Binocular disparity-based learning is retinotopically specific and independent of sleep

Sequence-specific delayed gains in motor fluency evolve after movement observation training in the absence of early sleep

Following physical practice, delayed, consolidation-phase, gains in the performance of the trained finger-to-thumb opposition sequence (FOS) can be expressed, in young adults, only after a sleep interval is afforded. These delayed gains are order-of-movements specific. However, in several perceptual learning tasks, time post-learning, rather than an interval of sleep, may suffice for the expression of delayed performance gains. Here we tested whether the affordance of a sleep interval is necessary for the expression of delayed performance gains after FOS training by repeated observation. Participants were trained by observing videos displaying a left hand repeatedly performing a 5-element FOS. To assess post-session observation-related learning and delayed gains participants were tested in performing the observed (trained) and an unobserved (new, the 5-elements mirror-reversed) FOS sequences. Repeated observation of a FOS conferred no advantage to its performance, compared to the unobserved FOS, immediately after practice. However, a clear advantage for the observed FOS emerged by 12 h post-training, irrespective of whether this interval included sleep or not; the largest gains appeared by 24 h post-training. These results indicate that time-dependent, offline consolidation processes take place after observation training even in the absence of sleep; akin to perceptual learning rather than physical FOS practice.

Sleep affects higher-level categorization of speech sounds, but not frequency encoding

Sleep can increase consolidation of new knowledge and skills. It is less clear whether sleep plays a role in other aspects of experience-dependent neuroplasticity, which underlie important human capabilities such as spoken language processing. Theories of sensory learning differ in their predictions; some imply rapid learning at early sensory levels, while other propose a slow, progressive timecourse such that higher-level categorical representations guide immediate, novice learning, while lower-level sensory changes do not emerge until later stages. In this study, we investigated the role of sleep across both behavioural and physiological indices of auditory neuroplasticity. Forty healthy young human adults (23 female) who did not speak a tonal language participated in the study. They learned to categorize non-native Mandarin lexical tones using a sound-to-category training paradigm, and were then randomly assigned to a Nap or Wake condition. Polysomnographic data were recorded to quantify sleep during a 3 h afternoon nap opportunity, or equivalent period of quiet wakeful activity. Measures of behavioural performance accuracy revealed a significant improvement in learning the sound-to-category training paradigm between Nap and Wake groups. Conversely, a neural index of fine sound encoding fidelity of speech sounds known as the frequency-following response (FFR) suggested no change due to sleep, and a null model was supported, using Bayesian statistics. Together, these results support theories that propose a slow, progressive and hierarchical timecourse for sensory learning. Sleep's effect may play the biggest role in the higher-level learning, although contributions to more protracted processes of plasticity that exceed the study duration cannot be ruled out.

The Birth of the Mammalian Sleep

Simple Summary

Mammals evolved from reptiles as a consequence of an evolutionary bottleneck. Some diurnal reptiles extended their activity, first to twilight and then to the entire dark time. This forced the change of the visual system. Pursuing maximal sensitivity, they abandoned the filters protecting the eyes against the dangerous diurnal light, which, in turn, forced immobility in lightproof burrows during light time. This was the birth of the mammalian sleep. Then, the Cretacic-Paleogene extinction of dinosaurs leaved free the diurnal niche and allowed the expansion of a few early mammals to diurnal life and the high variability of sleep traits. On the other hand, we propose that the idling rest is a state showing homeostatic regulation. Therefore, the difference between behavioral rest and wakeful idling is rather low: both show quiescence, raised sensory thresholds, reversibility, specific sleeping-resting sites and body positions, it is a pleasing state, and both are dependent of circadian and homeostatic regulation. Indeed, the most important difference is the unconsciousness of sleep and the consciousness of wakeful idling. Thus, we propose that sleep is a mere upgrade of the wakeful rest, and both may have the same function: guaranteeing rest during a part of the daily cycle.

Abstract

Mammals evolved from small-sized reptiles that developed endothermic metabolism. This allowed filling the nocturnal niche. They traded-off visual acuity for sensitivity but became defenseless against the dangerous daylight. To avoid such danger, they rested with closed eyes in lightproof burrows during light-time. This was the birth of the mammalian sleep, the main finding of this report. Improved audition and olfaction counterweighed the visual impairments and facilitated the cortical development. This process is called “The Nocturnal Evolutionary Bottleneck”. Pre-mammals were nocturnal until the Cretacic-Paleogene extinction of dinosaurs. Some early mammals returned to diurnal activity, and this allowed the high variability in sleeping patterns observed today. The traits of Waking Idleness are almost identical to those of behavioral sleep, including homeostatic regulation. This is another important finding of this report. In summary, behavioral sleep seems to be an upgrade of Waking Idleness Indeed, the trait that never fails to show is quiescence. We conclude that the main function of sleep consists in guaranteeing it during a part of the daily cycle.

Sleep does not aid the generalisation of binocular disparity-based learning to the other visual hemifield

Visual perceptual learning refers to long-lasting performance improvements on a visual skill - an ability supported by plastic changes in early visual brain areas. Visual perceptual learning has been shown to be induced by training and to benefit from consolidation during sleep, presumably via the reactivation of learning-associated neuronal firing patterns. However, previous studies have almost exclusively relied on a single paradigm, the texture discrimination task, on which performance improvements may rely on higher-order rather than lower-level perceptual skills. In the present study, we tested whether sleep has beneficial effects on a visual disparity discrimination task. We confirm previous findings in showing that the ability to discriminate different disparities is unaffected by sleep during a 12-hr retention period after training. Importantly, we extend these results by providing evidence against an effect of sleep on the generalisation of improved disparity discrimination across the vertical meridian. By relying on a between-subject design, we further exclude carry-over effects as a possible confound present in previous findings. These data argue against sleep as an important factor in the consolidation of a low-level perceptual skill. This sets important constraints on models of the role of sleep and sleep-associated neural reactivation in the consolidation of non-declarative memories.

Memories replayed: reactivating past successes and new dilemmas

Our experiences continue to be processed 'offline' in the ensuing hours of both wakefulness and sleep. During these different brain states, the memory formed during our experience is replayed or reactivated. Here, we discuss the unique challenges in studying offline reactivation, the growth in both the experimental and analytical techniques available across different animals from rodents to humans to capture these offline events, the important challenges this innovation has brought, our still modest understanding of how reactivation drives diverse synaptic changes across circuits, and how these changes differ (if at all), and perhaps complement, those at memory formation. Together, these discussions highlight critical emerging issues vital for identifying how reactivation affects circuits, and, in turn, behaviour, and provides a broader context for the contributions in this special issue. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.