{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T15:50:11Z","timestamp":1791561011559,"version":"4.3.4"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"5-6","license":[{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:00:00Z","timestamp":1791504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Biol Cybern"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Optimal behavior in volatile environments requires agents to deploy different value-control regimes across hidden latent structures. However, representing independent preferences, biases, and action confidence for every situation is computationally and statistically intractable. We introduce value profiles: a compact set of reusable parameter bundles\u2014comprising outcome preferences, policy priors, and action precision\u2014assigned to hidden states in a generative model. As posterior beliefs evolve trial-by-trial, effective control parameters emerge through belief-weighted mixing. This enables state-conditional strategy recruitment without the need for independent parameterization of every context. We evaluate this framework in a probabilistic reversal learning setting using simulation-based model recovery and parameter recovery, comparing profile-based models against static and uncertainty-coupled precision baselines. Model comparison favors the profile-based architecture, with consistent parameter recovery demonstrating its structural identifiability. Beyond predictive fit, we show how the framework allows for a mechanistic attribution of behavior to specific adaptive channels, distinguishing between changes in what an agent prefers and how decisively it acts. Overall, reusable value profiles provide a tractable computational account of belief-conditioned control, offering a mode-like representational scheme for behavioral flexibility that is both identifiable and theoretically grounded.<\/jats:p>","DOI":"10.1007\/s00422-026-01066-0","type":"journal-article","created":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T02:24:51Z","timestamp":1791512691000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Active inference with reusable state-dependent value profiles"],"prefix":"10.1007","volume":"120","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4102-7835","authenticated-orcid":false,"given":"Jacob","family":"Poschl","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,9]]},"reference":[{"key":"1066_CR1","doi-asserted-by":"crossref","unstructured":"Akaike H (1974) A new look at the statistical model identification. Springer Series in Statistics. Springer Series in Statistics. Springer, New York, New York, NY, pp 215\u2013222","DOI":"10.1007\/978-1-4612-1694-0_16"},{"key":"1066_CR2","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1146\/annurev.neuro.28.061604.135709","volume":"28","author":"G Aston-Jones","year":"2005","unstructured":"Aston-Jones G, Cohen JD (2005) An integrative theory of locus coeruleus-norepinephrine function: Adaptive gain and optimal performance. Annu Rev Neurosci 28:403\u2013450. https:\/\/doi.org\/10.1146\/annurev.neuro.28.061604.135709 (https:\/\/www.annualreviews.org\/content\/journals\/10.1146\/annurev.neuro.28.061604.135709)","journal-title":"Annu Rev Neurosci"},{"issue":"9","key":"1066_CR3","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1038\/nn1954","volume":"10","author":"TEJ Behrens","year":"2007","unstructured":"Behrens TEJ, Woolrich MW, Walton ME, Rushworth MFS (2007) Learning the value of information in an uncertain world. Nat Neurosci 10(9):1214\u20131221","journal-title":"Nat Neurosci"},{"key":"1066_CR4","doi-asserted-by":"publisher","first-page":"02","DOI":"10.1038\/npp.2013.48","volume":"38","author":"U Beierholm","year":"2013","unstructured":"Beierholm U, Guitart-Masip M, Economides M, Chowdhury R, Duzel E, Dolan R, Dayan P (2013) Dopamine modulates reward-related vigor. Neuropsychopharmacol Official Publ American College Neuropsychopharmacol 38:02. https:\/\/doi.org\/10.1038\/npp.2013.48","journal-title":"Neuropsychopharmacol Official Publ American College Neuropsychopharmacol"},{"key":"1066_CR5","doi-asserted-by":"publisher","first-page":"95","DOI":"10.3389\/fncom.2017.00095","volume":"11","author":"B de Vries","year":"2017","unstructured":"de Vries B, Friston KJ (2017) A factor graph description of deep temporal active inference. Front Comput Neurosci 11:95","journal-title":"Front Comput Neurosci"},{"key":"1066_CR6","unstructured":"Doshi-velez F (2009) The infinite partially observable markov decision process. In: Bengio Y, Schuurmans D, Lafferty J, Williams C, Culotta A, (eds.) Advances in Neural Information Processing Systems, volume\u00a022. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2009\/file\/ebd9629fc3ae5e9f6611e2ee05a31cef-Paper.pdf"},{"key":"1066_CR7","doi-asserted-by":"publisher","first-page":"1662","DOI":"10.3389\/fnhum.2010.00215","volume":"4","author":"H Feldman","year":"2010","unstructured":"Feldman H, Friston K (2010) Attention, uncertainty, and free-energy. Front Hum Neurosci 4:1662\u20135161. https:\/\/doi.org\/10.3389\/fnhum.2010.00215","journal-title":"Front Hum Neurosci"},{"issue":"2","key":"1066_CR8","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1038\/s41583-019-0253-y","volume":"21","author":"KA Ferguson","year":"2020","unstructured":"Ferguson KA, Cardin JA (2020) Mechanisms underlying gain modulation in the cortex. Nat Rev Neurosci 21(2):80\u201392","journal-title":"Nat Rev Neurosci"},{"issue":"7","key":"1066_CR9","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1016\/j.tics.2009.04.005","volume":"13","author":"K Friston","year":"2009","unstructured":"Friston K (2009) The free-energy principle: a rough guide to the brain? Trends Cogn Sci 13(7):293\u2013301","journal-title":"Trends Cogn Sci"},{"issue":"2","key":"1066_CR10","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1038\/nrn2787","volume":"11","author":"K Friston","year":"2010","unstructured":"Friston K (2010) The free-energy principle: a unified brain theory? Nat Rev Neurosci 11(2):127\u2013138","journal-title":"Nat Rev Neurosci"},{"issue":"4","key":"1066_CR11","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1080\/17588928.2015.1020053","volume":"6","author":"K Friston","year":"2015","unstructured":"Friston K, Rigoli F, Ognibene D, Mathys C, Fitzgerald T, Pezzulo G (2015) Active inference and epistemic value. Cogn Neurosci 6(4):187\u2013214","journal-title":"Cogn Neurosci"},{"issue":"1","key":"1066_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pcbi.1002327","volume":"8","author":"KJ Friston","year":"2012","unstructured":"Friston KJ, Shiner T, FitzGerald T, Galea JM, Adams R, Brown H, Dolan RJ, Moran R, Stephan KE, Bestmann S (2012) Dopamine, affordance and active inference. PLoS Comput Biol 8(1):1\u201320. https:\/\/doi.org\/10.1371\/journal.pcbi.1002327","journal-title":"PLoS Comput Biol"},{"key":"1066_CR13","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1016\/j.neubiorev.2017.04.009","volume":"77","author":"KJ Friston","year":"2017","unstructured":"Friston KJ, Rosch R, Parr T, Price C, Bowman H (2017) Deep temporal models and active inference. Neurosci Biobehav Rev 77:388\u2013402","journal-title":"Neurosci Biobehav Rev"},{"issue":"73","key":"1066_CR14","doi-asserted-by":"publisher","first-page":"4098","DOI":"10.21105\/joss.04098","volume":"7","author":"C Heins","year":"2022","unstructured":"Heins C, Millidge B, Demekas D, Klein B, Friston K, Couzin ID, Tschantz A (2022) pymdp: a python library for active inference in discrete state spaces. J Open Source Softw 7(73):4098. https:\/\/doi.org\/10.21105\/joss.04098","journal-title":"J Open Source Softw"},{"issue":"1668","key":"1066_CR15","doi-asserted-by":"publisher","first-page":"20140169","DOI":"10.1098\/rstb.2014.0169","volume":"370","author":"R Kanai","year":"2015","unstructured":"Kanai R, Komura Y, Shipp S, Friston K (2015) Cerebral hierarchies: predictive processing, precision and the pulvinar. Philos Trans R Soc Lond B Biol Sci 370(1668):20140169","journal-title":"Philos Trans R Soc Lond B Biol Sci"},{"issue":"11","key":"1066_CR16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1000209","volume":"4","author":"SJ Kiebel","year":"2008","unstructured":"Kiebel SJ, Daunizeau J, Friston KJ (2008) A hierarchy of time-scales and the brain. PLoS Comput Biol 4(11):e1000209","journal-title":"PLoS Comput Biol"},{"key":"1066_CR17","unstructured":"Lin W, Hubacher N, Khan ME (2018) Variational message passing with structured inference networks. arXiv:1803.05589"},{"issue":"7474","key":"1066_CR18","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1038\/nature12742","volume":"503","author":"V Mante","year":"2013","unstructured":"Mante V, Sussillo D, Shenoy KV, Newsome WT (2013) Context-dependent computation by recurrent dynamics in prefrontal cortex. Nature 503(7474):78\u201384","journal-title":"Nature"},{"key":"1066_CR19","doi-asserted-by":"publisher","unstructured":"Mathys C, Daunizeau J, Stephan FKJ, KE, (2011) A bayesian foundation for individual learning under uncertainty. Front Hum Neurosci 5(2011):1662\u20135161. https:\/\/doi.org\/10.3389\/fnhum.2011.00039","DOI":"10.3389\/fnhum.2011.00039"},{"key":"1066_CR20","doi-asserted-by":"crossref","unstructured":"Mathys CD, Lomakina EI, Daunizeau J, Iglesias S, Brodersen KH, Friston KJ, Stephan KE (2014) Uncertainty in perception and the hierarchical gaussian filter. Front Hum Neurosci 8","DOI":"10.3389\/fnhum.2014.00825"},{"key":"1066_CR21","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1007\/s00213-006-0502-4","volume":"191","author":"Y Niv","year":"2007","unstructured":"Niv Y, Daw ND, Joel D, Dayan P (2007) Tonic dopamine: opportunity costs and the control of response vigor. Psychopharmacology 191:507\u2013520 (https:\/\/api.semanticscholar.org\/CorpusID:7161073)","journal-title":"Psychopharmacology"},{"key":"1066_CR22","doi-asserted-by":"publisher","first-page":"90","DOI":"10.3389\/fncom.2018.00090","volume":"12","author":"T Parr","year":"2018","unstructured":"Parr T, Friston KJ (2018) The anatomy of inference: generative models and brain structure. Front Comput Neurosci 12:90","journal-title":"Front Comput Neurosci"},{"key":"1066_CR23","doi-asserted-by":"publisher","unstructured":"Parr T, Pezzulo G, Friston K (2022) Active Inference: The Free Energy Principle in Mind, Brain, and Behavior. 03. ISBN 9780262369978. https:\/\/doi.org\/10.7551\/mitpress\/12441.001.0001","DOI":"10.7551\/mitpress\/12441.001.0001"},{"key":"1066_CR24","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.pneurobio.2015.09.001","volume":"134","author":"G Pezzulo","year":"2015","unstructured":"Pezzulo G, Rigoli F, Friston K (2015) Active inference, homeostatic regulation and adaptive behavioural control. Prog Neurobiol 134:17\u201335","journal-title":"Prog Neurobiol"},{"issue":"4","key":"1066_CR25","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1016\/j.tics.2018.01.009","volume":"22","author":"G Pezzulo","year":"2018","unstructured":"Pezzulo G, Rigoli F, Friston KJ (2018) Hierarchical active inference: a theory of motivated control. Trends Cogn Sci 22(4):294\u2013306","journal-title":"Trends Cogn Sci"},{"issue":"6","key":"1066_CR26","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1013180","volume":"21","author":"M Priorelli","year":"2025","unstructured":"Priorelli M, Stoianov IP, Pezzulo G (2025) Embodied decisions as active inference. PLoS Comput Biol 21(6):e1013180. https:\/\/doi.org\/10.1371\/journal.pcbi.1013180","journal-title":"PLoS Comput Biol"},{"key":"1066_CR27","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.plrev.2025.05.008","volume":"54","author":"R Proietti","year":"2025","unstructured":"Proietti R, Parr T, Tessari A, Friston K, Pezzulo G (2025) Active inference and cognitive control: Balancing deliberation and habits through precision optimization. Phys Life Rev 54:27\u201351. https:\/\/doi.org\/10.1016\/j.plrev.2025.05.008","journal-title":"Phys Life Rev"},{"issue":"2017","key":"1066_CR28","doi-asserted-by":"publisher","first-page":"1664","DOI":"10.3389\/fpsyg.2017.00408","volume":"8","author":"F Rigoli","year":"2017","unstructured":"Rigoli F, Pezzulo G, Dolan R, Friston K (2017) A goal-directed bayesian framework for categorization. Front Psychol 8(2017):1664. https:\/\/doi.org\/10.3389\/fpsyg.2017.00408","journal-title":"Front Psychol"},{"issue":"3","key":"1066_CR29","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1162\/neco_a_01357","volume":"33","author":"N Sajid","year":"2021","unstructured":"Sajid N, Ball PJ, Parr T, Friston KJ (2021) Active inference: demystified and compared. Neural Comput 33(3):674\u2013712. https:\/\/doi.org\/10.1162\/neco_a_01357","journal-title":"Neural Comput"},{"issue":"5306","key":"1066_CR30","doi-asserted-by":"publisher","first-page":"1593","DOI":"10.1126\/science.275.5306.1593","volume":"275","author":"W Schultz","year":"1997","unstructured":"Schultz W, Dayan P, Montague PR (1997) A neural substrate of prediction and reward. Science 275(5306):1593\u20131599. https:\/\/doi.org\/10.1126\/science.275.5306.1593","journal-title":"Science"},{"key":"1066_CR31","doi-asserted-by":"crossref","unstructured":"Schwartenbeck, P, Friston K (2016)Computational phenotyping in psychiatry: a worked example. eNeuro, 3(4): ENEURO.0049\u201316.2016","DOI":"10.1523\/ENEURO.0049-16.2016"},{"issue":"2","key":"1066_CR32","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6(2):461\u2013464","journal-title":"Ann Stat"},{"key":"1066_CR33","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1098\/rstb.2002.1161","volume":"357","author":"M Sherman","year":"2003","unstructured":"Sherman M, Guillery R (2003) The role of the thalamus in the flow of information to the cortex. Philosophical transactions of the Royal Society of London. Series B Biol Sci 357:1695\u2013708. https:\/\/doi.org\/10.1098\/rstb.2002.1161","journal-title":"Series B Biol Sci"},{"key":"1066_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmp.2021.102632","volume":"107","author":"R Smith","year":"2022","unstructured":"Smith R, Friston KJ, Whyte CJ (2022) A step-by-step tutorial on active inference and its application to empirical data. J Math Psychol 107:102632","journal-title":"J Math Psychol"},{"key":"1066_CR35","unstructured":"Sutton RS, Barto AG (2018) Reinforcement Learning: An Introduction. MIT Press, (2nd edition)"},{"key":"1066_CR36","unstructured":"Torresan F, Kanai R, Baltieri M (2025) Prior preferences in active inference agents: soft, hard, and goal shaping. arXiv:2512.03293"},{"issue":"1","key":"1066_CR37","doi-asserted-by":"publisher","first-page":"9892","DOI":"10.1038\/s41467-024-54257-3","volume":"15","author":"T Van de Maele","year":"2024","unstructured":"Van de Maele T, Dhoedt B, Verbelen T, Pezzulo G (2024) A hierarchical active inference model of spatial alternation tasks and the hippocampal-prefrontal circuit. Nat Commun 15(1):9892. https:\/\/doi.org\/10.1038\/s41467-024-54257-3","journal-title":"Nat Commun"},{"key":"1066_CR38","doi-asserted-by":"publisher","unstructured":"Vance J (2017) Action prevents error. In Thomas\u00a0K. Metzinger and Wanja Wiese, editors, Philosophy and Predictive Processing, chapter\u00a025. MIND Group, Frankfurt am Main. ISBN 9783958573260. https:\/\/doi.org\/10.15502\/9783958573260. https:\/\/predictive-mind.net\/papers\/action-prevents-error","DOI":"10.15502\/9783958573260"},{"issue":"4","key":"1066_CR39","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1016\/j.neuron.2005.04.026","volume":"46","author":"AJ Yu","year":"2005","unstructured":"Yu AJ, Dayan P (2005) Uncertainty, neuromodulation, and attention. Neuron 46(4):681\u2013692. https:\/\/doi.org\/10.1016\/j.neuron.2005.04.026 (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0896627305003624)","journal-title":"Neuron"}],"container-title":["Biological Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00422-026-01066-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00422-026-01066-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00422-026-01066-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T15:02:04Z","timestamp":1791558124000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00422-026-01066-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,9]]},"references-count":39,"journal-issue":{"issue":"5-6","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1066"],"URL":"https:\/\/doi.org\/10.1007\/s00422-026-01066-0","relation":{},"ISSN":["1432-0770"],"issn-type":[{"value":"1432-0770","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,9]]},"assertion":[{"value":"28 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 October 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"40"}}