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README.txt
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README.txt
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# README file for Shuman et al, 2020 Breakdown of spatial coding and interneuron synchronization in epileptic mice. Nature Neuroscience
# UPDATED: MArch 20, 2021: all scripts are running under python 3.
# for more information, refer to the comments inside the scripts or contact me in: chavlis [DOT] spiros [AT] gmail [DOT] com
# Scripts' author: S. Chavlis, PhD, I. Pandi, M.Sc.
#################### INPUT CREATION #################################################################################
# First you have to create the Inputs, go in make_inputs_linear_track directory
cd make_inputs_linear_track
# In a command line execute
python make_grid_like_inputs.py <run_number>
python sp_make_place_inputs.py <run_number>
python glim_shuf_new_noisy.py <run_number> <desynch_level> <jitter_source>
# <run_number> is a specific run from one edge of the track to the other. To replicate the figures one needs 10 runs
# <desynch_level>: ms of desynchronization
# <jitter_source>: which input to randomize. Valid options: EC or CA3. Use EC to replicate the paper figures.
# e.g., python glim_v2_prelearning.py 1 20 EC
# Then enter background_noise directory
cd ../background_noise
# create the background noise by executing
python poisson_input.py <total_number_of_runs> <poisson_rate> # e.g., python poisson_input.py 1 5 --> creates run1 poisson random noise with lambda 5 Hz
#################### MAIN SIMULATIONS #######################################################################
# return to main directory
cd ../
# Compile all mechanisms (mod files)
nrnivmodl mechanisms/
# Run the simulation
./x86_64/special -nogui -nopython -c n_runs=<run_number> -c n_trials=<virtual_mouse_id> -c desynch=<desynch_level_in_ms> -c n_neuron=<deletion_type> -c factor=<reduction_factor> Network_CA1.hoc
# e.g., ./x86_64/special -nogui -nopython -c nruns=1 -c ntrials=1 -c n_neuron=0 -c desynch=0 -c factor=1 Network_CA1.hoc
# to replicate the results of the paper you need 10 runs/trial and 10 trials and all possible deletions (see below)
# Valid deletions:
# Control: All connections and cells, default -- option: 0
# SOMred: SOMs are removed by a specific percentage -- option: 1
# PVred: PVs are removed by a specific percentage -- option: 2
# Desynch: Desynchronization of EC/CA3 inputs by a specific amount -- option: 3
# ALL: SOMred, PVred and Desynch simultaneously -- option: 4
# SOMdel: All PVs are removed -- option: 5
# PVdel: All PVs are removed -- option: 6
** Notice: it is highly recommended to run all inputs first, and then run the simulations.
# Output of the simulation is saved into Simulation_Results/
#################### ANALYSIS OF LOCOMOTION DATA BEFORE PROCEEDING #####################################################
# First, one needs to extract the spiketimes for neurons in order to analyze them
# Go to AnalysisRawData directory
cd AnalysisRawData
# Exctract spike times
python spiketimes_analysis.py <neuron_type> <deletion_type> <number_of_trial> <number_of_run>
# Valid deletions_types:
# Control
# SOMred
# PVred
# Desynch
# ALL
# SOMdel
# PVdel
# Valid <neuron_type> values:
# _pvsoma_ : Pyramidal cells
# _aacell_ : Axoaxonic cells
# _bcell_ : Basket cells
# _bscell_ : Bistratified cells
# _olmcell_ : OLM cells
# _vipcck_ : VIP/CCK cells
# _vipcr_ : VIP/CR PVM cells
# _vipcrnvm_ : VIP/CR NVM cells
# After the analysis for all trials, runs and deletions execute:
python all_path_all_spiketimes.py <deletion_type> # e.g., python all_path_all_spiketimes.py Control
# This will create the subfolder final_results/metrics_permutations
# where the spiketimes and the path for all cases is stored (for better handling)
# Permutations for all cells to find spatial information and stability null distributions
python permutations_analysis_peyman.py <virtual_mouse> <pyramidalID> <deletion_type>
# Data save for using in GraphPad Prism and basic plotting
python analysis_path.py <virtual_mouse> <deletion_type>
python all_trials_paper_all.py
python all_trials_per_animal.py
# for more information, refer to the comments inside the scripts or contact me in: chavlis [DOT] spiros [AT] gmail [DOT] com