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Perceptual learning with Chevrons requires a minimal number of trials, transfers to untrained directions, but does not require sleep
In most models of perceptual learning, the amount of improvement of performance does not depend on the regime of stimulus presentations, but only on the sheer number of trials. Here, we kept theExpand
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Human Perceptual Learning by Mental Imagery
Perceptual learning is learning to perceive. For example, a radiologist is able to easily identify anomalies in medical images only after extended training. Theoretical and psychophysical studiesExpand
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Perceptual learning and roving: Stimulus types and overlapping neural populations
In perceptual learning, performance usually improves when observers train with one type of stimulus, for example, a bisection stimulus. Roving denotes the situation when, instead of one, two or moreExpand
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On the relationship between persistent delay activity, repetition enhancement and priming
Human efficiency in processing incoming stimuli (in terms of speed and/or accuracy) is typically enhanced by previous exposure to the same, or closely related stimuli—a phenomenon referred to asExpand
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New Percepts via Mental Imagery?
We are able to extract detailed information from mental images that we were not explicitly aware of during encoding. For example, we can discover a new figure when we rotate a previously seen imageExpand
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What to Choose Next? A Paradigm for Testing Human Sequential Decision Making
TLDR
We investigate key components of reinforcement learning models: the eligibility trace (i.e., the memory trace of previous decision steps), the external reward, and the ability to exploit the statistics of the environment. Expand
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Linking perceptual learning with identical stimuli to imagery perceptual learning.
Perceptual learning is usually thought to be exclusively driven by the stimuli presented during training (and the underlying synaptic learning rules). In some way, we are slaves of our visualExpand
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Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons
Electrophysiological recordings in cortex in vivo have revealed a rich variety of dynamical regimes ranging from irregular asynchronous states to a diversity of synchronized states, depending onExpand
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Perceptual learning of motion discrimination by mental imagery.
Perceptual learning can occur when stimuli are only imagined, i.e., without proper stimulus presentation. For example, perceptual learning improved bisection discrimination when only the two outerExpand
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Human and Machine Learning in Non-Markovian Decision Making
Humans can learn under a wide variety of feedback conditions. Reinforcement learning (RL), where a series of rewarded decisions must be made, is a particularly important type of learning.Expand
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