LCN-HippoModel: model of CA1 PCs deep-superficial theta firing dynamics (Navas-Olive et al 2020)

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Accession:258854
Using a biophysically realistic model of CA1 pyramidal cells together with a combination of single-cell and multisite electrophysiological recordings, we have studied factors underlying the internal theta phase preference of identified cell types from the dorsal CA1. We found that perisomatic inhibition delivered by complementary populations of basket cells interacts with input pathways to shape phase-locked specificity of deep and superficial CA1 pyramidal cells. Somatodendritic integration of fluctuating glutamatergic inputs defined cycle-by-cycle by nested waveforms demonstrated that firing selection is tuneable across sublayers under the relevant influence of intrinsic factors. Our data identify a set of testable physiological mechanisms underlying a phase specific firing reservoir that can be repurposed for high-level flexible dynamical representations. Documentation in https://acnavasolive.github.io/LCN-HippoModel/. More info: http://hippo-circuitlab.es/
Reference:
1 . Navas-Olive A, Valero M, Jurado-Parras T, de Salas-Quiroga A, Averkin RG, Gambino G, Cid E, de la Prida LM (2020) Multimodal determinants of phase-locked dynamics across deep-superficial hippocampal sublayers during theta oscillations. Nat Commun 11:2217 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I A; I h; I M; I Sodium; I Potassium; I Calcium; I_AHP; I T low threshold; I L high threshold; I K; I C;
Gap Junctions:
Receptor(s): Glutamate; GabaA;
Gene(s):
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON; Python;
Model Concept(s): Spatio-temporal Activity Patterns;
Implementer(s): Navas-Olive, Andrea [acnavasolive at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; GabaA; Glutamate; I L high threshold; I T low threshold; I A; I K; I M; I h; I Sodium; I Calcium; I Potassium; I_AHP; I C; Gaba; Glutamate; 
# LCN-HippoModel


One of the most studied brain rhythm is the theta rhythm. Theta (4-12 Hz) is considered the “on-line” status of the hippocampus, a highly rhythmic activity that acts as a global  synchronizer mechanism for encoding and information processing. During a theta cycle different neuronal populations of the hippocampus fire sequentially: each one at a distinct preferred phase.  Moreover, it has been recently discovered that pyramidal neurons of the CA1 hippocampal region,  generally considered a homogeneous population, can be classified into deep and superficial: not only each cell type shows a different preferred phase along theta cycles, but also a different response in other hippocampal rhythm, sharp wave-ripples, an oscillation associated to the  consolidation of memory. Understanding how this coordination holds up hippocampal functions as spatial navigation and memory, is a major question in the field.


The LCN-HippoModel is a biophysically realistic model of CA1 pyramidal cells aimed to get novel insights on firing dynamics in deep and superficial populations during the theta rhythm, and the role of the differential contribution of both the excitatory and inhibitory synaptic inputs,  and the biophysical intrinsic properties.


The model includes known excitatory and inhibitory inputs, using morphologically reconstructions from NeuroMorpho (http://neuromorpho.org/) (a public database), and a precise distribution of the  main ion channels via the Hodking-Huxley multi-compartment formalism in the NEURON+Python  (https://www.neuron.yale.edu/neuron/) platform.


To provide diversity among the pyramidal cells, we generated several sets of intrinsic properties and, called individuals, through a genetic algorithm (GA). The GA allowed us to identify a range of ionic conductances (called genes in the genetic algorithm terminology) that target experimental values in each given morphology. So our *individuals* are some of those *set of genes* that targeted experimental constraints. This procedure was repeated with the synaptic properties, so we ended up with several intrinsic and synaptic individuals that would give us heterogenous responses. 


The LCN-HippoModel offers an easy way to test hypotheses about the role of different synaptic and intrinsic factors in the firing dynamics of CA1 pyramidal cells by simply changing experimental parameters defined in the LCNhm_configurationfile.py.


# Documentation

Full documentation of the code can be found here:

https://acnavasolive.github.io/LCN-HippoModel/

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