Yuka Sasaki

The paper dissociates reward's physiological effects into value-independent arousal and value-dependent reinforcement using pupil dilation and EEG measurements.

The paper shows that task-irrelevant natural scenes induce visual perceptual learning through unsupervised learning, which is not suppressed by attention, unlike artificial stimuli.

The paper validates EEG-based E/I ratio algorithms against MRS-derived glutamate/GABA ratios, finding strong between-subject associations but weak within-subject ones.

The paper shows that during non-REM sleep, plasticity increases in the DLPFC, while during REM sleep, stability increases in the mPFC, both related to E/I balance changes and learning outcomes.

The paper shows that reduced glutamate levels, an excitatory neurotransmitter, are associated with better sleep onset in humans, while GABA levels remain stable.

The paper shows the first-night effect reduces sleep's benefit on visual plasticity and alters neurochemical processes during sleep.

The paper compares neuronal mechanisms of learning a visual task between patients with body dysmorphic disorder and healthy individuals, finding substantial differences in brain activation patterns.

This study investigates how the geometric relationship between trained and untrained locations affects visual perceptual learning transfer, finding significant transfer occurs diagonally or along a line through the fixation point.

The paper investigates the role of midbrain and cortical prediction error signals in visual perceptual learning, finding that only cortical signals contribute to performance improvement.

Children learn more efficiently than adults due to faster stabilization of learning with rapid GABA boosting after training.

This study uses DecNef to show that unconscious exposure-based visual perceptual learning occurs in V1/V2 without conscious perception of motion.

This study shows that sleep-dependent gains in visual perceptual learning are better explained by a learning-dependent model than a use-dependent model.

This study shows that reward during training interacts with sleep to enhance visual perceptual learning offline performance gains.

This study investigates whether REM sleep exhibits a night-watch system similar to NREM sleep during the first-night effect, finding increased vigilance in both hemispheres during REM's phasic period.

This study shows that offline performance gains in visual perceptual learning occur for an orientation detection task, with gains specific to the trained feature and linked to sigma activity during sleep.

This study investigates how reward influences visual perceptual learning by testing whether reward before or after stimulus presentation enhances learning.

This study investigates temporal perceptual learning by comparing fixed and random interval training, finding task-specific improvements without generalization.

This study shows that providing both correctness and location feedback during training enhances perceptual learning for detecting mammographic lesions, which is retained six months later.

The paper measures neurochemical balance during sleep stages and finds NREM sleep increases plasticity for performance gains while REM sleep stabilizes learning post-training.

The paper tests the hypothesis that long-term potentiation (LTP) competition causes interference in consecutive visual learning tasks and finds that disrupting LTP in the visual cortex reduces interference.

The paper shows that specific visual features, like Gabor orientation, are reactivated in human V1 after visual training, and this reactivation correlates with performance improvement.