Mathematical generation of data-driven hippocampal CA1 pyramidal neurons and interneurons copies via A-GLIF models for large-scale networks covering the experimental variability range-Reference-Cited by-同舟云学术

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Mathematical generation of data-driven hippocampal CA1 pyramidal neurons and interneurons copies via A-GLIF models for large-scale networks covering the experimental variability range

Published:2024-05 Issue: Volume:371 Page:109179
ISSN:0025-5564
Container-title:Mathematical Biosciences
language:en
Short-container-title:Mathematical Biosciences

Author:

Marasco A.^ORCID,Tribuzi C.,Iuorio A.,Migliore M.

Publisher

Elsevier BV

Reference41 articles.

1. Dynamic models of large-scale brain activity;Breakspear;Nature Neurosci.,2017

2. Biologically realistic mean-field models of conductance-based networks of spiking neurons with adaptation;di Volo;Neural Comput.,2019

3. Population spiking and bursting in next-generation neural masses with spike-frequency adaptation;Ferrara;Phys. Rev. E,2023

4. Mean-field based framework for forward modeling of LFP and MEG signals;Tesler;Front. Comput. Neurosci.,2022

5. Model design for networks of heterogeneous Hodgkin–Huxley neurons;Giannari;Neurocomputing,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modeling realistic synaptic inputs of CA1 hippocampal pyramidal neurons and interneurons via Adaptive Generalized Leaky Integrate-and-Fire models;Mathematical Biosciences;2024-06

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