Hippocampus CA1 Interneuron Specific 3 (IS3) in vivo-like virtual NN simulations (Luo et al 2020)

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Accession:265523
"Disinhibition is a widespread circuit mechanism for information selection and transfer. In the hippocampus, disinhibition of principal cells is provided by the interneuron-specific interneurons that express the vasoactive intestinal polypeptide (VIP-IS) and innervate selectively inhibitory interneurons. By combining optophysiological experiments with computational models, we determined the impact of synaptic inputs onto the network state-dependent recruitment of VIP-IS cells. We found that VIP-IS cells fire spikes in response to both the Schaffer collateral and the temporoammonic pathway activation. Moreover, by integrating their intrinsic and synaptic properties into computational models, we predicted recruitment of these cells between the rising phase and peak of theta oscillation and during ripples. Two-photon Ca2+-imaging in awake mice supported in part the theoretical predictions, revealing a significant speed modulation of VIP-IS cells and their preferential albeit delayed recruitment during theta-run epochs, with estimated firing at the rising phase and peak of the theta cycle. However, it also uncovered that VIP-IS cells are not activated during ripples. Thus, given the preferential theta-modulated firing of VIP-IS cells in awake hippocampus, we postulate that these cells may be important for information gating during spatial navigation and memory encoding."
Reference:
1 . Luo X, Guet-McCreight A, Villette V, Francavilla R, Marino B, Chamberland S, Skinner FK, Topolnik L (2020) Synaptic Mechanisms Underlying the Network State-Dependent Recruitment of VIP-Expressing Interneurons in the CA1 Hippocampus. Cereb Cortex [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Dendrite; Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampal CA1 CR/VIP cell;
Channel(s): I Na,t; I Na,p; I A;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Spatial Navigation; Oscillations; Activity Patterns;
Implementer(s): Guet-McCreight, Alexandre [alexandre.guet.mccreight at mail.utoronto.ca];
Search NeuronDB for information about:  I Na,p; I Na,t; I A; Gaba; Glutamate;
# IS3 In Vivo Virtual Network Simulations
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Luo X, Guet-McCreight A, Villette V, Francavilla R, Marino B, Chamberland S, Skinner FK, Topolnik L. (2020). Synaptic Mechanisms Underlying the Network State-Dependent Recruitment of VIP-Expressing Interneurons in the CA1 Hippocampus. Cerebral Cortex, bhz334,  https://doi.org/10.1093/cercor/bhz334

Run this script to simulate and plot the IS3 models (code also available at https://github.com/FKSkinnerLab/IS3-Cell-Model/tree/master/RhythmTests). Note that this code was written for use with python 2.7 but has been adapted here for use in python 3.

Directories
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1       /SWR/ - Simulates in vivo-like inputs + SWR-timed inputs and plots results

2       /Theta/ - Simulates in vivo-like inputs + theta-timed inputs and plots results

3       /Theta_DoubledInputs/ - Simulates in vivo-like inputs + theta-timed inputs + doubling specific inputs and then plots results

4       /Theta_RemovedInputs/ - Simulates in vivo-like inputs + theta-timed inputs + removing specific inputs and then plots results

5       /Theta_NoiseTests/ - Simulates in vivo-like inputs + theta-timed inputs + effects of noise and then plots results

List of models (ModelDB accession #: 223031)
-------------
The models currently available are:

1       /SDprox1/

2       /SDprox2/

From: Guet-McCreight A, Camiré O, Topolnik L, Skinner F. (2016). Using a semi-automated strategy to develop multi- compartment models that predict biophysical properties of interneuron- specific 3 (IS3) cells in hippocampus. eNeuro. 3:4. https://doi.org/10.1523/ENEURO.0087-16.2016


Model invocation
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Before running the simulations you must first compile the mod files using the following command:

		nrnivmodl

To run simulations, first cd into the directory of interest and then use python as a command-line argument as follows:

		python init.py

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