2026-04-14T06:35:01Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/727422026-03-13T20:25:21Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Grabenhorst, Fabian author Ponce-Alvarez, Adrián author Battaglia-Mayer, Alexandra author Deco, Gustavo author Schultz, Wolfram author 2026-03-09T12:31:06Z 2026-03-09T12:31:06Z 2023 2026-03-09T12:31:06Z Primates make decisions visually by shifting their view from one object to the next, comparing values between objects, and choosing the best reward, even before acting. Here, we show that when monkeys make value-guided choices, amygdala neurons encode their decisions in an abstract, purely internal representation defined by the monkey's current view but not by specific object or reward properties. Across amygdala subdivisions, recorded activity patterns evolved gradually from an object-specific value code to a transient, object-independent code in which currently viewed and last-viewed objects competed to reflect the emerging view-based choice. Using neural-network modeling, we identified a sequence of computations by which amygdala neurons implemented view-based decision making and eventually recovered the chosen object's identity when the monkeys acted on their choice. These findings reveal a neural mechanism in the amygdala that derives object choices from abstract, view-based computations, suggesting an efficient solution for decision problems with many objects. We thank A. David and C. Thompson for animal care; P. Taylor for anesthesia; H. Cousins and A. Stasiak for programming; R. Baez-Mendoza, S. Ferrari-Toniolo, F.-Y. Huang, A. Lak, M. O'Neill, and W. Stauffer for support and discussions; and A. Rangel for valuable comments on the manuscript. This work was funded by the Wellcome Trust and the Royal Society (Wellcome/Royal Society Sir Henry Dale Fellowship grants 206207/Z/17/Z and 206207/Z/17/A to F.G.; Wellcome Trust Principal Research Fellowship and Program Grant 095495 to W.S.). G.D. was supported by the Spanish national research project (ref. PID2019-105772GB-I00/AEI/10.13039/501100011033 MCIU AE) from the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI). A.P.-A. was supported by a Ramón y Cajal fellowship (RYC2020-029117-I) from FSE/Agencia Estatal de Investigación (AEI), Spanish Ministry of Science and Innovation. A.B.-M. was supported by the Ministry of University and Research, Italy (PRIN 2010XPMFW4_004 and PRIN 201794KEER_002). This research was funded in whole, or in part, by the Wellcome Trust. For the purpose of open access, the author has applied a CC BY public copyright license to any author accepted manuscript version arising from this submission. Decision making Choice Neural code Abstract representation Attractor Expansion recoding A view-based decision mechanism for rewards in the primate amygdala