Year |
Citation |
Score |
2024 |
Lowet AS, Zheng Q, Meng M, Matias S, Drugowitsch J, Uchida N. An opponent striatal circuit for distributional reinforcement learning. Biorxiv : the Preprint Server For Biology. PMID 38260354 DOI: 10.1101/2024.01.02.573966 |
0.578 |
|
2023 |
Bukwich M, Campbell MG, Zoltowski D, Kingsbury L, Tomov MS, Stern J, Kim HR, Drugowitsch J, Linderman SW, Uchida N. Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics. Biorxiv : the Preprint Server For Biology. PMID 37732217 DOI: 10.1101/2023.09.05.556267 |
0.392 |
|
2023 |
Noel JP, Bill J, Ding H, Vastola J, DeAngelis GC, Angelaki DE, Drugowitsch J. Causal inference during closed-loop navigation: parsing of self- and object-motion. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 378: 20220344. PMID 37545300 DOI: 10.1098/rstb.2022.0344 |
0.738 |
|
2023 |
Kutschireiter A, Basnak MA, Wilson RI, Drugowitsch J. Bayesian inference in ring attractor networks. Proceedings of the National Academy of Sciences of the United States of America. 120: e2210622120. PMID 36812206 DOI: 10.1073/pnas.2210622120 |
0.759 |
|
2023 |
Noel JP, Bill J, Ding H, Vastola J, DeAngelis GC, Angelaki DE, Drugowitsch J. Causal inference during closed-loop navigation: parsing of self- and object-motion. Biorxiv : the Preprint Server For Biology. PMID 36778376 DOI: 10.1101/2023.01.27.525974 |
0.732 |
|
2022 |
Bill J, Gershman SJ, Drugowitsch J. Visual motion perception as online hierarchical inference. Nature Communications. 13: 7403. PMID 36456546 DOI: 10.1038/s41467-022-34805-5 |
0.786 |
|
2022 |
Kutschireiter A, Rast L, Drugowitsch J. Projection Filtering with Observed State Increments with Applications in Continuous-Time Circular Filtering. Ieee Transactions On Signal Processing : a Publication of the Ieee Signal Processing Society. 70: 686-700. PMID 36338544 DOI: 10.1109/tsp.2022.3143471 |
0.737 |
|
2022 |
Drevet J, Drugowitsch J, Wyart V. Efficient stabilization of imprecise statistical inference through conditional belief updating. Nature Human Behaviour. PMID 36138224 DOI: 10.1038/s41562-022-01445-0 |
0.366 |
|
2022 |
Rouault M, Weiss A, Lee JK, Drugowitsch J, Chambon V, Wyart V. Controllability boosts neural and cognitive signatures of changes-of-mind in uncertain environments. Elife. 11. PMID 36097814 DOI: 10.7554/eLife.75038 |
0.708 |
|
2021 |
Weiss A, Chambon V, Lee JK, Drugowitsch J, Wyart V. Interacting with volatile environments stabilizes hidden-state inference and its brain signatures. Nature Communications. 12: 2228. PMID 33850124 DOI: 10.1038/s41467-021-22396-6 |
0.705 |
|
2021 |
Jang AI, Sharma R, Drugowitsch J. Optimal policy for attention-modulated decisions explains human fixation behavior. Elife. 10. PMID 33769284 DOI: 10.7554/eLife.63436 |
0.399 |
|
2021 |
Yang S, Bill J, Drugowitsch J, Gershman SJ. Human visual motion perception shows hallmarks of Bayesian structural inference. Scientific Reports. 11: 3714. PMID 33580096 DOI: 10.1038/s41598-021-82175-7 |
0.79 |
|
2021 |
Kafashan M, Jaffe AW, Chettih SN, Nogueira R, Arandia-Romero I, Harvey CD, Moreno-Bote R, Drugowitsch J. Scaling of sensory information in large neural populations shows signatures of information-limiting correlations. Nature Communications. 12: 473. PMID 33473113 DOI: 10.1038/s41467-020-20722-y |
0.625 |
|
2020 |
Lowet AS, Zheng Q, Matias S, Drugowitsch J, Uchida N. Distributional Reinforcement Learning in the Brain. Trends in Neurosciences. PMID 33092893 DOI: 10.1016/j.tins.2020.09.004 |
0.575 |
|
2020 |
Bill J, Pailian H, Gershman SJ, Drugowitsch J. Hierarchical structure is employed by humans during visual motion perception. Proceedings of the National Academy of Sciences of the United States of America. 117: 24581-24589. PMID 32938799 DOI: 10.1073/Pnas.2008961117 |
0.782 |
|
2020 |
Moreno-Bote R, Ramírez-Ruiz J, Drugowitsch J, Hayden BY. Heuristics and optimal solutions to the breadth-depth dilemma. Proceedings of the National Academy of Sciences of the United States of America. 117: 19799-19808. PMID 32759219 DOI: 10.1073/Pnas.2004929117 |
0.676 |
|
2020 |
Mendonça AG, Drugowitsch J, Vicente MI, DeWitt EEJ, Pouget A, Mainen ZF. The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs. Nature Communications. 11: 2757. PMID 32488065 DOI: 10.1038/S41467-020-16196-7 |
0.804 |
|
2019 |
Drugowitsch J, Mendonça AG, Mainen ZF, Pouget A. Learning optimal decisions with confidence. Proceedings of the National Academy of Sciences of the United States of America. PMID 31732671 DOI: 10.1073/Pnas.1906787116 |
0.81 |
|
2019 |
Shan H, Moreno-Bote R, Drugowitsch J. Family of closed-form solutions for two-dimensional correlated diffusion processes. Physical Review. E. 100: 032132. PMID 31640022 DOI: 10.1103/Physreve.100.032132 |
0.611 |
|
2019 |
Tajima S, Drugowitsch J, Patel N, Pouget A. Optimal policy for multi-alternative decisions. Nature Neuroscience. PMID 31384015 DOI: 10.1038/S41593-019-0453-9 |
0.753 |
|
2019 |
Rouault M, Drugowitsch J, Koechlin E. Prefrontal mechanisms combining rewards and beliefs in human decision-making. Nature Communications. 10: 301. PMID 30655534 DOI: 10.1038/S41467-018-08121-W |
0.751 |
|
2019 |
Bill J, Pailian H, Gershman SJ, Drugowitsch J. Hierarchical motion structure is employed by humans during visual perception Journal of Vision. 19: 282. DOI: 10.1167/19.10.282 |
0.766 |
|
2017 |
Nogueira R, Abolafia JM, Drugowitsch J, Balaguer-Ballester E, Sanchez-Vives MV, Moreno-Bote R. Lateral orbitofrontal cortex anticipates choices and integrates prior with current information. Nature Communications. 8: 14823. PMID 28337990 DOI: 10.1038/Ncomms14823 |
0.691 |
|
2016 |
Drugowitsch J, Wyart V, Devauchelle AD, Koechlin E. Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality. Neuron. PMID 27916454 DOI: 10.1016/J.Neuron.2016.11.005 |
0.723 |
|
2016 |
Tajima S, Drugowitsch J, Pouget A. Optimal policy for value-based decision-making. Nature Communications. 7: 12400. PMID 27535638 DOI: 10.1038/Ncomms12400 |
0.824 |
|
2016 |
Drugowitsch J. Becoming Confident in the Statistical Nature of Human Confidence Judgments. Neuron. 90: 425-7. PMID 27151633 DOI: 10.1016/J.Neuron.2016.04.023 |
0.342 |
|
2016 |
Arandia-Romero I, Tanabe S, Drugowitsch J, Kohn A, Moreno-Bote R. Multiplicative and Additive Modulation of Neuronal Tuning with Population Activity Affects Encoded Information. Neuron. PMID 26924437 DOI: 10.1016/J.Neuron.2016.01.044 |
0.637 |
|
2016 |
Pouget A, Drugowitsch J, Kepecs A. Confidence and certainty: distinct probabilistic quantities for different goals. Nature Neuroscience. 19: 366-74. PMID 26906503 DOI: 10.1038/Nn.4240 |
0.773 |
|
2016 |
Drugowitsch J. Fast and accurate Monte Carlo sampling of first-passage times from Wiener diffusion models. Scientific Reports. 6: 20490. PMID 26864391 DOI: 10.1038/Srep20490 |
0.321 |
|
2015 |
Moreno-Bote R, Drugowitsch J. Causal Inference and Explaining Away in a Spiking Network. Scientific Reports. 5: 17531. PMID 26621426 DOI: 10.1038/Srep17531 |
0.644 |
|
2015 |
Drugowitsch J, DeAngelis GC, Angelaki DE, Pouget A. Tuning the speed-accuracy trade-off to maximize reward rate in multisensory decision-making. Elife. 4. PMID 26090907 DOI: 10.7554/Elife.06678 |
0.783 |
|
2015 |
Kneissler J, Drugowitsch J, Friston K, Butz MV. Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering. Frontiers in Computational Neuroscience. 9: 47. PMID 25983690 DOI: 10.3389/Fncom.2015.00047 |
0.327 |
|
2015 |
Drugowitsch J, DeAngelis GC, Angelaki DE, Pouget A. Author response: Tuning the speed-accuracy trade-off to maximize reward rate in multisensory decision-making Elife. DOI: 10.7554/Elife.06678.007 |
0.766 |
|
2014 |
Drugowitsch J, DeAngelis GC, Klier EM, Angelaki DE, Pouget A. Optimal multisensory decision-making in a reaction-time task. Elife. 3. PMID 24929965 DOI: 10.7554/Elife.03005 |
0.768 |
|
2014 |
Drugowitsch J, Moreno-Bote R, Pouget A. Relation between belief and performance in perceptual decision making. Plos One. 9: e96511. PMID 24816801 DOI: 10.1371/Journal.Pone.0096511 |
0.812 |
|
2014 |
Drugowitsch J, DeAngelis GC, Klier EM, Angelaki DE, Pouget A. Author response: Optimal multisensory decision-making in a reaction-time task Elife. DOI: 10.7554/Elife.03005.018 |
0.769 |
|
2014 |
Drugowitsch J, Moreno-Bote R, Pouget A. Optimal decision-making with time-varying evidence reliability Advances in Neural Information Processing Systems. 1: 748-756. |
0.823 |
|
2013 |
Arandia-Romero I, Drugowitsch J, Kohn A, Moreno-Bote R. Spontaneous population activity fluctuations boost sensory tuning curves and gate information processing Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P281 |
0.648 |
|
2013 |
Nogueira R, Drugowitsch J, Navarra J, Moreno-Bote R. Trial by trial decoding of decisions in monkey MT cortex from small neuronal populations Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P280 |
0.749 |
|
2012 |
Drugowitsch J, Pouget A. Probabilistic vs. non-probabilistic approaches to the neurobiology of perceptual decision-making. Current Opinion in Neurobiology. 22: 963-9. PMID 22884815 DOI: 10.1016/J.Conb.2012.07.007 |
0.8 |
|
2012 |
Drugowitsch J, Moreno-Bote R, Churchland AK, Shadlen MN, Pouget A. The cost of accumulating evidence in perceptual decision making. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 32: 3612-28. PMID 22423085 DOI: 10.1523/Jneurosci.4010-11.2012 |
0.803 |
|
2011 |
Drugowitsch J, Pouget A, DeAngelis GC, Angelaki DE. Maximizing decision rate in multisensory integration Nature Precedings. DOI: 10.1038/Npre.2011.5822.1 |
0.753 |
|
2011 |
Drugowitsch J, Moreno-Bote R, Pouget A. Optimal decision bounds for probabilistic population codes and time varying evidence Nature Precedings. DOI: 10.1038/Npre.2011.5821.1 |
0.806 |
|
2010 |
Drugowitsch J, Pouget A. Quick thinking: perceiving in a tenth of a blink of an eye. Nature Neuroscience. 13: 279-80. PMID 20177419 DOI: 10.1038/Nn0310-279 |
0.76 |
|
2008 |
Drugowitsch J, Barry AM. A formal framework and extensions for function approximation in learning classifier systems Machine Learning. 70: 45-88. DOI: 10.1007/S10994-007-5024-8 |
0.324 |
|
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