Electrostimulation to reduce synaptic scaling driven progression of Alzheimers (Rowan et al. 2014)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:154096
"... As cells die and synapses lose their drive, remaining cells suffer an initial decrease in activity. Neuronal homeostatic synaptic scaling then provides a feedback mechanism to restore activity. ... The scaling mechanism increases the firing rates of remaining cells in the network to compensate for decreases in network activity. However, this effect can itself become a pathology, ... Here, we present a mechanistic explanation of how directed brain stimulation might be expected to slow AD progression based on computational simulations in a 470-neuron biomimetic model of a neocortical column. ... "
Reference:
1 . Rowan MS, Neymotin SA, Lytton WW (2014) Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease. Front Comput Neurosci 8:39 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic cell; Neocortex V1 L2/6 pyramidal intratelencephalic cell; Neocortex V1 interneuron basket PV cell; Neocortex fast spiking (FS) interneuron; Neocortex spiny stellate cell; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s):
Gap Junctions:
Receptor(s): GabaA; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON; Python;
Model Concept(s): Long-term Synaptic Plasticity; Aging/Alzheimer`s; Deep brain stimulation; Homeostasis;
Implementer(s): Lytton, William [bill.lytton at downstate.edu]; Neymotin, Sam [samn at neurosim.downstate.edu]; Rowan, Mark [m.s.rowan at cs.bham.ac.uk];
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic cell; Neocortex V1 L2/6 pyramidal intratelencephalic cell; Neocortex V1 interneuron basket PV cell; GabaA; AMPA; NMDA; Gaba; Glutamate;
/
RowanEtAl2014
batchscripts
mod
README
alz.hoc
alzinfo.m
autotune.hoc *
basestdp.hoc *
batch.hoc *
batch2.hoc *
batchcommon
checkirreg.hoc *
clusterrun.sh
col.dot *
col.hoc *
comppowspec.hoc *
condisconcellfig.hoc *
condisconpowfig.hoc *
declist.hoc *
decmat.hoc *
decnqs.hoc *
decvec.hoc *
default.hoc *
drline.hoc *
e2hubsdisconpow.hoc *
e2incconpow.hoc *
filtutils.hoc *
flexinput.hoc
geom.hoc *
graphplug.hoc *
grvec.hoc *
infot.hoc *
init.hoc *
labels.hoc *
load.hoc *
local.hoc *
makepopspikenq.hoc *
matfftpowplug.hoc *
matpmtmplug.hoc *
matpmtmsubpopplug.hoc *
matspecplug.hoc *
mosinit.hoc
network.hoc *
nload.hoc *
nqpplug.hoc *
nqs.hoc *
nqsnet.hoc *
nrnoc.hoc *
params.hoc
plot.py
plotavg.py
plotbatch.sh
plotbatchcluster.sh
plotdeletions.py
plotntes.py
powchgtest.hoc *
pyhoc.py
python.hoc *
pywrap.hoc *
ratlfp.dat *
redE2.hoc *
run.hoc
runsim.sh
setup.hoc *
shufmua.hoc *
sim.hoc
simctrl.hoc *
spkts.hoc *
stats.hoc *
syncode.hoc *
vsampenplug.hoc *
writedata.hoc
xgetargs.hoc *
                            
#!/bin/sh
#
# Usage:
# runsim.sh [savepath] [args]

# EXAMPLES:

# Basic run with default parameters from alz.hoc (saved in data/<time>):
#    ./runsim.sh

# Basic run with default alz.hoc params, but saved to a defined path:
#    ./runsim.sh data/testname

# Run with one alternative param:
#    ./runsim.sh data/testname infotriallength=8000

# Run with multiple alternative params (must be wrapped in "{ and }" ):
#    ./runsim.sh data/testname "{infotriallength=8000 segmentlength=1600e3}"

echo "Starting runsim.sh"
echo "savepath = $1"
echo "variable = $2"
echo "args = $@"

MODL_INCLUDE="./mod"

if [ $# -lt 1 ]; then
  savepath="data/`date +%Y-%m-%d_%H-%M-%S`" # Default to saving in 'data/<current_time>';
else
  savepath=$1 # Take first argument as the save path
  variable=$2 # Take second argument as the variable / list of variables to be pre-set
  shift # Remove savepath argument from the list
  shift # Remove variable argument from the list
fi

echo "Saving to $savepath"
# If savepath doesn't exist, create it
if [ ! -d $savepath ]; then mkdir -p $savepath; fi


# Run simulation.
# To pass extra args to nrniv, enter each after a '-c' flag, in the form:
#   ./runsim data/test -c "\"filepath=\"hello\"\" [-c ...]
echo nrniv -dll mod/`arch`/.libs/libnrnmech.so $@ -c \"$variable\" -c \"strdef filepath\" -c \"filepath=\\\"$savepath\\\"\" sim.hoc
nrniv -dll mod/`arch`/.libs/libnrnmech.so $@ -c "$variable" -c "strdef filepath" -c "filepath=\"$savepath\"" sim.hoc


# Make graphs
python plot.py $savepath activity noinhib: scale noinhib: deletionscale noinhib #: raster: power  # Don't plot raster, power or info by default as they take a long time
#python plot.py $savepath all noinhib