{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/practical-approximation-method-for-firing","title":"Practical Approximation Method for Firing Rate Models of Coupled Neural Networks with Correlated Inputs","arxiv_id":"1702.03474","date":"2017-09-29","proceeding":null,"authors":[],"abstract":"Rapid experimental advances now enable simultaneous electrophysiological\nrecording of neural activity at single-cell resolution across large regions of\nthe nervous system. Models of this neural network activity will necessarily\nincrease in size and complexity, thus increasing the computational cost of\nsimulating them and the challenge of analyzing them. Here we present a novel\nmethod to approximate the activity and firing statistics of a general firing\nrate network model (of Wilson-Cowan type) subject to noisy correlated\nbackground inputs. The method requires solving a system of transcendental\nequations and is fast compared to Monte Carlo simulations of coupled stochastic\ndifferential equations. We implement the method with several examples of\ncoupled neural networks and show that the results are quantitatively accurate\neven with moderate coupling strengths and an appreciable amount of\nheterogeneity in many parameters. This work should be useful for investigating\nhow various neural attributes qualitatively effect the spiking statistics of\ncoupled neural networks. Matlab code implementing the method is freely\navailable at GitHub (\\url{http://github.com/chengly70/FiringRateModReduction}).","url_abs":"http://arxiv.org/abs/1702.03474v4","url_pdf":"http://arxiv.org/pdf/1702.03474v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"practical-approximation-method-for-firing","repo_url":"https://github.com/chengly70/FiringRateModReduction","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}