The following small review adds more information on the previous article (a briefly modified extract from my master’s dissertation you can find here) about the role of sleep in learning and generalization. Here you can find more detailed and less summarized technical information about the subject.
As mentioned in the previous essay linked above, sleep has been considered a way in which the brain strengthens memory consolidation after a period of learning (Ekstrand, 1967; Fishbein, 1971; Yaroush, Sullivan & Ekstrand, 1971). Particularly, the recall of episodic memories has proven to be better after sleep as compared to the retention obtained after a period of wakefulness (Plihal & Born, 1997; Ellenbogen et al., 2009). The active system consolidation hypothesis, states that spontaneous reactivations of recently acquired memories during sleep contribute to their reorganization and integration into long-term memory networks, gradually losing their dependence on the hippocampus and parahippocampal structures and relaying more on the neocortex (Wilson & Mcnaughton, 1994; Skaggs & Mcnaughton, 1996; Peigneuxet al., 2004; Frankland & Bontempi, 2005; Diekelmann & Born, 2010).
It is commonly believed that this acquisition of declarative memories is underpinned by gradual changes in neocortical structures (Atir-Sharon, Gilboa, Hazan, Koilis & Manevitz, 2015). Recently however, it has been found that fast mapping (FM) learning, could facilitate rapid learning-induced cortical plasticity. FM involves inferring the meaning of new words and concepts, by which durable novel associations are incidentally formed. This process is thought to support early childhood’s exuberant learning (Atir-Sharon et al., 2015).
Another process linked to memory and sleep is generalization. This refers to a broad array of phenomena whereby past experience can be applied to novel settings (Kumaran, 2012). According to Censor (2013), generalization patterns are affected by the way in which the original memory is encoded and consolidated. They could be facilitated during fast learning, with possible engagement of higher-order brain areas recurrently interacting with the primary visual or motor cortices encoding the stimuli or movements memories.
A question arises then as to how can we consolidate a slow process of learning with the rapid effects seen by FM. An important point to consider in this case is that information that relates to a prior knowledge schema is remembered better and consolidates more rapidly than information that does not (Hennies, Ralph, Kempkes, Cousins, & Lewis, 2016). In accordance with this, in a study by Cairney, Durrant, Musgrove, and Lewis (2011), participants first established a schema over 2 weeks and next they encoded new facts, which were either related to the schema or completely unrelated. After a 24h retention interval, including a night of sleep, participants encoded a second set of facts. Memory for all facts was tested in a functional magnetic resonance imaging scanner. The authors found that sleep spindle density predicted an increase of the schema benefit to memory across the retention interval. Higher spindle densities were associated with reduced decay of schema-related memories. Also, spindle density predicted increased disengagement of the hippocampus across 24h for schema-related memories. The results suggest that sleep spindle activity is associated with the effect of prior knowledge on memory consolidation.
An explanation for the slow learning mechanism during sleep could be that there is selectivity during this process (Stickgold & Walker, 2013), meaning that only part of what is learned is consolidated and the rest is forgotten. Indeed, according to O’donnell and Sejnowski (2014), spatially patterned protein synthesis can enable selective consolidation of some memories but forgetting of others. At the same time, the functional clustering of synapses on dendrites and the sparsity and overlap of neural activity patterns at the circuit level are key factors regulating selectivity of memory consolidation and generalization. O’donnell and Sejnowski (2014) also argue that the overlap between strong and weak patterns at neural circuit level determines the degree of consolidation of the weak pattern.
According to Jurewicz et al. (2016)there is a presumably accompanied process of decontextualization of the memory trace during consolidation, which means a gradual loss of memory for the learning context. One could think that this is what supports generalization. A qualitative transformation from perceptually rich and detailed episodic memories to more abstract semantic knowledge could be supported by sleep according to Jurewicz et al. (2016). However, as Jurewicz et al. (2016)point out, the availability of contextual information generally facilitates memory recall. In their study, memory retrieval was significantly improved when the learning context was reinstated, as compared to a different context. This would go in tune with one model of generalization: the Temporal Context Model (TCM), which falls under the encoding-based models of generalization. According to Kumaran (2012), in this model, associations between individual items are mediated by their shared context instead of direct item–item associations. At the point of retrieval, items are therefore retrieved as a function of their similarity to the current state of context. Additionally, Javadi, Tolat and Spiers (2015)investigated whether sleep alters the subjective value associated with objects located in spatial clusters. They found that sleep enhances a generalization of the value of high-value objects to the value of locally clustered objects, suggesting that the spatial context helps to bind items together in long-term memory and serve as a basis for generalizing across memories and that sleep is mediating memory effects on salient/reward-related items.
Contrary to this, Cairney et al. (2011)found in their study a sleep-related reduction in the extent to which context impacts upon retrieval of memories, underpinned by the fact that superior memory after sleep than after wake was observed when learning, and retrieval took place in different environmental contexts. This would provide initial support for the possibility that sleep dependent processes may promote a decontextualisation of recently formed declarative representations.
Contrary to the above statements, in a study on toddlers by Werchan and Gómez (2014), it was found that only children who did not nap were able to generalize word learning. A 4hr period of wakefulness between learning and testing dramatically improved generalization in young children. According to the authors, these findings have critical implications for the functions of sleep versus wakefulness in generalization, implicating a role for forgetting during wakefulness in generalization, at least in young children. In a similar manner, according to Hennies, Lewis, Durrant, Cousins, and Lambon Ralph (2014), the formation of conceptual representations, which would require two key computational challenges: integrating information from different sensory modalities and abstracting statistical regularities across exemplars, although they are thought to be facilitated by off line memory consolidation, they seem to be enhanced by wakefulness instead of sleep. According to the results of these authors’ study, off line memory consolidation facilitated cross-modal category learning, but consolidation across wakefulness, not across sleep, showed this beneficial effect.
At the same time, in a study about sleep and the generalization of fear learning, Davidson, Carlsson, Jönsson and Johansson (2016)showed that there was no difference in the degree of generalization between the sleep and the wake group. Although, according to Pace-Schott, Germain and Milad (2015), sleep promotes both the consolidation of memory and the regulation of emotion, influencing the consolidation and modification of memories associated with both fear and its extinction. There appears to be a time-of-day effect on extinction learning and generalization of fear. REM sleep could be a sleep stage of particular importance for the consolidation of both fear and extinction memory as evidenced by selective REM deprivation experiments. REM sleep has been shown to be accompanied by selective activation of the same limbic structures implicated in the learning and memory of fear and extinction. It is suggested that improving sleep quality may ameliorate anxiety disorders by strengthening naturally acquired extinction(Pace-Schott, Germain, & Milad, 2015). According to Pace-Schott et al. (2015), sleep efficiency and morningness were negatively associated with neuroticism and anxiety. However, neuroticism and anxiety did not predict extinction learning, recall or generalization. It is thought therefore, that neuroticism or anxiety and deficient fear extinction, despite being both associated with poor quality and late timing of sleep, they are not directly associated with each other.
According to Batterink and Paller (2015), targeted memory reactivation during sleep can influence grammatical generalization. In the study, participants gradually acquired the grammatical rules of an artificial language through an interactive learning procedure. Compared to control participants, participants re-exposed to the language during sleep showed larger gains in grammatical generalization. According to the authors, sleep cues produced a bias, not necessarily a pure gain, which would suggest that the capacity for memory replay during sleep is limited. According to them, presenting the artificial language during sleep may have elicited an overlapping reactivation of individual phrases presented during the prior learning episode. In connection with this, Groch et al. (2016)investigated in healthy adolescents and adults whether stabilizing memories of positive or negative scenes modulates the later interpretation of similar scenes. In the study, participants learnt associations between ambiguous pictures and words that disambiguate the valence of the pictures in a positive or negative direction. During the study, half of the words were acoustically presented during post-learning sleep. Results show that cued compared to un-cued stimuli were remembered better the next morning, but also, cueing positively disambiguated pictures resulted in more positive interpretations whereas cueing negatively disambiguated pictures led to less positive interpretations of new ambiguous pictures with similar contents the next morning. These authors conclude that memory cueing during sleep can modify interpretation biases by benefitting memory stabilization and generalization.
We could assume that generalization depends on the strength of the representations used in such process, but apparently there is more to it. Fenn, Margoliash and Nusbaum (2013)directly compared consolidation of rote and generalized learning using a single speech identification task. They showed that training on a large set of novel stimuli resulted in substantial generalized learning, and sleep restored performance that had degraded after 12 waking hours. Rote learning resulted primarily after training on a small set of repeated stimuli. Performance was also degraded after 12 waking hours but was not restored by sleep. Moreover such performance was significantly worse 24h after rote training. This would suggest a functional dissociation between the mechanisms of consolidation for rote and generalized learning (Fenn et al., 2013).
On the other hand, sleep benefits on memory seem not to be consistent for all tasks and in all kinds of periods of time. According to Schönauer, Grätsch and Gais (2014), word pair, syllable, and motor sequence learning tasks benefit from sleep during the first day after encoding, when compared with daytime or night time wakefulness. But performance in the wake conditions recovers after another night of sleep, indicating that there is no lasting effect of sleep. While sleep deprivation before recall does not impair performance and thus, fatigue cannot adequately explain the lack of long-term effects, it is hypothesized that the hippocampus might serve as a buffer during the retention interval, and consolidation occurs during delayed sleep. In a similar fashion, studying the effects of sleep in motor tasks and their generalization, Witt, Margraf, Bieber, Born, and Deuschl (2010)examined whether offline consolidation contributes to the process of generalization in the extrinsic and intrinsic coordinate frame in the motor domain. In the study, participants trained with the left hand a sequential finger-tapping task that has proved sensitive to off line consolidation. The generalization of this task was tested by the ability to transfer the original sequence or the mirror sequence to the right hand. This was also compared with performance on a new sequence not learned before. Transfer was assessed immediately after training of the left hand. Also, participants were tested after an interval of daytime or after an interval of nighttime sleep. Results showed that training of the left hand induced significant transfer effects to the right hand for the extrinsic transformation of the sequence (original sequence), but there was no advantage for the intrinsic transformation (the mirror sequence). After a period of daytime wakefulness the transfer from the left to the right hand for the extrinsic sequence transformation had vanished and, again, there was no transfer effect for the intrinsic transformation of the sequence. But nocturnal sleep saved the initial transfer effect for the extrinsic sequence transformation, while the intrinsic sequence transformation was not affected by sleep. This would indicate that sleep has the capacity to consolidate this transfer and, in this way, contributes to the generalization of a motor skill (Witt et al., 2010).
However a study by Horváth et al. (2016)on 28, 16-moths old, typically developing toddlers, in which they were trained with two novel object-word pairs and tested their initial ability to generalize, indicates a significant interaction of group and session in preferential looking (which was used as a measure for the understanding of the labels of the items), as showed by the fact that performance of the nap group increased after the nap, whereas that of the wake group did not change. This would suggest that napping improves generalization in toddlers. At the same time, in Friedrich, Wilhelm, Born and Friederici (2015), infants aged between 9 and 16 months were given the opportunity to encode objects as specific word meanings and categories as general word meanings. Infants acquired only the specific but not the general word meanings. About 1.5h later, infants who napped during the retention period, but not infants who stayed awake, could remember the specific word meanings and also successfully generalize words to novel category exemplars. Interestingly, supporting what we showed previously, the semantic generalization effect was correlated with sleep spindle activity during the nap. This effect was independent of age (Friedrich et al., 2015). On the other hand, according to Earle and Myers (2015), who explored the generalization of phonetic learning across talkers following training on a non-native contrast, overnight consolidation promotes generalization across talkers in identification, but not necessarily discrimination, of non-native speech sounds.
As mentioned in the previous essay, according to Gómez and Edgin (2015), based on the extended trajectory of hippocampal development, it is argued that transitions in the nature of sleep-dependent learning are expected.
Sleep processes can also affect the accuracy of memories. It is suggested that there is an active reorganization of the memory trace during post-learning sleep periods.This could explain, in part, the generation of false memories (Diekelmann, Born, & Wagner, 2010). In a study by these authors, participants’ performance on memory recall was tested, taking into account a retention period of daytime wakefulness and post-learning nocturnal sleep. It was found that both post-learning nocturnal sleep as well as acute sleep deprivation at retrieval significantly enhanced false recall of theme words. These effects, however, were only observed in subjects with low general memory performance. It is suggested that sleep affects false memory generation through semantic generalization during the consolidation on the memory trace or through the recovery function of sleep that affects cognitive control processes of retrieval. According to Straube (2012), different neuro-cognitive processes have been linked to the formation of true and false memories, particularly brain processes in the medial temporal lobe and the medial and lateral prefrontal cortex.
Despite the above studies, overall, sleep seems to be linked to better memory performance and ability to generalize. Both slow-wave and rapid-eye-movement sleep seem to contribute. Batterink, Oudiette, Reber and Paller (2014), for example, conducted a study in which they exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article. Also, an afternoon nap was interposed between two 20-min learning sessions. Results show that participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. These authors conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. According to them, the combination of slow-wave and rapid-eye-movement sleep (SWS and REM) may synergistically facilitate the abstraction of complex patterns in linguistic input.
Sleep could also promote analogical problem solving, which requires using a known solution from one problem to apply to a related problem (Monaghan et al., 2015). In these authors’ study, participants were exposed to a set of source problems, and soon after there was a 12-h period involving sleep or wake. Participants attempted target problems structurally related to the source problems but with different surface features. It was shown that sleep improved analogical transfer, but the effects were not due to improvements in subjective memory or similarity recognition, but rather effects of structural generalization across problems, according to (Monaghan et al., 2015).
There seems to be an interaction between wakefulness and sleep in memory consolidation. In a study by Gregory et al. (2014), in which functional connectivity MR (fcMRI) was used to examine whether task-induced changes in resting-state connectivity correlate with performance improvement after sleep, it was found that physiological processes immediately after learning correlate with sleep-dependent performance improvement, suggesting that the wakeful resting brain prepares memories of recent experiences for later consolidation during sleep. Both the fcMRI and the sleep control groups showed significant improvement in a motor sequence task performance, while the wake control group did not. In the fcMRI group, increased connectivity in bilateral-motor cortex following the motor task training correlated with the next-day improvement. The increased connectivity did not appear to reflect initial learning, as it did not correlate with learning during training and was not greater after the motor task training than the motor control task performance. They hypothesize therefore, that the increased connectivity processed the new memories for sleep dependent consolidation.
There also appears to be brain asymmetries in sleep-dependent processes of memory consolidations, as well as sex differences in sleep-dependent perceptual learning.Peigneux, Schmitz and Willems (2007)investigated the effect of time, post-exposure sleep, and the brain hemisphere solicited on preference generalization toward objects viewed in different perspectives. For example, when objects presented in the right visual field (RVF), which promotes preferential processing in the left hemisphere, same and mirrored exemplars were preferred immediately after exposure. On the other hand, object presentation in the left visual field (LVF), promoting right hemisphere processing, elicited a “mere exposure effect” (MEE), in this case for same views immediately after exposure, then for mirror views after sleep. Sleep deprivation during the first post-exposure night, although followed by two recovery nights, extinguished this MEE for all views in the LVF but not in the RVF. Results suggest that post-exposure time and sleep facilitate the generalization process by which we integrate various representations of an object, but mostly in the right hemisphere, sleep may be mandatory to consolidate the memory bias underlying affective preference (Peigneux et al., 2007). At the same time, in their study, Mcdevitt, Rokem, Silver and Mednick (2014) found that REM sleep facilitates consolidation of perceptual learning (PL) but that the pattern of specificity in the REM condition differed between men and women. For men, whose naps contained REM sleep, the PL was highly specific to the trained direction of motion, while the REM sleep in women resulted in generalized learning to an untrained direction as well as to a novel direction that was not previously tested. At the same time, for subjects in the REM condition, men exhibited greater PL than women for the trained direction. This suggests sex differences in the magnitude and specificity of PL and in the role of REM sleep in implicit learning, according to these authors.
According to the study by Sweegers, Takashima, Fernández and Talamini (2014), the buildup of general knowledge regarding regular associations appears to involve the coordinated activity of the hippocampus and mediofrontal regions. According to them, the putative cross-talk between these two regions might support a mechanism for regularity extraction, suggesting that the consolidation of cross-episodic regularities may be a key mechanism underlying general knowledge acquisition.
According to Dudai, Karni and Born (2015), memory consolidation is assumed to be embodied in synaptic and cellular modifications at brain circuits in which the memory is initially encoded and then consolidated by recurrent reactivations. These reactivations occur both during wakefulness and sleep, distributing information to additional locales and integrating this into existing knowledge. An important component of this process, according to Dudai et al. (2015), is acetylcholine, which has been identified as one of the key determinants of information processing and flow in and out of the hippocampus. As highlighted by these authors, it appears that cholinergic activity is high during wakefulness and in this state suppresses, via intrahippocampal recurrent presynaptic inhibition, output to extrahippocampal target regions, however, SWS is characterized by reduced cholinergic activity and thus by the release of CA1 output from this inhibition. Glucocorticoid signalling could add to this shifting of network activity between a wakefulness mode of encoding and a SWS mode of consolidation, because their release is naturally suppressed to minimum levels during nocturnal SWS (Dudai et al., 2015). According to Breton and Robertson (2014), memory consolidation occurs partially via SWS-dependent replay of activity patterns originally evoked during waking. For these authors, SWS is ideal for replay given hyporesponsive sensory systems, and thus reduced interference. Their study’s results show that imposed replay during post-training SWS enhanced the subsequent strength of memory, whereas the identical replay during waking induced extinction (Breton & Robertson, 2014).
If such replay of leaning also occurs during wakefulness, this fact could explain results from studies that appear to show better performance on memory recall for the wake condition. Processes during wakefulness could play an important role. According to Bridge and Voss (2014), who tested whether across-episode binding preferentially occurs for memory content that is currently “active”, found that memory for faces was better when tested on the original background scenes in the active relative to passive condition, indicating that original episode content was bound with the active condition faces. According to these authors, early-onset negative ERP effects reflected binding of the face to the original episode content in the active but not the passive condition. This would suggest that active retrieval promotes binding of new information with contents of memory (Bridge & Voss, 2014).
According to Breton and Robertson (2014), some memories are enhanced during wakefulness while the enhancement of others is delayed until sleep. According to these authors, converging evidence suggests that inhibitory mechanisms can “switch off” a processing route, thereby preventing the consolidation of selected memories during wakefulness. This is explained by the authors, due to an actively imposed “bottleneck” generated by the brain. Transcranial magnetic stimulation (TMS) can interfere with this bottleneck, resulting in multiple memories being consolidated simultaneously during wakefulness. This mechanism could be important for the selection or relevant memories to be consolidated, for example, those that imply reward (Breton & Robertson, 2014).
According to Spencer (2013), generalization over sleep cannot be explained by simple neural replay or spindle induced cortical plasticity. The author argues, for example, that in the case of spider exposure therapy, neural replay would reinforce the veridical memory for the exposed spider but this mechanism should not necessarily enhance the memory for, or decrease reactivity to, an unexposed spider. It is also suggested that hippocampal replay may be adapted to serve both a preparatory role (forward pre-play in anticipation of an experience) and an exploratory role (recently explored sequences via reverse replay) (Spencer, 2013). Although, this author argue that generalization may occur through “replay” of novel sequences.
Indeed this phenomenon is far from being understood and more research is needed to clarify the mechanism under which consolidation and generalization take place. From the studies and evidence reviewed, poor emphasis is given to define a specific mechanism of generalization.
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