Membrane electrical properties of mouse CA1 pyramidal cells during strong inputs (Bianchi et al 22)

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Accession:266900
ABSTRACT: In this work we highlight an electrophysiological feature, often observed in recordings from mouse CA1 pyramidal cells, which has been so far ignored by experimentalists and modelers. It consists of a large and dynamic increase in the depolarization baseline (i.e. the minimum value of the membrane potential between successive action potentials during a sustained input) in response to strong somatic current injections. Such an increase can directly affect neurotransmitter release properties and, more generally, efficacy of synaptic transmission. However, it cannot be explained by any currently available conductance-based computational model. Here we present a model addressing this issue, demonstrating that experimental recordings can be reproduced by assuming that an input current modifies, in a time-dependent manner, the electrical and permeability properties of the neuron membrane by shifting the ionic reversal potentials and channel kinetics. For this reason, we propose that any detailed model of ion channel kinetics, for neurons exhibiting this characteristic, should be adapted to correctly represent the response and the synaptic integration process during strong and sustained inputs.
Reference:
1 . Bianchi D, Migliore R, Vitale P, Garad M, Pousinha PA, Marie H, Lessmann V, Migliore M (2022) Membrane electrical properties of mouse hippocampal CA1 pyramidal neurons during strong inputs Biophysical Journal [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Channel/Receptor;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s):
Channel(s): I K; I h; I CAN; I K,Ca; I Na,t; I M;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Detailed Neuronal Models; Membrane Properties;
Implementer(s): Migliore, Michele [Michele.Migliore at Yale.edu]; Bianchi, Daniela [danielabianchi12 -at- gmail.com]; Migliore, Rosanna [rosanna.migliore at cnr.it]; Vitale, Paola [paola.vitale at ibf.cnr.it];
Search NeuronDB for information about:  I Na,t; I K; I M; I h; I K,Ca; I CAN;
 
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