{ "cells": [ { "cell_type": "markdown", "id": "d48013ba-af79-4804-aa7a-ed6720fd2e59", "metadata": {}, "source": [ "# A flexible and precise approximation to the Wang (2002) NMDA Model\n", "Jan-Eirik Welle Skaar and Hans Ekkehard Plesser, Spring 2024" ] }, { "cell_type": "markdown", "id": "bca71cf0-a616-4077-9334-a72861e24e76", "metadata": {}, "source": [ "This notebook briefly describes the approximation underlying the `iaf_bw_2001` model in NEST. The model itself was first published in\n", "\n", "Wang, X.-J. (2002). Probabilistic Decision Making by Slow Reverberation in Cortical Circuits. Neuron, 36(5), 955–968. https://doi.org/10.1016/S0896-6273(02)01092-9\n", "\n", "## Synaptic currents of the Wang (2002) model\n", "\n", "The synaptic input currents of the model are defined as follows (Wang 2002, p 966):\n", "$$\\begin{align}\n", " I_\\mathrm{syn}(t) &= \n", " I_\\mathrm{rec, AMPA}(t) \n", " + I_\\mathrm{rec, NMDA}(t) \n", " + I_\\mathrm{rec, GABA}(t) \\mathrm{,}\\\\[1.5ex]\n", " I_\\mathrm{ext,AMPA} &= g_\\mathrm{ext,AMPA}\\times (V(t) - V_E) \\times S_{j,\\mathrm{ext, AMPA}}(t)\\mathrm{,}\\\\\n", " I_\\mathrm{rec,AMPA} &= g_\\mathrm{rec,AMPA}\\times (V(t) - V_E) \\times \\sum_{j=1}^{N_E}w_jS_{j,\\mathrm{rec,AMPA}}(t) \\mathrm{,}\\\\\n", " I_\\mathrm{rec,NMDA} &= \\frac{g_\\mathrm{rec,NMDA}\\times (V(t) - V_E)}{1+[\\mathrm{Mg^{2+}}]\\mathrm{exp}(-0.062V(t))/3.57}\\times \\sum_{j=1}^{N_E}w_jS_{j,\\mathrm{NMDA}}(t) \\mathrm{,}\\\\\n", " I_\\mathrm{rec,GABA} &= g_\\mathrm{rec,GABA}\\times(V(t) - V_I) \\times\\sum_{j=1}^{N_E}w_jS_{j,\\mathrm{GABA}}(t) \\;\\mathrm{.}\n", "\\end{align}\n", "$$\n", "\n", "Note that in contrast to common practice, $I_\\mathrm{syn}\\sim g (V-V_\\text{rev})$ is defined with positive sign and then entered into the membrane potential equation with negative sign as $\\dot{V} \\sim \\dots - I_\\mathrm{syn}$. For consistency with the model definition, the NEST implementation follows this convention.\n", "\n", "The synaptic activations $S_{j,\\mathrm{ext,AMPA}},S_{j,\\mathrm{rec,AMPA}},S_{j,\\mathrm{NMDA}},\\ \\mathrm{ and }\\ S_{j,\\mathrm{GABA}}$\n", "are governed by the equations\n", "\n", "$$\\begin{align} \n", " \\frac{dS_{j,\\mathrm{AMPA}}}{dt} &= -\\frac{S_{j,\\mathrm{AMPA}}}{\\tau_\\mathrm{AMPA}}+\\sum_k \\delta (t - t_j^k) \\\\\n", " \\frac{dS_{j,\\mathrm{GABA}}}{dt} &= -\\frac{S_{j,\\mathrm{GABA}}}{\\tau_\\mathrm{GABA}} + \\sum_k \\delta (t - t_j^k) \\\\\n", " \\frac{dS_{j,\\mathrm{NMDA}}}{dt} &= -\\frac{S_{j,\\mathrm{NMDA}}}{\\tau_\\mathrm{NMDA,decay}}+ \\alpha x_j (1 - S_{j,\\mathrm{NMDA}}) \\\\\n", " \\frac{dx_j}{dt} &= - \\frac{x_j}{\\tau_\\mathrm{NMDA,rise}} + \\sum_k \\delta (t - t_j^k) \\;\\mathrm{,}\n", "\\end{align}\n", "$$\n", "where indices $j$ mark presynaptic neurons and $k$ spike times.\n", "\n", "This original model by Wang (2002) is implemented in NEST as `iaf_bw_2001_exact`. Due to the nonlinear term $x_j (1 - S_{j,\\mathrm{NMDA}})$, NMDA synapses cannot be combined together, so each incoming synapse to a neuron needs to be integrated individually, significantly impacting performance. Note that $S_{j,\\mathrm{NMDA}}(t)$ represents the input to a given neuron from presynaptic neuron $j$. Importantly, the same $S_j(t)$ describes input to all neurons postsynaptic to $j$, although shifted by possibly different delays and weighted by different input weights. This allows us to compute $S_j(t)$ only once in neuron $j$ and then distribute this value, for each simulation time step, to all post-synaptic neurons of $j$.\n", "\n", "Prior implementations of the model, such as the [Brian2 implementation by Wimmer and Stimberg](https://brian2.readthedocs.io/en/stable/examples/frompapers.Wang_2002.html) and presumably Wang's original implementation, circumvent address this by investigating a model with all-to-all connectivity with a single delay value and fixed-timestep forward Euler integration. The NEST implementation supports arbitrary connectivity and delays, and uses RKF45 adaptive stepsize integration. " ] }, { "cell_type": "markdown", "id": "a3a552e1-72db-4bc3-a494-cd852d879ed9", "metadata": {}, "source": [ "## Approximation of NMDA dynamics\n", "\n", "We will from now on only focus on the last two equations, which are the subjects of the approximation in the model. We drop the subscript NMDA in the following and abbreviate \"rise\" and \"decay\" as \"r\" and \"d\", respectively. \n", "\n", "Assume that neuron $j$ last spiked at time zero and does not spike again until $t$. Then we obtain the following expression for time evolution of $S_j$ until $t$ by plugging in the solution for $x_j$ on the interval $(0, t]$:\n", "$$\n", "\\begin{align}\n", " \\frac{dS_{j}}{dt} + \\bigg(\\frac{1}{\\tau_\\mathrm{d}} + \\alpha x_j^0 \\mathrm{exp}\\bigg[-\\frac{t}{\\tau_\\mathrm{r}}\\bigg] \\bigg) S_{j,\\mathrm{NMDA}} &= \\alpha x_j^0 \\mathrm{exp}\\bigg[-\\frac{t}{\\tau_\\mathrm{r}}\\bigg] \\;\\mathrm{.}\n", "\\end{align}\n", "$$\n", "We obtain the formal solution by an integrating factor as\n", "$$\n", " S_{j}(t) = \\mathrm{exp}\\Bigg[-\\int_0^t \\frac{1}{\\tau_\\mathrm{d}} + \\alpha x_j^0 \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}} \\bigg] dt' \\Bigg] \n", " \\Bigg( S_{j}^0 +\\int_0^t \\mathrm{exp}\\Bigg[\\int_0^{t'} \\frac{1}{\\tau_\\mathrm{d}} + \\alpha x_j^0 \\mathrm{exp}\\bigg[-\\frac{t''}{\\tau_\\mathrm{r}} \\bigg] dt'' \\Bigg]\\alpha x_j^0 \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}}\\bigg] dt' \\Bigg) \\mathrm{,}\n", "$$\n", "\n", "with $S_j^0=S_j(t=0)$. The first and innermost integrals can be solved in closed form, which gives\n", "$$\n", " S_{j}(t) \n", " = \n", " \\mathrm{exp}\\Bigg[-\\frac{t}{\\tau_\\mathrm{d}} - \\alpha x_j^{0} \\tau_\\mathrm{r} \\bigg( 1-\\mathrm{exp}\\bigg[-\\frac{t}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg]\n", " \\Bigg(S_{j}^0+ \\alpha x_j^0 \\int_0^{t} \\mathrm{exp}\\Bigg[\\bigg( \\frac{1}{\\tau_\\mathrm{d}} - \\frac{1}{\\tau_\\mathrm{r}} \\bigg)t' + \\alpha x_j^0 \\tau_\\mathrm{r} \\bigg( 1 - \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg] dt' \\Bigg) \\mathrm{.}\n", "$$\n", "\n", "Since we have two different time scales in the exponential inside the remaining integral, there is no exact solution for arbitrary limits of integration. We would like to approximate this function with an exponential function, such that we can integrate the sum of multiple such functions in a single variable, as we do for the AMPA and GABA synapses.\n", "\n", "For NMDA synapses we have $\\tau_\\mathrm{r}\\ll\\tau_\\mathrm{d}$, whence we define our approximate function between spikes in terms of the decay time constant as\n", "$$\n", "\\hat{S_j} (t) = S_\\mathrm{post} \\mathrm{exp}\\Big(-\\frac{t}{\\tau_d}\\Big) \\;.\n", "$$\n", "Here $S_\\mathrm{post}$ is some initial condition immediately after receiving a spike. We set the value of $S_\\mathrm{post}$ such that the approximation is exact in the limit of large $t$, i.e.,\n", "$$\n", "\\lim_{t \\to \\infty} \\frac{S_j(t)}{\\hat{S}_j(t)}\\to 1 \\;.\n", "$$\n", "Note that a new $S_\\mathrm{post}$ is computed after every spike of neuron $j$.\n", "\n", "To obtain $S_\\mathrm{post}$, we assume that $x_0 = 0$ immediately before every spike, i.e., that the effect on $x_j$ of the previous spike has vanished by the time the next spike arrives. Since $\\tau_r$ is very small (e.g. $2$ ms), this is reasonable unless the neuron is firing very rapidly. Since $x$ is increased by $1$ on every spike, we have $x_0=1$ immediately after spiking. \n", "\n", "We now set our approximation ansatz equal to the exact solution, inserting $x_0=1$, and move the exponential in $\\tau_\\mathrm{d}$ to the right hand side\n", "$$\\begin{align}\n", " S_\\mathrm{post} \\mathrm{exp}\\Big(-\\frac{t}{\\tau_d}\\Big)\n", " &=\n", " \\mathrm{exp}\\Bigg[-\\frac{t}{\\tau_\\mathrm{d}} - \\alpha \\tau_\\mathrm{r} \\bigg( 1-\\mathrm{exp}\\bigg[-\\frac{t}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg]\n", " \\Bigg(S_{j}^0 + \\alpha \\int_0^{t} \\mathrm{exp}\\Bigg[(t') \\bigg( \\frac{1}{\\tau_\\mathrm{d}} - \\frac{1}{\\tau_\\mathrm{r}} \\bigg) + \\alpha \\tau_\\mathrm{r} \\bigg( 1 - \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg] dt' \\Bigg) \\mathrm{,} \\\\\n", " \\Leftrightarrow S_\\mathrm{post}\n", " &=\n", " \\mathrm{exp}\\Bigg[- \\alpha \\tau_\\mathrm{r} \\bigg( 1-\\mathrm{exp}\\bigg[-\\frac{t}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg]\n", " \\Bigg( S_{j}^0 + \\alpha \\int_0^{t} \\mathrm{exp}\\Bigg[\\bigg( \\frac{1}{\\tau_\\mathrm{d}} - \\frac{1}{\\tau_\\mathrm{r}} \\bigg) t' + \\alpha \\tau_\\mathrm{r} \\bigg( 1 - \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg]dt' \\Bigg) \\;.\n", "\\end{align}\n", "$$\n", "\n", "Taking the limit $t\\to\\infty$, the remaining integral becomes\n", "\n", "$$\n", "\\begin{align}\n", "&\\ \\int_0^\\infty \\mathrm{exp}\\Bigg[\\bigg( \\frac{1}{\\tau_\\mathrm{d}} - \\frac{1}{\\tau_\\mathrm{r}} \\bigg) t' + \\alpha \\tau_\\mathrm{r} \\bigg( 1 - \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}} \\bigg] \\bigg) \\Bigg] dt' \\\\\n", "&= -\\frac{1}{\\alpha}\\mathrm{exp}[\\alpha \\tau_r](\\alpha \\tau_r)^{\\frac{\\tau_r}{\\tau_d}} \\int_0^\\infty \\bigg(\\alpha \\tau_r \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}}\\bigg]\\bigg)^{-\\frac{\\tau_r}{\\tau_d}} \\mathrm{exp}\\Bigg[-\\alpha \\tau_r\\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_\\mathrm{r}} \\bigg] \\Bigg] \\bigg(-\\alpha \\mathrm{exp}\\bigg[-\\frac{t'}{\\tau_r}\\bigg] \\bigg) dt' \\\\\n", "&= \\frac{1}{\\alpha}\\mathrm{exp}[\\alpha \\tau_r](\\alpha \\tau_r)^{\\frac{\\tau_r}{\\tau_d}} \\int_0^{\\alpha \\tau_r} u^{-\\frac{\\tau_r}{\\tau_d}} \\mathrm{exp}[-u]du \\\\\n", "&= \\frac{1}{\\alpha}\\mathrm{exp}[\\alpha \\tau_r](\\alpha \\tau_r)^{\\frac{\\tau_r}{\\tau_d}} \\gamma \\big[1 - \\frac{\\tau_r}{\\tau_d}, \\alpha \\tau_r \\big] \\mathrm{,}\n", "\\end{align}\n", "$$\n", "where we make the substitution $u = \\alpha \\tau_r \\mathrm{exp}\\big[-\\frac{t'}{\\tau_r} \\big]$, and $\\gamma$ is the [lower incomplete gamma function](https://en.wikipedia.org/wiki/Incomplete_gamma_function).\n", "\n", "We thus have\n", "\n", "$$\\begin{align}\n", " S_\\mathrm{post} = \n", " \\mathrm{exp}\\Big[-\\alpha \\tau_\\mathrm{r} \\Big] S_j^0\n", " +\n", " (\\alpha \\tau_r)^{\\frac{\\tau_r}{\\tau_d}} \\gamma \\big[1 - \\frac{\\tau_r}{\\tau_d}, \\alpha \\tau_r \\big] \\mathrm{,}\n", "\\end{align}\n", "$$\n", "where $S_j^0$ is the value of $S_j$ immediately before spiking. Note that since the exact solution $S_j(t)$ includes the full history of $S_j$, and thus $S_\\mathrm{post}$ as its approxmation also includes the full history. \n", "\n", "Defining\n", "$$\\begin{align}\n", " k_0 &= (\\alpha \\tau_r)^{\\frac{\\tau_r}{\\tau_d}} \\gamma \\big[1 - \\frac{\\tau_r}{\\tau_d}, \\alpha \\tau_r \\big] \\\\[3ex]\n", " k'_1 &= \\mathrm{exp}(-\\alpha \\tau_\\mathrm{r}) \n", "\\end{align} \n", "$$\n", "we can write\n", "$$\n", " S_\\mathrm{post} = k_0 + k'_1 S_j^0 \\;.\n", "$$\n", "\n", "In a presynaptic neuron $j$, let $t_\\mathrm{ls}$ be the time of the previous spike and $t^-$ the time immediately before the next spike. Then we have from the definition of our approximation\n", "$$\n", "S_j(t^-) = S_j(t_\\mathrm{ls}) \\mathrm{exp}\\big[-\\frac{t^- - t_\\mathrm{ls}}{\\tau_d}\\big] \\;.\n", "$$\n", "The value of $S_j$ at $t^+$ immediately after the spike is then given by\n", "$$\n", "S_j(t^+) = S_\\mathrm{post} = k_0 + k'_1 S_j(t^-)\n", "$$\n", "and the change in $S_j$ upon the spike at $t$ is given by\n", "$$\n", "\\Delta S_j = S_j(t^+)-S_j(t^-) = k_0 + k'_1 S_j(t^-) - S_j(t^-) = k_0 + k_1 S_j(t^-) \\;.\n", "$$\n", "with $k_1 = k'_1 - 1$. The change $\\Delta S_j$ is then transmitted to all postsynaptic neurons and added to their aggregated $S$ input variable.\n", "\n", "\n", "In the exact implementation, the spike only affects $S_j$ through the variable $x_j$, and everything is integrated post-synaptically. After receiving a spike, the variable is updated as\n", "$$\n", "x_j(t^+) = x_j(t^-) + 1\n", "$$\n", "in the post-synaptic neuron, and the value of $S_j$ is updated during the integration of the entire system described in the beginning." ] }, { "cell_type": "markdown", "id": "a6fa9697-6765-421e-ba8d-640e14f27399", "metadata": {}, "source": [ "## Comparing exact solution and approximation\n", "\n", "### Single neuron\n", "\n", "The first case compares a single neuron simulated with the exact and the approximating models." ] }, { "cell_type": "code", "execution_count": 1, "id": "524ec469-ba8d-4b0d-a9e9-1941828f16d5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " -- N E S T --\n", " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: 3.6.0-post0.dev0\n", " Built: Apr 28 2024 17:23:19\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 nest\n", "import matplotlib.pyplot as plt\n", "\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "id": "3ec686e2-2ae2-4479-9b57-7d6151f7a1f1", "metadata": {}, "outputs": [], "source": [ "w_ext = 40.0\n", "w_ex = 1.0\n", "w_in = 15.0\n", "\n", "params = {\n", " \"tau_AMPA\": 2.0,\n", " \"tau_GABA\": 5.0,\n", " \"tau_rise_NMDA\": 2.0,\n", " \"tau_decay_NMDA\": 100.0,\n", " \"conc_Mg2\": 1.0,\n", " \"E_ex\": 0.0,\n", " \"E_in\": -70.0,\n", " \"E_L\": -70.0,\n", " \"V_th\": -55.0,\n", " \"C_m\": 500.0,\n", " \"g_L\": 25.0,\n", " \"V_reset\": -70.0,\n", " \"alpha\": 0.5,\n", " \"t_ref\": 2.0,\n", "}" ] }, { "cell_type": "markdown", "id": "ab7b922a-1ab7-4c40-8dd5-35c23c1b4fde", "metadata": {}, "source": [ "We create 1 pre-synaptic approximate neuron, 1 post-synaptic approximate and 1 post-synaptic exact neuron. Stimulating the pre-synaptic neuron, we will compare the synaptic variables and membrane potential in the approximate and exact post-synaptic neurons." ] }, { "cell_type": "code", "execution_count": 3, "id": "77c6bf6b-c422-46e3-a88e-4925e9bd7842", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Apr 28 21:14:41 NodeManager::add_node [Info]: \n", " Neuron models emitting precisely timed spikes exist: the kernel property \n", " off_grid_spiking has been set to true.\n", " \n", " NOTE: Mixing precise-spiking and normal neuron models may lead to inconsistent results.\n", "\n", "Apr 28 21:14:41 NodeManager::add_node [Info]: \n", " Neuron models emitting precisely timed spikes exist: the kernel property \n", " off_grid_spiking has been set to true.\n", " \n", " NOTE: Mixing precise-spiking and normal neuron models may lead to inconsistent results.\n", "\n", "Apr 28 21:14:41 NodeManager::prepare_nodes [Info]: \n", " Preparing 7 nodes for simulation.\n", "\n", "Apr 28 21:14:41 SimulationManager::start_updating_ [Info]: \n", " Number of local nodes: 7\n", " Simulation time (ms): 1000\n", " Number of OpenMP threads: 1\n", " Number of MPI processes: 1\n", "\n", "Apr 28 21:14:41 SimulationManager::run [Info]: \n", " Simulation finished.\n" ] } ], "source": [ "nest.ResetKernel()\n", "nest.rng_seed = 12345\n", "\n", "# pre-synaptic neuron, must be approximate model since the post-synaptic approximate model needs the offset\n", "nrn_pre = nest.Create(\"iaf_bw_2001\", params)\n", "nrn_post_approx = nest.Create(\"iaf_bw_2001\", params)\n", "nrn_post_exact = nest.Create(\"iaf_bw_2001_exact\", params)\n", "\n", "pg = nest.Create(\"poisson_generator\", {\"rate\": 50.0})\n", "\n", "vm_pre = nest.Create(\"voltmeter\", {\"interval\": nest.resolution})\n", "vm_post_approx = nest.Create(\"voltmeter\", {\"interval\": nest.resolution})\n", "vm_post_exact = nest.Create(\"voltmeter\", {\"interval\": nest.resolution})\n", "\n", "receptors = nest.GetDefaults(\"iaf_bw_2001\")[\"receptor_types\"]\n", "ampa_ext_syn_spec = {\"synapse_model\": \"static_synapse\", \"weight\": w_ext, \"receptor_type\": receptors[\"AMPA\"]}\n", "\n", "rec_syn_specs = nest.CollocatedSynapses(\n", " {\"synapse_model\": \"static_synapse\", \"weight\": w_ex, \"receptor_type\": receptors[\"AMPA\"]},\n", " {\"synapse_model\": \"static_synapse\", \"weight\": w_ex, \"receptor_type\": receptors[\"NMDA\"]},\n", " {\"synapse_model\": \"static_synapse\", \"weight\": w_in, \"receptor_type\": receptors[\"GABA\"]},\n", ")\n", "\n", "nest.Connect(pg, nrn_pre, syn_spec=ampa_ext_syn_spec)\n", "nest.Connect(nrn_pre, nrn_post_approx, syn_spec=rec_syn_specs)\n", "nest.Connect(nrn_pre, nrn_post_exact, syn_spec=rec_syn_specs)\n", "\n", "# nest.Connect(nrn_pre, sr)\n", "nest.Connect(vm_pre, nrn_pre)\n", "nest.Connect(vm_post_approx, nrn_post_approx)\n", "nest.Connect(vm_post_exact, nrn_post_exact)\n", "\n", "nest.Simulate(1000.0)" ] }, { "cell_type": "code", "execution_count": 4, "id": "4e734c3c-e9a7-476f-b262-2bfa215fabe9", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(2, 3)\n", "fig.set_size_inches([15, 6])\n", "# fig.subplots_adjust(hspace=0.5, wspace=0.3)\n", "\n", "ax[0, 0].plot((ev := vm_pre.events)[\"times\"], ev[\"V_m\"])\n", "ax[0, 0].set_xlabel(\"Time [ms]\")\n", "ax[0, 0].set_ylabel(\"Membrane potential [mV]\")\n", "ax[0, 0].set_title(\"Presynaptic neuron\")\n", "\n", "ax[0, 1].plot((ev := vm_post_approx.events)[\"times\"], ev[\"V_m\"], label=\"Approximation\")\n", "ax[0, 1].plot((ev := vm_post_exact.events)[\"times\"], ev[\"V_m\"], \"--\", label=\"Exact model\")\n", "ax[0, 1].set_title(\"Postsynaptic neuron\")\n", "\n", "ax[0, 2].plot((ev := vm_post_approx.events)[\"times\"], ev[\"V_m\"], label=\"Approximation\")\n", "ax[0, 2].plot((ev := vm_post_exact.events)[\"times\"], ev[\"V_m\"], \"--\", label=\"Exact model\")\n", "ax[0, 2].set_title(\"Postsynaptic neuron\")\n", "ax[0, 2].legend()\n", "ax[0, 2].set_xlim(300, 400)\n", "\n", "ax[1, 0].axis(\"off\")\n", "\n", "ax[1, 1].plot((ev := vm_post_approx.events)[\"times\"], ev[\"V_m\"] - vm_post_exact.events[\"V_m\"], label=\"Approximation\")\n", "ax[1, 1].set_xlabel(\"Time [ms]\")\n", "ax[1, 1].set_ylabel(\"Error [mV]\")\n", "\n", "ax[1, 2].plot((ev := vm_post_approx.events)[\"times\"], ev[\"V_m\"] - vm_post_exact.events[\"V_m\"], label=\"Approximation\")\n", "ax[1, 2].set_xlabel(\"Time [ms]\")\n", "ax[1, 2].set_xlim(300, 400);" ] }, { "cell_type": "markdown", "id": "026369ac-7b52-4a72-a059-42554754bac9", "metadata": {}, "source": [ "### Systematic parameter scan\n", "\n", "- In the following, vary\n", " - number of presynaptic neurons\n", " - firing rate of the presynaptic neurons\n", " - weight from pre- to postsynaptic neurons\n", "- Technical aspects\n", " - drive presynaptic neurons by poisson processes\n", " - this requires some experimentation with poisson rates to get approximately the desired rates from the presynaptic neuron" ] }, { "cell_type": "code", "execution_count": 5, "id": "7c373def-4f75-4d20-a692-d2e0b51c1a0f", "metadata": {}, "outputs": [], "source": [ "def do_sim(n_pre, r_pre, weight, t_sim=1000, show=False, seed=955):\n", " nest.set_verbosity(\"M_ERROR\")\n", " nest.ResetKernel()\n", " nest.rng_seed = seed\n", " nest.local_num_threads = 4\n", " sg = nest.Create(\"poisson_generator\", params={\"rate\": r_pre})\n", "\n", " pp = params.copy()\n", " pp[\"t_ref\"] = 0\n", " pre = nest.Create(\"iaf_bw_2001\", n=n_pre, params=pp) # t_ref==0 to make \"parroting\" easier\n", " post_app = nest.Create(\"iaf_bw_2001\", params=params)\n", " post_exa = nest.Create(\"iaf_bw_2001_exact\", params=params)\n", " rec_pre, rec_post_app, rec_post_exa = nest.Create(\"spike_recorder\", n=3)\n", " vm_app, vm_exa = nest.Create(\"voltmeter\", params={\"interval\": nest.resolution}, n=2)\n", "\n", " nest.Connect(sg, pre, syn_spec={\"receptor_type\": 1, \"weight\": 76}) # gives approx one spike out for one in\n", " nest.Connect(pre, post_app + post_exa, syn_spec={\"receptor_type\": 3, \"weight\": weight})\n", " nest.Connect(pre, rec_pre)\n", " nest.Connect(post_app, rec_post_app)\n", " nest.Connect(post_exa, rec_post_exa)\n", " nest.Connect(vm_app, post_app)\n", " nest.Connect(vm_exa, post_exa)\n", " nest.Simulate(t_sim)\n", "\n", " rate_in = rec_pre.n_events / (n_pre * t_sim) * 1000\n", " rate_post_app = rec_post_app.n_events / t_sim * 1000\n", " rate_post_exa = rec_post_exa.n_events / t_sim * 1000\n", " e_app = vm_app.events\n", " e_exa = vm_exa.events\n", " rms_Vm = np.mean((e_app[\"V_m\"] - e_exa[\"V_m\"]) ** 2) ** 0.5\n", " mean_Vm_exa = np.mean(e_exa[\"V_m\"])\n", " mean_Vm_app = np.mean(e_app[\"V_m\"])\n", "\n", " if show:\n", " plt.plot(e_app[\"times\"], e_app[\"V_m\"], label=\"approx\")\n", " plt.plot(e_exa[\"times\"], e_exa[\"V_m\"], label=\"exact\")\n", " plt.xlabel(\"Time [ms]\")\n", " plt.ylabel(\"Membrane potential [mV]\")\n", " plt.legend()\n", "\n", " return {\n", " \"n_pre\": n_pre,\n", " \"w\": weight,\n", " \"r_pre\": r_pre,\n", " \"r_in\": rate_in,\n", " \"r_app\": rate_post_app,\n", " \"r_exa\": rate_post_exa,\n", " \"rms_Vm\": rms_Vm,\n", " \"mean_Vm_exa\": mean_Vm_exa,\n", " \"mean_Vm_app\": mean_Vm_app,\n", " }" ] }, { "cell_type": "markdown", "id": "23559c7b-5c3d-47b1-ac7e-d60a0ff81444", "metadata": {}, "source": [ "#### Example run to show that we get behavior consistent with first example" ] }, { "cell_type": "code", "execution_count": 6, "id": "70e0d8fe-0c06-4282-8513-2c45d84b134c", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "do_sim(1, 10, 1, show=True);" ] }, { "cell_type": "code", "execution_count": 7, "id": "4464fa0a-d5f0-4a78-81d6-fff64b2cbfef", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 8, "id": "74efe493-f9a4-4c85-9e1b-b506d92f9026", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " 1:....:....:....:....:....:....:\n", " 10:....:....:....:....:....:....:\n", " 100:....:....:....:..:..:.:\n", " 1000:....:....:.:.:::\n", " 1600:....:...:.::::\n", " 3200:....:..:::::\n" ] } ], "source": [ "n_pre = [1, 10, 100, 1000, 1600, 3200]\n", "weight = [0.1, 1, 10, 20, 50, 100]\n", "r_pre = [4.5, 18, 54, 100] # chosen so that actual input rates to post neuron are 1, 10, 50, 100\n", "\n", "res = []\n", "for npr in n_pre:\n", " print(f\"{npr:6d}\", end=\":\")\n", " for w in weight:\n", " for rp in r_pre:\n", " if npr * rp * w > 1e5:\n", " continue # skip unrealistically high input regimes\n", " print(\".\", end=\"\")\n", " res.append(do_sim(npr, rp, w))\n", " print(\":\", end=\"\")\n", " print()\n", "\n", "d = pd.DataFrame.from_records(res)\n", "d[\"Total input\"] = d.n_pre * d.r_in * d.w" ] }, { "cell_type": "markdown", "id": "f8f73c7d-0507-43aa-b241-e7d42b3d3de6", "metadata": {}, "source": [ "### Errors in V_m and s_NMDA \n", "\n", "- Plot against total input, i.e., product of number of presynaptic neurons, input rate and weight\n", "- For Fig 2 in Wang (2002), the total input is 1600 neurons * 25 spikes/neuron/s * 0.165 nS * 1.7 ≈ 11220 nS/s ≈ 10^4\n", "- Color in plots indicates synaptic weight\n", "- Plateau in membrane potential error related to start of spiking regime\n", "- Scale on colorbars is log10(weight)\n", "- Marker size is sqrt(number of presynaptic neurons)" ] }, { "cell_type": "code", "execution_count": 9, "id": "f0bea39d-ca88-42b8-b036-cce030a6c2e2", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "d.plot(\n", " x=\"Total input\",\n", " y=\"rms_Vm\",\n", " kind=\"scatter\",\n", " c=np.log10(d.w),\n", " s=d.n_pre**0.5,\n", " logx=True,\n", " logy=True,\n", " title=\"Error in membrane potential\",\n", " colormap=\"viridis\",\n", ");" ] } ], "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": "3.12.2" } }, "nbformat": 4, "nbformat_minor": 5 }