[{"issue":"1","_id":"8017","date_updated":"2021-01-12T08:16:32Z","article_processing_charge":"No","publication_identifier":{"issn":["0147-006X","1545-4126"]},"citation":{"ieee":"G. Hennequin, E. J. Agnes, and T. P. Vogels, “Inhibitory plasticity: Balance, control, and codependence,” <i>Annual Review of Neuroscience</i>, vol. 40, no. 1. Annual Reviews, pp. 557–579, 2017.","chicago":"Hennequin, Guillaume, Everton J. Agnes, and Tim P Vogels. “Inhibitory Plasticity: Balance, Control, and Codependence.” <i>Annual Review of Neuroscience</i>. Annual Reviews, 2017. <a href=\"https://doi.org/10.1146/annurev-neuro-072116-031005\">https://doi.org/10.1146/annurev-neuro-072116-031005</a>.","apa":"Hennequin, G., Agnes, E. J., &#38; Vogels, T. P. (2017). Inhibitory plasticity: Balance, control, and codependence. <i>Annual Review of Neuroscience</i>. Annual Reviews. <a href=\"https://doi.org/10.1146/annurev-neuro-072116-031005\">https://doi.org/10.1146/annurev-neuro-072116-031005</a>","short":"G. Hennequin, E.J. Agnes, T.P. Vogels, Annual Review of Neuroscience 40 (2017) 557–579.","ista":"Hennequin G, Agnes EJ, Vogels TP. 2017. Inhibitory plasticity: Balance, control, and codependence. Annual Review of Neuroscience. 40(1), 557–579.","mla":"Hennequin, Guillaume, et al. “Inhibitory Plasticity: Balance, Control, and Codependence.” <i>Annual Review of Neuroscience</i>, vol. 40, no. 1, Annual Reviews, 2017, pp. 557–79, doi:<a href=\"https://doi.org/10.1146/annurev-neuro-072116-031005\">10.1146/annurev-neuro-072116-031005</a>.","ama":"Hennequin G, Agnes EJ, Vogels TP. Inhibitory plasticity: Balance, control, and codependence. <i>Annual Review of Neuroscience</i>. 2017;40(1):557-579. doi:<a href=\"https://doi.org/10.1146/annurev-neuro-072116-031005\">10.1146/annurev-neuro-072116-031005</a>"},"pmid":1,"external_id":{"pmid":["28598717"]},"extern":"1","language":[{"iso":"eng"}],"publication_status":"published","publisher":"Annual Reviews","volume":40,"date_published":"2017-07-01T00:00:00Z","oa_version":"None","intvolume":"        40","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","publication":"Annual Review of Neuroscience","title":"Inhibitory plasticity: Balance, control, and codependence","month":"07","day":"01","page":"557-579","author":[{"last_name":"Hennequin","first_name":"Guillaume","full_name":"Hennequin, Guillaume"},{"last_name":"Agnes","first_name":"Everton J.","full_name":"Agnes, Everton J."},{"orcid":"0000-0003-3295-6181","first_name":"Tim P","last_name":"Vogels","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"}],"year":"2017","doi":"10.1146/annurev-neuro-072116-031005","article_type":"original","status":"public","quality_controlled":"1","date_created":"2020-06-25T12:55:53Z","abstract":[{"lang":"eng","text":"nhibitory neurons, although relatively few in number, exert powerful control over brain circuits. They stabilize network activity in the face of strong feedback excitation and actively engage in computations. Recent studies reveal the importance of a precise balance of excitation and inhibition in neural circuits, which often requires exquisite fine-tuning of inhibitory connections. We review inhibitory synaptic plasticity and its roles in shaping both feedforward and feedback control. We discuss the necessity of complex, codependent plasticity mechanisms to build nontrivial, functioning networks, and we end by summarizing experimental evidence of such interactions."}],"type":"journal_article"},{"page":"357-376","day":"21","doi":"10.1146/annurev.neuro.28.061604.135637","year":"2005","author":[{"orcid":"0000-0003-3295-6181","last_name":"Vogels","first_name":"Tim P","full_name":"Vogels, Tim P","id":"CB6FF8D2-008F-11EA-8E08-2637E6697425"},{"full_name":"Rajan, Kanaka","last_name":"Rajan","first_name":"Kanaka"},{"full_name":"Abbott, L.F.","first_name":"L.F.","last_name":"Abbott"}],"article_type":"review","title":"Neural network dynamics","month":"07","date_created":"2020-06-25T13:13:11Z","abstract":[{"lang":"eng","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."}],"type":"journal_article","status":"public","quality_controlled":"1","pmid":1,"citation":{"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>.","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.","ista":"Vogels TP, Rajan K, Abbott LF. 2005. Neural network dynamics. Annual Review of Neuroscience. 28(1), 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>","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>.","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."},"publication_identifier":{"issn":["0147-006X","1545-4126"]},"external_id":{"pmid":["16022600"]},"extern":"1","language":[{"iso":"eng"}],"issue":"1","_id":"8029","article_processing_charge":"No","date_updated":"2021-01-12T08:16:37Z","user_id":"D865714E-FA4E-11E9-B85B-F5C5E5697425","intvolume":"        28","publication":"Annual Review of Neuroscience","publisher":"Annual Reviews","publication_status":"published","date_published":"2005-07-21T00:00:00Z","volume":28,"oa_version":"None"}]