"""
netParams.py
Specifications for EEE model using NetPyNE
Originally:
High-level specifications for M1 network model using NetPyNE
Contributors: salvadordura@gmail.com
"""
from netpyne import specs
import os
import numpy as np
# Find path to cells directory
curpath = os.getcwd()
while os.path.split(curpath)[1] != "sim":
curpath = os.path.split(curpath)[0]
cellpath = os.path.join(curpath, "cells")
try:
from __main__ import cfg # import SimConfig object with params from parent module
except:
from cfg import cfg # if no simConfig in parent module, import directly from cfg module
###############################################################################
#
# NETWORK PARAMETERS
#
###############################################################################
netParams = specs.NetParams() # object of class NetParams to store the network parameters
netParams.defaultThreshold = -20.0
###############################################################################
# Cell parameters
###############################################################################
# EEE cell model with uniform spine distribution (7 comps)
cellRule = netParams.importCellParams(label='eee7us', conds={'cellType': 'eee7us', 'cellModel': 'HH_reduced'}, fileName=os.path.join(cellpath, 'eee7us.py'), cellName='eee7us')
# EEE cell model with physiological spine distribution (7 comps)
cellRule = netParams.importCellParams(label='eee7ps', conds={'cellType': 'eee7ps', 'cellModel': 'HH_reduced'}, fileName=os.path.join(cellpath, 'eee7ps.py'), cellName='eee7ps')
# define section lists
cellRule['secLists']['alldend'] = ['Bdend1', 'Bdend2', 'Adend1', 'Adend2', 'Adend3']
cellRule['secLists']['apicdend'] = ['Adend1', 'Adend2', 'Adend3']
cellRule['secLists']['basaldend'] = ['Bdend1', 'Bdend2']
cellRule['secLists']['stimheads'] = []
cellRule['secLists']['stimnecks'] = []
# set up spine stim
numActiveSpines = cfg.glutSpread
spine_glut_delay = np.ones(numActiveSpines)
shaft_glut_delay = spine_glut_delay + cfg.spillDelay * np.ones(numActiveSpines)
indWeightNMDA = cfg.glutAmp / cfg.glutSpread
activeSpineNums = cfg.glutSpine + np.arange(cfg.glutSpread)
activeSpineHeads = ["head_" + str(num) for num in activeSpineNums]
activeSpineNecks = ["neck_" + str(num) for num in activeSpineNums]
spine_NMDA_weight = [indWeightNMDA for head in activeSpineHeads]
shaft_glut_weight = [indWeightNMDA * cfg.spillFraction for neck in activeSpineNecks]
# apply values to parameters
for cell_label, cell_params in netParams.cellParams.iteritems():
for secName,sec in cell_params['secs'].iteritems():
sec['vinit'] = -75.0413649414 # set vinit for all secs
if "neck" in secName:
diam = cellRule['secs'][secName]['geom']['diam']
leng = cellRule['secs'][secName]['geom']['L']
if hasattr(cfg, 'Rneck'):
cellRule['secs'][secName]['geom']['Ra'] = cfg.Rneck * 100 * 3.1416 * (diam/2) * (diam/2) / leng
###############################################################################
# Population parameters
###############################################################################
netParams.popParams['eee7us']= {'cellModel':'HH_reduced', 'cellType':'eee7us', 'numCells':1}
netParams.popParams['eee7ps']= {'cellModel':'HH_reduced', 'cellType':'eee7ps', 'numCells':1}
###############################################################################
# Synaptic mechanism parameters
###############################################################################
netParams.synMechParams['NMDA'] = {'mod': 'NMDA', 'Cdur': cfg.CdurNMDAScale * 1.0, 'Cmax': cfg.CmaxNMDAScale * 1.0, 'Alpha': cfg.NMDAAlphaScale * 4.0, 'Beta': cfg.NMDABetaScale * 0.0015}
netParams.synMechParams['AMPA'] = {'mod': 'AMPA'}
###############################################################################
# NetStim inputs
###############################################################################
if cfg.addNetStim:
for nslabel in [k for k in dir(cfg) if k.startswith('NetStim')]:
ns = getattr(cfg, nslabel, None)
if ns['sec'] == 'spineheads':
ns['sec'] = list(activeSpineHeads)
cur_weight = list([cfg.glutAmp / cfg.glutSpread for head in activeSpineHeads])
cur_loc = 0.99999
cur_delay = list(spine_glut_delay)
elif ns['sec'] == 'spinenecks':
ns['sec'] = list(activeSpineNecks)
cur_weight = list(shaft_glut_weight)
cur_loc = 0.00001
cur_delay = list(shaft_glut_delay)
else:
print("######################################################")
print("NetStim sec needs to be 'spineheads' or 'spinenecks'")
print("######################################################")
# add stim source
netParams.stimSourceParams[nslabel] = {'type': 'NetStim', 'start': ns['start'], 'interval': ns['interval'], 'noise': ns['noise'], 'number': ns['number']}
# connect stim source to target
for i in range(len(ns['synMech'])):
if ns['synMech'][i] == 'AMPA':
cur_weight = list(np.array(cur_weight) * cfg.ratioAMPANMDA)
for curpop in ns['pop']:
netParams.stimTargetParams[nslabel+'_'+curpop+'_'+ns['synMech'][i]] = \
{'source': nslabel, 'conds': {'pop': ns['pop']}, 'sec': ns['sec'], 'synsPerConn': numActiveSpines, 'loc': cur_loc, 'synMech': ns['synMech'][i], 'weight': cur_weight, 'delay': cur_delay}