{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "2ee1d062",
"metadata": {},
"outputs": [],
"source": [
"# This code is written by Nooshin Abdollahi\n",
"# Information about this code:\n",
"# - Motor axons are not included\n",
"# - there are not transverse connections between Boundary and Boundary"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "af4c646e",
"metadata": {},
"outputs": [],
"source": [
"# show the time of execution\n",
"from datetime import datetime\n",
"start_time = datetime.now()\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "493e7e8a",
"metadata": {},
"outputs": [],
"source": [
"from neuron import h\n",
"import netpyne \n",
"from netpyne import specs, sim \n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from typing import Tuple, List\n",
"import math\n",
"import sys\n",
"\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "d05a8722",
"metadata": {},
"outputs": [],
"source": [
"# Import nesseccery files from Matlab\n",
"\n",
"R = np.loadtxt(\"R.txt\") # All axons with different radius\n",
"G = np.loadtxt(\"G.txt\") # Axon's groups\n",
"C = np.loadtxt(\"C.txt\") # Coordinates of each axon (x,y)\n",
"neighboringAxon = np.loadtxt(\"neighboringAxon.txt\")\n",
"dist = np.loadtxt(\"dist.txt\") \n",
"dist_edge = np.loadtxt(\"Distance_edge.txt\") \n",
"AVE_area_around_axon = np.loadtxt(\"Ave_area_around_axon.txt\")\n",
"\n",
"unique_radius = np.loadtxt(\"unique_radius.txt\") # including different types\n",
"Number_of_nodes = np.loadtxt(\"Number_of_nodes.txt\") # Number of nodes for the specified axon total length\n",
"\n",
"parameters = np.loadtxt(\"parameters.txt\") \n",
"\n",
"# importing all the connections\n",
"import scipy.io as io\n",
"\n",
"for i in range(1,2):\n",
" for j in range(1,2):\n",
" if j>=i:\n",
" l = [i, j]\n",
" z = ''.join([str(n) for n in l])\n",
" Input = io.loadmat('Connect_types_{}.mat'.format(z) , squeeze_me=True) \n",
" I = Input['SAVE']; \n",
" locals()[\"Connect_types_\"+str(z)]=[]\n",
" for v in range(len(I)):\n",
" D = I[v].strip() \n",
" locals()[\"Connect_types_\"+str(z)].append(D) \n",
"\n",
"\n",
"# Boundary connections\n",
"for i in range(1,2):\n",
" Input = io.loadmat('Boundary_to_{}.mat'.format(i) , squeeze_me=True) \n",
" I = Input['SAVE']; \n",
" locals()[\"Boundary_to_\"+str(i)]=[]\n",
" for v in range(len(I)):\n",
" D = I[v].strip() \n",
" locals()[\"Boundary_to_\"+str(i)].append(D) \n",
" \n",
"\n",
"\n",
"#\n",
"Boundary_coordinates = np.loadtxt(\"Boundary_coordinates.txt\")\n",
"Boundary_neighboring = np.loadtxt(\"Boundary_neighboring.txt\")\n",
"Boundary_dist = np.loadtxt(\"Boundary_dist.txt\") \n",
"\n",
"\n",
"############## importing files related to transverse resistance (Rg) and Areas\n",
"\n",
"for i in range(1,2):\n",
" for j in range(1,2):\n",
" if j>=i:\n",
" l = [i, j]\n",
" z = ''.join([str(n) for n in l])\n",
" Input = np.loadtxt('Rg_{}.txt'.format(z) ) \n",
" locals()[\"Rg_\"+str(z)]=Input\n",
" \n",
"\n",
"\n",
" \n",
"for i in range(1,2):\n",
" Input = np.loadtxt('Boundary_Rg_{}.txt'.format(i) ) \n",
" locals()[\"Boundary_Rg_\"+str(i)]=Input\n",
"\n",
" \n",
" \n",
" \n",
" \n",
"for i in range(1,2):\n",
" for j in range(1,2):\n",
" if j>i:\n",
" l = [i, j]\n",
" z = ''.join([str(n) for n in l])\n",
" Input = np.loadtxt('Areas_{}.txt'.format(z) ) \n",
" locals()[\"Areas_\"+str(z)]=Input\n",
" \n",
" \n",
" \n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "cf1c9f69",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\t1 \n",
"\t1 \n"
]
}
],
"source": [
"# Network parameters\n",
"netParams = specs.NetParams()\n",
"\n",
"netParams.sizeX=3000\n",
"netParams.sizeY=3000\n",
"netParams.sizeZ=3000\n",
"\n",
"\n",
"################################# Importing Axons(including C fibers and the others) and Boundary ####################################\n",
"\n",
"netParams.importCellParams(\n",
" cellInstance=True,\n",
" label='Boundary', \n",
" conds={'cellType': 'Boundary', 'cellModel': 'Boundary'},\n",
" fileName='Boundarycable.hoc', \n",
" cellName='Boundary', \n",
" importSynMechs=True) ;\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"# Myelinated axons have different types (i.e. diameters)\n",
"# How many types... do I have? print(len(unique_radius)-1), -1 because the first eleman is for C fiber\n",
"# each type is a specific diameter\n",
"\n",
"netParams.importCellParams(\n",
" cellInstance=True,\n",
" label='type1', \n",
" conds={'cellType': 'type1', 'cellModel': 'type1'},\n",
" fileName='type1.hoc', \n",
" cellName='type1', \n",
" importSynMechs=True) ;\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "d5ef8f97",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"40\n"
]
}
],
"source": [
"###################################### Locating each axon in specific (x,y) #################################################\n",
"\n",
"\n",
"for i in range(len(R)):\n",
" x = np.where(unique_radius == R[i])\n",
" \n",
" if x[0]==0:\n",
" netParams.popParams[\"Axon%s\" %i] = {\n",
" 'cellType': 'type1', \n",
" 'numCells':1 , \n",
" 'cellModel': 'type1', \n",
" 'xRange':[C[i][0], C[i][0]], \n",
" 'yRange':[0, 0], \n",
" 'zRange':[C[i][1], C[i][1]]} \n",
"\n",
" \n",
" \n",
" \n",
" \n",
"########################################### Locating Boundary Cables ########################################################\n",
"\n",
"\n",
"for i in range(len(Boundary_coordinates)):\n",
" \n",
" netParams.popParams[\"Boundary%s\" %i] = {\n",
" 'cellType': 'Boundary', \n",
" 'numCells':1 , \n",
" 'cellModel': 'Boundary', \n",
" 'xRange':[Boundary_coordinates[i][0], Boundary_coordinates[i][0]], \n",
" 'yRange':[0, 0], \n",
" 'zRange':[Boundary_coordinates[i][1], Boundary_coordinates[i][1]]} \n",
"\n",
"\n",
"\n",
"# in Total, how many Cells does Netpyne generate? Length(R)+len(Boundary_coordinates)\n",
"print(len(R)+len(Boundary_coordinates))\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "03c9154d",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 7,
"id": "4adc83be",
"metadata": {},
"outputs": [],
"source": [
"################################################### Stimulation ############################################################\n",
"# Which group of axons do you want to stimulate?\n",
"# Group1: motor axons Group2: C fibers Group3: Adelta Group4: Abeta\n",
"\n",
"\n",
"# netParams.stimSourceParams['Input1'] = {'type': 'IClamp', 'del': 1, 'dur': 0.1, 'amp': 0.4}\n",
"netParams.stimSourceParams['Input1'] = {'type': 'VClamp', 'dur': [1, 0.02, 0], 'amp':[-80, 0, 0]}\n",
"\n",
"\n",
"# for i in range(len(R)): \n",
"# if G[i]==4: # Group 4\n",
"# netParams.stimTargetParams['Input1->\"Stim_%s\"' %i] = {'source': 'Input1', 'sec':'node_0', 'loc': 0.5, 'conds': {'pop':\"Axon%s\" %i}} \n",
" \n",
"\n",
" \n",
"netParams.stimTargetParams['Input1->Stim_1'] = {'source': 'Input1', 'sec':'node_0', 'loc': 0.5, 'conds': {'pop':\"Axon0\"}} \n",
" \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "90a2f08b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Start time: 2022-10-29 09:47:01.058371\n",
"\n",
"Creating network of 40 cell populations on 1 hosts...\n",
" Number of cells on node 0: 40 \n",
" Done; cell creation time = 4.37 s.\n",
"Making connections...\n",
" Number of connections on node 0: 0 \n",
" Done; cell connection time = 0.00 s.\n",
"Adding stims...\n",
" Number of stims on node 0: 1 \n",
" Done; cell stims creation time = 0.00 s.\n",
"Recording 60 traces of 2 types on node 0\n"
]
}
],
"source": [
"simConfig = specs.SimConfig()\n",
"simConfig.hParams = {'celsius': 37 }\n",
"\n",
"simConfig.dt = 0.005 # Internal integration timestep to use default is 0.025\n",
"simConfig.duration = 6\n",
"simConfig.recordStim = True\n",
"simConfig.recordStep = 0.005 # Step size in ms to save data (e.g. V traces, LFP, etc) default is 0.1\n",
"#simConfig.cache_efficient = True\n",
"#simConfig.cvode_active = True\n",
"# simConfig.cvode_atol=0.0001\n",
"# simConfig.cvode_rtol=0.0001\n",
"\n",
"\n",
"simConfig.recordTraces = {'V_node_0' :{'sec':'node_0','loc':0.5,'var':'v'}}\n",
"simConfig.analysis['plotTraces'] = {'include': ['allCells']} # ['Axon0','Axon1']\n",
"\n",
"simConfig.analysis['plot2Dnet'] = True\n",
"simConfig.analysis['plot2Dnet'] = {'include': ['allCells'], 'view': 'xz'}\n",
"\n",
"\n",
"\n",
"#simConfig.recordLFP = [[56.39,-4000,51.74]] # Determine the location of the LFP electrode\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"sim.create(netParams, simConfig)\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "9045099d",
"metadata": {},
"source": [
"### xraxial and transverese conductances"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "41af5705",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n",
"3.0\n",
"1903.5717144126938\n"
]
}
],
"source": [
"# Since by default Netpyne does not insert the parameters of the extracellular mechanism, I insert them in this section\n",
"# this section includes \"longitudinal\" resistivities (i.e. xraxial)\n",
"\n",
"#Total_Length=10000\n",
"\n",
"number_boundary = 4000 #Total_Length/Section_Length \n",
"number_boundary = int(number_boundary)\n",
"\n",
"\n",
"\n",
"\n",
"rhoa=0.7e6 \n",
"mycm=0.1 \n",
"mygm=0.001 \n",
"\n",
"space_p1=0.002 \n",
"space_p2=0.004\n",
"space_i=0.004\n",
"\n",
"\n",
"\n",
"\n",
"############################# For Boundary Cables #################################################\n",
"\n",
"# soma section is just for LFP recording, LFP in Netpyne does not work if at least one section is not called soma \n",
"\n",
"\n",
"for j in range(len(R),len(R)+len(Boundary_coordinates)):\n",
" \n",
" S = sim.net.cells[j].secs[\"soma\"][\"hObj\"] \n",
" for seg in S:\n",
" seg.xraxial[0] = 1e9\n",
" seg.xraxial[1] = 1e9\n",
" seg.xg[0] = 1e9\n",
" seg.xg[1] = 1000 #1e9\n",
" seg.xc[0] = 0\n",
" seg.xc[1] = 0\n",
"\n",
"\n",
" for i in range(number_boundary): \n",
" S = sim.net.cells[j].secs[\"section_%s\" %i][\"hObj\"]\n",
" for seg in S:\n",
" seg.xraxial[0] = 1e9\n",
" seg.xraxial[1] = 1e9\n",
" seg.xg[0] = 1e9\n",
" seg.xg[1] = 1000 #1e9\n",
" seg.xc[0] = 0\n",
" seg.xc[1] = 0\n",
" \n",
" \n",
" \n",
" \n",
"\n",
"############################# For C fibers #######################################################\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" \n",
" \n",
" \n",
"\n",
" \n",
"############################## For myelinated sensory axons ##################################### \n",
"\n",
"\n",
"rho2 = 1211 * 1e-6 # Mohm-cm\n",
"\n",
"\n",
"\n",
"\n",
"for j in range(len(R)):\n",
" if G[j]!=2: # if it is not a C fiber \n",
" x = np.where(unique_radius == R[j]) \n",
" x = int(x[0])\n",
" nodes = Number_of_nodes\n",
" nodes=int(nodes)\n",
" \n",
" \n",
" nl = parameters[4]\n",
" nodeD = parameters[1]\n",
" paraD1 = nodeD\n",
" axonD = parameters[0]\n",
" paraD2 = axonD\n",
" \n",
" Rpn0 = (rhoa*.01)/((math.pi)*((((nodeD/2)+space_p1)**2)-((nodeD/2)**2)))\n",
" Rpn1 = (rhoa*.01)/((math.pi)*((((paraD1/2)+space_p1)**2)-((paraD1/2)**2)))\n",
" Rpn2 = (rhoa*.01)/((math.pi)*((((paraD2/2)+space_p2)**2)-((paraD2/2)**2)))\n",
" Rpx = (rhoa*.01)/((math.pi)*((((axonD/2)+space_i)**2)-((axonD/2)**2)))\n",
" \n",
" \n",
" ################### xraxial[1]\n",
" \n",
" radi = R[j]\n",
" \n",
" AVE = (AVE_area_around_axon[j]+0) /2\n",
" \n",
" xr = rho2 / ((math.pi)*(((radi+AVE)**2) - (radi**2)) * 1e-8) # Mohm/cm\n",
" \n",
" xr = xr /1\n",
" \n",
" print(AVE_area_around_axon[j]+0)\n",
" print(xr)\n",
" \n",
" ##################\n",
" \n",
" \n",
" \n",
"\n",
" S = sim.net.cells[j].secs[\"soma\"][\"hObj\"]\n",
" for seg in S:\n",
" seg.xraxial[0] = Rpn1\n",
" seg.xraxial[1] = xr \n",
" seg.xg[0] = mygm/(nl*2)\n",
" seg.xg[1] = 1e-9 # disconnect from ground\n",
" seg.xc[0] = mycm/(nl*2)\n",
" seg.xc[1] = 0\n",
"\n",
" \n",
" for i in range(nodes):\n",
" S = sim.net.cells[j].secs[\"node_%s\" %i][\"hObj\"]\n",
" for seg in S:\n",
" seg.xraxial[0] = Rpn0\n",
" seg.xraxial[1] = xr\n",
" seg.xg[0] = 1e6\n",
" seg.xg[1] = 1e-9\n",
" seg.xc[0] = 0\n",
" seg.xc[1] = 0\n",
"\n",
"\n",
" for i in range(2*nodes):\n",
" S = sim.net.cells[j].secs[\"MYSA_%s\" %i][\"hObj\"]\n",
" for seg in S:\n",
" seg.xraxial[0] = Rpn1\n",
" seg.xraxial[1] = xr\n",
" seg.xg[0] = mygm/(nl*2)\n",
" seg.xg[1] = 1e-9\n",
" seg.xc[0] = mycm/(nl*2)\n",
" seg.xc[1] = 0\n",
"\n",
"\n",
" for i in range(10*nodes):\n",
" S = sim.net.cells[j].secs[\"FLUT_%s\" %i][\"hObj\"]\n",
" for seg in S:\n",
" seg.xraxial[0] = Rpn2\n",
" seg.xraxial[1] = xr\n",
" seg.xg[0] = mygm/(nl*2)\n",
" seg.xg[1] = 1e-9\n",
" seg.xc[0] = mycm/(nl*2)\n",
" seg.xc[1] = 0 \n",
"\n",
"\n",
" for i in range(40*nodes):\n",
" S = sim.net.cells[j].secs[\"STIN_%s\" %i][\"hObj\"]\n",
" for seg in S:\n",
" seg.xraxial[0] = Rpx\n",
" seg.xraxial[1] = xr\n",
" seg.xg[0] = mygm/(nl*2)\n",
" seg.xg[1] = 1e-9\n",
" seg.xc[0] = mycm/(nl*2)\n",
" seg.xc[1] = 0\n",
" \n",
" \n",
" \n",
" \n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "afaf323f",
"metadata": {},
"outputs": [],
"source": [
"\n",
"##############################This section is about transverse connections between axons #####################################\n",
"# *** If you do not want to include ephaptic interaction, do not run this section\n",
"# To model ephaptic effect, \"LinearMechanism\" in NEURON is used.\n",
"\n",
"\n",
"\n",
"rho = 1211 * 10000 # ohm-micron\n",
"\n",
"count = 0\n",
"\n",
"for i in range(len(R)): \n",
"\n",
" \n",
" for j in range(len(R)): \n",
" \n",
" if neighboringAxon[i][j]==1:\n",
" \n",
"\n",
" a1 = np.where(unique_radius == R[i]) # find type of R[i]\n",
" a1 = a1[0][0]+1\n",
" a2 = np.where(unique_radius == R[j]) # find type of R[j]\n",
" a2 = a2[0][0]+1\n",
"\n",
"\n",
" NSEG = 0\n",
"\n",
"\n",
"\n",
" if a1==a2:\n",
" SEC = locals()[\"Connect_types_\"+str(a1)+str(a1)]\n",
" RG = locals()[\"Rg_\"+str(a1)+str(a1)]\n",
" area = (math.pi)*(parameters[1])*(np.ones((len(RG),1))) # micron^2\n",
" area = area * 1e-8 #cm^2\n",
" b1=i\n",
" b2=j\n",
" if a1==0:\n",
" area = (math.pi)*0.8*10*(np.ones((len(RG),1))) # micron^2\n",
" area = area * 1e-8 #cm^2\n",
" \n",
" \n",
"\n",
" if a1<a2:\n",
" SEC = locals()[\"Connect_types_\"+str(a1)+str(a2)]\n",
" RG = locals()[\"Rg_\"+str(a1)+str(a2)]\n",
" b1=i\n",
" b2=j\n",
" if a1==0:\n",
" area = (math.pi)*(parameters[a2][1])*(np.ones((len(RG),1)))\n",
" area = area * 1e-8 #cm^2\n",
" b1=j\n",
" b2=i\n",
" \n",
" else:\n",
" area = locals()[\"Areas_\"+str(a1)+str(a2)]\n",
" area = area[ : , np.newaxis]\n",
" area = area * 1e-8\n",
" \n",
" \n",
"\n",
" if a1>a2:\n",
" SEC = locals()[\"Connect_types_\"+str(a2)+str(a1)]\n",
" RG = locals()[\"Rg_\"+str(a2)+str(a1)]\n",
" b1=j\n",
" b2=i\n",
" if a2==0:\n",
" area = (math.pi)*(parameters[a1][1])*(np.ones((len(RG),1)))\n",
" area = area * 1e-8 #cm^2\n",
" b1=i\n",
" b2=j\n",
" \n",
" else:\n",
" area = locals()[\"Areas_\"+str(a2)+str(a1)]\n",
" area = area[ : , np.newaxis]\n",
" area = area * 1e-8\n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n",
"\n",
" locals()[\"sl\"+str(count)] = h.SectionList()\n",
"\n",
" for z1 in range(int(len(SEC)/2)): \n",
"\n",
" S = sim.net.cells[b1].secs[SEC[z1]][\"hObj\"]\n",
" NSEG=NSEG+S.nseg\n",
" locals()[\"sl\"+str(count)].append(S)\n",
"\n",
" for z2 in range(int(len(SEC)/2),int(len(SEC))):\n",
"\n",
" S = sim.net.cells[b2].secs[SEC[z2]][\"hObj\"]\n",
" locals()[\"sl\"+str(count)].append(S) \n",
" \n",
" \n",
"\n",
" nsegs=int(NSEG)\n",
"\n",
" locals()[\"gmat\"+str(count)] =h.Matrix(2*nsegs, 2*nsegs)\n",
" locals()[\"cmat\"+str(count)] =h.Matrix(2*nsegs, 2*nsegs)\n",
" locals()[\"bvec\"+str(count)] =h.Vector(2*nsegs)\n",
" locals()[\"xl\"+str(count)] =h.Vector(2*nsegs)\n",
" locals()[\"layer\"+str(count)] =h.Vector(2*nsegs)\n",
" locals()[\"layer\"+str(count)].fill(2) # connect layer 2\n",
" locals()[\"e\"+str(count)] = h.Vector(2*nsegs)\n",
"\n",
" for z3 in range(2*nsegs):\n",
" locals()[\"xl\"+str(count)][z3] = 0.5\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" d = dist_edge[i][j] + 2.991374 #dist[i][j]\n",
" rd = rho*d\n",
" s = ((unique_radius*2)+(unique_radius*2))/2\n",
" locals()[\"RG\"+str(count)] = np.array(RG)*s\n",
" locals()[\"Resistance\"+str(count)] = rd/locals()[\"RG\"+str(count)]\n",
" locals()[\"Conductance\"+str(count)]=[]\n",
" for z4 in range(len(locals()[\"Resistance\"+str(count)])):\n",
" locals()[\"Conductance\"+str(count)].append(1/(locals()[\"Resistance\"+str(count)][z4]*area[z4]))\n",
" \n",
"\n",
" \n",
" for z5 in range(0,nsegs,1):\n",
"\n",
" locals()[\"gmat\"+str(count)].setval(z5, z5, locals()[\"Conductance\"+str(count)][z5][0] )\n",
" locals()[\"gmat\"+str(count)].setval(z5, nsegs+z5, -locals()[\"Conductance\"+str(count)][z5][0])\n",
" locals()[\"gmat\"+str(count)].setval(nsegs+z5, z5, -locals()[\"Conductance\"+str(count)][z5][0])\n",
" locals()[\"gmat\"+str(count)].setval(nsegs+z5, nsegs+z5, locals()[\"Conductance\"+str(count)][z5][0])\n",
" \n",
" \n",
" locals()[\"GMAT\"+str(i)+str(j)] = locals()[\"gmat\"+str(count)]\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n",
"\n",
"\n",
"\n",
"\n",
"# geA= 1000\n",
" \n",
"# for z5 in range(0,nsegs,1):\n",
"# locals()[\"gmat\"+str(count)].setval(z5, z5, geA)\n",
"# locals()[\"gmat\"+str(count)].setval(z5, nsegs+z5, -geA)\n",
"# locals()[\"gmat\"+str(count)].setval(nsegs+z5, z5, -geA)\n",
"# locals()[\"gmat\"+str(count)].setval(nsegs+z5, nsegs+z5, geA)\n",
"\n",
"\n",
"\n",
"\n",
" locals()[\"lm\"+str(count)] = h.LinearMechanism(locals()[\"cmat\"+str(count)], locals()[\"gmat\"+str(count)], locals()[\"e\"+str(count)], locals()[\"bvec\"+str(count)], locals()[\"sl\"+str(count)], locals()[\"xl\"+str(count)], locals()[\"layer\"+str(count)])\n",
"\n",
" count=count+1\n",
" \n",
" SEC.clear\n",
" del RG\n",
" del area\n",
" \n",
" \n",
"\n",
" \n",
"#print(count) \n",
" \n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b71ff07f",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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]
},
{
"data": {
"text/plain": [
"0.0"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"GMAT1516.printf() "
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "9f7204b0",
"metadata": {},
"outputs": [],
"source": [
" \n",
" \n",
" \n",
"############################### Transverse connections between Boundary cables and Axons ######################################\n",
"\n",
"\n",
"rho = 1.136e5 * 10000 * 4.7e-4 * 10000 # ohm-micron^2\n",
"\n",
"\n",
"\n",
"rows = len(Boundary_neighboring)\n",
"\n",
"for i in range(rows):\n",
" \n",
" for j in range(len(R)):\n",
" \n",
" if Boundary_neighboring[i][j]==1:\n",
" \n",
" NSEG = 0\n",
"\n",
" a2 = np.where(unique_radius == R[j]) # find type \n",
" a2 = a2[0][0]+1\n",
" \n",
" Boundary_RG = locals()[\"Boundary_Rg_\"+str(1)]\n",
" area = (math.pi)*(parameters[1])*(np.ones((len(Boundary_RG),1)))\n",
" area = area * 1e-8 #cm^2\n",
" \n",
"\n",
" SEC = locals()[\"Boundary_to_\"+str(1)]\n",
"\n",
"\n",
" locals()[\"sl\"+str(count)] = h.SectionList()\n",
"\n",
" for z1 in range(int(len(SEC)/2)): \n",
"\n",
" S = sim.net.cells[j].secs[SEC[z1]][\"hObj\"]\n",
" NSEG=NSEG+S.nseg\n",
" locals()[\"sl\"+str(count)].append(S)\n",
"\n",
" for z2 in range(int(len(SEC)/2),int(len(SEC))):\n",
"\n",
" S = sim.net.cells[len(R)+i].secs[SEC[z2]][\"hObj\"]\n",
" locals()[\"sl\"+str(count)].append(S) \n",
"\n",
"\n",
"\n",
"\n",
" nsegs=int(NSEG)\n",
"\n",
" locals()[\"gmat\"+str(count)] =h.Matrix(2*nsegs, 2*nsegs)\n",
" locals()[\"cmat\"+str(count)] =h.Matrix(2*nsegs, 2*nsegs)\n",
" locals()[\"bvec\"+str(count)] =h.Vector(2*nsegs)\n",
" locals()[\"xl\"+str(count)] =h.Vector(2*nsegs)\n",
" locals()[\"layer\"+str(count)] =h.Vector(2*nsegs)\n",
" locals()[\"layer\"+str(count)].fill(2) # connect layer 2\n",
" locals()[\"e\"+str(count)] = h.Vector(2*nsegs)\n",
"\n",
" for z3 in range(2*nsegs):\n",
" locals()[\"xl\"+str(count)][z3] = 0.5\n",
"\n",
"\n",
" \n",
" \n",
" rd = rho + (1211 * 10000 * Boundary_dist[i][j] )\n",
" s = (unique_radius*2)\n",
" locals()[\"Boundary_RG\"+str(count)] = np.array(Boundary_RG)*s\n",
" locals()[\"Resistance\"+str(count)] = rd/locals()[\"Boundary_RG\"+str(count)]\n",
" locals()[\"Conductance\"+str(count)]=[]\n",
" for z4 in range(len(locals()[\"Resistance\"+str(count)])):\n",
" locals()[\"Conductance\"+str(count)].append(1/(locals()[\"Resistance\"+str(count)][z4]*area[z4]))\n",
"\n",
" \n",
" for z5 in range(0,nsegs,1):\n",
"\n",
" locals()[\"gmat\"+str(count)].setval(z5, z5, locals()[\"Conductance\"+str(count)][z5][0] * 1)\n",
" locals()[\"gmat\"+str(count)].setval(z5, nsegs+z5, - locals()[\"Conductance\"+str(count)][z5][0] * 1)\n",
" locals()[\"gmat\"+str(count)].setval(nsegs+z5, z5, - locals()[\"Conductance\"+str(count)][z5][0] * 1)\n",
" locals()[\"gmat\"+str(count)].setval(nsegs+z5, nsegs+z5, locals()[\"Conductance\"+str(count)][z5][0] * 1)\n",
" \n",
" \n",
" \n",
" locals()[\"GMAT_BOUNDARY\"+str(i)+str(j)] = locals()[\"gmat\"+str(count)]\n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n",
"\n",
"\n",
" \n",
"# geB= 1\n",
" \n",
"# for z6 in range(0,nsegs,1):\n",
"\n",
"# locals()[\"gmat\"+str(count)].setval(z6, z6, geB)\n",
"# locals()[\"gmat\"+str(count)].setval(z6, nsegs+z6, -geB)\n",
"# locals()[\"gmat\"+str(count)].setval(nsegs+z6, z6, -geB)\n",
"# locals()[\"gmat\"+str(count)].setval(nsegs+z6, nsegs+z6, geB)\n",
"\n",
"\n",
"\n",
"\n",
" locals()[\"lm\"+str(count)] = h.LinearMechanism(locals()[\"cmat\"+str(count)], locals()[\"gmat\"+str(count)], locals()[\"e\"+str(count)], locals()[\"bvec\"+str(count)], locals()[\"sl\"+str(count)], locals()[\"xl\"+str(count)], locals()[\"layer\"+str(count)])\n",
"\n",
" count=count+1\n",
" \n",
" \n",
" SEC.clear\n",
" del Boundary_RG\n",
" del area\n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n",
"#print(count) \n",
" \n",
" \n",
" \n",
"# from IPython.display import clear_output\n",
"\n",
"# clear_output(wait=True)\n",
"\n",
"\n",
" \n",
"#gmat0.printf() \n",
"\n",
"# for sec in sl0:\n",
"# print(sec)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "7808a6c6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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]
},
{
"name": "stdout",
"output_type": "stream",
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]
},
{
"data": {
"text/plain": [
"0.0"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"GMAT_BOUNDARY55.printf() "
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "5eb4dcc1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"30.0\n"
]
}
],
"source": [
"print(Boundary_dist[0][0])"
]
},
{
"cell_type": "markdown",
"id": "b2a6c256",
"metadata": {},
"source": [
"#### Recordings"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "d1494f97",
"metadata": {},
"outputs": [],
"source": [
"## Recording vext\n",
"\n",
"\n",
"# v1 = sim.net.cells[45].secs[\"node_0\"][\"hObj\"]\n",
"# ap1 = h.Vector()\n",
"# t = h.Vector()\n",
"# ap1.record(v1(0.5)._ref_v)\n",
"\n",
"# t.record(h._ref_t)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "ca5603a0",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
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},
{
"data": {
"text/plain": [
"Vector[1583]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Recording v and vext[0], Abeta\n",
"\n",
"\n",
"\n",
"for i1 in range(len(R)): \n",
" if G[i1]==4: \n",
" print(i1)\n",
" F = np.where(unique_radius == R[i1]) \n",
" #nodes = int (Number_of_nodes[F]-1)\n",
" for i3 in range(int(Number_of_nodes)):\n",
"\n",
" locals()[\"Abeta_v\"+str(i1)+str(i3)] = sim.net.cells[i1].secs[\"node_%s\"%i3][\"hObj\"]\n",
" locals()[\"Abeta_ap\"+str(i1)+str(i3)] = h.Vector()\n",
" locals()[\"Abeta_ap\"+str(i1)+str(i3)].record(locals()[\"Abeta_v\"+str(i1)+str(i3)](0.5)._ref_v)\n",
"# locals()[\"Abeta_v_ext\"+str(i1)] = sim.net.cells[i1].secs[\"node_%s\"%nodes][\"hObj\"]\n",
"# locals()[\"Abeta_ap_ext\"+str(i1)] = h.Vector()\n",
"# locals()[\"Abeta_ap_ext\"+str(i1)].record(locals()[\"Abeta_v_ext\"+str(i1)](0.5)._ref_vext[0])\n",
" \n",
" print(i3)\n",
"# print(nodes)\n",
" \n",
"\n",
" \n",
" \n",
"t = h.Vector()\n",
"t.record(h._ref_t)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "e3f90783",
"metadata": {},
"outputs": [],
"source": [
"for i1 in range(36):\n",
"\n",
" locals()[\"Abeta0_imembrane\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
" locals()[\"Abeta0_imembrane_node\"+str(i1)] = h.Vector()\n",
" locals()[\"Abeta0_imembrane_node\"+str(i1)].record(locals()[\"Abeta0_imembrane\"+str(i1)](0.5)._ref_i_membrane)\n",
" \n",
" \n",
" \n",
"# for i1 in range(12):\n",
"\n",
"# locals()[\"Abeta0_icap\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
"# locals()[\"Abeta0_icap_node\"+str(i1)] = h.Vector()\n",
"# locals()[\"Abeta0_icap_node\"+str(i1)].record(locals()[\"Abeta0_icap\"+str(i1)](0.5)._ref_i_cap) \n",
" \n",
"\n",
" \n",
" \n",
"# for i1 in range(12):\n",
"\n",
"# locals()[\"Abeta0_ik\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
"# locals()[\"Abeta0_ik_node\"+str(i1)] = h.Vector()\n",
"# locals()[\"Abeta0_ik_node\"+str(i1)].record(locals()[\"Abeta0_ik\"+str(i1)](0.5)._ref_ik_axnode) \n",
" \n",
" \n",
" \n",
"# for i1 in range(12):\n",
"\n",
"# locals()[\"Abeta0_il\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
"# locals()[\"Abeta0_il_node\"+str(i1)] = h.Vector()\n",
"# locals()[\"Abeta0_il_node\"+str(i1)].record(locals()[\"Abeta0_il\"+str(i1)](0.5)._ref_il_axnode) \n",
" \n",
" \n",
"\n",
"# for i1 in range(12):\n",
"\n",
"# locals()[\"Abeta0_ina\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
"# locals()[\"Abeta0_ina_node\"+str(i1)] = h.Vector()\n",
"# locals()[\"Abeta0_ina_node\"+str(i1)].record(locals()[\"Abeta0_ina\"+str(i1)](0.5)._ref_ina_axnode) \n",
" \n",
" \n",
" \n",
" \n",
"# for i1 in range(12):\n",
"\n",
"# locals()[\"Abeta0_inap\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
"# locals()[\"Abeta0_inap_node\"+str(i1)] = h.Vector()\n",
"# locals()[\"Abeta0_inap_node\"+str(i1)].record(locals()[\"Abeta0_inap\"+str(i1)](0.5)._ref_inap_axnode) \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "23017f07",
"metadata": {},
"outputs": [],
"source": [
"\n",
"for i1 in range(36):\n",
"\n",
" locals()[\"Abeta0_v\"+str(i1)] = sim.net.cells[0].secs[\"node_%s\"%i1][\"hObj\"]\n",
" locals()[\"Abeta0_v_node\"+str(i1)] = h.Vector()\n",
" locals()[\"Abeta0_v_node\"+str(i1)].record(locals()[\"Abeta0_v\"+str(i1)](0.5)._ref_v)\n",
"\n",
"\n",
"\n",
"# for i2 in range(12):\n",
"\n",
"# locals()[\"Abeta0_vex\"+str(i2)] = sim.net.cells[0].secs[\"node_%s\"%i2][\"hObj\"]\n",
"# locals()[\"Abeta0_vext1_node\"+str(i2)] = h.Vector()\n",
"# locals()[\"Abeta0_vext1_node\"+str(i2)].record(locals()[\"Abeta0_vex\"+str(i2)](0.5)._ref_vext[1])\n",
"\n",
" \n",
" \n",
"# for i3 in range(0,24,2):\n",
" \n",
"# locals()[\"Abeta_vMext\"+str(i3)] = sim.net.cells[0].secs[\"MYSA_%s\"%i3][\"hObj\"]\n",
"# locals()[\"Abeta0_vext1_MYSA\"+str(i3)] = h.Vector()\n",
"# locals()[\"Abeta0_vext1_MYSA\"+str(i3)].record(locals()[\"Abeta_vMext\"+str(i3)](0.5)._ref_vext[1])\n",
"\n",
"\n",
" \n",
"# for i4 in range(12):\n",
"\n",
"# locals()[\"Abeta1_vext1\"+str(i4)] = sim.net.cells[1].secs[\"node_%s\"%i4][\"hObj\"]\n",
"# locals()[\"Abeta1_vext1_node\"+str(i4)] = h.Vector()\n",
"# locals()[\"Abeta1_vext1_node\"+str(i4)].record(locals()[\"Abeta1_vext1\"+str(i4)](0.5)._ref_vext[1]) \n",
" \n",
" \n",
" \n",
"# locals()[\"Abeta_vSext\"+str(220)] = sim.net.cells[0].secs[\"STIN_220\"][\"hObj\"]\n",
"# locals()[\"Abeta0_vext1_STIN\"+str(220)] = h.Vector()\n",
"# locals()[\"Abeta0_vext1_STIN\"+str(220)].record(locals()[\"Abeta_vSext\"+str(220)](0.5)._ref_vext[1]) \n",
" \n",
"# locals()[\"Abeta_v\"+str(220)] = sim.net.cells[0].secs[\"STIN_220\"][\"hObj\"]\n",
"# locals()[\"Abeta0_v_STIN\"+str(220)] = h.Vector()\n",
"# locals()[\"Abeta0_v_STIN\"+str(220)].record(locals()[\"Abeta_v\"+str(220)](0.5)._ref_v) \n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "4b9344bb",
"metadata": {},
"outputs": [],
"source": [
"## Recording v and vext[0], Adelta\n",
"\n",
"\n",
"\n",
"# for i2 in range(len(R)): \n",
"# if G[i2]==3: \n",
"# F = np.where(unique_radius == R[i2]) \n",
"# nodes = int (Number_of_nodes[F]-1)\n",
"# locals()[\"Adelta_v\"+str(i2)] = sim.net.cells[i2].secs[\"node_%s\"%nodes][\"hObj\"]\n",
"# locals()[\"Adelta_ap\"+str(i2)] = h.Vector()\n",
"# locals()[\"Adelta_ap\"+str(i2)].record(locals()[\"Adelta_v\"+str(i2)](0.5)._ref_v)\n",
"# locals()[\"Adelta_v_ext\"+str(i2)] = sim.net.cells[i2].secs[\"node_%s\"%nodes][\"hObj\"]\n",
"# locals()[\"Adelta_ap_ext\"+str(i2)] = h.Vector()\n",
"# locals()[\"Adelta_ap_ext\"+str(i2)].record(locals()[\"Adelta_v_ext\"+str(i2)](0.5)._ref_vext[0])\n",
"# print(i2)\n",
" \n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "d83f15db",
"metadata": {},
"source": [
"#### Simulate and Analyze"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "cd6d9f09",
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Running simulation for 6.0 ms...\n",
" Done; run time = 3085.87 s; real-time ratio: 0.00.\n",
"\n",
"Gathering data...\n",
" Done; gather time = 6.71 s.\n",
"\n",
"Analyzing...\n",
" Cells: 40\n",
" Connections: 0 (0.00 per cell)\n",
" Spikes: 1 (4.17 Hz)\n",
" Simulated time: 0.0 s; 1 workers\n",
" Run time: 3085.87 s\n",
" Done; saving time = 0.00 s.\n",
"Plotting recorded cell traces ... cell\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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q4lXBpps27++8c7R1kSRpPjIwal6Y6pJ20oskSYNnYNTEq4KFC5v3BkZJkgbPwKiJZ2CUJKldBkZNPAOjJEntMjBqXjAwSpLUHgOjJl53C6OzpCVJGjwDoyaeXdKSJLXLwKiJZ2CUJKldBkbNC67DKElSewyMmni2MEqS1C4Do+YFJ71IktQeA6MmWlXzOvUsaVsYJUkaPAOj5gXHMEqS1B4DoybaVAujYxglSWqPgVETzcAoSVL7DIyaaAZGSZLaZ2DUvDA1htFZ0pIkDZ6BURPNFkZJktpnYNREc1kdSZLaZ2DUvOCyOpIktcfAqIlml7QkSe0zMGqiGRglSWqfgVETrTcwOktakqTBMzBqXrCFUZKk9hgYNdHskpYkqX0GRk00A6MkSe0zMGqiGRglSWqfgVHzguswSpLUHgOjJpqzpCVJap+BURPNLmlJktpnYNRE81nSkiS1z8CoecExjJIktWdsAmOS1T3b2iTv6Tr+oiSXd459KcnOfa714CTnJrmpc87/6Tn++CSXJbklydeT7NZ1LElOSHJDZ3tHkrTzrbWhploYDYySJLVnbAJjVS2Z2oAdgVuB0wGSHAAcDxwEbAdcAZw23XWSLAQ+C3yhU/YI4GNJHtg5vgNwJnBs5/hy4JNdlzgCeCawH7Av8HTgyAF+VQ3QVGBcsAASA6MkSW0Ym8DY49nAdcD5nc/PAE6vqkur6nbgLcD+SfaY5ty9gJ2Bd1XV2qo6F7gQOLRz/FnApVV1elWtAY4D9kuyV+f44cA7q+rqqroGeCfwwoF/Qw3EVGBMmlZGZ0lLkjR44xoYDwdOrZqKA6Sz0fUZYJ9pzp2u+zhdZfcGLp46UFU3Az/t7L/H8c77vdFYS5qZ0rYwSpI0eGMXGJPsChwAfKRr99nAc5Psm2QL4A1AAVtOc4nLaFonj0myaZIndq43VXYJcFPPOTcBW81w/CZgyUzjGJMckWR5kuUrVqyY7dfUgPzPf1LQtDAaGCVJGryhBMYk5yWpGbYLeoofBlxQVVdM7aiqrwFvBM4ArgKuBFYBV/feq6ruoBmD+DTgWuBVwKe6yq4Gtu45bevO9aY7vjWwuqu1s/d+p1TVsqpatnTp0n4/g1rQ2yVtYJQkafCGEhir6sCqygzbY3uKH8bdWxenrnFyVe1ZVfemCY4LgR/McL9LquqAqtq+qp4E3B+4qHP4UpoJLQAkWQzs0dl/j+Od95eisWRglCSpfWPVJZ3k0cAudGZHd+1flGSfzpI3uwKnACdW1Y0zXGffzjlbJvkrYCfgw53DZwH7JDk4ySKa7u1LquqyzvFTgVcm2aWzdM+rus7VmHLSiyRJ7RmrwEgz2eXMqlrVs38R8Ama7uKLgG/RLIsDQJLXJjmnq/yhwC9pxjI+HnhCVd0GUFUrgIOBtwI3Ao8CDuk69wPA54Hv07RgfrGzT2PIMYySJLVv4agr0K2qpl3vsKp+Q7Mm4kznHd/z+RjgmD7lv0qz/M50xwp4dWfTmOvuknaWtCRJ7Ri3FkZpThzDKElS+wyMmhcMjJIktcfAqInmGEZJktpnYNRE89GAkiS1z8CoieYYRkmS2mdg1LzgLGlJktpjYNREcwyjJEntMzBqotklLUlS+wyMmmgGRkmS2mdg1LzgLGlJktpjYNREcwyjJEntMzBqovksaUmS2mdg1LzgGEZJktpjYNREs0takqT2GRg10ZwlLUlS+wyMmmg+S1qSpPYZGDUv2MIoSVJ7DIyaaN1jGJ0lLUlSOwyMmmiOYZQkqX0GRk00A6MkSe0zMGpecNKLJEntMTBqorkOoyRJ7TMwaqLZJS1JUvsMjJpoPktakqT2GRg1L9jCKElSewyMmmiOYZQkqX0GRk00Hw0oSVL7DIyaaE56kSSpfQZGzQsGRkmS2mNg1ETzWdKSJLXPwKiJZpe0JEntMzBqovUGxir47W9HWydJkuYbA6PmhanACLYySpI0aAZGTbTedRjBwChJ0qAZGDXRerukwcAoSdKgGRg10QyMkiS1z8CoeSFpltUBA6MkSYNmYNREcwyjJEntMzBqok3XJe3zpCVJGqyxCYxJVvdsa5O8p+v4i5Jc3jn2pSQ797nWg5Ocm+Smzjn/p+vY7yf5SpJfJ1mR5PQkO3UdPy7JHT11uX9731wbwjGMkiS1b2wCY1UtmdqAHYFbgdMBkhwAHA8cBGwHXAGcNt11kiwEPgt8oVP2COBjSR7YKbItcAqwO7AbsAr4UM9lPtldn6r62cC+qFphYJQkqT1jExh7PBu4Dji/8/kZwOlVdWlV3Q68Bdg/yR7TnLsXsDPwrqpaW1XnAhcChwJU1TlVdXpVrayqW4CTgMe0/H3UEscwSpLUvnENjIcDp1b9TxxIZ6PrM8A+05ybGfZNVxZgf+DSnn3P6HRZX5rkqFnWWSPQ3SXtLGlJktoxdoExya7AAcBHunafDTw3yb5JtgDeABSw5TSXuIymdfKYJJsmeWLnevcom2TfzrWO6dr9KeDBwFLgxcAbkjyvT32PSLI8yfIVK1bM4ZtqEBzDKElS+4YSGJOcl6Rm2C7oKX4YcEFVXTG1o6q+BrwROAO4CriSZuzh1b33qqo7gGcCTwOuBV5FEwLvVjbJA4BzgL+sqvO7zv9hVf2i0539TeBEmi7yaVXVKVW1rKqWLV26dLY/iQbMWdKSJLVnKIGxqg6sqsywPban+GHcvXVx6honV9WeVXVvmuC4EPjBDPe7pKoOqKrtq+pJwP2Bi6aOJ9kN+Crwlqr66Lqqz/Td3BoDjmGUJKl9Y9UlneTRwC50Zkd37V+UZJ80dqWZ5XxiVd04w3X27ZyzZZK/AnYCPtw5tgtwLnByVb1/mnMPSrJt516PBF5GM+taY8guaUmS2jdWgZFmssuZVbWqZ/8i4BPAapqWwm8Bx04dTPLaJOd0lT8U+CXNWMbHA0+oqts6x15E0+L4xu61FrvOPQS4nKbL+1TghKq6R4unxouBUZKk9iwcdQW6VdWRM+z/DbBvn/OO7/l8DHefyNJ97E3Am/pca8YJLho/3V3SzpKWJKkd49bCKM2JjwaUJKl9Y9XCKM1Vd2Bc0PnPH1sYJUkaLFsYNS84hlGSpPYYGDXRXFZHkqT2GRg10VxWR5Kk9hkYNdF8lrQkSe0zMGpecJa0JEntMTBqojmGUZKk9hkYNdEcwyhJUvsMjJpoBkZJktpnYNS8YGCUJKk9BkZNNJ8lLUlS+wyMmmg+S1qSpPYZGDXRHMMoSVL7DIyaFwyMkiS1x8CoieY6jJIktc/AqIlml7QkSe0zMGqi+SxpSZLaZ2DUvOAsaUmS2mNg1ERzDKMkSe0zMGqiTdclbQujJEmDZWDUROsOjJtu2ry/447R1UeSpPnIwKh5IbkrNN5226hrI0nS/GJg1ETrHsMIsPnmcPvto6mLJEnzlYFRE627Sxpgs81sYZQkadAMjJpo0wVGWxglSRosA6PmhanAuPnmtjBKkjRoBkZNtN4xjLYwSpI0eAZGTbTeLmknvUiSNHgGRk00J71IktS+hbMplOSJwAuBvYGtgFXApcCHquorrdVOmiVbGCVJas86A2OSVwCvBv4JOAO4Cdga2A/4SJITqurEVmspzWC6MYy2MEqSNFizaWE8BnhcVV3Ws//MJKcBXwcMjBqJ6bqkV60aXX0kSZqPZjOGcTHwixmOXQtsObjqSOvHZXUkSWrPbALjGcDnkzw+ydIkmyXZIcnjgbOAT7dbRWlmLqsjSVL7ZhMY/xz4JvAR4FfArZ3XjwD/DhzVWu2kdZhuWR1bGCVJGqx1jmGsqtuBvwH+Jsk2wBJgdVX9prdsksdU1YWDrqQ0Ex8NKElS+2a1rM6UTkj8TZ8i59DMoJaGymV1JElqz6AX7s6Aryf15bI6kiS1b9CBsdZdZHpJVvdsa5O8p+v4i5Jc3jn2pSQ797nWg5Ocm+Smzjn/p+vY7kmq517Hdh1PkhOS3NDZ3pHEIDymerukt9gCbr11dPWRJGk+GptHA1bVkqkN2JFmcs3pAEkOAI4HDgK2A64ATpvuOkkWAp8FvtApewTwsSQP7Cm6Tdc939K1/wjgmTQLk+8LPB04ciBfUgPXGxgXL4Y1a2Dt2tHVSZKk+WZsAmOPZwPXAed3Pj8DOL2qLu1MwnkLsH+SPaY5dy9gZ+BdVbW2qs4FLgQOneW9DwfeWVVXV9U1wDtpHouoMTYVGJcsaV5vvnl0dZEkab4Z1zGMhwOnVv3PCLX0XHvq/T6zrEOmKXtVkquTfCjJDl379wYu7vp8cWefxlDvGEYDoyRJgzenwJhk+ySHJnl15/POSX5n6nhVbbWhFUqyK3AAzTqPU84Gnptk3yRbAG+gGS853VNmLqNpnTwmyaZJnti53lTZ64FHALsBDwe2Aj7edf4SmudlT7kJWDLTOMYkRyRZnmT5ihUr5vZltcGm65IGWL16NPWRJGk+mnVg7Iwj/C/gBcDUJJE9gffN4tzzOhNNptsu6Cl+GHBBVV0xtaOqvga8keapM1cBVwKrgKt771VVd9CMQXwazaMLXwV8aqpsVa2uquVVdWdV/Qp4CfDEJFPLAa3m7ksDbU2z7uS0E3qq6pSqWlZVy5YuXbqun0ID1hsYbWGUJGnw5tLC+G7gj6vqycCdnX3fBh65rhOr6sCqygzbY3uKH8bdWxenrnFyVe1ZVfemCY4LgR/McL9LquqAqtq+qp4E3B+4aKbqdV6nWhAvpZnwMmW/zj6NMVsYJUlqz1wC4+6dlj64K2TdzhwX/+4nyaOBXejMju7avyjJPp0lb3YFTgFOrKobZ7jOvp1ztkzyV8BOwIc7xx6V5EFJFiTZHvhH4LyqmuqGPhV4ZZJdOkv3vGrqXI0fxzBKktS+uQTGHyZ5Us++PwK+P8D6HA6cWVWrevYvAj5B0118EfAt7uoWJ8lrk5zTVf5Q4Jc0YxkfDzyhqqaWc74/8CWaLu0fALcBz+s69wPA52m+1w+AL3b2aQw5hlGSpPbNpXXwVcAXknwR2CLJB2iWuzloUJWpqmnXO+w8knDfPucd3/P5GOCYGcqexgxrOHaOF/DqzqYx5xhGSZLaN+sWxqr6d+4az/f/aBbPfmRVfaelukmzNhUYt+rM01+5cnR1kSRpvpnT+MPOQtbvaKku0pz1jmHcZpvm9cZpR7dKkqT10TcwJvkos3g+dFUdNrAaSXPQ2yW96aZNt7SBUZKkwVlXl/TlwE8720006xtuQrOm4QKa8Yu/aa96Un+9gRFg220NjJIkDVLfFsaqetPU+yRfBp5WVed37XssXbOVpVHpDozbbQe//vXo6iJJ0nwzl2V1fh/495593wb+YHDVkeZmuufv2MIoSdJgzSUw/idwfOdZznRe3wp8r4V6SbMyXZe0LYySJA3WXALjC4HHADcl+RXNmMbH0jzKTxoJxzBKktS+WS+rU1VXAo9Ocl9gZ+CXVfXfbVVMmovewGgLoyRJgzOXFkaSbAs8DvhfwIGdz9LITDeGcbvtYM0auPXW4ddHkqT5aNaBMckf0Cyv8+c0j+k7EvhpZ780EjN1SYPd0pIkDcpcnvTybuDoqvqXqR1J/hj4R+ARA66XNCszTXqBJjDuvPPw6yRJ0nwzly7pBwKf6tn3aeABg6uOtH5sYZQkqT1zCYw/AQ7p2fccmm5qaSRmWocRnPgiSdKgzKVL+uXAF5K8DLgK2B3YE3j64Kslzc50XdI77NC8Xn/98OsjSdJ8NJdldb6ZZA/gaTTL6nweOLuqbMfRyEwXGJcubV6vu2749ZEkaT6aSwsjVXUj8LGW6iKtt+7AuHhxsxkYJUkajFkHxiT3o3kU4EOBJd3HqmrXwVZLmp3pxjAC3PveBkZJkgZlLi2Mn6CZ4PIq4JZ2qiPNzXRd0mBglCRpkOYSGPcGHlNVv22rMtL66g2MO+4IP/vZaOoiSdJ8M5dldf4N+L22KiKtj5m6pHfdFf7bJ51LkjQQc2lhvBL4cpIzgWu7D1TVGwZZKWm2ZuqS3m03WLkSfvMb2GabYddKkqT5ZS6BcTHNUjqbAvft2j9DG4/Uvn6BEeCqqwyMkiRtqLmsw/in6yqT5HlVddqGVUmau97AuOeezetll8F++w2/PpIkzSdzGcM4Gx8Y8PWkvmYaw7j33rD55vCd7wy3PpIkzUeDDoxZdxFpcGbqkt50U3jYw+D884dfJ0mS5ptBB0bHM2qoZgqMAE9/Olx0EVx99XDrJEnSfDPowCiNxHSB8eCDm9ezzhpuXSRJmm/WOeklyQIX69a4mmkMI8CDHgQPeQiccQa89KXDq5MkSTOpgjvvhNtua7Y1a9b9frbl5vp+LmYzS/qaJB8FTq2qH6yjrEsla6j6dUlD08r41rfCL34BO+88vHpJksbP2rVNULr11iY4zXYbdLD77YCa4TbfvNkWLbrrfe/nrbaaudzf//3s7zWbwPjnwJ8A30nyI+AjwCeqakVvwaraZ/a3ljbcugLjYYfB3/5t83+Kf/iH4dVLknRPVXD77XcFsdkGt0GVu+OODf8O04Wv3vdTIa1fkJvN+37HNtts5n/3zdZAA2NVfRb4bJJtgD8GDgVOSPKvNOHxc1U1gP8JpPU30/9pHvAAePGL4V3vgic8AZ7ylOHWS5LGUdVdLW292y23TL9/KoxtaHjbUIsWTb9tsUXzusMO/Y/323rLdIe0RYuaFTg2NKRNqrks3P0bmnUWP5DkfjTB8V2dfTu0UjtpHfqNYZzy7nfDt78NhxwC3/xms0ajJI2T3/72rpC1rq1foJtt+TVrZvf3czoLF/YPWUuW3DO0rSuszfb4IFrVtH7m8mhAAJJsDjwCeBSwI/DNQVdKmq11dUlD84fm85+HRz4SnvQk+MxnYNmyoVRP0oS7444mcN18c/M63dbv2GwD3VwnIHTbbDPYcsvmb13vdq97wX3uc8/9M5WfaZsqv2hRExi18Zn1/+xJHgscBjwXuA74KHB0VV3VUt2kdZpNYAS4733hy1+GZzwDHvtYeP/74YUvbL16kloyNRauX2Bbn5DXu//OO+det6kWselC1/bbzy2grWtbtAg22WTwv6/UazbL6hxH0/28HXA68LSqurDleklzMpsuin33heXLm67pP/1T+Na3mokwixe3Xz9pY7R2bRPAVq9uXrvfT7ev+/1swtz6zDTdcsvpt3vdq1lJYbpjixfPfv8WWxjgND/NpoXx94HXAZ+pqgEMV5UGZ65jcJYubVoaX/c6+Lu/g699DU49FR796HbqJ427qmY82/qEunW9n2s36xZbNCFsapsKYTvsMHPQm0uYW7QIFvi4Cmm9zGaW9JOHURFpfcy2S7rbwoVwwgnw1Kc23dJ/+Ifw6lfDccc1M+GkcVXVjHlbvRpWrWq22b7vFwLn8h9eCxc2YWzJkruC3ZIlTVfrrrvec/9s32+5pS1z0jhz6Kom2voExikHHACXXAKvfCW8/e3whS/ABz5ga6MGp6oJZHMJdv3er17ddPPOxmabNWFsq63uel28uGmtW99Qt3ixs1SljZWBUfPC+v4LbKut4J/+CQ46CI4+Gh7zGDjiCHjb22C77QZbR02O22+HlSvhppua1+73M+2bLujNpfVuiy3uCnZTIW/77WH33e+5v9/7qdfNNmv1J5K0kRmbwJhkdc+uLYD3VtVLO8dfBLwGuA9wAfB/q+oXM1zrwcDJwMOBFcAxVXVW59gLaNaOnLKgc69lVfXdziSf1wHdo2/2raqfbdg3VBvWdx2xXk9/Ohx4YNMt/e53w1lnwfHHN13WLiExOdauvWeYm03Y6903m8WFN920mShxr3s1AW3rrWGnndYd5KZ7v2SJ/5xJGm9j8yeqqpZMvU+yGPgVzaxskhwAHA88DvgJcCJwGnBA73WSLAQ+C7wfeEKnzOeT/F5V/biqPg58vKv8C4Fjgf/ouswnq+pPBvn91I4N6ZLutWRJ85ikQw9tWhtf/GJ4xzvgzW+G5zzH8VVt+u1vm9a43hA319B3883rvteCBU3I23rru17vcx944APvvm/qdaZ9ixa1/7tI0rgYm8DY49k0az2e3/n8DOD0qroUIMlbgGuS7FFVP+05dy9gZ+BdVVXAuUkupFka6Nhp7nU4cGqnrCbMIAPjlP32gwsuaBb7ft3r4HnPa16PPrpZjseu6rtMjdGbCnDd21y7c2fz/8CpsDYV3rbdtumy7RfsevdtuaVj8CRprsY1MPaGuHQ2uj4D7AP0Bsbp/lWQTtm770x2A/YH/m/PoWck+TXwS+CkqnrfTBVNcgRwBMCuu+46UzG1bNABIIH//b/haU+DM8+E97wH/uqv4DWvgcc/Hg4+GB73ONhjj/EPH2vXNsub9G5r1txz3+rV04e/mbZVq2a3Ft7UOnfdIe4+91l3K173viVLXBJFkkZl7AJjkl1pupH/rGv32cAnk7yfpkv6DUABW05zictoWiePSfIumm7sA4CvT1P2MOD8qrqia9+ngFNousQfBZyR5DdVddp09a2qUzrlWbZsma2UQ9Z2u/AmmzTd0c95Dlx8MXziE3D66c3EGGhCz777wl57wZ57wr3v3cxCvde9mjFpm2zSvP72t00gu/32Zut9P9M2Xaib6/71eVLFlCVL7t6qNzVOrzfQ9W5bbXX3Y47Pk6TJNpQ/40nOY5rxhh0XVtVjuz4fBlzQHeKq6mtJ3gicAdwLeBewCri692JVdUeSZwLvAf4aWE4TAqdbQvYwmrGR3ef/sOvjN5OcSNNFPm1g1GgNcyDBfvs129vfDpddBv/2b3DhhfDDH8IHPzi78XNztdlmzVi5zTe/5za1f9ttp98/U/l++7sD4pIljtuUJDWGEhir6sA5FD8MePs01ziZZuYzSR4IvB74wQz3u4SugJrkm8BHusskeQzNWMdPr6M+xfTd3BoDVcPvEk7gwQ9utiOPvKse110H11/fbCtXNi17a9fCHXc0wWuzzZpQttlm93w/XTB0vTtJ0rgYq46iJI8GdqEzO7pr/yLgAcClwH1puoBPrKobZ7jOvsCPaZbMORrYCfhwT7HDgTOqalXPuQcB/wb8BngE8DLgtRvwtdSycQhVCey4Y7NJkjTfjNsQ8sOBM3tDHLAI+ASwGrgI+BZdM56TvDbJOV3lD6WZsHId8HjgCVV1W1f5RcBz6Wl17DgEuJymy/tU4ISqmq6cxoBz2yVJat9YtTBW1ZEz7P8NsG+f83rHIR4DHNOn/BpgmxmOPW8WVdWYGEWXtCRJG5txa2GU5sTAKElS+8aqhVGaTlWzuPPVV99z++IXDYySJLXNwKiRu/12+PnP4aqr7r51B8PVPU8aT5qZx3fe2TzTV5IktcfAqNbdcstdIfDKK+8ZDH/xi7tPXkmaxaHve1/YZx948pPhd37n7ttOO8Hznw9nnGELoyRJbTMwaoNVNWsP/vSncPnl93xdseLu5RcubMLgbrvBH/1R87rbbs0zgXfbrQmEm28++/sbGCVJapeBUbN2/fXwox/Bj398z2C4cuVd5ZIm9D3gAXDQQXC/+909FO6002CeIGJQlCRpOAyMupvf/rbpJr7ssiYc/uhHd72/4Ya7yi1c2ATBBzwAHvOY5nWPPZrtfvdrnlrStqnAaHCUJKldBsaN2HXXwcUXwyWXNK/f/34TDtesuavMDjvAXnvBs57VPApvr73gQQ+CXXdtQuMoGRglSRoOA+NGoKrpOv7Od5pgOLVde+1dZXbaCfbdFx73uLuek7zXXk1gHHcGRkmS2mVgnIdWrICLLmq2b3+7eb2x89TtTTeFvfeGJz4R9tuv2fbdF5YuHW2d14dBUZKk4TAwzgPXXAPf+Aacd16z/eQnzf4FC5plaQ4+GB75yGZ7yEPmz7qFdklLkjQcBsYJdPPNcO65zVNOzj33roB4r3vBAQfAi18Mj3oUPOxhsGTJaOvaJgOjJEnDYWCcENddB5/+NHz+8/D1r8NttzVh8HGPg6OOggMPbLqWB7FczaQwMEqSNBwGxjG2ciWceSacdhp87Wuwdi3suWcTEJ/2NNh/f9hss1HXUpIkzXcGxjH0gx/AySfDRz/adD/f737w138Nz3teMyZRDVsYJUkaDgPjGDnvPHjzm5su5803b56VfMQRzXhEQ9E9GRglSRoOA+MY+OY34XWvawLjzjvDCSfAn/0ZbL/9qGs23gyMkiQNh4FxhK67rulq/vCH4T73gXe/u2lR3GKLUddMkiTpLgbGETnzTHjRi2DVKnjNa+D1r4fFi0ddq8liC6MkScOxYNQV2NisWQN/8RfNYtp77NE8ou9tbzMsrg8DoyRJw2EL4xDdcAMcdBBceCG86lVw/PEui7MhDIySJA2HgXFIrr4a/uiP4Mor4VOfguc8Z9Q1mnwGRUmShsPAOAQrVjRh8Ze/hK98Bf7wD0ddo/nF4ChJUrsMjC1bvRqe/GS46ir41381LA6SXdKSJA2HgbFFVfDiF8P3vgef+5xhcdAMjJIkDYeBsUXvfz/8y780k1ue9rRR12b+MShKkjQcLqvTkp//HF79anjiE5vFuTV4tjBKkjQcBsaWvPSlsHZt08q4wF+5VQZGSZLaZZd0C84/Hz772aYr+n73G3Vt5i9bGCVJGg7bvlrwpjfBjjvCX/7lqGsyvxkUJUkaDgPjgP3oR/C1r8HLXw5bbjnq2sxvtjBKkjQcBsYB++d/hoUL4U//dNQ12XgYGCVJapeBccA++Ul4+tObLmm1yxZGSZKGw8A4QGvWwDXXwFOfOuqabBwMipIkDYeBcYBWrmxen/CE0dZjY2ELoyRJw2FgHKCVK+EBD4Dddx91TTYOBkZJkobDwDhAt9wCf/AHo67FxsfAKElSuwyMA3THHfC7vzvqWmw8DIqSJA2HgXHA9t571DXYeNglLUnScIxNYEyye5Kzk9yY5NokJyVZ2HX88UkuS3JLkq8n2a3PtbZLclaSm5NcleT5PcdnvFYaJyS5obO9I5l9JPFRgMNjYJQkaTjGJjAC7wWuA3YCHgocABwNkGQH4EzgWGA7YDnwyT7XOhm4HdgReAHwviR7z/JaRwDPBPYD9gWeDhw52y+x666zLSlJkjQZxikw3g/4VFWtqaprgS8BUx28zwIurarTq2oNcBywX5K9ei+SZDFwMHBsVa2uqguAzwGHzvJahwPvrKqrq+oa4J3AC2fzBTbZBBYvnuvX1vqyhVGSpOEYp8B4InBIki2T7AI8hSY0QhMcL54qWFU3Az/lrkDZ7YHA2qr6cde+i7vKrutadzvec+49JDkiyfIkyzfZ5M51fkkNjoFRkqThGKfA+A2aYLYSuJqmq/gznWNLgJt6yt8EbDXNddZVdq7HbwKWzDSOsapOqaplVbVs770XTldELTEwSpI0HEMJjEnOS1IzbBckWQB8mWZs4WJgB2Bb4ITOJVYDW/dcdmtg1TS3W1fZuR7fGlhdVbWu77lgnOL3RsCgKEnScAwl4lTVgVWVGbbH0kw+uS9wUlXdVlU3AB8Cpp7KfCnNJBTgf8Yp7tHZ3+vHwMIke3bt26+r7LqudbfjPedqDBkcJUlq11i0iVXV9cAVwFFJFibZhmbyydRYwrOAfZIcnGQR8Abgkqq6bJpr3UzTUvnmJIuTPAY4CPjoLK91KvDKJLsk2Rl4FfDhwX9rbSi7pCVJGo6xCIwdzwKeDKwALgfuBF4BUFUraGY+vxW4EXgUcMjUiUlem+ScrmsdDWxBs0zPacBRVXXpbK4FfAD4PPB94AfAFzv7NGYMjJIkDcfYzNKoqu8BB/Y5/lXgHsvodI4d3/P51zRrKa7PtQp4dWfTGDMoSpI0HOPUwiitF4OjJEntMjBqYtklLUnScBgYNbEMjJIkDYeBURPLoChJ0nAYGDWxbGGUJGk4DIyaeAZGSZLaZWDUxLKFUZKk4TAwamIZFCVJGg4DoyaWLYySJA2HgVETy8AoSdJwGBg18QyMkiS1y8CoiWVQlCRpOAyMmlgGRkmShsPAqInlGEZJkobDwKiJVzXqGkiSNL8ZGDWxbFmUJGk4DIyaWAZGSZKGw8CoiWVglCRpOAyMmlgGRkmShsPAKEmSpL4MjJpYtjBKkjQcBkZNLAOjJEnDYWDUxDIwSpI0HAZGSZIk9WVg1MSyhVGSpOEwMGpiTQVGHw0oSVK7DIyaWLYwSpI0HAZGTaypwGhwlCSpXQZGSZIk9WVg1MRyDKMkScNhYNTEsitakqThMDBqYk0FxgX+UyxJUqv8V60mni2NkiS1y8CoiWVQlCRpOAyMmlguqyNJ0nAYGDWxDIySJA2HgVETy8AoSdJwGBg18QyMkiS1y8CoiWVQlCRpOMYmMCbZPcnZSW5Mcm2Sk5Is7Dr++CSXJbklydeT7NbnWtslOSvJzUmuSvL8rmO/n+QrSX6dZEWS05Ps1HX8uCR3JFndtd2/vW+u9WWXtCRJwzE2gRF4L3AdsBPwUOAA4GiAJDsAZwLHAtsBy4FP9rnWycDtwI7AC4D3Jdm7c2xb4BRgd2A3YBXwoZ7zP1lVS7q2n23ol9PgGRglSRqOhesuMjT3A06qqjXAtUm+BEyFvGcBl1bV6dC0AgLXJ9mrqi7rvkiSxcDBwD5VtRq4IMnngEOB11TVOT3lTwK+0eL3UssMjJIktWucWhhPBA5JsmWSXYCnAF/qHNsbuHiqYFXdDPyUuwJltwcCa6vqx137Lp6hLMD+wKU9+57R6bK+NMlR/Sqd5Igky5MsX7FiRb+iGjCDoiRJwzFOgfEbNKFuJXA1TbfzZzrHlgA39ZS/CdhqmuvMumySfYE3AMd07f4U8GBgKfBi4A1JnjdTpavqlKpaVlXLli5dOlMxtcAuaUmShmMogTHJeUlqhu2CJAuAL9OMU1wM7EAz1vCEziVWA1v3XHZrmvGHvWZVNskDgHOAv6yq86f2V9UPq+oXVbW2qr5J0/L57PX53mqXgVGSpOEYSmCsqgOrKjNsj6WZyHJfmjGMt1XVDTQTUZ7aucSlwH5T1+uMU9yDe3YlA/wYWJhkz659+3WX7cyw/irwlqr66LqqDxhJxpCBUZKk4RiLLumquh64AjgqycIk2wCHc9e4xbOAfZIcnGQRTTfyJb0TXjrXupmmpfLNSRYneQxwEPBRgM74yHOBk6vq/b3nJzkoybZpPBJ4GfDZAX9lDZCBUZKkdo1FYOx4FvBkYAVwOXAn8AqAqlpBM/P5rcCNwKOAQ6ZOTPLaJN2zn48GtqBZpuc04KiqmmphfBFwf+CN3Wstdp17SOf+q4BTgROq6iMD/q4aAIOiJEnDMTbL6lTV94AD+xz/KrDXDMeO7/n8a+CZM5R9E/CmPveZcYKLxotd0pIkDcc4tTBKc2JglCRpOAyMmlgGRkmShsPAqIlnYJQkqV0GRk0sg6IkScNhYNTEsktakqThMDBqYhkYJUkaDgOjJp6BUZKkdhkYNbFsYZQkaTgMjJpYBkVJkobDwKiJZQujJEnDYWDUxDIwSpI0HAZGTTwDoyRJ7TIwamLZwihJ0nAYGDWxDIqSJA2HgVETyxZGSZKGw8CoiWdglCSpXQZGTSxbGCVJGg4DoyaWgVGSpOEwMGpiGRglSRoOA6MmloFRkqThMDBKkiSpLwOjJpYtjJIkDYeBUZIkSX0ZGDWxqprXBf5TLElSq/xXrSbWVGC0S1qSpHYZGDWxpgKjJElql4FRE88WRkmS2mVg1MSyhVGSpOEwMGpiOelFkqTh8F+1mlhOepEkaTgMjJpYdklLkjQcBkZNPFsYJUlql4FRE8suaUmShsPAqIllYJQkaTgMjJpYBkZJkobDwKiJ5aQXSZKGw8CoiWcLoyRJ7TIwamLZJS1J0nAYGDWxDIySJA3H2ATGJLsnOTvJjUmuTXJSkoVdxx+f5LIktyT5epLd+lxruyRnJbk5yVVJnt9zn0qyums7tut4kpyQ5IbO9o7ESDKOHMMoSdJwjE1gBN4LXAfsBDwUOAA4GiDJDsCZwLHAdsBy4JN9rnUycDuwI/AC4H1J9u4ps01VLelsb+nafwTwTGA/YF/g6cCRG/LF1A5bGCVJGo5xCoz3Az5VVWuq6lrgS8BUyHsWcGlVnV5Va4DjgP2S7NV7kSSLgYOBY6tqdVVdAHwOOHSW9TgceGdVXV1V1wDvBF64Ad9LLTMwSpLUrnEKjCcChyTZMskuwFNoQiM0wfHiqYJVdTPwU+4KlN0eCKytqh937bt4mrJXJbk6yYc6LZhT7navGc79H0mOSLI8yfIVK1b0/4YaKFsYJUkajnEKjN+gCWYrgatpup0/0zm2BLipp/xNwFbTXGddZa8HHgHsBjy8s//jfc6/CVgy0zjGqjqlqpZV1bKlS5fO9N3UAgOjJEnDMZTAmOS8zkST6bYLkiwAvkwzTnExsAOwLXBC5xKrga17Lrs1sGqa2/Ut2+mmXl5Vd1bVr4CXAE9MsvUM528NrK5yisW48X8RSZKGYyiBsaoOrKrMsD2WZiLLfYGTquq2qroB+BDw1M4lLqWZhAL8zzjFPTr7e/0YWJhkz659+81QFmAqdky1U93tXus4VyNkC6MkScMxFl3SVXU9cAVwVJKFSbahmXwyNZbwLGCfJAcnWQS8Abikqi6b5lo307RUvjnJ4iSPAQ4CPgqQ5FFJHpRkQZLtgX8EzquqqW7oU4FXJtklyc7Aq4APt/PNtSEMjJIkDcdYBMaOZwFPBlYAlwN3Aq8AqKoVNDOf3wrcCDwKOGTqxCSvTXJO17WOBragWabnNOCoqppqJbw/zWSaVcAPgNuA53Wd+wHg88D3O8e/2NmnMWNglCRpOBauu8hwVNX3gAP7HP8qcI9ldDrHju/5/GuatRSnK3saTYic6T4FvLqzaQIYGCVJatc4tTBKc+KkF0mShsPAqIlll7QkScNhYNTEMjBKkjQcBkZNLAOjJEnDYWDUxDMwSpLULgOjJpaTXiRJGg4DoyaWXdKSJA3H2KzDKM3V4YfDuefC618/6ppIkjS/GRg1sbbeGs46a9S1kCRp/rNLWpIkSX0ZGCVJktSXgVGSJEl9GRglSZLUl4FRkiRJfRkYJUmS1JeBUZIkSX0ZGCVJktSXgVGSJEl9GRglSZLUl4FRkiRJfRkYJUmS1JeBUZIkSX0ZGCVJktSXgVGSJEl9GRglSZLUl4FRkiRJfRkYJUmS1FeqatR1mDeSrAL+a9T12MjsAFw/6kpsZPzNh8/ffPj8zYfP33z4HlRVW82m4MK2a7KR+a+qWjbqSmxMkiz3Nx8uf/Ph8zcfPn/z4fM3H74ky2db1i5pSZIk9WVglCRJUl8GxsE6ZdQV2Aj5mw+fv/nw+ZsPn7/58PmbD9+sf3MnvUiSJKkvWxglSZLUl4FRkiRJfRkYByDJdknOSnJzkquSPH/UdZrvkrwkyfIktyX58KjrM98l2TzJBzv/fK9K8p9JnjLqes13ST6W5JdJVib5cZIXjbpOG4skeyZZk+Rjo67LfJfkvM5vvbqzuZ7xECQ5JMmPOtnlp0n+sF9512EcjJOB24EdgYcCX0xycVVdOtJazW+/AP4WeBKwxYjrsjFYCPwcOAD4b+CpwKeS/G5VXTnKis1zbwP+rKpuS7IXcF6S/6yq7466YhuBk4HvjLoSG5GXVNU/j7oSG4skTwBOAP4YuAjYaV3n2MK4gZIsBg4Gjq2q1VV1AfA54NDR1mx+q6ozq+ozwA2jrsvGoKpurqrjqurKqvptVX0BuAJ4+KjrNp9V1aVVddvUx862xwirtFFIcgjwG+BrI66K1JY3AW+uqn/v/E2/pqqu6XeCgXHDPRBYW1U/7tp3MbD3iOojtS7JjjT/7NuK3rIk701yC3AZ8Evg7BFXaV5LsjXwZuBVo67LRuZtSa5PcmGSA0ddmfksySbAMmBpksuTXJ3kpCR9e+sMjBtuCXBTz76bgFk9m1GaNEk2BT4OfKSqLht1fea7qjqa5u/JHwJnArf1P0Mb6C3AB6vq56OuyEbkr4H7A7vQrAv4+SS2pLdnR2BT4Nk0f1ceCvwe8Pp+JxkYN9xqYOuefVsDq0ZQF6lVSRYAH6UZs/uSEVdno1FVazvDXX4HOGrU9ZmvkjwU+CPgXSOuykalqr5dVauq6raq+ghwIc04abXj1s7re6rql1V1PfAPrOM3d9LLhvsxsDDJnlX1k86+/bCrTvNMkgAfpPmv06dW1R0jrtLGaCGOYWzTgcDuwH83/7izBNgkyUOq6mEjrNfGpoCMuhLzVVXdmORqmt951mxh3EBVdTNNN9GbkyxO8hjgIJpWGLUkycIki4BNaP6gL0rifwC1633Ag4FnVNWt6yqsDZPk3p1lL5Yk2STJk4DnAeeOum7z2Ck0gfyhne39wBdpVmNQC5Jsk+RJU3/Dk7wA2B/48qjrNs99CHhp5+/MtsDLgS/0O8F/wQ7G0cD/A66jmbV7lEvqtO71wBu7Pv8Jzayv40ZSm3kuyW7AkTTj567ttL4AHFlVHx9Zxea3oul+fj/Nf9xfBby8qj470lrNY1V1C3DL1Ockq4E1VbVidLWa9zalWSJtL2AtzeSuZ1aVazG26y3ADjS9pGuATwFv7XeCz5KWJElSX3ZJS5IkqS8DoyRJkvoyMEqSJKkvA6MkSZL6MjBKkiSpLwOjJEmS+jIwStKAJLk0yYFDutdDkixv4bpnJnnyoK8rabK5DqMkzVJnIecpW9IsZL6283moi5gnOQM4var+ZcDXfSTwvqp6+CCvK2myGRglaT0kuRJ4UVV9dQT33onmefU7V9WaFq7/E+B5VTXwFkxJk8kuaUkakCRXJvmjzvvjkpye5GNJViX5fpIHJvmbJNcl+XmSJ3ade68kH0zyyyTXJPnbJJvMcKsnAP/RHRY79z4mySVJbu5ca8ck53Tu/9XOM2PpPLf3Y0luSPKbJN9JsmPX9c8DnjbwH0jSxDIwSlJ7ngF8FNgW+E/gyzR/d3cB3gx8oKvsR4A7gQcAvwc8EXjRDNf9XWC6Z+0eTBMmH9i59znAa2meGbsAeFmn3OHAvYD7AtsDfw7c2nWdHwH7zfpbSpr3DIyS1J7zq+rLVXUncDqwFHh7Vd0B/Auwe5JtOq17TwFeXlU3V9V1wLuAQ2a47jbAqmn2v6eqflVV1wDnA9+uqv+sqtuAs2iCKMAdNEHxAVW1tqq+W1Uru66zqnMPSQJg4agrIEnz2K+63t8KXF9Va7s+AywBdgY2BX6ZZKr8AuDnM1z3RmCrWdyv9/OSzvuP0rQu/kuSbYCPAa/rBFk61/7NTF9K0sbHFkZJGr2f08y43qGqtulsW1fV3jOUv4Sm23m9VNUdVfWmqnoI8Gjg6cBhXUUeDFy8vteXNP8YGCVpxKrql8C/Au9MsnWSBUn2SHLADKd8BXhYkkXrc78kj0vyu51JNStpuqjXdhU5gGb8oyQBBkZJGheHAZsBP6Tpcv40sNN0BavqV8C5wEHrea/7dK6/kmaCyzdouqVJ8gjg5qq6aD2vLWkech1GSZpASR5CM7P6kTXAP+SdBcE/WFVnD+qakiafgVGSJEl92SUtSZKkvgyMkiRJ6svAKEmSpL4MjJIkSerLwChJkqS+DIySJEnqy8AoSZKkvgyMkiRJ6uv/A0osDE2NerkHAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
]
},
"metadata": {
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},
"output_type": "display_data"
},
{
"data": {
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"metadata": {},
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{
"data": {
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{
"data": {
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"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
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},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
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},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
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},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
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},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
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},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"data": {
"text/plain": [
"<Figure size 720x576 with 0 Axes>"
]
},
"metadata": {},
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},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Plotting 2D representation of network cell locations and connections...\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x864 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Done; plotting time = 4.93 s\n",
"\n",
"Total time = 3103.20 s\n",
"\n",
"End time: 2022-10-29 10:38:44.262942\n"
]
}
],
"source": [
"sim.simulate()\n",
"sim.analyze()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "ceb34061",
"metadata": {},
"outputs": [],
"source": [
"# plotting\n",
"\n",
"#sim.analysis.plotLFP( plots = ['timeSeries', 'locations'] , electrodes=[ 'all'], lineWidth=1000 , fontSize=14, saveFig=True)\n",
"\n",
"# from matplotlib import pyplot\n",
"# %matplotlib inline\n",
"# pyplot.plot(t, ap1 )\n",
"# #pyplot.xlim((0, 10))\n",
"# pyplot.show()\n"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "ddb4904a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Duration: 0:51:46.754626\n"
]
}
],
"source": [
"# show the execution time\n",
"\n",
"end_time = datetime.now()\n",
"print('Duration: {}'.format(end_time - start_time))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3ce6eb39",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 23,
"id": "b23076f1",
"metadata": {},
"outputs": [],
"source": [
"# Longitudinal Current: picoamp\n",
"\n",
"\n",
"\n",
"# xraxia = xr*1e6 #ohm/cm\n",
"# xraxia = xraxia*2*1e-4 # ohm, length between node to MYSA is 2 micron\n",
"\n",
"\n",
"# v_diff_00 = (Abeta0_vext1_node0-Abeta0_vext1_MYSA0)/1000 #volt\n",
"# Longi_Current_node0_MYSA0 = v_diff_00/xraxia #amp\n",
"# Longi_Current_node0_MYSA0 = Longi_Current_node0_MYSA0*1e12 #picoamp\n",
"\n",
"# v_diff_12 = (Abeta0_vext1_node1-Abeta0_vext1_MYSA2)/1000 #volt\n",
"# Longi_Current_node1_MYSA2 = v_diff_12/xraxia \n",
"# Longi_Current_node1_MYSA2 = Longi_Current_node1_MYSA2*1e12 \n",
"\n",
"# v_diff_24 = (Abeta0_vext1_node2-Abeta0_vext1_MYSA4)/1000 #volt\n",
"# Longi_Current_node2_MYSA4 = v_diff_24/xraxia \n",
"# Longi_Current_node2_MYSA4 = Longi_Current_node2_MYSA4*1e12 \n",
"\n",
"# v_diff_36 = (Abeta0_vext1_node3-Abeta0_vext1_MYSA6)/1000 #volt\n",
"# Longi_Current_node3_MYSA6 = v_diff_36/xraxia \n",
"# Longi_Current_node3_MYSA6 = Longi_Current_node3_MYSA6*1e12 \n",
"\n",
"# v_diff_48 = (Abeta0_vext1_node4-Abeta0_vext1_MYSA8)/1000 #volt\n",
"# Longi_Current_node4_MYSA8 = v_diff_48/xraxia \n",
"# Longi_Current_node4_MYSA8 = Longi_Current_node4_MYSA8*1e12 \n",
"\n",
"# v_diff_510 = (Abeta0_vext1_node5-Abeta0_vext1_MYSA10)/1000 #volt\n",
"# Longi_Current_node5_MYSA10 = (v_diff_510/xraxia)*1e12 \n",
"\n",
"# v_diff_612 = (Abeta0_vext1_node6-Abeta0_vext1_MYSA12)/1000 #volt\n",
"# Longi_Current_node6_MYSA12 = (v_diff_612/xraxia)*1e12 \n",
"\n",
"# v_diff_714 = (Abeta0_vext1_node7-Abeta0_vext1_MYSA14)/1000 #volt\n",
"# Longi_Current_node7_MYSA14 = (v_diff_714/xraxia)*1e12 \n",
"\n",
"# v_diff_816 = (Abeta0_vext1_node8-Abeta0_vext1_MYSA16)/1000 #volt\n",
"# Longi_Current_node8_MYSA16 = (v_diff_816/xraxia)*1e12 \n",
"\n",
"# v_diff_918 = (Abeta0_vext1_node9-Abeta0_vext1_MYSA18)/1000 #volt\n",
"# Longi_Current_node9_MYSA18 = (v_diff_918/xraxia)*1e12 \n",
"\n",
"# v_diff_1020 = (Abeta0_vext1_node10-Abeta0_vext1_MYSA20)/1000 #volt\n",
"# Longi_Current_node10_MYSA20 = (v_diff_1020/xraxia)*1e12 \n",
"\n",
"# v_diff_1122 = (Abeta0_vext1_node11-Abeta0_vext1_MYSA22)/1000 #volt\n",
"# Longi_Current_node11_MYSA22 = (v_diff_1122/xraxia)*1e12 \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a336588c",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 24,
"id": "e600ae81",
"metadata": {},
"outputs": [],
"source": [
"# import csv\n",
"\n",
"# with open('LongTranVoltageDifference_stimulateonlyAbeta0_edgedist0.1_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , v_diff_36 ))\n",
" "
]
},
{
"cell_type": "markdown",
"id": "8f3b15f1",
"metadata": {},
"source": [
"#### saving the data"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "bc5f9cde",
"metadata": {},
"outputs": [],
"source": [
"\n",
"import csv\n",
"\n",
" \n",
" \n",
" \n",
" \n",
" \n",
"with open('BoundarytoGround1000_radius6_20Fibers_v_Abeta0_stimulateonlyAbeta0_edgedist3_.csv', 'w', newline='') as f:\n",
" csv.writer(f).writerows(zip( t , Abeta0_v_node0 , Abeta0_v_node1 , Abeta0_v_node2 , Abeta0_v_node3 , Abeta0_v_node4 , Abeta0_v_node5 , Abeta0_v_node6 , Abeta0_v_node7 , Abeta0_v_node8 , Abeta0_v_node9 , Abeta0_v_node10 , Abeta0_v_node11 , Abeta0_v_node12 , Abeta0_v_node13 , Abeta0_v_node14 , Abeta0_v_node15 , Abeta0_v_node16 , Abeta0_v_node17 , Abeta0_v_node18 , Abeta0_v_node19 , Abeta0_v_node20 , Abeta0_v_node21 , Abeta0_v_node22 , Abeta0_v_node23 , Abeta0_v_node24 , Abeta0_v_node25 , Abeta0_v_node26 , Abeta0_v_node27 , Abeta0_v_node28 , Abeta0_v_node29 , Abeta0_v_node30 , Abeta0_v_node31 , Abeta0_v_node32 , Abeta0_v_node33 , Abeta0_v_node34 , Abeta0_v_node35 )) \n",
"\n",
"\n",
" \n",
" \n",
"with open('BoundarytoGround1000_radius6_20Fibers_imembrane_Abeta0_stimulateonlyAbeta0_edgedist3_.csv', 'w', newline='') as f:\n",
" csv.writer(f).writerows(zip( t , Abeta0_imembrane_node0 , Abeta0_imembrane_node1 , Abeta0_imembrane_node2 , Abeta0_imembrane_node3 , Abeta0_imembrane_node4 , Abeta0_imembrane_node5 , Abeta0_imembrane_node6 , Abeta0_imembrane_node7 , Abeta0_imembrane_node8 , Abeta0_imembrane_node9 , Abeta0_imembrane_node10 , Abeta0_imembrane_node11 , Abeta0_imembrane_node12 , Abeta0_imembrane_node13 , Abeta0_imembrane_node14 , Abeta0_imembrane_node15 , Abeta0_imembrane_node16 , Abeta0_imembrane_node17 , Abeta0_imembrane_node18 , Abeta0_imembrane_node19 , Abeta0_imembrane_node20 , Abeta0_imembrane_node21 , Abeta0_imembrane_node22 , Abeta0_imembrane_node23 , Abeta0_imembrane_node24 , Abeta0_imembrane_node25 , Abeta0_imembrane_node26 , Abeta0_imembrane_node27 , Abeta0_imembrane_node28 , Abeta0_imembrane_node29 , Abeta0_imembrane_node30 , Abeta0_imembrane_node31 , Abeta0_imembrane_node32 , Abeta0_imembrane_node33 , Abeta0_imembrane_node34 , Abeta0_imembrane_node35 )) \n",
" \n",
" \n",
" \n",
" \n",
" \n",
"# with open('boundary1_stimulateALL_Abeta0_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap00 , Abeta_ap01 , Abeta_ap02 , Abeta_ap03, Abeta_ap04 , Abeta_ap05 , Abeta_ap06 , Abeta_ap07 , Abeta_ap08 , Abeta_ap09 , Abeta_ap010 , Abeta_ap011 ))\n",
"\n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta1_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap10 , Abeta_ap11 , Abeta_ap12 , Abeta_ap13, Abeta_ap14 , Abeta_ap15 , Abeta_ap16 , Abeta_ap17 , Abeta_ap18 , Abeta_ap19 , Abeta_ap110 , Abeta_ap111 ))\n",
"\n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta2_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap20 , Abeta_ap21 , Abeta_ap22 , Abeta_ap23, Abeta_ap24 , Abeta_ap25 , Abeta_ap26 , Abeta_ap27 , Abeta_ap28 , Abeta_ap29 , Abeta_ap210 , Abeta_ap211 ))\n",
" \n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta3_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap30 , Abeta_ap31 , Abeta_ap32 , Abeta_ap33, Abeta_ap34 , Abeta_ap35 , Abeta_ap36 , Abeta_ap37 , Abeta_ap38 , Abeta_ap39 , Abeta_ap310 , Abeta_ap311 ))\n",
"\n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta4_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap40 , Abeta_ap41 , Abeta_ap42 , Abeta_ap43, Abeta_ap44 , Abeta_ap45 , Abeta_ap46 , Abeta_ap47 , Abeta_ap48 , Abeta_ap49 , Abeta_ap410 , Abeta_ap411 ))\n",
" \n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta5_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap50 , Abeta_ap51 , Abeta_ap52 , Abeta_ap53, Abeta_ap54 , Abeta_ap55 , Abeta_ap56 , Abeta_ap57 , Abeta_ap58 , Abeta_ap59 , Abeta_ap510 , Abeta_ap511 ))\n",
" \n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta6_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap60 , Abeta_ap61 , Abeta_ap62 , Abeta_ap63, Abeta_ap64 , Abeta_ap65 , Abeta_ap66 , Abeta_ap67 , Abeta_ap68 , Abeta_ap69 , Abeta_ap610 , Abeta_ap611 ))\n",
" \n",
" \n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta7_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap70 , Abeta_ap71 , Abeta_ap72 , Abeta_ap73, Abeta_ap74 , Abeta_ap75 , Abeta_ap76 , Abeta_ap77 , Abeta_ap78 , Abeta_ap79 , Abeta_ap710 , Abeta_ap711 ))\n",
" \n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta8_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap80 , Abeta_ap81 , Abeta_ap82 , Abeta_ap83, Abeta_ap84 , Abeta_ap85 , Abeta_ap86 , Abeta_ap87 , Abeta_ap88 , Abeta_ap89 , Abeta_ap810 , Abeta_ap811 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta9_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap90 , Abeta_ap91 , Abeta_ap92 , Abeta_ap93, Abeta_ap94 , Abeta_ap95 , Abeta_ap96 , Abeta_ap97 , Abeta_ap98 , Abeta_ap99 , Abeta_ap910 , Abeta_ap911 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta10_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap100 , Abeta_ap101 , Abeta_ap102 , Abeta_ap103, Abeta_ap104 , Abeta_ap105 , Abeta_ap106 , Abeta_ap107 , Abeta_ap108 , Abeta_ap109 , Abeta_ap1010 , Abeta_ap1011 ))\n",
" \n",
"\n",
"# with open('stimulateonlyAbeta0_Abeta11_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap110 , Abeta_ap111 , Abeta_ap112 , Abeta_ap113, Abeta_ap114 , Abeta_ap115 , Abeta_ap116 , Abeta_ap117 , Abeta_ap118 , Abeta_ap119 , Abeta_ap1110 , Abeta_ap1111 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta12_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap120 , Abeta_ap121 , Abeta_ap122 , Abeta_ap123, Abeta_ap124 , Abeta_ap125 , Abeta_ap126 , Abeta_ap127 , Abeta_ap128 , Abeta_ap129 , Abeta_ap1210 , Abeta_ap1211 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta13_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap130 , Abeta_ap131 , Abeta_ap132 , Abeta_ap133, Abeta_ap134 , Abeta_ap135 , Abeta_ap136 , Abeta_ap137 , Abeta_ap138 , Abeta_ap139 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta14_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap140 , Abeta_ap141 , Abeta_ap142 , Abeta_ap143, Abeta_ap144 , Abeta_ap145 , Abeta_ap146 , Abeta_ap147 , Abeta_ap148 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta15_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap150 , Abeta_ap151 , Abeta_ap152 , Abeta_ap153, Abeta_ap154 , Abeta_ap155 , Abeta_ap156 , Abeta_ap157 , Abeta_ap158 , Abeta_ap159 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta16_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap160 , Abeta_ap161 , Abeta_ap162 , Abeta_ap163, Abeta_ap164 , Abeta_ap165 , Abeta_ap166 , Abeta_ap167 , Abeta_ap168 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta17_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap170 , Abeta_ap171 , Abeta_ap172 , Abeta_ap173, Abeta_ap174 , Abeta_ap175 , Abeta_ap176 , Abeta_ap177 , Abeta_ap178 , Abeta_ap179 , Abeta_ap1710 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta18_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap180 , Abeta_ap181 , Abeta_ap182 , Abeta_ap183, Abeta_ap184 , Abeta_ap185 , Abeta_ap186 , Abeta_ap187 , Abeta_ap188 ))\n",
" \n",
" \n",
"# with open('stimulateonlyAbeta0_Abeta19_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap190 , Abeta_ap191 , Abeta_ap192 , Abeta_ap193, Abeta_ap194 , Abeta_ap195 , Abeta_ap196 , Abeta_ap197 , Abeta_ap198 , Abeta_ap199 , Abeta_ap1910 ))\n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "890baeb5",
"metadata": {},
"outputs": [],
"source": [
"## saving the data\n",
"\n",
"\n",
"\n",
"\n",
"# ## writing\n",
"\n",
"\n",
"import csv\n",
"\n",
"# with open('v_Abeta0_stimulateonlyAbeta0_dist0.1_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap00 , Abeta_ap01 , Abeta_ap02 , Abeta_ap03, Abeta_ap04 , Abeta_ap05 , Abeta_ap06 , Abeta_ap07 , Abeta_ap08 , Abeta_ap09 , Abeta_ap010 , Abeta_ap011 ))\n",
"\n",
"\n",
"\n",
"# with open('imembrane_Abeta0_stimulateALL_dist0.1_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta0_imembrane_node0 , Abeta0_imembrane_node1 , Abeta0_imembrane_node2 , Abeta0_imembrane_node3, Abeta0_imembrane_node4 , Abeta0_imembrane_node5 , Abeta0_imembrane_node6 , Abeta0_imembrane_node7 , Abeta0_imembrane_node8 , Abeta0_imembrane_node9 , Abeta0_imembrane_node10 , Abeta0_imembrane_node11 ))\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" \n",
"# with open('stimulateAbeta4_v_Abeta4_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap40 , Abeta_ap41 , Abeta_ap42 , Abeta_ap43, Abeta_ap44 , Abeta_ap45 , Abeta_ap46 , Abeta_ap47 , Abeta_ap48 , Abeta_ap49 , Abeta_ap410 , Abeta_ap411 ))\n",
"\n",
" \n",
"# with open('stimulateAbeta5_v_Abeta5_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap50 , Abeta_ap51 , Abeta_ap52 , Abeta_ap53, Abeta_ap54 , Abeta_ap55 , Abeta_ap56 , Abeta_ap57 , Abeta_ap58 , Abeta_ap59 , Abeta_ap510 , Abeta_ap511 ))\n",
" \n",
"\n",
"# with open('stimulateAbeta7_v_Abeta7_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap70 , Abeta_ap71 , Abeta_ap72 , Abeta_ap73, Abeta_ap74 , Abeta_ap75 , Abeta_ap76 , Abeta_ap77 , Abeta_ap78 , Abeta_ap79 , Abeta_ap710 , Abeta_ap711 ))\n",
"\n",
"\n",
"# with open('stimulateAbeta9_v_Abeta9_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap90 , Abeta_ap91 , Abeta_ap92 , Abeta_ap93, Abeta_ap94 , Abeta_ap95 , Abeta_ap96 , Abeta_ap97 , Abeta_ap98 , Abeta_ap99 , Abeta_ap910 , Abeta_ap911 ))\n",
" \n",
"\n",
"# with open('stimulateAbeta12_v_Abeta12_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap120 , Abeta_ap121 , Abeta_ap122 , Abeta_ap123, Abeta_ap124 , Abeta_ap125 , Abeta_ap126 , Abeta_ap127 , Abeta_ap128 , Abeta_ap129 , Abeta_ap1210 , Abeta_ap1211 ))\n",
" \n",
"\n",
"# with open('stimulateAbeta15_v_Abeta15_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap150 , Abeta_ap151 , Abeta_ap152 , Abeta_ap153, Abeta_ap154 , Abeta_ap155 , Abeta_ap156 , Abeta_ap157 , Abeta_ap158 , Abeta_ap159 , Abeta_ap1510 , Abeta_ap1511 ))\n",
" \n",
" \n",
"\n",
"# with open('stimulateAbeta17_v_Abeta17_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap170 , Abeta_ap171 , Abeta_ap172 , Abeta_ap173, Abeta_ap174 , Abeta_ap175 , Abeta_ap176 , Abeta_ap177 , Abeta_ap178 , Abeta_ap179 , Abeta_ap1710 , Abeta_ap1711 ))\n",
" \n",
"\n",
"# with open('stimulateAbeta18_v_Abeta18_boundary17.1_dist0.2_dt0.005_.csv', 'w', newline='') as f:\n",
"# csv.writer(f).writerows(zip( t , Abeta_ap180 , Abeta_ap181 , Abeta_ap182 , Abeta_ap183, Abeta_ap184 , Abeta_ap185 , Abeta_ap186 , Abeta_ap187 , Abeta_ap188 , Abeta_ap189 , Abeta_ap1810 , Abeta_ap1811 ))\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "16d8bddc",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 27,
"id": "9766ae7e",
"metadata": {},
"outputs": [],
"source": [
"# netParams.cellParams.keys()\n",
"# netParams.cellParams['']['']"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "e19fa77c",
"metadata": {},
"outputs": [],
"source": [
"# pyplot.plot(t, ap1 )\n",
"# #pyplot.xlim((0, 10))\n",
"# pyplot.show()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "94e4f559",
"metadata": {},
"outputs": [],
"source": [
"#(1211 * 1e-6 ) / (0.1225 * 1e-8)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "aca60f88",
"metadata": {},
"outputs": [],
"source": []
}
],
"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",
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