Computational Learning and Memory Group

Publications

Contextual inference in learning and memory
Heald JB, Lengyel M* and Wolpert DM*
Trends in Cognitive Sciences, 2022
Planning in the brain
Mattar MG and Lengyel M
Neuron, 2022
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Adaptive erasure of spurious sequences in sensory cortical circuits
Bernacchia A, Fiser J, Hennequin G* and Lengyel M*
Neuron, 2022
Representations of uncertainty: where art thou?
Koblinger Á, Fiser J and Lengyel M
Current Opinion in Behavioral Sciences, 2021
A universal probabilistic spike count model reveals ongoing modulations of neural variability
Liu D and Lengyel M
Advances in Neural Information Processing Systems, 2021
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Contextual inference underlies the learning of sensorimotor repertoires
Heald JB, Lengyel M* and Wolpert DM*
Nature, 2021
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Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference
Echeveste R, Aitchison L, Hennequin G* and Lengyel M*
Nature Neuroscience, 2020
Unimodal statistical learning produces multimodal object-like representations
Lengyel G, Žalalytė G, Pantelides A, Ingram J, Fiser J*, Lengyel M* and Wolpert DM*
eLife, 2019
Representational untangling by the firing rate nonlinearity in V1 simple cells
Gáspár ME, Polack P-O, Golshani P, Lengyel M and Orbán G
eLife, 2019
Editorial overview: Computational neuroscience
Doiron B and Lengyel M
Current Opinion in Neurobiology, 2019
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Global and multiplexed dendritic computations under in vivo-like conditions.
Ujfalussy B, Makara JK, Lengyel M* and Branco T*
Neuron, 2018
The redemption of noise: inference with neural populations
Echeveste R and Lengyel M
Trends in Neurosciences, 2018
Exact natural gradient in deep linear networks and application to the nonlinear case
Bernacchia A, Lengyel M and Hennequin G
Advances in Neural Information Processing Systems, 2018
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability
Aitchison L, Hennequin G and Lengyel M
arXiv, 2018
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The dynamical regime of sensory cortex: stable dynamics around a single stimulus-tuned attractor account for patterns of noise variability
Hennequin G, Ahmadian Y*, Rubin DB*, Lengyel MŦ and Miller KDŦ
Neuron, 2018
With or without you: predictive coding and Bayesian inference in the brain
Aitchison L and Lengyel M
Current Opinion in Neurobiology, 2017
Asymptotic scaling properties of the posterior mean and variance in the Gaussian scale mixture model
Echeveste R, Hennequin G and Lengyel M
arXiv, 2017
Goal-directed decision making with spiking neurons
Friedrich J and Lengyel M
Journal of Neuroscience, 2016
Statistical treatment of looking-time data
Csibra G, Hernik M, Mascaro O, Tatone D and Lengyel M
Developmental Psychology, 2016
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Active sensing in the categorization of visual patterns
Yang S-CH, Lengyel M* and Wolpert DM*
eLife, 2016
Theoretical perspectives on active sensing
Yang S-CH, Wolpert DM* and Lengyel M*
Current Opinion in Behavioural Sciences, 2016
Efficient state-space modularization for planning: theory, behavioral and neural signatures
McNamee D, Wolpert DM and Lengyel M
Advances in Neural Information Processing Systems, 2016
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Neural variability and sampling-based probabilistic representations in the visual cortex
Orbán G, Berkes P, Fiser J and Lengyel M
Neuron 92:530-543, 2016
The Hamiltonian brain: efficient probabilistic inference with excitatory-inhibitory neural circuit dynamics
Aitchison L and Lengyel M
PLoS Computational Biology, 2016
Characterizing variability in nonlinear recurrent neuronal networks
Hennequin G and Lengyel M
arXiv, 2016
On the role of time in perceptual decision making
Lengyel M, Koblinger Á, Popović M and Fiser J
arXiv, 2015
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Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits
Ujfalussy B, Makara JK, Branco T and Lengyel M
eLife, 2015
Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3
Savin C, Dayan P and Lengyel M
PLoS Computational Biology, 2014
The Hamiltonian brain
Aitchison L and Lengyel M
arXiv, 2014
A dual algorithm for olfactory computation in the locust brain
Tootoonian S and Lengyel M
Advances in Neural Information Processing Systems, 2014
Analog memories in a balanced rate-based network of E/I neurons
Festa D, Hennequin G and Lengyel M
Advances in Neural Information Processing Systems, 2014
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Fast sampling-based inference in balanced neuronal networks
Hennequin G, Aitchison L and Lengyel M
Advances in Neural Information Processing Systems, 2014
How (not) to assess the importance of correlations for the matching of spontaneous and evoked activity
Fiser J, Lengyel M, Savin C, Orbán G and Berkes P
arXiv, 2013
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Cognitive tomography reveals complex, task-independent mental representations
Houlsby NMT#, Huszár F#, Ghassemi MM, Orbán G, Wolpert DM* and Lengyel M*
Current Biology, 2013
Correlations strike back (again): the case of associative memory retrieval
Savin C, Dayan P and Lengyel M
Advances in Neural Information Processing Systems, 2013
Remme MWH, Lengyel M, Gutkin BS
Remme MWH, Lengyel M and Gutkin BS
In: Phase response curves in neuroscience: theory, experiment, and analysis (eds. NW Schultheis, AA Prinz, RJ Butera), Springer, 2012