{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Synaptic transmission\n", "\n", "[![Download JupyterNotebook](https://img.shields.io/badge/Download-Notebook-orange?style=for-the-badge&logo=Jupyter)](https://raw.githubusercontent.com/ANNarchy/ANNarchy.github.io/master/notebooks/SynapticTransmission.ipynb) [![Download JupyterNotebook](https://img.shields.io/badge/Open_in-Colab-blue?style=for-the-badge&logo=Jupyter)](https://colab.research.google.com/github/ANNarchy/ANNarchy.github.io/blob/master/notebooks/SynapticTransmission.ipynb)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#!pip install ANNarchy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "This notebook simply demonstrates the three main type of synaptic transmission for spiking neurons:\n", "\n", "1. Instantaneous\n", "2. Exponentially-decreasing\n", "3. Alpha-shaped " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ANNarchy 4.8 (4.8.2) on darwin (posix).\n" ] } ], "source": [ "import numpy as anp\n", "\n", "import ANNarchy as ann\n", "ann.clear()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use here a simple LIF neuron receving three types of projections (a, b, c). The conductance `g_a` uses instantaneous transmission, as it is reset to 0 after each step. `g_b` decreases exponentially with time following a first order ODE. `g_c` is integrated twice in `alpha_c`, leading to the alpha shape.\n", "\n", "All methods use the exponential numerical method, as they are first order linear ODEs and can be solved exactly." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "LIF = ann.Neuron(\n", " parameters=\"\"\"\n", " tau = 20.\n", " E_L = -70.\n", " v_T = 0.\n", " v_r = -58.\n", " tau_b = 10.0\n", " tau_c = 10.0\n", " \"\"\",\n", " equations=\"\"\"\n", " # Membrane potential\n", " tau * dv/dt = (E_L - v) + g_a + g_b + alpha_c : init=-70.\n", " \n", " # Exponentially decreasing\n", " tau_b * dg_b/dt = -g_b : exponential\n", " \n", " # Alpha-shaped\n", " tau_c * dg_c/dt = -g_c : exponential\n", " tau_c * dalpha_c/dt = exp((tau_c - dt/2.0)/tau_c) * g_c - alpha_c : exponential\n", " \"\"\",\n", " spike=\"v >= v_T\",\n", " reset=\"v = v_r\",\n", " refractory = 2.0\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The LIF neuron will receive a single spike at $t = 10$ ms, using the `SpikeSourceArray` specific population." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "inp = ann.SpikeSourceArray([10.])\n", "pop = ann.Population(1, LIF)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We implement three different projections between the same neurons, to highlight the three possible transmission mechanisms." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "proj = ann.Projection(inp, pop, 'a')\n", "proj.connect_all_to_all(weights=1.0)\n", "\n", "proj = ann.Projection(inp, pop, 'b')\n", "proj.connect_all_to_all(weights=1.0)\n", "\n", "proj = ann.Projection(inp, pop, 'c')\n", "proj.connect_all_to_all(weights=1.0)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Compiling ... OK \n" ] } ], "source": [ "ann.compile()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We monitor the three conductances:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "m = ann.Monitor(pop, ['g_a', 'g_b', 'alpha_c'])" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "inp.clear()\n", "ann.simulate(100.)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "data = m.get()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "plt.figure(figsize=(10, 10))\n", "plt.subplot(311)\n", "plt.plot(data['g_a'][:, 0])\n", "plt.ylabel(\"Instantaneous\")\n", "plt.subplot(312)\n", "plt.plot(data['g_b'][:, 0])\n", "plt.ylabel(\"Exponential\")\n", "plt.subplot(313)\n", "plt.plot(data['alpha_c'][:, 0])\n", "plt.xlabel(\"Time (ms)\")\n", "plt.ylabel(\"Alpha\")\n", "plt.show()" ] } ], "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 }