{"title":"在逼真的 CA1 神经元模型中实现海马同步","authors":"Alessandro Fiasconaro, Michele Migliore","doi":"arxiv-2409.10431","DOIUrl":null,"url":null,"abstract":"This work delves into studying the synchronization in two realistic neuron\nmodels using Hodgkin-Huxley dynamics. Unlike simplistic point-like models,\nexcitatory synapses are here randomly distributed along the dendrites,\nintroducing strong stochastic contributions into their signal propagation. To\nfocus on the role of different excitatory positions, we use two copies of the\nsame neuron whose synapses are located at different distances from the soma and\nare exposed to identical Poissonian distributed current pulses. The\nsynchronization is investigated through a specifically defined spiking\ncorrelation function, and its behavior is analyzed as a function of several\nparameters: inhibition weight, distance from the soma of one synaptic group,\nexcitatory inactivation delay, and weight of the excitatory synapses.","PeriodicalId":501517,"journal":{"name":"arXiv - QuanBio - Neurons and Cognition","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hippocampal synchronization in a realistic CA1 neuron model\",\"authors\":\"Alessandro Fiasconaro, Michele Migliore\",\"doi\":\"arxiv-2409.10431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work delves into studying the synchronization in two realistic neuron\\nmodels using Hodgkin-Huxley dynamics. Unlike simplistic point-like models,\\nexcitatory synapses are here randomly distributed along the dendrites,\\nintroducing strong stochastic contributions into their signal propagation. To\\nfocus on the role of different excitatory positions, we use two copies of the\\nsame neuron whose synapses are located at different distances from the soma and\\nare exposed to identical Poissonian distributed current pulses. The\\nsynchronization is investigated through a specifically defined spiking\\ncorrelation function, and its behavior is analyzed as a function of several\\nparameters: inhibition weight, distance from the soma of one synaptic group,\\nexcitatory inactivation delay, and weight of the excitatory synapses.\",\"PeriodicalId\":501517,\"journal\":{\"name\":\"arXiv - QuanBio - Neurons and Cognition\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Neurons and Cognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.10431\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Neurons and Cognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hippocampal synchronization in a realistic CA1 neuron model
This work delves into studying the synchronization in two realistic neuron
models using Hodgkin-Huxley dynamics. Unlike simplistic point-like models,
excitatory synapses are here randomly distributed along the dendrites,
introducing strong stochastic contributions into their signal propagation. To
focus on the role of different excitatory positions, we use two copies of the
same neuron whose synapses are located at different distances from the soma and
are exposed to identical Poissonian distributed current pulses. The
synchronization is investigated through a specifically defined spiking
correlation function, and its behavior is analyzed as a function of several
parameters: inhibition weight, distance from the soma of one synaptic group,
excitatory inactivation delay, and weight of the excitatory synapses.