924 [INFO] Done.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Done.\n" ] } ], "source": [ "configure = pointnet.Config.from_json('sim_dyn_syn/config.pointnet.json')\n", "configure.build_env()\n", "\n", "network = pointnet.PointNetwork.from_config(configure)\n", "sim = pointnet.PointSimulator.from_config(configure, network)\n", "sim.run()" ] }, { "cell_type": "code", "execution_count": 14, "id": "0ee909cf", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Presynaptic cell\n", "_ = plot_traces(config_file='sim_dyn_syn/config.pointnet.json', report_name='V_m_report', node_ids = [0])" ] }, { "cell_type": "code", "execution_count": 15, "id": "36f97d55", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Postsynaptic cell\n", "_ = plot_traces(config_file='sim_dyn_syn/config.pointnet.json', report_name='V_m_report', node_ids = [1])" ] }, { "cell_type": "markdown", "id": "87a8e25e", "metadata": {}, "source": [ "This time, the IPSP's get incrementally larger as they occur closely in succession, simulating synaptic facilitation. We can use the same model, just changing the parameters, to create a depressing synapse. We will add these parameter values to the dynamic_params:\n", "\n", "```json\n", "{\n", " \"U\": 0.67, \n", " \"u\": 0.67, \n", " \"x\": 1.0,\n", " \"tau_rec\": 450.0,\n", " \"tau_fac\": 0.0, \n", " \"weight\": 250.0\n", "}\n", "```" ] }, { "cell_type": "code", "execution_count": 16, "id": "dcbe4929", "metadata": {}, "outputs": [], "source": [ "# Clear the network folder\n", "\n", "for f in glob.glob('sim_dyn_syn/network/*'):\n", " try:\n", " os.remove(f)\n", " except FileNotFoundError as fnfe:\n", " pass" ] }, { "cell_type": "code", "execution_count": 17, "id": "1d764dcd", "metadata": {}, "outputs": [], "source": [ "net3 = NetworkBuilder('two_cell_dep')\n", "\n", "# Build Nodes\n", "\n", "net3.add_nodes(\n", " N=1,\n", " model_type='point_neuron',\n", " model_template= 'nest:iaf_psc_alpha',\n", " dynamics_params='472363762_point_with_cc.json',\n", " ei_type='e',\n", " pop_name='presyn'\n", ")\n", "\n", "net3.add_nodes(\n", " N=1,\n", " model_type='point_neuron',\n", " model_template= 'nest:glif_lif_asc_psc',\n", " dynamics_params='Scnn1a_515806250_glif_lif_asc.json',\n", " ei_type='e',\n", " pop_name='postsyn'\n", ")" ] }, { "cell_type": "code", "execution_count": 18, "id": "3017c907", "metadata": {}, "outputs": [], "source": [ "net3.add_edges(\n", " source=net3.nodes(pop_name='presyn'),\n", " target=net3.nodes(pop_name='postsyn'),\n", " connection_rule = 1, \n", " model_template='tsodyks2_synapse',\n", " dynamics_params='TsodyksDep_glif.json', \n", " delay=2.0,\n", " syn_weight=-100\n", ")\n", "\n", "net3.build()\n", "net3.save(output_dir='network')" ] }, { "cell_type": "code", "execution_count": 19, "id": "89c0c6c1", "metadata": {}, "outputs": [], "source": [ "create_environment(\n", " 'pointnet',\n", " base_dir='sim_dyn_syn',\n", " config_file='config.pointnet.json',\n", " components_dir='../sources/pointnet_files/dynamic_synapses',\n", " network_dir='network',\n", " output_dir='output_pointnet',\n", " tstop=3000.0, dt=0.1,\n", " report_vars=['V_m'],\n", " run_script='run_pointnet.py',\n", " overwrite=True,\n", ")" ] }, { "cell_type": "code", "execution_count": 20, "id": "85d89a30", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,260 [INFO] Created log file\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Created log file\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,272 [INFO] Batch processing nodes for two_cell_dep/0.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Batch processing nodes for two_cell_dep/0.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,282 [INFO] Setting up output directory\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Setting up output directory\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,283 [INFO] Building cells.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Building cells.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,289 [INFO] Building recurrent connections\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Building recurrent connections\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,294 [INFO] Network created.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Network created.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,299 [INFO] Starting Simulation\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Starting Simulation\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,437 [INFO] Simulation finished, finalizing results.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Simulation finished, finalizing results.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "2022-10-28 17:27:54,485 [INFO] Done.\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "INFO:NestIOUtils:Done.\n" ] } ], "source": [ "configure = pointnet.Config.from_json('sim_dyn_syn/config.pointnet.json')\n", "configure.build_env()\n", "\n", "network = pointnet.PointNetwork.from_config(configure)\n", "sim = pointnet.PointSimulator.from_config(configure, network)\n", "sim.run()" ] }, { "cell_type": "code", "execution_count": 21, "id": "7b45e92a", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Presynaptic cell\n", "_ = plot_traces(config_file='sim_dyn_syn/config.pointnet.json', report_name='V_m_report', node_ids = [0])" ] }, { "cell_type": "code", "execution_count": 22, "id": "1f8e7fa9", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Postsynaptic cell\n", "_ = plot_traces(config_file='sim_dyn_syn/config.pointnet.json', report_name='V_m_report', node_ids = [1])" ] }, { "cell_type": "code", "execution_count": null, "id": "ba37afb1", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.16" } }, "nbformat": 4, "nbformat_minor": 5 }