[{"publication":"PLoS Computational Biology","status":"public","acknowledgement":"The authors thank Corey Ziemba and Zoe Boundy-Singer for valuable discussion and feedback.","date_published":"2023-06-08T00:00:00Z","pmid":1,"external_id":{"isi":["001003410200003"],"pmid":["37289753"]},"isi":1,"year":"2023","ddc":["570"],"quality_controlled":"1","publisher":"Public Library of Science","article_processing_charge":"No","doi":"10.1371/journal.pcbi.1011104","type":"journal_article","_id":"13230","date_updated":"2023-08-02T06:33:50Z","language":[{"iso":"eng"}],"oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"apa":"Charlton, J. A., Mlynarski, W. F., Bai, Y. H., Hermundstad, A. M., &#38; Goris, R. L. T. (2023). Environmental dynamics shape perceptual decision bias. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1011104\">https://doi.org/10.1371/journal.pcbi.1011104</a>","mla":"Charlton, Julie A., et al. “Environmental Dynamics Shape Perceptual Decision Bias.” <i>PLoS Computational Biology</i>, vol. 19, no. 6, e1011104, Public Library of Science, 2023, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011104\">10.1371/journal.pcbi.1011104</a>.","ista":"Charlton JA, Mlynarski WF, Bai YH, Hermundstad AM, Goris RLT. 2023. Environmental dynamics shape perceptual decision bias. PLoS Computational Biology. 19(6), e1011104.","chicago":"Charlton, Julie A., Wiktor F Mlynarski, Yoon H. Bai, Ann M. Hermundstad, and Robbe L.T. Goris. “Environmental Dynamics Shape Perceptual Decision Bias.” <i>PLoS Computational Biology</i>. Public Library of Science, 2023. <a href=\"https://doi.org/10.1371/journal.pcbi.1011104\">https://doi.org/10.1371/journal.pcbi.1011104</a>.","ieee":"J. A. Charlton, W. F. Mlynarski, Y. H. Bai, A. M. Hermundstad, and R. L. T. Goris, “Environmental dynamics shape perceptual decision bias,” <i>PLoS Computational Biology</i>, vol. 19, no. 6. Public Library of Science, 2023.","short":"J.A. Charlton, W.F. Mlynarski, Y.H. Bai, A.M. Hermundstad, R.L.T. Goris, PLoS Computational Biology 19 (2023).","ama":"Charlton JA, Mlynarski WF, Bai YH, Hermundstad AM, Goris RLT. Environmental dynamics shape perceptual decision bias. <i>PLoS Computational Biology</i>. 2023;19(6). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1011104\">10.1371/journal.pcbi.1011104</a>"},"issue":"6","month":"06","file":[{"relation":"main_file","checksum":"800761fa2c647fabd6ad034589bc526e","file_name":"2023_PloSCompBio_Charlton.pdf","success":1,"content_type":"application/pdf","access_level":"open_access","file_id":"13247","date_created":"2023-07-18T08:07:59Z","file_size":2281868,"date_updated":"2023-07-18T08:07:59Z","creator":"dernst"}],"article_number":"e1011104","department":[{"_id":"MaJö"}],"abstract":[{"text":"To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages knowledge about the statistical structure of the task to maximize decision accuracy, including knowledge about the dynamics of the environment. We show that its decisions are biased by the dynamically changing task context. The magnitude of this decision bias depends on the observer’s continually evolving belief about the current context. The model therefore not only predicts that decision bias will grow as the context is indicated more reliably, but also as the stability of the environment increases, and as the number of trials since the last context switch grows. Analysis of human choice data validates all three predictions, suggesting that the brain leverages knowledge of the statistical structure of environmental change when interpreting ambiguous sensory signals.","lang":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"        19","has_accepted_license":"1","file_date_updated":"2023-07-18T08:07:59Z","publication_status":"published","publication_identifier":{"eissn":["1553-7358"]},"oa_version":"Published Version","title":"Environmental dynamics shape perceptual decision bias","scopus_import":"1","day":"08","author":[{"first_name":"Julie A.","full_name":"Charlton, Julie A.","last_name":"Charlton"},{"first_name":"Wiktor F","full_name":"Mlynarski, Wiktor F","id":"358A453A-F248-11E8-B48F-1D18A9856A87","last_name":"Mlynarski"},{"first_name":"Yoon H.","full_name":"Bai, Yoon H.","last_name":"Bai"},{"full_name":"Hermundstad, Ann M.","last_name":"Hermundstad","first_name":"Ann M."},{"first_name":"Robbe L.T.","full_name":"Goris, Robbe L.T.","last_name":"Goris"}],"date_created":"2023-07-16T22:01:09Z","article_type":"original","volume":19},{"acknowledgement":"We thank Hiroki Asari for sharing the dataset of naturalistic images, Anton Sumser for sharing visual stimulus code, Yoav Ben Simon for initial explorative work with the generation of AAVs, and Tomas Vega-Zuñiga for help with immunostainings. We also thank Gasper Tkacik and members of the Neuroethology group for their comments on the manuscript. This research was supported by the Scientific Service Units of IST Austria through resources provided by Scientific Computing, the Preclinical Facility, the Lab Support Facility, and the Imaging and Optics Facility. This work was supported by European Union Horizon 2020 Marie Skłodowska-Curie grant 665385 (DG), Austrian Science Fund (FWF) stand-alone grant P 34015 (WM), Human Frontiers Science Program LT000256/2018-L (AS), EMBO ALTF 1098-2017 (AS) and the European Research Council Starting Grant 756502 (MJ).","date_published":"2023-04-01T00:00:00Z","pmid":1,"ec_funded":1,"project":[{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"International IST Doctoral Program","grant_number":"665385"},{"_id":"626c45b5-2b32-11ec-9570-e509828c1ba6","grant_number":"P34015","name":"Efficient coding with biophysical realism"},{"_id":"2634E9D2-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Circuits of Visual Attention","grant_number":"756502"},{"_id":"266D407A-B435-11E9-9278-68D0E5697425","name":"Neuronal networks of salience and spatial detection in the murine superior colliculus","grant_number":"LT000256"},{"_id":"264FEA02-B435-11E9-9278-68D0E5697425","grant_number":"ALTF 1098-2017","name":"Connecting sensory with motor processing in the superior colliculus"}],"status":"public","publication":"Nature Neuroscience","external_id":{"pmid":["36959418"],"isi":["000955258300002"]},"related_material":{"record":[{"id":"12370","relation":"research_data","status":"public"}]},"isi":1,"year":"2023","quality_controlled":"1","ddc":["570"],"page":"606-614","type":"journal_article","date_updated":"2023-10-04T11:41:05Z","_id":"12349","publisher":"Springer Nature","doi":"10.1038/s41593-023-01280-0","article_processing_charge":"Yes (in subscription journal)","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ieee":"D. Gupta, W. F. Mlynarski, A. L. Sumser, O. Symonova, J. Svaton, and M. A. Jösch, “Panoramic visual statistics shape retina-wide organization of receptive fields,” <i>Nature Neuroscience</i>, vol. 26. Springer Nature, pp. 606–614, 2023.","short":"D. Gupta, W.F. Mlynarski, A.L. Sumser, O. Symonova, J. Svaton, M.A. Jösch, Nature Neuroscience 26 (2023) 606–614.","ama":"Gupta D, Mlynarski WF, Sumser AL, Symonova O, Svaton J, Jösch MA. Panoramic visual statistics shape retina-wide organization of receptive fields. <i>Nature Neuroscience</i>. 2023;26:606-614. doi:<a href=\"https://doi.org/10.1038/s41593-023-01280-0\">10.1038/s41593-023-01280-0</a>","apa":"Gupta, D., Mlynarski, W. F., Sumser, A. L., Symonova, O., Svaton, J., &#38; Jösch, M. A. (2023). Panoramic visual statistics shape retina-wide organization of receptive fields. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-023-01280-0\">https://doi.org/10.1038/s41593-023-01280-0</a>","mla":"Gupta, Divyansh, et al. “Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields.” <i>Nature Neuroscience</i>, vol. 26, Springer Nature, 2023, pp. 606–14, doi:<a href=\"https://doi.org/10.1038/s41593-023-01280-0\">10.1038/s41593-023-01280-0</a>.","chicago":"Gupta, Divyansh, Wiktor F Mlynarski, Anton L Sumser, Olga Symonova, Jan Svaton, and Maximilian A Jösch. “Panoramic Visual Statistics Shape Retina-Wide Organization of Receptive Fields.” <i>Nature Neuroscience</i>. Springer Nature, 2023. <a href=\"https://doi.org/10.1038/s41593-023-01280-0\">https://doi.org/10.1038/s41593-023-01280-0</a>.","ista":"Gupta D, Mlynarski WF, Sumser AL, Symonova O, Svaton J, Jösch MA. 2023. Panoramic visual statistics shape retina-wide organization of receptive fields. Nature Neuroscience. 26, 606–614."},"language":[{"iso":"eng"}],"oa":1,"file":[{"access_level":"open_access","content_type":"application/pdf","success":1,"file_name":"2023_NatureNeuroscience_Gupta.pdf","checksum":"a33d91e398e548f34003170e10988368","relation":"main_file","date_updated":"2023-10-04T11:40:51Z","creator":"dernst","date_created":"2023-10-04T11:40:51Z","file_size":6144866,"file_id":"14395"}],"department":[{"_id":"GradSch"},{"_id":"MaJö"}],"month":"04","publication_status":"published","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]},"file_date_updated":"2023-10-04T11:40:51Z","abstract":[{"text":"Statistics of natural scenes are not uniform - their structure varies dramatically from ground to sky. It remains unknown whether these non-uniformities are reflected in the large-scale organization of the early visual system and what benefits such adaptations would confer. Here, by relying on the efficient coding hypothesis, we predict that changes in the structure of receptive fields across visual space increase the efficiency of sensory coding. We show experimentally that, in agreement with our predictions, receptive fields of retinal ganglion cells change their shape along the dorsoventral retinal axis, with a marked surround asymmetry at the visual horizon. Our work demonstrates that, according to principles of efficient coding, the panoramic structure of natural scenes is exploited by the retina across space and cell-types.","lang":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"intvolume":"        26","acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"PreCl"},{"_id":"LifeSc"},{"_id":"Bio"}],"has_accepted_license":"1","article_type":"original","date_created":"2023-01-23T14:14:19Z","volume":26,"oa_version":"Published Version","title":"Panoramic visual statistics shape retina-wide organization of receptive fields","author":[{"last_name":"Gupta","full_name":"Gupta, Divyansh","id":"2A485EBE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7400-6665","first_name":"Divyansh"},{"last_name":"Mlynarski","id":"358A453A-F248-11E8-B48F-1D18A9856A87","full_name":"Mlynarski, Wiktor F","first_name":"Wiktor F"},{"orcid":"0000-0002-4792-1881","first_name":"Anton L","last_name":"Sumser","full_name":"Sumser, Anton L","id":"3320A096-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Symonova, Olga","id":"3C0C7BC6-F248-11E8-B48F-1D18A9856A87","last_name":"Symonova","orcid":"0000-0003-2012-9947","first_name":"Olga"},{"full_name":"Svaton, Jan","id":"f7f724c3-9d6f-11ed-9f44-e5c5f3a5bee2","last_name":"Svaton","first_name":"Jan","orcid":"0000-0002-6198-2939"},{"first_name":"Maximilian A","orcid":"0000-0002-3937-1330","last_name":"Jösch","full_name":"Jösch, Maximilian A","id":"2BD278E6-F248-11E8-B48F-1D18A9856A87"}],"scopus_import":"1","day":"01"},{"isi":1,"year":"2022","external_id":{"isi":["000925192000001"]},"status":"public","publication":"PLoS Biology","project":[{"name":"Efficient coding with biophysical realism","grant_number":"P34015","_id":"626c45b5-2b32-11ec-9570-e509828c1ba6"},{"grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"ec_funded":1,"acknowledgement":"We thank Robbe Goris for generously providing figures from his work and Ann M. Hermundstad for helpful discussions.\r\nGT & WM were supported by the Austrian Science Fund Standalone Grant P 34015 \"Efficient Coding with Biophysical Realism\" (https://pf.fwf.ac.at/) WM was additionally supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 754411 (https://ec.europa.eu/research/mariecurieactions/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","date_published":"2022-12-21T00:00:00Z","article_processing_charge":"No","doi":"10.1371/journal.pbio.3001889","publisher":"Public Library of Science","_id":"12332","date_updated":"2023-08-03T14:23:49Z","type":"journal_article","page":"e3001889","ddc":["570"],"quality_controlled":"1","month":"12","department":[{"_id":"GaTk"}],"file":[{"access_level":"open_access","content_type":"application/pdf","success":1,"file_name":"2022_PloSBiology_Mlynarski.pdf","checksum":"5d7f1111a87e5f2c1bf92f8886738894","relation":"main_file","date_updated":"2023-01-23T08:46:40Z","creator":"dernst","file_size":4248838,"date_created":"2023-01-23T08:46:40Z","file_id":"12337"}],"oa":1,"language":[{"iso":"eng"}],"citation":{"short":"W.F. Mlynarski, G. Tkačik, PLoS Biology 20 (2022) e3001889.","ieee":"W. F. Mlynarski and G. Tkačik, “Efficient coding theory of dynamic attentional modulation,” <i>PLoS Biology</i>, vol. 20, no. 12. Public Library of Science, p. e3001889, 2022.","ama":"Mlynarski WF, Tkačik G. Efficient coding theory of dynamic attentional modulation. <i>PLoS Biology</i>. 2022;20(12):e3001889. doi:<a href=\"https://doi.org/10.1371/journal.pbio.3001889\">10.1371/journal.pbio.3001889</a>","mla":"Mlynarski, Wiktor F., and Gašper Tkačik. “Efficient Coding Theory of Dynamic Attentional Modulation.” <i>PLoS Biology</i>, vol. 20, no. 12, Public Library of Science, 2022, p. e3001889, doi:<a href=\"https://doi.org/10.1371/journal.pbio.3001889\">10.1371/journal.pbio.3001889</a>.","apa":"Mlynarski, W. F., &#38; Tkačik, G. (2022). Efficient coding theory of dynamic attentional modulation. <i>PLoS Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pbio.3001889\">https://doi.org/10.1371/journal.pbio.3001889</a>","chicago":"Mlynarski, Wiktor F, and Gašper Tkačik. “Efficient Coding Theory of Dynamic Attentional Modulation.” <i>PLoS Biology</i>. Public Library of Science, 2022. <a href=\"https://doi.org/10.1371/journal.pbio.3001889\">https://doi.org/10.1371/journal.pbio.3001889</a>.","ista":"Mlynarski WF, Tkačik G. 2022. Efficient coding theory of dynamic attentional modulation. PLoS Biology. 20(12), e3001889."},"issue":"12","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","scopus_import":"1","day":"21","author":[{"first_name":"Wiktor F","full_name":"Mlynarski, Wiktor F","id":"358A453A-F248-11E8-B48F-1D18A9856A87","last_name":"Mlynarski"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik","orcid":"1","first_name":"Gašper"}],"title":"Efficient coding theory of dynamic attentional modulation","oa_version":"Published Version","volume":20,"date_created":"2023-01-22T23:00:55Z","article_type":"original","has_accepted_license":"1","intvolume":"        20","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)"},"abstract":[{"text":"Activity of sensory neurons is driven not only by external stimuli but also by feedback signals from higher brain areas. Attention is one particularly important internal signal whose presumed role is to modulate sensory representations such that they only encode information currently relevant to the organism at minimal cost. This hypothesis has, however, not yet been expressed in a normative computational framework. Here, by building on normative principles of probabilistic inference and efficient coding, we developed a model of dynamic population coding in the visual cortex. By continuously adapting the sensory code to changing demands of the perceptual observer, an attention-like modulation emerges. This modulation can dramatically reduce the amount of neural activity without deteriorating the accuracy of task-specific inferences. Our results suggest that a range of seemingly disparate cortical phenomena such as intrinsic gain modulation, attention-related tuning modulation, and response variability could be manifestations of the same underlying principles, which combine efficient sensory coding with optimal probabilistic inference in dynamic environments.","lang":"eng"}],"file_date_updated":"2023-01-23T08:46:40Z","publication_identifier":{"eissn":["1545-7885"]},"publication_status":"published"},{"quality_controlled":"1","main_file_link":[{"url":"https://doi.org/10.1101/848374","open_access":"1"}],"page":"1227-1241.e5","type":"journal_article","date_updated":"2025-06-30T13:21:05Z","_id":"7553","publisher":"Cell Press","doi":"10.1016/j.neuron.2021.01.020","article_processing_charge":"No","date_published":"2021-04-07T00:00:00Z","acknowledgement":"The authors thank Dario Ringach for providing the V1 receptive fields and Olivier Marre for providing the retinal receptive fields. W.M. was funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 754411. M.H. was funded in part by Human Frontiers Science grant no. HFSP RGP0032/2018.","ec_funded":1,"project":[{"_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships"}],"publication":"Neuron","status":"public","external_id":{"isi":["000637809600006"]},"related_material":{"record":[{"id":"15020","status":"public","relation":"dissertation_contains"}],"link":[{"relation":"press_release","description":"News on IST Homepage","url":"https://ist.ac.at/en/news/can-evolution-be-predicted/"}]},"isi":1,"year":"2021","publication_status":"published","abstract":[{"text":"Normative theories and statistical inference provide complementary approaches for the study of biological systems. A normative theory postulates that organisms have adapted to efficiently solve essential tasks, and proceeds to mathematically work out testable consequences of such optimality; parameters that maximize the hypothesized organismal function can be derived ab initio, without reference to experimental data. In contrast, statistical inference focuses on efficient utilization of data to learn model parameters, without reference to any a priori notion of biological function, utility, or fitness. Traditionally, these two approaches were developed independently and applied separately. Here we unify them in a coherent Bayesian framework that embeds a normative theory into a family of maximum-entropy “optimization priors.” This family defines a smooth interpolation between a data-rich inference regime (characteristic of “bottom-up” statistical models), and a data-limited ab inito prediction regime (characteristic of “top-down” normative theory). We demonstrate the applicability of our framework using data from the visual cortex, and argue that the flexibility it affords is essential to address a number of fundamental challenges relating to inference and prediction in complex, high-dimensional biological problems.","lang":"eng"}],"intvolume":"       109","date_created":"2020-02-28T11:00:12Z","volume":109,"title":"Statistical analysis and optimality of neural systems","oa_version":"Preprint","author":[{"id":"358A453A-F248-11E8-B48F-1D18A9856A87","full_name":"Mlynarski, Wiktor F","last_name":"Mlynarski","first_name":"Wiktor F"},{"first_name":"Michal","last_name":"Hledik","id":"4171253A-F248-11E8-B48F-1D18A9856A87","full_name":"Hledik, Michal"},{"first_name":"Thomas R","orcid":"0000-0002-1287-3779","id":"3E999752-F248-11E8-B48F-1D18A9856A87","full_name":"Sokolowski, Thomas R","last_name":"Sokolowski"},{"last_name":"Tkačik","full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","orcid":"0000-0002-6699-1455"}],"scopus_import":"1","day":"07","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","issue":"7","citation":{"mla":"Mlynarski, Wiktor F., et al. “Statistical Analysis and Optimality of Neural Systems.” <i>Neuron</i>, vol. 109, no. 7, Cell Press, 2021, p. 1227–1241.e5, doi:<a href=\"https://doi.org/10.1016/j.neuron.2021.01.020\">10.1016/j.neuron.2021.01.020</a>.","apa":"Mlynarski, W. F., Hledik, M., Sokolowski, T. R., &#38; Tkačik, G. (2021). Statistical analysis and optimality of neural systems. <i>Neuron</i>. Cell Press. <a href=\"https://doi.org/10.1016/j.neuron.2021.01.020\">https://doi.org/10.1016/j.neuron.2021.01.020</a>","chicago":"Mlynarski, Wiktor F, Michal Hledik, Thomas R Sokolowski, and Gašper Tkačik. “Statistical Analysis and Optimality of Neural Systems.” <i>Neuron</i>. Cell Press, 2021. <a href=\"https://doi.org/10.1016/j.neuron.2021.01.020\">https://doi.org/10.1016/j.neuron.2021.01.020</a>.","ista":"Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. 2021. Statistical analysis and optimality of neural systems. Neuron. 109(7), 1227–1241.e5.","short":"W.F. Mlynarski, M. Hledik, T.R. Sokolowski, G. Tkačik, Neuron 109 (2021) 1227–1241.e5.","ieee":"W. F. Mlynarski, M. Hledik, T. R. Sokolowski, and G. Tkačik, “Statistical analysis and optimality of neural systems,” <i>Neuron</i>, vol. 109, no. 7. Cell Press, p. 1227–1241.e5, 2021.","ama":"Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. Statistical analysis and optimality of neural systems. <i>Neuron</i>. 2021;109(7):1227-1241.e5. doi:<a href=\"https://doi.org/10.1016/j.neuron.2021.01.020\">10.1016/j.neuron.2021.01.020</a>"},"language":[{"iso":"eng"}],"oa":1,"department":[{"_id":"GaTk"}],"month":"04"},{"page":"998-1009","quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/669200 "}],"publisher":"Springer Nature","article_processing_charge":"No","doi":"10.1038/s41593-021-00846-0","type":"journal_article","_id":"9439","date_updated":"2023-08-08T13:51:14Z","publication":"Nature Neuroscience","status":"public","project":[{"_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411","name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020"}],"date_published":"2021-05-20T00:00:00Z","acknowledgement":"We thank D. Kastner and T. Münch for generously providing figures from their work. We also thank V. Jayaraman, M. Noorman, T. Ma, and K. Krishnamurthy for useful discussions and feedback on the manuscript. W.F.M. was funded by the European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie Grant Agreement No. 754411. A.M.H. was supported by the Howard Hughes Medical Institute.","ec_funded":1,"external_id":{"isi":["000652577300003"]},"year":"2021","isi":1,"intvolume":"        24","abstract":[{"lang":"eng","text":"The ability to adapt to changes in stimulus statistics is a hallmark of sensory systems. Here, we developed a theoretical framework that can account for the dynamics of adaptation from an information processing perspective. We use this framework to optimize and analyze adaptive sensory codes, and we show that codes optimized for stationary environments can suffer from prolonged periods of poor performance when the environment changes. To mitigate the adversarial effects of these environmental changes, sensory systems must navigate tradeoffs between the ability to accurately encode incoming stimuli and the ability to rapidly detect and adapt to changes in the distribution of these stimuli. We derive families of codes that balance these objectives, and we demonstrate their close match to experimentally observed neural dynamics during mean and variance adaptation. Our results provide a unifying perspective on adaptation across a range of sensory systems, environments, and sensory tasks."}],"publication_status":"published","publication_identifier":{"eissn":["1546-1726"],"issn":["1097-6256"]},"oa_version":"Preprint","title":"Efficient and adaptive sensory codes","day":"20","scopus_import":"1","author":[{"first_name":"Wiktor F","id":"358A453A-F248-11E8-B48F-1D18A9856A87","full_name":"Mlynarski, Wiktor F","last_name":"Mlynarski"},{"full_name":"Hermundstad, Ann M.","last_name":"Hermundstad","first_name":"Ann M."}],"date_created":"2021-05-30T22:01:24Z","article_type":"original","volume":24,"language":[{"iso":"eng"}],"oa":1,"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"apa":"Mlynarski, W. F., &#38; Hermundstad, A. M. (2021). Efficient and adaptive sensory codes. <i>Nature Neuroscience</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41593-021-00846-0\">https://doi.org/10.1038/s41593-021-00846-0</a>","mla":"Mlynarski, Wiktor F., and Ann M. Hermundstad. “Efficient and Adaptive Sensory Codes.” <i>Nature Neuroscience</i>, vol. 24, Springer Nature, 2021, pp. 998–1009, doi:<a href=\"https://doi.org/10.1038/s41593-021-00846-0\">10.1038/s41593-021-00846-0</a>.","ista":"Mlynarski WF, Hermundstad AM. 2021. Efficient and adaptive sensory codes. Nature Neuroscience. 24, 998–1009.","chicago":"Mlynarski, Wiktor F, and Ann M. Hermundstad. “Efficient and Adaptive Sensory Codes.” <i>Nature Neuroscience</i>. Springer Nature, 2021. <a href=\"https://doi.org/10.1038/s41593-021-00846-0\">https://doi.org/10.1038/s41593-021-00846-0</a>.","ieee":"W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,” <i>Nature Neuroscience</i>, vol. 24. Springer Nature, pp. 998–1009, 2021.","short":"W.F. Mlynarski, A.M. Hermundstad, Nature Neuroscience 24 (2021) 998–1009.","ama":"Mlynarski WF, Hermundstad AM. Efficient and adaptive sensory codes. <i>Nature Neuroscience</i>. 2021;24:998-1009. doi:<a href=\"https://doi.org/10.1038/s41593-021-00846-0\">10.1038/s41593-021-00846-0</a>"},"month":"05","department":[{"_id":"GaTk"}]}]