This model of a dentate granule cell was taken from the following paper and modified by Ivan Raikov:
Pedro Mateos-Aparicio, Ricardo Murphy and Johan F. Storm (2014). Complementary functions of SK and Kv7/M potassium channels in excitability control and synaptic integration in rat hippocampal dentate granule cells. Journal of Physiology 592, 669-693.
It is based on the model of Aradi & Holmes (1999; Journal of Computational Neuroscience 6, 215-235) which uses an idealized morphology (DGC_Morphology.hoc). The model was used to help understand the contribution of M and SK channels to the medium afterhyperpolarization (mAHP) following one or seven spikes, as well as the contribution of M channels to the slow afterhyperpolarization (sAHP).
- This version of the model is compatible with NEURON versions newer than 8.1 (#5)
# NOTE: you need different version of NEURON build for CPU and GPU i.e.
# -DCORENRN_ENABLE_GPU=ON and -DCORENRN_ENABLE_GPU=OFF
# NEURON is built as:
module load unstable nvhpc cuda cmake python hpe-mpi
cmake .. .. -DCMAKE_INSTALL_PREFIX=$HOME/bbp/nrn/build_gpu/install \
-DCORENRN_ENABLE_GPU=ON -DNRN_ENABLE_CORENEURON=ON \
-DNRN_ENABLE_INTERVIEWS=OFF -DNRN_ENABLE_RX3D=OFF
make -j8
make install
# lets use GPU enabled NEURON version
export PATH=$HOME/bbp/nrn/build_gpu/install/bin:$PATH
export PYTHONPATH=$HOME/bbp/nrn/build_gpu/install/lib/python/:$PYTHONPATH
# GPU partition of BB5
salloc --partition=prod --account=proj16 --nodes=1 --time=8:00:00 --exclusive --constraint=volta
# cd to reduced_dentat model dir
nrnivmodl -coreneuron mechanisms
export HOC_LIBRARY_PATH=`pwd`/templates
# run neuron on CPU
rm -rf results out.nrn.spk
srun -n 4 ./x86_64/special -c mytstop=10 run.hoc -mpi
cat results/*spike* | sort -k 1n,1n -k 2n,2n > out.nrn.spk
# run with coreneuron gpu
rm -rf results out.cnrn.spk
#srun -n 4 ./x86_64/special -c mytstop=10 -c coreneuron=1 -c gpu=0 run.hoc -mpi
srun -n 4 ./x86_64/special -c mytstop=10 -c coreneuron=1 -c gpu=1 run.hoc -mpi
cat results/*spike* | sort -k 1n,1n -k 2n,2n > out.cnrn.spkAnd then diff out.nrn.spk and out.cnrn.spk. They should be same unless there is possibility of floating point discrepencies.