Modulation of cortical activity by spherical blur and its correlation with retinal defocus.

Cortical activity, as recorded via electroencephalography, has been linked to the refractive error of an individual. It is however unclear which optical metric modulates this response. Here, we measured simultaneously the brain activity and the retinal defocus of a visual stimulus perceived through several values of spherical blur.

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 on species, anesthesia, and external stimulation. The average population firing rate in these states is typically low. We study analytically and numerically a network of sparsely connected excitatory and inhibitory integrate-and-fire neurons in the inhibition-dominated, low firing rate regime.

What to Choose Next? A Paradigm for Testing Human Sequential Decision Making.

Many of the decisions we make in our everyday lives are sequential and entail sparse rewards. While sequential decision-making has been extensively investigated in theory (e.g.

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 visual experiences. However, learning can occur even when no stimuli are presented at all.

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. Computational and behavioral studies of RL have focused mainly on Markovian decision processes, where the next state depends on only the current state and action.

Modulation of network excitability by persistent activity: how working memory affects the response to incoming stimuli.

Persistent activity and match effects are widely regarded as neuronal correlates of short-term storage and manipulation of information, with the first serving active maintenance and the latter supporting the comparison between memory contents and incoming sensory information. The mechanistic and functional relationship between these two basic neurophysiological signatures of working memory remains elusive. We propose that match signals are generated as a result of transient changes in local network excitability brought about by persistent activity.

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 as priming. In spite of the large body of knowledge accumulated in behavioral studies about the conditions conducive to priming, and its relationship with other forms of memory, the underlying neuronal correlates of priming are still under debate. The idea has repeatedly been advanced that a major neuronal mechanism supporting behaviorally-expressed priming is repetition suppression, a widespread reduction of spiking activity upon stimulus repetition which has been routinely exposed by single-unit recordings in non-human primates performing delayed-response, as well as passive fixation tasks.

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 image in our mind. However, such discoveries are not "really" new but just new "interpretations.

Perceptual learning of motion discrimination by mental imagery.

Perceptual learning can occur when stimuli are only imagined, i.e., without proper stimulus presentation.

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 studies [1-12] suggest that such improvements of performance are accomplished by neural synaptic changes driven by the repetitive presentation of stimuli.

Anesthesia prevents auditory perceptual learning.

Background: An auditory perceptual learning paradigm was used to investigate whether implicit memories are formed during general anesthesia.

Methods: Eighty-seven patients who had an American Society of Anesthesiologists physical status of I-III and were scheduled to undergo an elective surgery with general anesthesia were randomly assigned to one of two groups. One group received auditory stimulation during surgery, whereas the other did not.

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 the number of stimulus presentations constant while varying the number of trials per session. We show that a minimal number of stimulus presentations per session is necessary, transfer depends strongly on the presentation regime, but sleep has only weak, if at all, effects.

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 more types of stimuli are presented randomly interleaved, for example, a bisection stimulus and a vernier. For some combinations of stimulus types, performance improves in roving situations whereas for others it does not.