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Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2026,9,29]]},"abstract":"<jats:p>Collective decision-making arises from individual agents integrating their own personal observations with information obtained from social partners. In many biological systems that exhibit collective decision-making, the process by which social information is produced, transmitted, and used is subject to two key constraints. First, individuals often do not observe the internal states or personal observations of their neighbors; instead, they observe neighbors\u2019 discrete actions. Second, agents often have limited attention and preferentially attend to a subset of the social signals that are most salient. Using methods from nonlinear dynamics, we show that either of these constraints can cause collective accuracy to become extremely sensitive to the weight individuals place on the information they receive from others. This sensitivity arises from the spontaneous formation of echo chamber\u2013like states in which individuals receive and transmit homogeneous social messages. Under such conditions, collectives become locked in self-reinforcing states that prevent them from tracking changes in the environment. We reveal the mathematical basis of this phenomenon, and show that it emerges not only in generic models of collective decision-making but also in models developed to describe specific biological systems, including neural circuits, eusocial insect colonies, and mobile animal groups. Finally, we identify biologically plausible mechanisms through which individuals may reduce the risk of echo chamber formation and achieve robust yet sensitive collective decisions without requiring fine-tuning parameters. Our results reveal how fundamental constraints on communication shape the dynamics and reliability of collective decisions across diverse biological systems.<\/jats:p>","DOI":"10.1073\/pnas.2613908123","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T16:12:31Z","timestamp":1790093551000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":0,"title":["Messaging strategies and the emergence of echo chambers in collective decision-making"],"prefix":"10.1073","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8921-1642","authenticated-orcid":false,"given":"Ling-Wei","family":"Kong","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05bnh6r87","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Computational Biology, Cornell University","place":["Ithaca"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5328-3871","authenticated-orcid":false,"given":"Naomi Ehrich","family":"Leonard","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00hx57361","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Mechanical and Aerospace Engineering, Princeton University","place":["Princeton"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7217-6185","authenticated-orcid":false,"given":"Andrew M.","family":"Hein","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05bnh6r87","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Computational Biology, Cornell University","place":["Ithaca"]},{"id":[{"id":"https:\/\/ror.org\/05bnh6r87","id-type":"ROR","asserted-by":"publisher"}],"name":"Center for Applied Mathematics, Cornell University","place":["Ithaca"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.geb.2010.01.005"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1257\/mic.2.1.112"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1080\/0022250X.1990.9990069"},{"key":"e_1_3_4_4_2","unstructured":"M. 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