{"issue":"MAY","year":"2014","date_updated":"2025-09-29T12:11:13Z","article_processing_charge":"No","citation":{"chicago":"Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations in Working Memory Circuits.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2014. https://doi.org/10.3389/fncom.2014.00057.","ama":"Savin C, Triesch J. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 2014;8(MAY). doi:10.3389/fncom.2014.00057","apa":"Savin, C., & Triesch, J. (2014). Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2014.00057","ieee":"C. Savin and J. Triesch, “Emergence of task-dependent representations in working memory circuits,” Frontiers in Computational Neuroscience, vol. 8, no. MAY. Frontiers Research Foundation, 2014.","ista":"Savin C, Triesch J. 2014. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 8(MAY), 57.","short":"C. Savin, J. Triesch, Frontiers in Computational Neuroscience 8 (2014).","mla":"Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations in Working Memory Circuits.” Frontiers in Computational Neuroscience, vol. 8, no. MAY, 57, Frontiers Research Foundation, 2014, doi:10.3389/fncom.2014.00057."},"external_id":{"isi":["000336715400001"]},"doi":"10.3389/fncom.2014.00057","_id":"1931","oa_version":"Submitted Version","volume":8,"date_published":"2014-05-28T00:00:00Z","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","main_file_link":[{"url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035833/","open_access":"1"}],"month":"05","day":"28","title":"Emergence of task-dependent representations in working memory circuits","abstract":[{"text":"A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP) and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity.","lang":"eng"}],"intvolume":" 8","publication":"Frontiers in Computational Neuroscience","publication_status":"published","type":"journal_article","corr_author":"1","publist_id":"5163","author":[{"full_name":"Savin, Cristina","first_name":"Cristina","last_name":"Savin","id":"3933349E-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Triesch, Jochen","first_name":"Jochen","last_name":"Triesch"}],"scopus_import":"1","department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"acknowledgement":"Supported in part by EC MEXT project PLICON and the LOEWE-Program “Neuronal Coordination Research Focus Frankfurt” (NeFF). Jochen Triesch was supported by the Quandt foundation.","date_created":"2018-12-11T11:54:46Z","article_number":"57","quality_controlled":"1","publisher":"Frontiers Research Foundation","isi":1,"status":"public","oa":1}