From 3da43d494c0af68ec43b018f1fc4ec35b66894f9 Mon Sep 17 00:00:00 2001 From: EnfxcFCb6 Date: Tue, 27 May 2025 16:32:29 -0400 Subject: [PATCH 1/2] Standardized README to Markdown format --- README.md | 31 +++++++++++++++++++++++ readme.html | 72 ----------------------------------------------------- 2 files changed, 31 insertions(+), 72 deletions(-) create mode 100644 README.md delete mode 100644 readme.html diff --git a/README.md b/README.md new file mode 100644 index 0000000..03adc61 --- /dev/null +++ b/README.md @@ -0,0 +1,31 @@ +# Readme for the Model Associated with the Paper + +**Vijayalakshmi Santhakumar, Ildiko Aradi and Ivan Soltesz** +Role of Mossy Fiber Sprouting and Mossy Cell Loss in Hyperexcitability: A Network Model of the Dentate Gyrus Incorporating Cell Types and Axonal Topography +*J Neurophysiol* 93: 437-453, 2005. + +Mossy cell loss and mossy fiber sprouting are two characteristic consequences of repeated seizures and head trauma. However, their precise contributions to the hyperexcitable state are not well understood. Because it is difficult, and frequently impossible, to independently examine using experimental techniques whether it is the loss of mossy cells or the sprouting of mossy fibers that leads to dentate hyperexcitability, we built a biophysically realistic and anatomically representative computational model of the dentate gyrus to examine this question. The 527-cell model, containing granule, mossy, basket, and hilar cells with axonal projections to the perforant-path termination zone, showed that even weak mossy fiber sprouting (10-15% of the strong sprouting observed in the pilocarpine model of epilepsy) resulted in the spread of seizure-like activity to the adjacent model hippocampal laminae after focal stimulation of the perforant path. The simulations also indicated that the spatially restricted, lamellar distribution of the sprouted mossy fiber contacts reported in in vivo studies was an important factor in sustaining seizure-like activity in the network. In contrast to the robust hyperexcitability-inducing effects of mossy fiber sprouting, removal of mossy cells resulted in decreased granule cell responses to perforant-path activation in agreement with recent experimental data. These results indicate the crucial role of mossy fiber sprouting even in situations where there is only relatively weak mossy fiber sprouting as is the case after moderate concussive experimental head injury. + +## Usage + +Compile the NEURON mod files with `nrnivmodl` (unix) or `mknrndll` (mac or mswin) and then start the network simulation with +`nrngui mosinit.hoc` (unix) or double clicking on the `mosinit.hoc` file (mac or mswin). + +## Figure 7 A2, B2 + +For 10% sprouting (see reference) traces look similar to this: + +![sample network cell traces](dgnettraces.jpg) + +## Network activity: + +![sample network activity](dgnetactivity.jpg) + +The initial network connections takes 5 minutes (prints to the oc prompt window), then the network starts running and begins to generate the above traces graph. The activity graph is created at the end of the simulation (a little over twenty minutes to finish on a 1 GHz Linux Pentium). Note: a processor time seeded random number generator makes every run different (for statistical analysis). + +--- + +Changelog +2022-05: Updated MOD files to contain valid C++ and be compatible with the upcoming versions 8.2 and 9.0 of NEURON. +2022-12: Fix 9.0.0 Upcoming error: new_seed used as both variable and function in file Gfluct.mod +2025-05-27 – Standardized to Markdown. \ No newline at end of file diff --git a/readme.html b/readme.html deleted file mode 100644 index 14a1d6a..0000000 --- a/readme.html +++ /dev/null @@ -1,72 +0,0 @@ - -
-This is the readme for the model associated with the paper
-
-Vijayalakshmi Santhakumar, Ildiko Aradi and Ivan Soltesz
-Role of Mossy Fiber Sprouting and Mossy Cell Loss in
-Hyperexcitability:A Network Model of the Dentate Gyrus Incorporating
-Cell Types and Axonal Topography
-J Neurophysiol 93: 437-453, 2005.
-
-Mossy cell loss and mossy fiber sprouting are two characteristic
-consequences of repeated seizures and head trauma. However, their
-precise contributions to the hyperexcitable state are not well
-understood. Because it is difficult, and frequently impossible, to
-independently examine using experimental techniques whether it is the
-loss of mossy cells or the sprouting of mossy fibers that leads to
-dentate hyperexcitability, we built a biophysically realistic and
-anatomically representative computational model of the dentate gyrus
-to examine this question. The 527-cell model, containing granule,
-mossy, basket, and hilar cells with axonal projections to the
-perforant-path termination zone, showed that even weak mossy fiber
-sprouting (10-15% of the strong sprouting observed in the pilocarpine
-model of epilepsy) resulted in the spread of seizure-like activity to
-the adjacent model hippocampal laminae after focal stimulation of the
-perforant path. The simulations also indicated that the spatially
-restricted, lamellar distribution of the sprouted mossy fiber
-contacts reported in in vivo studies was an important factor in
-sustaining seizure-like activity in the network. In contrast to the
-robust hyperexcitability-inducing effects of mossy fiber sprouting,
-removal of mossy cells resulted in decreased granule cell responses
-to perforant-path activation in agreement with recent experimental
-data. These results indicate the crucial role of mossy fiber
-sprouting even in situations where there is only relatively weak
-mossy fiber sprouting as is the case after moderate concussive
-experimental head injury.
-
-Usage:
-Compile the NEURON mod files with nrnivmodl (unix) or mknrndll (mac
-or mswin) and then start the network simulation with
-nrngui mosinit.hoc
-(unix) or double clicking on the mosinit.hoc file (mac or mswin).
-
-
-Figure 7 A2,B2
-For 10% sprouting (see reference) traces look similar to this
-
-
-sample network cell traces -
-
-Network activity:
-
-
-sample network activity -
-
-The initial network connections takes 5 minutes (prints to the oc
-prompt window), then the network starts running and begins to generate
-the above traces graph.  The activity graph is created at the end
-of the simulation (a little over twenty minutes to finish on a
-1 GHz Linux Pentium).  Note: a processor time seeded random number
-generator makes every run different (for statistical analysis).
-
-
-Changelog
----------
-2022-05: Updated MOD files to contain valid C++ and be compatible with
-         the upcoming versions 8.2 and 9.0 of NEURON.
-2022-12: Fix 9.0.0 Upcoming error: new_seed used as both variable and function in file Gfluct.mod 
-
- - From 3e3edd667cc44ecd82e906658be6d8b5c1e6d670 Mon Sep 17 00:00:00 2001 From: rsakai Date: Fri, 30 May 2025 10:36:23 -0400 Subject: [PATCH 2/2] Update README.md --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 03adc61..b0e282f 100644 --- a/README.md +++ b/README.md @@ -25,7 +25,9 @@ The initial network connections takes 5 minutes (prints to the oc prompt window) --- -Changelog +## Changelog 2022-05: Updated MOD files to contain valid C++ and be compatible with the upcoming versions 8.2 and 9.0 of NEURON. + 2022-12: Fix 9.0.0 Upcoming error: new_seed used as both variable and function in file Gfluct.mod -2025-05-27 – Standardized to Markdown. \ No newline at end of file + +2025-05-27: Standardized to Markdown.