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Censor, N.

Publications and source records attributed to Censor, N..

3 recordsLinked to original sources

Context-dependent benefits of training and reminders in visual skill learning

Previous studies using a visual texture discrimination task (TDT) have demonstrated that performance enhancements resulting from extensive daily training (full training condition) remained intact after replacing all training, except for the first and last session, with a few daily reminder trials (reminder condition). Omitting reminders (control condition) yielded only limited learning, supporting their crucial contribution. We first confirmed these findings and excluded gaze position differences among conditions as a contributing factor. Next, we tested whether the reminders effectiveness is specific to a context of limited attention to the peripheral target caused by simultaneously performing a demanding fixation task. Removing the fixation task yielded performance levels in the first session matching those normally reached after lengthy daily training, suggesting that learning in the standard TDT involves the redeployment of attention. After changing texture parameters to increase the difficulty of the task, performing the TDT without a fixation task yielded learning in all three conditions. This indicates that in a dual-task, reminders can produce learning outcomes comparable to full training. In contrast, when the TDT is performed with full attention to the target, consolidation of the initial session alone can yield improvements equivalent to those observed in reminder and full training conditions.

neuroscience↗

Unconscious switching of dorsal and medial pathways for plasticity and stability during NREM and REM sleep

While visual perceptual learning improves during non-REM sleep and stabilizes during REM sleep via excitatory-inhibitory neurotransmitter (E/I) balance in early visual areas (EVA), the role of prefrontal regions remains unclear. Here, we show that contributions of the dorsolateral prefrontal cortex (DLPFC) and medial prefrontal cortex (mPFC) differ by sleep stage in human adults. During non-REM sleep, plasticity increased in DLPFC--indexed by elevated E/I balance measured with magnetic resonance spectroscopy and polysomnography--in correlation with performance gains. During REM sleep, stability increased in mPFC--indexed by reduced E/I balance--in correlation with resilience to retrograde interference from new learning. E/I balance changes and their effects on learning paralleled those in EVA. Connectivity weights between EVA and DLPFC, and between EVA and mPFC, switched with sleep stage. These findings suggest the presence of dorsal and medial pathways that unconsciously alternate between non-REM sleep and REM sleep to improve and stabilize learning.

neuroscience↗

Predicting individual skill learning, a cautionary tale

People show vast variability in skill learning. What determines a persons individual learning ability? In this study we explored the possibility to predict participants future learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We trained machine learning models to predict future skill learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. While the models did not explain learning, strong correlations were observed between initial and final performance. In addition, the results suggest that in correspondence with other empirical fields testing human behavior, canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, relevant for real-life scenarios. Overall, implementing machine learning tools on large-scale data sets may provide a powerful approach towards revealing what differentiates between high and low innate learning abilities, paving the way for learning optimization techniques which may generalize beyond motor skill learning to broad learning abilities.

neuroscience↗