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Dentate gyrus network model (Santhakumar et al 2005)
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<html> <pre> 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 </pre> <img src="dgnettraces.jpg" alt="sample network cell traces"> <pre> Network activity: </pre> <img src="dgnetactivity.jpg" alt="sample network activity"> <pre> 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 </pre> </html>
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Dentate gyrus network model (Santhakumar et al 2005)