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Statistical treatment of looking-time data.Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment.Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentialsStatistically optimal perception and learning: from behavior to neural representationsOptimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3.Computational theories on the function of theta oscillations.The Hamiltonian Brain: Efficient Probabilistic Inference with Excitatory-Inhibitory Neural Circuit DynamicsBayesian learning of visual chunks by human observers.Goal-Directed Decision Making with Spiking Neurons.Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.Neural Variability and Sampling-Based Probabilistic Representations in the Visual Cortex.Cognitive tomography reveals complex, task-independent mental representations.Active sensing in the categorization of visual patterns.Correction: Active sensing in the categorization of visual patterns.Dynamically detuned oscillations account for the coupled rate and temporal code of place cell firing.Theta-modulated feedforward network generates rate and phase coded firing in the entorhino-hippocampal system.Theta oscillation-coupled dendritic spiking integrates inputs on a long time scale.Matching storage and recall: hippocampal spike timing-dependent plasticity and phase response curves.With or without you: predictive coding and Bayesian inference in the brain.Properties of a random attachment growing network.The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability.Theoretical perspectives on active sensingThe Redemption of Noise: Inference with Neural PopulationsGlobal and Multiplexed Dendritic Computations under In Vivo-like ConditionsUnimodal statistical learning produces multimodal object-like representationsMulticompartmental modeling of hippocampal pyramidal cells and interneurons with the GENESIS software toolPhase coding: spikes get a boost from local fieldsRepresentational untangling by the firing rate nonlinearity in V1 simple cells
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P50
description
hulumtues
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researcher
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wetenschapper
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հետազոտող
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name
Mate Lengyel
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Mate Lengyel
@en
Mate Lengyel
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Mate Lengyel
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Mate Lengyel
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type
label
Mate Lengyel
@ast
Mate Lengyel
@en
Mate Lengyel
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Mate Lengyel
@nl
Mate Lengyel
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prefLabel
Mate Lengyel
@ast
Mate Lengyel
@en
Mate Lengyel
@es
Mate Lengyel
@nl
Mate Lengyel
@sl
P106
P1153
7006336372
P21
P2456
P31
P496
0000-0001-7266-0049