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One of these methods, based on a semianalytical approach, has previously been applied to different types of single-neuron models, but never to models based on a quadratic form. In this work, we adapted this method to quadratic integrate-and-fire neuron models with adaptation and conductance-based synaptic interactions. We validated the mean-field model by comparing it to the spiking network model. This mean-field model should be useful to model large-scale activity based on quadratic neurons interacting with conductance-based synapses.<\/jats:p>","DOI":"10.1162\/neco_a_01670","type":"journal-article","created":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T18:52:04Z","timestamp":1716403924000},"page":"1433-1448","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":7,"title":["A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models"],"prefix":"10.1162","volume":"36","author":[{"given":"Christoffer G.","family":"Alexandersen","sequence":"first","affiliation":[{"name":"Mathematical Institute, University of Oxford, OX2 6GG, Oxford, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chlo\u00e9","family":"Duprat","sequence":"additional","affiliation":[{"name":"Paris-Saclay University, Institute of 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