Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

https://www.zora.uzh.ch/id/eprint/77770/1/physiol_rev_93.pdf

About sleep's role in memory

Visual input often arrives in a noisy and discontinuous stream, owing to head and eye movements, occlusion, lighting changes, and many other factors. Yet the physical world is generally stable; objects and physical characteristics rarely change spontaneously. How then does the human visual system capitalize on continuity in the physical environment over time? We found that visual perception in humans is serially dependent, using both prior and present input to inform perception at the present moment. Using an orientation judgment task, we found that, even when visual input changed randomly over time, perceived orientation was strongly and systematically biased toward recently seen stimuli. Furthermore, the strength of this bias was modulated by attention and tuned to the spatial and temporal proximity of successive stimuli. These results reveal a serial dependence in perception characterized by a spatiotemporally tuned, orientation-selective operator-which we call a continuity field-that may promote visual stability over time.

/pdf/serial-dependence-in-visual-perception-42od2fyv33.pdf

Serial dependence in visual perception.

Our environment contains regularities distributed in space and time that can be detected by way of statistical learning. This unsupervised learning occurs without intent or awareness, but little is known about how it relates to other types of learning, how it affects perceptual processing, and how quickly it can occur. Here we use fMRI during statistical learning to explore these questions. Participants viewed statistically structured versus unstructured sequences of shapes while performing a task unrelated to the structure. Robust neural responses to statistical structure were observed, and these responses were notable in four ways: First, responses to structure were observed in the striatum and medial temporal lobe, suggesting that statistical learning may be related to other forms of associative learning and relational memory. Second, statistical regularities yielded greater activation in category-specific visual regions (object-selective lateral occipital cortex and word-selective ventral occipito-temporal cortex), demonstrating that these regions are sensitive to information distributed in time. Third, evidence of learning emerged early during familiarization, showing that statistical learning can operate very quickly and with little exposure. Finally, neural signatures of learning were dissociable from subsequent explicit familiarity, suggesting that learning can occur in the absence of awareness. Overall, our findings help elucidate the underlying nature of statistical learning.

/pdf/neural-evidence-of-statistical-learning-efficient-detection-21zv74jkpb.pdf

Neural evidence of statistical learning: Efficient detection of visual regularities without awareness

It is controversial whether the adult primate early visual cortex is sufficiently plastic to cause visual perceptual learning (VPL). The controversy occurs partially because most VPL studies have examined correlations between behavioral and neural activity changes rather than cause-and-effect relationships. With an online-feedback method that uses decoded functional magnetic resonance imaging (fMRI) signals, we induced activity patterns only in early visual cortex corresponding to an orientation without stimulus presentation or participants' awareness of what was to be learned. The induced activation caused VPL specific to the orientation. These results suggest that early visual areas are so plastic that mere inductions of activity patterns are sufficient to cause VPL. This technique can induce plasticity in a highly selective manner, potentially leading to powerful training and rehabilitative protocols.

/pdf/perceptual-learning-incepted-by-decoded-fmri-neurofeedback-25p8qbu6w8.pdf

Perceptual Learning Incepted by Decoded fMRI Neurofeedback Without Stimulus Presentation

Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.

https://science.sciencemag.org/content/sci/340/6132/639.full.pdf

Neural Decoding of Visual Imagery During Sleep

Visual perceptual learning (VPL) is defined as a long-term improvement in performance on a visual task. In recent years, the idea that conscious effort is necessary for VPL to occur has been challenged by research suggesting the involvement of more implicit processing mechanisms, such as reinforcement-driven processing and consolidation. In addition, we have learnt much about the neural substrates of VPL and it has become evident that changes in visual areas and regions beyond the visual cortex can take place during VPL.

/pdf/advances-in-visual-perceptual-learning-and-plasticity-2h0tjonkfo.pdf

Advances in visual perceptual learning and plasticity

https://authors.library.caltech.edu/15362/1/Yotsumoto2009p5716Curr_Biol.pdf

Location-specific cortical activation changes during sleep after training for perceptual learning

Critical flicker fusion thresholds (CFFT) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases. The threshold at which CFF occurs has been shown to remain constant under repeated testing. Additionally, CFF thresholds are correlated with various measures of intelligence, and have been regarded by clinicians as a general measure of cortical processing capacity. For these reasons, CFF is used as a cognitive indicator in drug studies, as a measure of fatigue, and has been suggested as a diagnostic measure for various brain diseases. Here we report that CFFT increases dramatically in subjects who are trained with a motion-direction learning procedure. Control tasks demonstrate that CFFT changes are tightly coupled with improvements in discriminating the direction of motion stimuli, and are likely related to plasticity in low-level visual areas that are specialized to process motion signals. This plasticity is long-lasting and is retained for at least one year after training. Combined, these results show that CFFT relates to a specialized sensory process and bring into question that CFFT is a measure of high-level, or general, processes.

/pdf/perceptual-learning-of-motion-leads-to-faster-flicker-x2gzwdnerg.pdf

Perceptual learning of motion leads to faster-flicker perception

Visual perceptual learning (VPL) is defined as visual performance improvement after visual experiences. VPL is often highly specific for a visual feature presented during training. Such specificity is observed in behavioral tuning function changes with the highest improvement centered on the trained feature and was originally thought to be evidence for changes in the early visual system associated with VPL. However, results of neurophysiological studies have been highly controversial concerning whether the plasticity underlying VPL occurs within the visual cortex. The controversy may be partially due to the lack of observation of neural tuning function changes in multiple visual areas in association with VPL. Here using human subjects we systematically compared behavioral tuning function changes after global motion detection training with decoded tuning function changes for 8 visual areas using pattern classification analysis on functional magnetic resonance imaging (fMRI) signals. We found that the behavioral tuning function changes were extremely highly correlated to decoded tuning function changes only in V3A, which is known to be highly responsive to global motion with human subjects. We conclude that VPL of a global motion detection task involves plasticity in a specific visual cortical area.

/pdf/decoding-reveals-plasticity-in-v3a-as-a-result-of-motion-1mtv4p9f35.pdf

Decoding Reveals Plasticity in V3A as a Result of Motion Perceptual Learning

In the United States, approximately 7% to 10% of children are raised in bilingual households. Despite inherent advantages to bilingualism, some bilingual children experience a significant lag in academic success relative to other groups. Bridging the fields of cognitive psychology and education, this volume presents research-based knowledge on language acquisition and learning to leverage the strengths and achievements of bilingual children. By understanding the neurocognitive mechanisms of the bilingual brain and the need for socioculturally inclusive pedagogy, educational researchers and practitioners can better serve this rapidly growing population.

José E. Náñez

Papers

Advances in visual perceptual learning and plasticity

Location-specific cortical activation changes during sleep after training for perceptual learning

Perceptual learning of motion leads to faster-flicker perception

Decoding Reveals Plasticity in V3A as a Result of Motion Perceptual Learning

Bilingualism and Cognition: Informing Research, Pedagogy, and Policy.