added files and simulation scripts for Hagen et al (submitted)

README.txt

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+Files and data used for the study:
+==================================
+
+Hagen E, Fossum JC, Pettersen KH, Alonso JM, Swadlow HA, Einevoll GT.
+"Focal local field potential (LFP) signature of the single-axon monosynaptic
+thalamocortical connection" (submitted)
+
+
+Files:
+======
+
+initialize_simulations.py:
+    Defines parameters, initializes simulations, creates jobscripts, submits to
+    cluster queue using the Slurm job manager. Adapt accordingly.
+
+lfp_simulation.py:
+    Main simulation procedure used for the LFP predictions
+
+create_figures.py:
+    Produce figures from simulation output
+
+tools.py:
+    Auxiliary function declarations and classes used by the above scripts
+
+morphologies/*.hoc:
+    morphology files converted to NEURON's HOC language
+
+add_spines.hoc:
+    HOC language file for modifying surface area dependent on spine density
+
+data/*:
+    Files with the experimental stLFPs from previous studies by
+    Swadlow et al. (2002) and Stoelzel et al. (2008)
+
+README.txt:
+    This file
+
+
+Workflow:
+=========
+
+In order to generate all simulated data, the workflow is as follows:
+
+-   put all files on a compute cluster ideally running the Slurm job manager.
+    If the cluster is using a different setup, adapt initialize_simulations.py
+    accordingly. Make sure that all Python dependencies are met, installing
+    various packages from Python package index for example
+    (pip install <package-name> --user)
+-   run initialize_simulations.py:
+        $ python initialize_simulations.py
+
+    The script will delete all simulation output and corresponding files by
+    default, create different parameter files with different md5 hashes
+    in the subfolder "parameters" using the Neurotools.parameterspace module,
+    jobscripts will be put in the folder "jobs". The script will also send all
+    jobs to the queue before terminating. The folder "logs" should when jobs
+    start contain various output for each job. The folder "savedata" should
+    contain simulated data for each parametercombination.
+-   Make sure no jobs are running with "squeue -u $USER"
+-   Run the script create_figures.py to produce all figures
+        $ python create_figures.py
+    pdf images will be stored in this folder.
+
+
+License:
+========
+
+Copyright (C) 2016 Espen Hagen
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with this program.  If not, see <http://www.gnu.org/licenses/>.

add_spines.hoc

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+// --------------------------------------------------------------
+// Spines
+// --------------------------------------------------------------
+    // Based on the "Folding factor" described in
+    // Jack et al (1989), Major et al (1994)
+    // note, this assumes active channels are present in spines 
+    // at same density as dendrites
+spine_dens = 1
+    // just using a simple spine density model due to lack of data on some 
+    // neuron types.
+spine_area = 0.83 // um^2  -- K Harris
+proc add_spines() { local a
+    is_spiny = 1
+    if (strcmp($s1,"dend") == 0) {
+        forall {
+            ifsec "dend" {
+                a = 0
+                for (x,0) {
+                    a = a + area(x)
+                }
+                F = (L*spine_area*spine_dens + a)/a
+                //print F
+                L = L * F^(2/3)
+                for (x,0) {
+                    diam(x) = diam(x) * F^(1/3)
+                }
+                //original algorithm;
+                //a = 0
+                //for (x) print x
+                //for(x) print diam(x)
+                //for(x) a=a+area(x)
+                //F = (L*spine_area*spine_dens + a)/a
+                //L = L * F^(2/3)
+                //for(x) diam(x) = diam(x) * F^(1/3)
+                //for(x) print diam(x)
+            }
+        }
+    }
+    define_shape()
+}
+add_spines("dend")