{"type":"journal_article","extern":"1","date_published":"2005-07-21T00:00:00Z","pmid":1,"article_processing_charge":"No","publication_identifier":{"issn":["0147-006X","1545-4126"]},"title":"Neural network dynamics","volume":28,"oa_version":"None","page":"357-376","issue":"1","month":"07","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","publication":"Annual Review of Neuroscience","external_id":{"pmid":["16022600"]},"date_created":"2020-06-25T13:13:11Z","status":"public","citation":{"ieee":"T. P. Vogels, K. Rajan, and L. F. Abbott, “Neural network dynamics,” <i>Annual Review of Neuroscience</i>, vol. 28, no. 1. Annual Reviews, pp. 357–376, 2005.","ista":"Vogels TP, Rajan K, Abbott LF. 2005. Neural network dynamics. Annual Review of Neuroscience. 28(1), 357–376.","mla":"Vogels, Tim P., et al. “Neural Network Dynamics.” <i>Annual Review of Neuroscience</i>, vol. 28, no. 1, Annual Reviews, 2005, pp. 357–76, doi:<a href=\"https://doi.org/10.1146/annurev.neuro.28.061604.135637\">10.1146/annurev.neuro.28.061604.135637</a>.","chicago":"Vogels, Tim P, Kanaka Rajan, and L.F. Abbott. “Neural Network Dynamics.” <i>Annual Review of Neuroscience</i>. Annual Reviews, 2005. <a href=\"https://doi.org/10.1146/annurev.neuro.28.061604.135637\">https://doi.org/10.1146/annurev.neuro.28.061604.135637</a>.","ama":"Vogels TP, Rajan K, Abbott LF. Neural network dynamics. <i>Annual Review of Neuroscience</i>. 2005;28(1):357-376. doi:<a href=\"https://doi.org/10.1146/annurev.neuro.28.061604.135637\">10.1146/annurev.neuro.28.061604.135637</a>","short":"T.P. Vogels, K. Rajan, L.F. Abbott, Annual Review of Neuroscience 28 (2005) 357–376.","apa":"Vogels, T. P., Rajan, K., &#38; Abbott, L. F. (2005). Neural network dynamics. <i>Annual Review of Neuroscience</i>. Annual Reviews. <a href=\"https://doi.org/10.1146/annurev.neuro.28.061604.135637\">https://doi.org/10.1146/annurev.neuro.28.061604.135637</a>"},"day":"21","publication_status":"published","year":"2005","quality_controlled":"1","article_type":"review","abstract":[{"text":"Neural network modeling is often concerned with stimulus-driven responses, but most of the activity in the brain is internally generated. Here, we review network models of internally generated activity, focusing on three types of network dynamics: (a) sustained responses to transient stimuli, which provide a model of working memory; (b) oscillatory network activity; and (c) chaotic activity, which models complex patterns of background spiking in cortical and other circuits. We also review propagation of stimulus-driven activity through spontaneously active networks. Exploring these aspects of neural network dynamics is critical for understanding how neural circuits produce cognitive function.","lang":"eng"}],"date_updated":"2021-01-12T08:16:37Z","language":[{"iso":"eng"}],"author":[{"first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425","orcid":"0000-0003-3295-6181","last_name":"Vogels"},{"first_name":"Kanaka","full_name":"Rajan, Kanaka","last_name":"Rajan"},{"first_name":"L.F.","full_name":"Abbott, L.F.","last_name":"Abbott"}],"intvolume":"        28","publisher":"Annual Reviews","doi":"10.1146/annurev.neuro.28.061604.135637","_id":"8029"}