Mate Lengyel, Ph.D.
Affiliations: | Engineering | University of Cambridge, Cambridge, England, United Kingdom |
Area:
computational neuroscienceWebsite:
http://www.eng.cam.ac.uk/~m.lengyelGoogle:
"Mate Lengyel"Mean distance: 13.22 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentor| Peter Erdi | grad student | 2000-2003 | Eötvös Loránd University |
| Peter Dayan | post-doc | UCL |
Children
Sign in to add trainee| Jeroen Olieslagers | research assistant | 2020-2021 | Cambridge |
| Nikon A. Rasumov | grad student | 2008-2011 | Cambridge |
| David GT Barrett | post-doc | Cambridge | |
| Jake Patrick Stroud | post-doc | ||
| Marcelo Gomes Mattar | post-doc | 2016- | Cambridge |
| Yul H R Kang | post-doc | 2018-2022 | Cambridge |
BETA: Related publications
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Publications
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| Stroud JP, Duncan J, Lengyel M. (2024) The computational foundations of dynamic coding in working memory. Trends in Cognitive Sciences |
| Stroud JP, Watanabe K, Suzuki T, et al. (2023) Optimal information loading into working memory explains dynamic coding in the prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America. 120: e2307991120 |
| Mattar MG, Lengyel M. (2022) Planning in the brain. Neuron |
| Echeveste R, Aitchison L, Hennequin G, et al. (2020) Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference. Nature Neuroscience |
| Gáspár ME, Polack PO, Golshani P, et al. (2019) Representational untangling by the firing rate nonlinearity in V1 simple cells. Elife. 8 |
| Ujfalussy BB, Makara JK, Lengyel M, et al. (2018) Global and Multiplexed Dendritic Computations under In Vivo-like Conditions. Neuron. 100: 579-592.e5 |
| Hennequin G, Ahmadian Y, Rubin DB, et al. (2018) The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability. Neuron. 98: 846-860.e5 |
| Aitchison L, Lengyel M. (2017) With or without you: predictive coding and Bayesian inference in the brain. Current Opinion in Neurobiology. 46: 219-227 |
| Aitchison L, Lengyel M. (2016) The Hamiltonian Brain: Efficient Probabilistic Inference with Excitatory-Inhibitory Neural Circuit Dynamics. Plos Computational Biology. 12: e1005186 |
| Orbán G, Berkes P, Fiser J, et al. (2016) Neural Variability and Sampling-Based Probabilistic Representations in the Visual Cortex. Neuron. 92: 530-543 |