{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Stroud JP"],"funding":["Human Frontier Science Program","Gates Cambridge Trust","Medical Research Council","Clarendon Fund","James S. McDonnell Foundation","Wellcome Trust","Biotechnology and Biological Sciences Research Council"],"pagination":["RP94961"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11750133"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13"],"pubmed_abstract":["Cognitive flexibility requires both the encoding of task-relevant and the ignoring of task-irrelevant stimuli. While the neural coding of task-relevant stimuli is increasingly well understood, the mechanisms for ignoring task-irrelevant stimuli remain poorly understood. Here, we study how task performance and biological constraints jointly determine the coding of relevant and irrelevant stimuli in neural circuits. Using mathematical analyses and task-optimized recurrent neural networks, we show that neural circuits can exhibit a range of representational geometries depending on the strength of neural noise and metabolic cost. By comparing these results with recordings from primate prefrontal cortex (PFC) over the course of learning, we show that neural activity in PFC changes in line with "],"journal":["eLife"],"pubmed_title":["Effects of noise and metabolic cost on cortical task representations."],"pmcid":["PMC11750133"],"funding_grant_id":["212262/Z/18/Z","10.35802/215909","BB/M010732/1","10.37717/220020405","10.35802/101092","RGP0044/2018","10.35802/212262","MC_UU_00030/7"],"pubmed_authors":["Wojcik M","Duncan J","Kusunoki M","Stokes MG","Jensen KT","Lengyel M","Kadohisa M","Stroud JP","Buckley MJ"],"additional_accession":[]},"is_claimable":false,"name":"Effects of noise and metabolic cost on cortical task representations.","description":"Cognitive flexibility requires both the encoding of task-relevant and the ignoring of task-irrelevant stimuli. While the neural coding of task-relevant stimuli is increasingly well understood, the mechanisms for ignoring task-irrelevant stimuli remain poorly understood. Here, we study how task performance and biological constraints jointly determine the coding of relevant and irrelevant stimuli in neural circuits. Using mathematical analyses and task-optimized recurrent neural networks, we show that neural circuits can exhibit a range of representational geometries depending on the strength of neural noise and metabolic cost. By comparing these results with recordings from primate prefrontal cortex (PFC) over the course of learning, we show that neural activity in PFC changes in line with ","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jan","modification":"2025-04-04T14:05:44.899Z","creation":"2025-04-04T14:05:44.899Z"},"accession":"S-EPMC11750133","cross_references":{"pubmed":["39836111"],"doi":["10.7554/eLife.94961"]}}