Synchrony by synapse location (McTavish et al. 2012)

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Accession:144054
This model considers synchrony between mitral cells induced via shared granule cell interneurons while taking into account the spatial constraints of the system. In particular, since inhibitory inputs decay passively along the lateral dendrites, this model demonstrates that an optimal arrangement of the inhibitory synapses will be near the cell bodies of the relevant mitral cells.
Reference:
1 . McTavish TS, Migliore M, Shepherd GM, Hines ML (2012) Mitral cell spike synchrony modulated by dendrodendritic synapse location. Front Comput Neurosci 6:3 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Olfactory bulb;
Cell Type(s): Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron granule MC GABA cell;
Channel(s): I Na,t; I A; I K;
Gap Junctions:
Receptor(s): GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Synchronization; Olfaction;
Implementer(s): McTavish, Thomas S [thomas.mctavish at yale.edu];
Search NeuronDB for information about:  Olfactory bulb main mitral GLU cell; Olfactory bulb main interneuron granule MC GABA cell; GabaB; AMPA; NMDA; I Na,t; I A; I K;
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mctavish_syncbylocation
src
ampanmda.mod
fi.mod
kamt.mod
kdrmt.mod
naxn.mod
ThreshDetect.mod *
allsynhinton.hoc *
analysis.py
animtest.py
antest.ses *
bulbspikes.py
clear.hoc
connect.hoc
control.ses
default.hoc
granule.hoc *
hinton.hoc
init.hoc *
iterator.hoc *
lptiter.hoc
mgrs.hoc
michele_movie.hoc
mitral.hoc
mosinit.hoc
net.hoc
param.hoc
params.py
parinit.hoc
pattern.hoc
perfrun.hoc
show.hoc
showw.hoc
somesyn.hoc *
sortspike *
split.hoc
start.hoc
start.ses
stimodors.hoc
subset.hoc
subset_control.ses *
synweightsnapshot.py
viewspikes.hoc
viewspikes1.hoc
weight_movie.hoc
weightsave.hoc
                            
# -*- coding: utf-8 -*-
"""
Default parameters for nrnproject.

AUTHORS:

- THOMAS MCTAVISH (2010-08-01): initial version
"""
from os.path import join

tstopval = 20000 # Used multiple times below

# SIMULATION PARAMETERS
sim_var = { \
'subsim' : False, #
'run_parallel' : False,
'tstop' : tstopval,  # Duration of simulation

# NETWORK PARAMETERS
'net_spatial_len' : 1000, # Lateral spread (width in microns) of the network
'secdenlen' : 1000,  # mitral lateral dendrite length of one branch
'num_granule' : 100,  # number of granule cells
'num_mitral' : 5,     # number of mitral cells
'ring' : False, # Whether or not the network wraps as a ring network.
'plasticity' : False, # Whether or not we are using plasticity

# CONNECTION PARAMETERS
'g2m_mean': 1, 
'g2m_var' : 0,
'g2m_ranseed' : 1,
'g2m_priden_seed_offset' : 0,  # 0 means all at 0.5

# WEIGHTS
'read_weights_normalized' : True, # Interpret the weights file as going from 0 to 1.
'write_weights_normalized' : True, # Write weights 0 to 1 from maximal conductances.
# Weight snapshot file to use as input.
# This should be something like "weights.dat". If None, then no 
# weight snapshot file is used. This weights file should be inside the weight_dir.
# If weight_dir is None, then the sim output directory will be used.
'weight_dir' : join('in','weights'),
'wt_input_file' : 'weight_input.dat',  # weight_zeros.dat
# The wt_input_file will be written dynamically if the wt_clusters variable is not
# None. Each cluster is expressed in 4 parameters. The first parameter is
# the location, centered by granule cell index. The second parameter is the
# width of the column, which should be an odd number. The third parameter is 
# the maximum normalized magnitude at that location. The fourth parameter
# is a list of mitral cell ids that should be connected with this magnitude.
'wt_clusters' : [(10,5,1,[0,4]), (90,5,1,[0,4]), \
                 (30,5,1,[1,3]),(70,5,1,[1,3])], # None #
'wt_cluster_seed' : None, # If specified, this will shuffle/permute the weight file.

# Weight snapshot file to write as output.
# If empty, this will write a file
# "weights_<stim_odors>_<stim_odor_mags>.dat"
'wt_output_file' : 'weight_snapshot.dat',
'ws_start' : tstopval, # Weight snapshot start time
'ws_interval' : tstopval, # Weight snapshot interval between snapshots.

'fi_gmax' : 0.005, # Fast inhibitory (granule-to-mitral) maximal conductance
'fi_tau1' : 0.1, # Fast inhibitory rise time
'fi_tau2' : 4., # Fast inhibitory decay time
'ampanmda_gmax' : 1.5, #Excitatory drive (mitral-to-granule) magnification.

# INPUT
'spike_input_file' : 'spikeout.spk', # Spike input file for subsimulations
'odor_dir' : 'in', # Directory relative to the project directory
'odor_file' : 'M5_Odors.txt',
'stim_odor_ids' : [0, 1, 2, 3, 4],   # Odor ID vector, zero-based.
'stim_odor_mags' : [.55, .55, .55, .55, .55],  # Odor magnitude vector.
#'stim_odor_mags' : [.0, .0, .0, .0, .0],  # Odor magnitude vector.
    # Individual odor vectors are multiplied by this value.
# End times of each odor. If using a mixture, duplicate the
# end times. For example, for a mixture of two odors followed by
# another mixture of two odors, each with a duration of 20000 ms,
# the vector would be "[20000, 20000, 40000, 40000]"
'stim_odors_start' : [2, 2, 2, 2, 2],
'stim_odors_end' : [tstopval, tstopval, tstopval, tstopval, tstopval],
'stim_odors_seed' : [100, 101, 102, 103, 104],
'stim_odor_max_delay' : 15, # Uniform random between 0 and this number that is
    # the onset of activation after the start of an inhilation.

'numodors' : 5, # Number of odors in the odors file. TODO: Deprecate
# Interval for time between "breaths", uniformly distributed.
'odorfreq' : 40, # Maximum stim rate at the beginning of odor onset.
'breath_interval' : [150, 250],
# Each breath can be thought of a occuring from 0 to 2*pi. During this interval,
# the cell will be driven with random synaptic inputs or weight breath_noise_mag.
# These events will occur as a Poisson process at rate breath_noise_freq.
# The selection of events can be thought of as drawing a random number between
# [0,1] at double the frequency. Those values > 0.5 will pass, and those below will
# not. We can also use this scheme to pass values more freqently at different times
# of the phase cycle.
'breath_seed' : 1, # Seed for breaths
#'breath_noise_mags': [.06, .06, .06, .08, .08], # On top of ampanmda_gmax
'breath_noise_mags': [.0, .0, .0, .0, .0], # On top of ampanmda_gmax
'breath_noise_freqs': [40, 40, 40, 30, 30],
'breath_noise_amps' : [0.0, 0.0, 0.0, 0.0, 0.0], # 0.5 +/- these values
                        # 0.2 at the bottom (better chance of firing), an
                        # 0.8 at the top (less of a chance).
'breath_noise_func' : 'cos', # Can be 'cos' or '-cos'. Simply set breath_noise_amp
                             # to zero to make evenly distributed.
'breath_events_file' : 'breathevents.txt',

# OUTPUT PARAMETERS
'sim_path' : '', # 'sims' # Main simulation output directory path relative to
        # project path. Individual simulations go in subdirectories of here.
'spike_file_name' : 'spikeout', # Name of spike output file (without any extension)
}

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