{ "cells": [ { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "view-in-github" }, "source": [ "\"Open" ] }, { "cell_type": "markdown", "metadata": { "id": "ozr3W25l4RMG" }, "source": [ "# Movement Control: Motor Cortex\n", "\n", "This notebook contains a series of interactive plots to explore the tuning and population coding principles presented by [Georgopoulos et al (1982)](https://www.jneurosci.org/content/2/11/1527). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Setup" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "cellView": "form", "id": "lsLegXKnaptb", "tags": [ "hide-input" ] }, "outputs": [], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to set up notebook coding environment.\n", "import numpy as np\n", "import math\n", "import plotly.express as px\n", "import plotly.graph_objects as go\n", "from ipywidgets import widgets,interactive \n", "from numpy import NaN\n", "import matplotlib.pyplot as plt\n", "\n", "my_layout = widgets.Layout()\n", "# def tuningcurve(theta, b0, b1, b2):\n", "# return [b0 + b1*math.sin(math.radians(t)) - b2*math.cos(math.radians(t)) for t in theta]\n", "plt.style.use(\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content/master/nma.mplstyle\")\n", "\n", "\n", "theta=[0,45,90,135,180,225,270,315,360]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Directional Tuning" ] }, { "cell_type": "markdown", "metadata": { "id": "7DWhQraJOr_y" }, "source": [ "There are two different equations that can be used to describe the directional tuning of neurons in M1. \n", "\n", "1. y = b0 + b1*sin(theta) + b2*cos(theta)\n", "\n", "2. y = b0 + c1*cos(theta - theta0)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "cellView": "form", "id": "5detrJopp38Q", "tags": [ "hide-input" ] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "18473dc78900493e81ad7a5a2c8f19f8", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(FloatSlider(value=0.0, description='b0', layout=Layout(width='600px'), step=2.0), FloatS…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to enable an interactive plot\n", "#@markdown exploring the parameters b0, b1, and b2 in equation 1.\n", "\n", "my_layout.width = '600px'\n", "style = {'description_width': 'initial'}\n", "@widgets.interact(\n", " b0=widgets.FloatSlider(0., min=0., max=100., step=2,\n", " layout=my_layout),\n", " b1=widgets.FloatSlider(0., min=0., max=100., step=2,\n", " layout=my_layout),\n", " b2=widgets.FloatSlider(0., min=0., max=100., step=2,\n", " layout=my_layout)\n", ")\n", "\n", "def tuning(b0, b1, b2):\n", " response = [b0 + b1*math.sin(math.radians(t)) + b2*math.cos(math.radians(t)) for t in [0,45,90,135,180,225,270,315,360]]\n", " fig = go.Figure()\n", " fig.add_trace(go.Scatter(x=[0,45,90,135,180,225,270,315,360],y=response,line_color='black',name='tuning curve'))\n", " fig.update_layout(xaxis_title=\"degree\", yaxis_title='spike rate',width=600, height=400)\n", " fig.show()" ] }, { "cell_type": "markdown", "metadata": { "id": "JdQVtSOBmY_k" }, "source": [ "- Why is b0 super important for spiking tuning curve functions? \n", "- What does the ratio betweeen b1 and b2 change?\n", "- What does the absolute value of b1 and b2 change?" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "cellView": "form", "id": "GMeQRb7ZeZNN", "tags": [ "hide-input" ] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "69f36bfa9cbb4697a1494d3f9b054cc6", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(FloatSlider(value=0.0, description='theta', layout=Layout(width='600px'), max=360.0, ste…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to enable an interactive plot\n", "#@markdown exploring the parameters theta, b0, and c1 in equation 2.\n", "\n", "my_layout.width = '600px'\n", "style = {'description_width': 'initial'}\n", "@widgets.interact(\n", " theta=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", " b0=widgets.FloatSlider(0., min=0., max=100., step=2,\n", " layout=my_layout),\n", " c1=widgets.FloatSlider(0., min=0., max=100., step=2,\n", " layout=my_layout)\n", ")\n", "\n", "def preferred_direction(theta, b0, c1):\n", " response = [b0 + c1*math.cos(math.radians(t-theta)) for t in [0,45,90,135,180,225,270,315,360]]\n", " fig = go.Figure()\n", " fig.add_trace(go.Scatter(x=[0,45,90,135,180,225,270,315,360],y=response,line_color='black',name='tuning curve'))\n", " fig.update_layout(xaxis_title=\"degree\", yaxis_title='spike rate',width=600, height=400)\n", " fig.show()" ] }, { "cell_type": "markdown", "metadata": { "id": "SYQYSfeIyho3" }, "source": [ "Challenge: Re-create Figure 4 from the paper using each of the two formulations of the tuning curve. (Hint: the regression coefficient values for the example cell are reported in the paper) \n", "\n", "So far, we have been plotting the neuron's response only at the experimentally tested directions. However, with the regression coefficients, we can plot a smooth tuning function with the estimated response at all locations. In the following interactive demos, you can see the result of using the regression (\"fit\") coefficients to estimate the response at all locations. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Directional Tuning index" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "cellView": "form", "id": "qcpErbvu0A24", "tags": [ "hide-input" ] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "95ebc11296ac49dbaf5196fa14e7fcf5", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(FloatSlider(value=0.0, description='theta', max=360.0, step=2.0, style=SliderStyle(descr…" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d53d0d9ad3cd448c9ba36505c07de6c7", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Label(value='directional tuning index = 0.9890109890109888', layout=Layout(width='800px'))" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to create an interactive \n", "#@markdown plot to investigate the directional tuning index.\n", "\n", "slider_theta = widgets.FloatSlider(\n", " min = 0,\n", " max=360,\n", " value=0,\n", " step=2,\n", " description='theta',\n", " style = {'description_width': '100px'},\n", " disabled=False\n", ")\n", "\n", "slider_b0 = widgets.FloatSlider(\n", " min = 0,\n", " max=100,\n", " value=1,\n", " step=1,\n", " description='b0',\n", " style = {'description_width': '100px'},\n", " disabled=False\n", ")\n", "\n", "slider_c1 = widgets.FloatSlider(\n", " min = 0,\n", " max=100,\n", " value=1,\n", " step=1,\n", " description='c1',\n", " style = {'description_width': '100px'},\n", " disabled=False\n", ")\n", "\n", "DTI_readout = widgets.Label(\n", " value=f'directional tuning index = {NaN}'\n", ")\n", "DTI_readout.layout.width = '800px'\n", "\n", "\n", "def update_plot(theta_,b0_,c1_):\n", " fig, ax = plt.subplots(figsize=(8,4),num=1); #specify figure number so that it does not keep creating new ones\n", " ax.set_xlabel('degree')\n", " ax.set_ylabel('spike rate')\n", " \n", " x = np.arange(0,361,2)\n", " response = [b0_ + c1_*math.cos(math.radians(t-theta_)) for t in x]\n", " DI=0\n", " if ((np.mean(response)>0) | (np.mean(response)<0)) & (b0_!=0):\n", " DI = (np.max(response) - np.mean(response)) / np.mean(response)\n", " ax.plot(x,response,color='black')\n", "\n", " DTI_readout.value=f'directional tuning index = {DI}'\n", "\n", "\n", "w_dti_ = interactive(update_plot, theta_=slider_theta, b0_= slider_b0, c1_=slider_c1);\n", "display(w_dti_,DTI_readout)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Polar Plot\n", "\n", "Polar plots are a common an be a great way to more intuitively visualize directional tuning curves." ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "cellView": "form", "id": "yox10Zm-wF9k", "tags": [ "hide-input" ] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "abce3903ffd747f087f4b69bd6d192f8", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(FloatSlider(value=0.0, description='theta', layout=Layout(width='300px'), max=360.0, ste…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to enable the interactive demo.\n", "\n", "my_layout.width = '300px'\n", "style = {'description_width': 'initial'}\n", "@widgets.interact(\n", " theta=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", " b0=widgets.FloatSlider(1., min=0., max=100., step=1,\n", " layout=my_layout),\n", " c1=widgets.FloatSlider(1., min=0., max=100., step=1,\n", " layout=my_layout)\n", ")\n", "\n", "def polar_tuning(theta, b0, c1):\n", " x = np.arange(0,360,2)\n", " response = [b0 + c1*math.cos(math.radians(t-theta)) for t in x]\n", "\n", " fig = go.Figure(data=\n", " go.Scatterpolar(\n", " r = response,\n", " theta = x,\n", " mode='lines'\n", " ))\n", "\n", " fig.update_layout(showlegend=False,height = 400, width=400)\n", " fig.show()\n", "\n", "\n", "# #peak should be halfway between the two, and minimum spike rate above zero\n", "\n", "# response = tuningcurve(theta,b0,b1,b2) \n", "\n", "# fig = go.Figure(data=\n", "# go.Scatterpolar(\n", "# r = response,\n", "# theta = theta,\n", "# ))\n", "\n", "# fig.update_layout(showlegend=False,height = 400, width=400)\n", "# fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Population coding\n", "\n", "In this section, you can examine population tuning using these types of neurons.\n", " > For this demo, c1 = 1 and b0 = 1" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "cellView": "form", "id": "TLsIOudOxLgB", "tags": [ "hide-input" ] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "6dfc4a64fc0248c49a795d522247df38", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(FloatSlider(value=0.0, description='theta_1', layout=Layout(width='400px'), max=360.0, s…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to enable the interactive demo.\n", "\n", "my_layout.width = '400px'\n", "style = {'description_width': 'initial'}\n", "@widgets.interact(\n", " theta_1=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", " theta_2=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", " theta_3=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout)\n", ")\n", "\n", "def multineuron_tuning(theta_1, theta_2, theta_3):\n", " b0 = 1\n", " c1 = 1\n", " x = np.arange(0,360,1)\n", " N_1 = [b0 + c1*math.cos(math.radians(t-theta_1)) for t in x]\n", " N_2 = [b0 + c1*math.cos(math.radians(t-theta_2)) for t in x]\n", " N_3 = [b0 + c1*math.cos(math.radians(t-theta_3)) for t in x]\n", " fig = go.Figure()\n", " fig.add_trace(go.Scatter(x=x,y=N_1,name='neuron 1'))\n", " fig.add_trace(go.Scatter(x=x,y=N_2,name='neuron 2'))\n", " fig.add_trace(go.Scatter(x=x,y=N_3,name='neuron 3'))\n", " fig.update_layout(xaxis_title=\"degree\", yaxis_title='spike rate',width=600, height=400)\n", " fig.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Population manifolds\n", "\n", "In 3-dimensions, we can visualize how the firing rate of neurons among the population combine to define a unique location in 2-D space (0-360 degrees). \n", " > For this demo, c1 = 1 and b0 = 1\n", " \n", "Notice that with just one neuron (ie. when all 3 neurons have the same direction selectivity), you cannot encode 2-Dimensional space. \n", " > Puzzle: what does the difference in tuning preference between two neurons need to be in order to encode 360 degrees with equal magnitude at each location? Does it depend on the relative tuning preference between/among the neurons or on the direction from which you view the space? Or both?\n", "\n", "**The *perspective* from which you view the neural activity in 2D space (the 2D manifold) is analagous to different convergent/divergent synaptic connectivity of the population on two post-synaptic (downstream) neurons.** We will uncover this concept further when we talk about the Churchland lab's work on the motor cortex later in the course ." ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "cellView": "form", "id": "D0YbppQSlCn6", "tags": [ "hide-input" ] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "517e78b139f841ccb6f80cef9ecf6589", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(FloatSlider(value=0.0, description='theta_1', layout=Layout(width='400px'), max=360.0, s…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#@title {display-mode: \"form\"}\n", "\n", "#@markdown Run this cell to enable the interactive demo\n", "\n", "my_layout.width = '400px'\n", "style = {'description_width': 'initial'}\n", "@widgets.interact(\n", " theta_1=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", " theta_2=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", " theta_3=widgets.FloatSlider(0., min=0., max=360., step=2,\n", " layout=my_layout),\n", ")\n", "\n", "def multineuron_tuning_3D(theta_1, theta_2, theta_3): #, b0, c1):\n", " b0 = 1\n", " c1 = 1\n", " x = np.arange(0,360,1)\n", " N_1 = [b0 + c1*math.cos(math.radians(t-theta_1)) for t in x]\n", " N_2 = [b0 + c1*math.cos(math.radians(t-theta_2)) for t in x]\n", " N_3 = [b0 + c1*math.cos(math.radians(t-theta_3)) for t in x]\n", " fig = go.Figure()\n", " fig.add_trace(go.Scatter3d(x=N_1,y=N_2,z = N_3, line_color='black'))\n", " fig.update_layout(width=500, height=500)\n", " fig.show()" ] } ], "metadata": { "colab": { "authorship_tag": "ABX9TyPyHkRvfLoln7YTJkWFswQg", "collapsed_sections": [], "include_colab_link": true, "name": 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\n", 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\n", 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\n", 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\n", 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