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Abstract

Learning and memory are among the key cognitive functions that drive the human experience. As such, any defective condition associated with these cognitive domains could affect our navigation through everyday life. For years, researchers have been working toward having a clear understanding of how learning and memory work, as well as ways to improve them. Many advances have been made, as well as some challenges that have also been faced in the process. That notwithstanding, there are prospects with regards to the frontier of the enhancement of learning and memory in humans. This review article selectively highlights four broad areas of focus in research into the understanding and enhancement of learning and memory. Brain stimulation, effects of sleep, effects of stress and emotion, and synaptic plasticity are the main focal areas of this review, in terms of some pivotal research works, findings and theories.

Keywords

learning and memory synaptic plasticity long‐term memory hippocampus amygdala brain stimulation stress sleep

1 Introduction

An intriguing question that remains yet to be clearly answered in the fields of neuroscience and psychology is about how exactly the mind is generated by the brain. The brain, which is a key component of the central nervous system, is essential for the cognitive functions that help us navigate everyday life. We typically employ the spatial and temporal representation of the world around us created by our brains to enable us relive past events and imagine future plausible or fictitious events [1]. Learning and memory functions are cognitive functions that are driven by networks of brain regions, and any kind of defect in how these networks are set up and operate typically results in some neurological or cognitive disorders. This is key for appreciating how various brain regions work to maintain a functional cognitive process.

As humans, we seem to be naturally fascinated with wanting to improve our quality of life, and that involves apt cognitive functionality. Typically, it would make sense for a person to not want to lose their memories or their ability to make and store new ones. Interestingly, researchers, over the years, have aimed at gaining a more profound understanding of how memory and learning work, and also exploring options capable of enhancing learning and memory functions. Having a comprehensive understanding of how memory and learning work as well as all the mechanisms that underpin them presents an avenue to leverage that knowledge to provide effective solutions to problems and defects associated with learning and memory. As such, experimental paradigms set up for the investigation of the functions of certain brain regions or networks would typically require test and control groups, in order to compare and contrast normal function with dysfunction based on specific testing parameters and conditions. Neuromodulation procedures, along with neuroimaging techniques, have proven invaluable in these kinds of assessments. Rather than the physiological process involving the diffuse release of neurotransmitters known as neuromodulators, the term neuromodulation as used in this review specifically refers to the therapeutic methods that involve electrical or magnetic stimulation of nerve activity, as in, for example, brain stimulation.

Learning and memory are closely related domains of human cognition that are apparently almost always discussed as a pair, and for good reason. Memory is defined by Azzam and Easteal as “the sum of past experiences” [2], although it can be argued that this definition is quite limiting and reductionist. However, that could be because there is perhaps no one correct and perfect way to define memory, owing to its complexity, and so a definition may be acceptable depending on the context. Learning influences the memory process primarily in that learning directly feeds into the encoding stage of the memory process as that is the point where information is initially acquired. Following encoding are storage and retrieval, in that order [3]. Since learning informs memory, it presupposes that a learning challenge translates to an impairment of some memory function. Just as there cannot be memory without learning, there also cannot be learning without memory.

Learning and memory are also important because they have been shown to guide behavior in animals, including humans, for instance, through the memories that underlie the defensive motivational system of fear [4, 5]. They make it possible to avoid risky or dangerous routes, situations or behavior, and are essential for self‐preservation. By making a conceptual assessment of how important memory is to us as humans, is it really farfetched to posit that the sum total of one’s memories (both declarative and non‐declarative) is the essence of one’s being or existence? Without memory, life would be unbearable, as made evident with people living with some form of amnesia or neurogenerative disorders like Alzheimer’s disease. That said, one question which may boggle the minds of some is simply “How much memory is sufficient or too much for a person?” Some people living with hyperthymesia, also known as highly superior autobiographical memory syndrome [6], may argue that there is perhaps such a thing as too much memory.

It is important, however, to emphasize that the human memory in itself is not always perfect, as it is prone to error and is quite malleable and manipulatable [7, 8]. Memory, or more specifically episodic memory is understood more as an error‐prone reconstruction rather than an authentic replica of past events. False memories, therefore, do serve as proof of how erroneous and distorted memory can be [9]. The infallible and subjective nature of human memory also somewhat explains why two people may remember the same thing differently even though they had the same exposure to it. Individual differences in the way memory works from person to person also demonstrate the complexity and subjectivity of human memory.

The flexibility of memory, mediated by the workings of working memory, also accounts for our ability to update our knowledge on certain topics or pieces of information. The working memory allows for integration of newly encoded information from the sensory memory with retrieved preexisting long‐term memory (LTM) [2, 10]. This occurs when the new information acquired is in congruence with schemas from LTM, and is hence combined with memory retrieved from LTM by the central executive system, and then re‐encoded together and reconsolidated to make the memory more robust [2, 11, 12].

Memory can be categorized into four main types namely sensory/short‐term memory, working memory, recent memory, and long‐term memory (LTM) [2]. The various forms of memory can be distinguished on the bases of their content and the modes of acquisition [13], as well as their duration. Interestingly, the categorization of memory into its main types is not uniform across literature as there are some slight variations and different interpretations of what exactly means what, which ultimately presents the likelihood for some of them to be conflated, for example, short‐term memory and working memory. Even though short‐term memory and working memory are different theoretical concepts, there is some evidence of an overlap between them [14]. The working memory model by Baddeley and Hitch [11] was devised to address everyday memory functions like that which is employed in reading [15]. Working memory is essentially limited in terms of amount of content and durability.

Memory storage, an important part of the memory process is driven by various brain regions. Long‐term memory is specifically mostly stored in the parieto‐temporal‐occipital (PTO) junction of the association cortex, as well as on the ventromedial and dorsolateral surfaces of the prefrontal cortex (PFC) [16]. Within the PTO junction, long‐tern memory is stored in specialized representations known as schemas [2, 17]. Strong connections between neuronal assemblies during encoding form engrams, while the strongly connected cortical cell bodies in engrams can be integrated into schemas of long‐term memory [2]. Engrams form an associative, interconnected network that gets activated during the processing of mnemonic content or information. [2]. Schemas and engrams are essential for the process of memory from encoding to consolidation to retrieval. They also facilitate mnemonic learning.

Long‐term memory is broadly categorized into declarative (explicit) and non‐declarative (implicit or procedural) memory. Most knowledge we gain that enter long‐term memory are through two main sensory modalities, images and speech [13], which respectively engage the visual and auditory cortices [2]. Information from long‐term memory has to be retrieved back into working memory for it to be useful.

The brain structures mainly responsible for declarative memory are the medial temporal lobe (MTL) structures [13]. Under the declarative memories are two main sub‐types, which are semantic memories and episodic memories. Semantic memories mainly have to do with general knowledge accumulated throughout one’s life, including facts, concepts, and things of the like. Knowing that the number “13” is a prime number essentially depends on one’s semantic memory of what a prime number is or means. Likewise, for instance, the use of a person’s semantic memory of the meaning of a circular definition should enable the person recognize “Semantic memories are memories that are semantic” as a circular definition.

Episodic memories, however, are different from semantic memories in that they are concerned with personal experiences or episodes of autobiographical events that are typically contextual and time‐locked. Episodic memory recall may be triggered by some memory cues which may cause some feeling of yearning for the past. This feeling, commonly known as nostalgia, has been revealed to likely have a significant analgesic effect [18]. An interplay between memory and reward systems seems to be in effect during nostalgic episodes [19]. The brain networks that are responsible the recall of episodic memory basically seem to have much in common with other cognitive functions like episodic future thinking and navigation, while the process of scene construction is thought to underpin other cognitive functions that activate the similar brain networks [20].

This selective review highlights some of the relevant and some current knowledge on learning and memory and ways to enhance them, including some research findings of interest and insights from literature. More specifically, this review addresses some of the advances in the understanding of how learning and memory work and ways in which they can be improved upon, as well as the prospects and the challenges faced by researchers in this area of research.

2 What we know so far

From some of the oft‐cited research findings and discoveries like that of the role of the hippocampus in memory functions as in the case of Henry Molaison (HM) [21] to some relatively recent ones [22 –25], much progress has been made over the years in terms of research into human memory and learning. This review draws on the similarities, differences and contradictions among some of these theories, hypotheses and research findings.

In response to his intractable seizures, HM underwent a surgical procedure involving the bilateral removal of his hippocampus, which eventually left him unable to form new memories, while he also lost some memories that he had acquired a few days prior to the surgery. By studying the case of HM, Scoville and Milner [21], through their groundbreaking work, determined that the hippocampus is required for the formation (acquisition and storage) of new memories. This finding has since informed later prominent research findings about memory and learning and the role of the hippocampus in memory functions. For instance, the anterior hippocampus is currently known to mediate the cognitive functions of perception, imagination and recall of events and scenes [1]. About half a century following the discovery by Scoville and Milner in 1957 [21], the hippocampus was found to not only be pivotal in the recollection of past events, but also key for the imagination of new events with lucid spatial coherence [25]. The study by Hassabis et al which tested amnesic subjects with bilateral hippocampal damage indicated that the hippocampus is needed for holistic imagination of scenes [25].

Knowledge of long‐term memory formation helps inform an understanding of ways in which memory could be enhanced [26], as targeting the mechanisms underlying long‐term memory formation could prove effective in memory enhancement. When new information acquired to be committed to memory is congruent with an existing schema, that information is more likely to be memorized and remembered as it is more likely to get integrated. The way mnemonic devices aid memorization is that individual bits of information are set up into their own schemas [2]. This is known as chunking, and has been demonstrated to be effective for the memorization of information [2]. Repeated study, involving rereading and active memorization, of new information also stimulates the cingulate gyrus to continually transform recent memory from the hippocampus to long‐term memory in the association cortex, effectively cycling the Circuit of Papez to promote storage of long‐term memory in the association cortex [2].

There is also pharmacological evidence to show that acetylcholine and its receptors play a role in encoding new episodic memories. Drugs like scopolamine that block muscarinic cholinergic receptors elicit the impairment of the encoding of new memories, but do not necessarily weaken the retrieval of acquired memories [27, 28]. Blocking these receptors could also impair working memory for certain stimuli as shown in a study by Green et al. [29].

The focus of this review is primarily on declarative memories, although non‐declarative memories are as well important and are also addressed. In this section, the focus shifts to some salient approaches to the understanding and enhancement of learning and memory, as outlined in the following subsections. Due to the rapidly expanding body of the literature on the topic of learning and memory, this is in no way meant to be an exhaustive review of all studies that have employed or explored these approaches. Instead, this review highlights some of the rather major ones that are of relevance to the scope of the review. Discussed in the following subsections are how invasive and noninvasive brain stimulation, the effects of sleep on memory, the effects of stress and emotion on memory, and the phenomenon of synaptic plasticity in the brain can be studied and employed in approaches aimed at better understanding and enhancing memory and learning functions.

2.1 Brain stimulation

Neuromodulation—or more specifically, brain stimulation—can be used to study the cause‐effect relationship between a particular kind of stimulation to brain regions and the responses elicited. Aside its utility in elucidating the mechanisms underpinning normal brain function, human brain stimulation also presents a means for therapeutic approaches for treating mental or cognitive disorders [30]. Brain stimulation techniques can be broadly classified as invasive or noninvasive.

In order to effectively study learning and memory functions, many studies have employed the use of noninvasive brain stimulation in both healthy and brain‐injured subjects [13]. These techniques as well as other brain stimulation techniques generally provide insights that can be translated into effective therapeutic procedures for the treatment of disorders of learning and memory, and into memory‐enhancing approaches in healthy populations as well [13]. Aside being useful in studying and establishing cause and effect associations, noninvasive brain stimulation techniques can also be used to identify the chronometric underpinnings of neural mechanisms that mediate cognitive functions and processes.

The alteration of brain activity in response to the stimulation is typically dependent on the stimulation parameters [13]. The behavioral response generated by brain stimulation depends on the specific brain region that is stimulated [31]. Noninvasive brain stimulation techniques like transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) can cause “virtual lesions” through their interference with brain activity [13]. They also serve as important noninvasive interference methods that can be used in combination with functional neuroimaging techniques like electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) in real time for the purpose of conducting neuropsychological research. In addition to the advantage of recording brain activity with both good spatial and temporal resolutions, this combination of EEG and fMRI is also quite important for clarifying physiological and behavioral interactions and for the testing and enhancement of cognitive models which may eventually result in better methods of neurorehabilitation [13].

Functional neuroimaging techniques are typically employed to study brain regions that are associated with cognitive processes and interactions. While the fMRI techniques perform indirect measurements by examining hemodynamic responses, the EEG performs direct measurement of electrical dynamics of the brain, in response to specific tasks of interest, typically cognitive and emotional tasks [32]. A positron emission tomography (PET) scan, which is also an indirect measure of brain activity, has good spatial resolution but a poor temporal resolution, as compared to EEG. EEG has a high temporal resolution but a poor spatial resolution as compared to fMRI. From the comparisons, it is quite evident that these neuroimaging techniques have their pros and cons and could be best suited if used complementarily to maximize efficiency. For instance, the combined use of EEG and fMRI leverages the good temporal resolution of the former and the good spatial resolution of the latter to maximize efficiency.

One major form of invasive brain stimulation of interest in terms of learning and memory is deep brain stimulation (DBS). According to a review by Suthana and Fried [31], memory‐enhancing effects can be triggered by deep stimulation of the human MTL circuitry which comprises the amygdala, hippocampus, entorhinal cortex, perirhinal cortex and parahippocampal cortex. They [31] also explored the prospects of using DBS in the treatment of neurological disorders involving memory. Since DBS is capable of enhancing memory dependent on the MTL regions, it should assumably be useful in the treatment of MTL‐related disorders like Alzheimer’s. Even though DBS, like cortical surface stimulation, has an apparent memory‐enhancing effect, it is yet to be elucidated whether the promising results from DBS experiments can generally be applicable to a wider population and other patients of other neurological diseases like Alzheimer’s, since the subjects of these studies have primarily been epileptic patients who actually needed the intracranial electrode implants for clinical reasons [31].

In an experimental study by Ezzyat et al. [33], intracranial brain stimulation delivered in poor encoding states to epileptic subjects resulted in increased encoding state estimates, an enhanced memory performance and recall‐related brain activity as well. This experiment and its key findings proffer therapeutic approaches for the treatment of memory dysfunction [33]. In the study, subjects had intracranially‐implanted electrodes.

Also, it has been demonstrated that sleep‐dependent memory processing can be enhanced by stimulating slow brain oscillations [34]. When these slow oscillations are electrically or auditorily intensified, learning and consolidation of memory have been found to be enhanced [35, 36]. Marshall et al. performed a study where subjects had to learn word pair association tasks in the evening, followed by a period of sleep in which they underwent transcranial electric stimulation (TES) at the same frequency as natural slow oscillations (˜ 0.75 Hz) [35]. What was observed from this experiment was that the stimulation to which the participants were subjected increased the intensity of slow oscillations alongside spindle activity, while also enhancing sleep‐dependent consolidation of the word pairs learned priorly [35].

Brain stimulation studies have as well shown that the amygdala is capable of modulating the consolidation of memory in other brain regions like the perirhinal cortex and the hippocampus [30]. Work by Inman et al. has shown that brief, direct electrical amygdalar stimulation improves human declarative memory [30]. In setting out to test the amygdala’s ability to enhance declarative memory without the reliance on emotions, brief amygdalar stimulations performed on subjects with intractable epilepsy resulted in enhanced human declarative memory of emotionally‐neutral images that were used in the experimental study, suggesting that the amygdala can endogenously initiate the memory prioritization process and mediate a strong consolidation of memory of learning content without an emotional component [30]. This is in agreeance with studies in rodents that have also demonstrated that the direct stimulation of the amygdala can enhance memory during non‐emotional situations [30].

Since majority of studies that have shown DBS‐related improvement of human memory have been conducted in patients with epilepsy and in need of intracranial depth electrode implants [30, 31, 33, 37, 38], it raises the question of whether DBS effects on memory can be in fact generalizable and extended to other patient populations. Nevertheless, DBS and other types of brain stimulation techniques still remain very promising and possess much potential with regards to practical means of enhancing human learning and memory. Even though the invasive brain stimulation techniques have their benefits, it is important to recognize how some of their downsides may be offset by noninvasive brain stimulation techniques or approaches.

2.2 Effects of sleep

Sleep has been implicated in plastic changes that occur in the brain that modulate learning and memory. A growing body of experimental findings and data seem to suggest that sleep aids in the consolidation of fresh memory traces [39]. Sleep consolidation is an essential process that makes the connections between working memory in the hippocampus and long‐term memory in the association cortex more robust [2]. Sleep‐dependent consolidation reactivates the labile memory traces that were encoded in the period of preceding wakefulness. This betters the retrieval of semantic memory after sleep as compared to when the learning took place, which is before sleep. Sleep can be regarded as a state of “offline” information processing essential to the appropriate functioning of learning and memory, as there is very reduced responsiveness to the environment as sensory inputs are quite minimal during this state [2]. The processing of sleep‐dependent memory can be boosted through the stimulation of slow brain oscillations [34].

Sleep has been evinced to not only affect procedural memory which is considered hippocampus‐independent, but to also affect hippocampus‐dependent declarative memory. In experiments by Gais, Lucas and Born [40] where high school students were tested on vocabulary, it was observed that a period of sleep that shortly followed learning enhanced declarative memory. The study also found that sleep deprivation has negative effects on memory.

For declarative memories, slow wave sleep (the deepest part of non‐rapid eye movement sleep) presents the greatest benefit for the consolidation of memories acquired during the period of wakefulness prior to sleep [34]. It is thought that during the slow wave sleep (SWS) stage of non‐rapid eye movement (non‐REM) sleep, information transfer from the hippocampus to the association cortex is activated. The K‐complexes produced by the hippocampus during SWS are clustered by the thalamic spindles, which then results in the initiation of rapid repetition of long‐term potentiation in the association cortex [2, 41]. The synaptic consolidation thus drives systems consolidation resulting in the increase in neocortical LTM as well as the concurrent decline in hippocampal recent memory [2]. Also, during “offline” brain states such as non‐REM sleep, sharp wave‐ripples (SWRs) that occur in the hippocampal CA1 region have been reported to promote memory consolidation as well as memory retrieval [42 –45]. A disruption of these SWRs could therefore adversely affect memory [43, 44].

Interestingly, a study by Wagner, Gais and Born showed that during rapid eye movement (REM) sleep, the amygdala is selectively activated for the key purpose of emotional stimuli processing [46]. They found that the selective processing of emotional memories over memories of neutral content occurs better in late sleep dominated by REM sleep than early sleep dominated by non‐REM slow wave sleep. REM sleep resulted in the enhancement of memory for the emotional text better than the neutral text. It is also worth noting that from the study, cortisol levels varied across early and late retention intervals.

Sleep also enhances the consolidation of new memories acquired after sleep (post‐sleep memories). This may be due to the synaptic weight renormalization that occurs during sleep as proffered by the theory of synaptic homeostasis [34]. During sleep, synapses that were potentiated during the period of wakefulness prior to sleep get downscaled [47 –49]. The extensive synaptic potentiation that occurs during wakefulness when information is encoded results in a heightened demand of brain space and energy, which is basically what the synaptic homeostasis hypothesis propounds [47 –49]. What this also implies is that we therefore need sleep to downscale and renormalize synaptic weights, lest the brain reaches its encoding limits. Sleep in this regard can be described as the “the price we pay for plasticity” [49, 50]. The improvement of learning right after sleep, as opposed to right after a period of wakefulness, is attributable to synaptic downscaling [34, 51]. Synaptic spines have in fact been observed to dwindle during periods of sleep [52, 53].

Using fMRI and other functional neuroimaging techniques, studies have shown that in humans, there is a reactivation of learning‐related neuronal activity during sleep following a period of wakeful learning [54, 55]. Aside the hippocampus, other brain regions—such as the striatum, motor cortex, and thalamus—have been implicated in this kind of neuronal reactivation during sleep [56 –60]. Sleep can also transform and reorganize memory, aside its capability of strengthening memories [34]. This reorganization and transformation can even help in the triggering of false memories [61, 62], and gaining new insights into problems and facilitate problem‐solving [63].

The duration of sleep is also important in how it promotes learning and memory, as longer periods of sleep have been shown to be instrumental to memory boosts [64], even though there is also evidence that suggests that shorter periods of sleep can also be beneficial to declarative memory [65]. The findings by Lahl et al. showed memory improvements from short naps that last only few minutes [65]. To optimize the beneficial effect of sleep on learning and memory, the interval between learning and sleep should be shorter rather than longer. To put this into context, a study by Gais, Lucas, and Born observed that the consolidation of English– German vocabulary is bettered by sleep that follows 3 hours after encoding as compared to sleep that follows 10 after hours of encoding [40].

Sleep has also been shown to improve prospective memory of future tasks [66 –68], and so, it is important to highlight during learning, how the learning material is relevant for some future purpose, as a way to manipulate sleep’s selective and preferential encoding of memory to boost the chances of effective recall. Aside that, when the learning content is associated with some type of reward, sleep consolidates such memory selectively and preferentially as well, as was observed in a study where participants anticipating a monetary reward performed better in a procedural memory task [69]. There is also an apparent tie‐in between the enhancing effects of both emotion and sleep on memory, as studies have also shown that the emotional value of the learning material also represents its relevance to the individual which results in the elicitation of more robust sleep‐dependent memory consolidation [46, 70 –75]. As long as there is an established relevance of the learning content to the individual, optimal enhancing effects of sleep on memory can be attained.

Effects of sleep on memory can also be optimized for psychotherapeutic outcomes. For instance, sleep helps in the abatement of phobias through the consolidation and generalization of the extinction of conditioned fear responses [76, 77]. Also, since many hormones and neurotransmitters that play key roles in learning and memory exhibit typical variations across the sleep‐wake cycle, the use of drugs that target them during sleep for the therapeutic enhancement of memory seems like a reasonable approach [34]. Drugs that show enhancing effects on sleep and memory show some promise for clinical applications, but more studies need to be done to shed light on the potential adverse effects [34].

Even though sleep is beneficial for the enhanced consolidation of memory, it cannot be overemphasized that bad sleeping patterns could have negative impacts on the individual. REM fragmentation during sleep, for instance, adversely affects extinction learning and safety learning, which seems to exacerbate posttraumatic stress disorder (PTSD) and poses a challenge in its treatment [78]. Sleep disturbance has been posited and demonstrated to cause a maladaptive fear conditioning which underpins PTSD [78]. Defective extinction learning and safety learning seem to be the more convincing underpinnings of the likelihood to suffer a stressful condition after a traumatic experience, as opposed to the likelihood of natural recovery. Therefore, REM fragmentation and essentially disturbed sleep which precedes some sort of trauma portends the onset of PTSD. This review also suggests that addressing fragmented sleep presents a way to potentially enhance emotional memory and learning, hence mitigating responses to trauma exposure, minimizing acute PTSD and improving its treatment [78]. This is quite relevant as there exists a high level of comorbidity of sleep disorders and PTSD [78 –81].

2.3 Effects of stress and emotion

Stress has been studied and revealed to be a modulator of learning and memory. Despite being regarded as a “negative emotional state”, stress can enhance and/or impair learning and memory, depending on varying factors like duration and intensity [82]. Stress apparently affects memory in a time‐dependent manner, as stress is thought to enhance the formation of memory around the time of learning, while it could also significantly impair the retrieval of memory, depending on the temporal proximity between the action of the stressor and the particular stage of the memory process involved [82]. The stressors have significant implications in an educational setting with regards to how they modulate memory functions. Lower levels of stress in a school setting may improve upon memory, but such an effect of stress is typically stronger for an emotional rather than neutral learning material. It has also been observed experimentally that if the learning material is related to the stress or stressor, then memory is more likely to be enhanced [83]. Otherwise, the opposite effect is observed [84].

While chronic stress is detrimental to learning and memory, mild and acute stress is capable of significantly enhancing learning, memory and general cognition [32, 85, 86], in spite of some evidence showing that stress could negatively impact memory [82, 87 –89]. Some findings also seem to suggest that when stress significantly enhances memory [85, 86], such stress‐induced memory boosts could potentially lead to disorders like PTSD [90]. Interesting results from experiments investigating the effects of stress on hippocampus‐dependent memory in rodents do affirm the memory‐enhancing effects of stress [90]. However, translating these findings to practical applications with respect to human declarative memory has proven to be quite a challenge [84, 90 –92].

Glucocorticoids and adrenergic hormones are known to be instrumental in mediating functional memory processes and enhance memory in response to acute stress. The release of catecholamines and neurotransmitters during stress regulates the functions of human learning and memory. The main ones at play are noradrenaline which is released from the autonomic nervous system in response to stress, and cortisol which is released from the hypothalamus‐pituitary‐adrenal axis (HPA) also in response to stress. When the HPA axis becomes “overactive”, synaptic plasticity is impaired, hence learning is negatively affected [93]. The effects stress has on learning and memory basically depend on the interaction between noradrenaline and cortisol mainly in the amygdala, a small nucleus ventrally positioned on the hippocampus, which is key in reward‐related motivation [2]. This interaction has a strong impact on memory formation of emotional value [82]. Thus, inclusion of elements of emotional value into neutral learning material for students has a likelihood of helping students recall what they learn. From pharmacological investigations, the administration of cortisol prior to learning boosted later memory [94 –96], especially for emotionally arousing pictures [90], indicating how beneficial increased cortisol levels during memory encoding can be. In response to emotional arousal, noradrenaline release in the hippocampus from the locus coeruleus mediates LTP essential for memory processing, including consolidation of acquired memory into LTM [97 –100].

Activation of the amygdala by emotional learning material is influenced by noradrenaline availability as it is blocked by the beta‐blocker propranolol [101]. Due to its role in reward‐related motivation, the amygdala is essential in academic learning or studies where for instance, the goal is to get excellent grades or a great sense of achievement [2]. The amygdala is known for its role in the processing of typically strong emotions like fear, anger and pleasure, and has been shown by pertinent neuroimaging findings to modulate memory consolidation, while other brain regions, specifically the hippocampus has been found to be responsible for successful learning and LTM retention, and the prefrontal cortex found to aid in the encoding and formation of memory [32]. These findings essentially demonstrate how different key brain regions (the amygdala, prefrontal cortex and medial temporal lobe) work in tandem for learning and memory to be successful. Quite a number of studies have shown that the hippocampus and amygdala are activated in synergy during memory encoding leading to consolidation into LTM of emotional content, which is more likely to be better retained and remembered than neutral content [102 –104]. Interestingly, even though learning content that is to be encoded and stored in LTM engages the amygdala, it has also been observed that the amygdala can still initiate memory prioritization even in the absence of an emotional input, based on a study by Inman et al. [30], thereby showing that an emotional input may not entirely be necessary for stimulating the amygdala for the memory process.

The basal amygdala and lateral amygdala make up the basolateral amygdala (BLA) whose projections to key brain regions like the prefrontal cortex and hippocampus are essential for learning and memory [32, 105 –107]. The sensory cortices, during emotional processing, receive these amygdalar projections in a manner which improves the attentional mechanism which might also allow for the parallel processing of the attentional system [108]. This leads us to believe that there is an association between the activation of the amygdala and enhanced attention, as well as showing that information retention can be enhanced through salience [32]. Emotionally stimulating events do actually tend to result in attentional bias during memory encoding [32], as they also trigger adrenal stress hormone release. This then leads to activation of β‐noradrenergic receptors in the BLA, subsequently resulting in the release of epinephrine and glucocorticoids in the BLA. These processes, and more essentially the release of these hormones enhance memory consolidation of emotional events or experiences [109]. This has now served as evidence of the consolidation of new memory being triggered by emotionally arousing experiences. Therefore, it can be inferred from this discovery that the modulation of the effects of the release of these stress hormones and stress‐activated neurotransmitters associated with the activation of the amygdala can enhance memory consolidation [32].

As mentioned earlier, emotion, just like stress, heavily influences cognitive processes and functions in humans. Emotion is known to aid in the encoding of information into memory as well as in its retrieval. However, emotion has varying effects on memory, as it could either enhance or limit memory functions depending on a range of circumstances and factors [32]. Even though it has been well established that emotions play a role in learning and memory (retention and recall) [32], studies have also shown that specifically positive emotions enhance academic learning and memory by means of self‐motivation and personal satisfaction with the learning content [110]. This is apparently mediated by the reward‐motivation system of the amygdala [2].

Studies that have investigated the underlying neuronal mechanisms of the emotional processing of valence and arousal have identified the amygdala and the prefrontal cortex as the main brain regions involved [32]. While the PFC responds to the emotional valence of non‐arousing stimuli, the amygdala is concerned with response to emotionally arousing stimuli. The emotional stimuli typically used in the relevant neuroimaging studies are typically emotional images and some other kinds of visual emotional stimuli. [32]. While attentional components of learning and memory improve perceptual processing [108], motivational components trigger a state of curiosity which in turn stimulates the brain to learn and remember [111]. Using various attentional tasks, experimental studies have investigated the attentional processing of information of emotional valence for encoding and retrieval of memory [112], and they have shown evidence for the biased attentional processing towards content that is emotionally‐stimulating [32].

Findings from another study by D’Mello et al. have also interestingly shown that confusion [113], which is more of a negative learning‐centered state rather than a typical emotion, can also facilitate learning and memory in an academic setting through an increased attentional focus. If the new information being learned is incongruent with what one already knows from one’s LTM, it creates a state of cognitive disequilibrium, which could induce the emotional states of “rage” and “seeking”, but with an enhanced activation of the latter and minimal activation of the former for this to be effective [32]. This explains how this state of confusion, through curiosity, is likely to drive a motivated student to seek understanding, leading to enhanced learning.

At the core of these studies that examine the effects of emotions and stress on memory and learning are key neuroimaging tools such as fMRI, PET, and functional near‐infrared spectroscopy (fNIRS). Since each technique has its strengths and weaknesses, using these techniques in an integrated, yet selective manner may yield exceptionally optimized results [32]. Also, since the findings from such neuroimaging studies have also informed a better understanding of the influence of emotion on learning and memory, they are therefore valuable in serving as the basis for the design of efficient educational or academic curricula necessary for having a learning environment that is most conducive [32]. That stress and emotion, however, do not always trigger strong memories of new information simply cannot be overemphasized, as evidence has been shown that under certain conditions associated with mood and chronic stress, stress and emotion can impair working memory and long‐term memory [84].

2.4 Synaptic plasticity

Synaptic plasticity is essentially an activity‐dependent change in the strength of neuronal connections. The response elicited in a post‐synapse due to some pre‐synaptic activity indicates the strength of a synaptic connection [114]. The connectivity of synapses can also be fine‐tuned through synaptic scaling [115]. Synaptic plasticity is key in the modification of neural networks and underlies the mechanisms of learning and memory [116, 117]. It is widely believed that changes in synaptic strengths are the principal mechanisms underlying the encoding of memory traces and subsequent storage in the central nervous system. Cortical spindles typically enhance the integration of new memories into LTM storage by enhancing plasticity in the cortex [118]. This proffers the benefit of later recall [34]. Recently, computational studies seem to have corroborated synaptic plasticity as an important component of learning and memory functions [119].

As models of Hebbian synaptic plasticity, long‐term potentiation (LTP) and long‐term depression (LTD) show that molecular changes in synapses can drive the plasticity of existing synapses, which is essential for learning and memory mechanisms [120]. Long‐term potentiation enhances synaptic strength, while long‐term depression decreases synaptic strength. LTP at the connections between the cingulate gyrus and the association cortex leads to synaptic memory consolidation [2]. Through LTP, the neural networks between the hippocampal and cortical neurons are strengthened as a result of a protein cascade in the cortical neurons [2]. During LTP, α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazolepropionic acid receptors (AMPARs) are inserted into synapses, and are removed from synapses during LTD [121 –123]. Tan et al. revealed that glutamate receptor interacting protein 1 (GRIP1), a scaffolding protein which binds and AMPARs and regulates their trafficking and targeting at synapses promotes LTP and hence beneficial for learning and memory [123]. Hippocampal LTD, on the other hand, is thought to be responsible for the clearing of old memory traces [124].

Knowledge of the roles of non‐neuronal key players of plasticity including the extracellular matrix (ECM) and glial cells at synapses gives a better appreciation of the complexity, dynamism and transience of the synaptic structure, and presents a rather interesting frontier for the study and enhancement of learning and memory [120, 125, 126]. This is based on evidence that suggests that “ramified” microglia that have long been thought to be quiescent are actually not, and are instead dynamic and highly plastic, most likely through cytokine and growth factor release [120]. Morris et al. posit that maintaining the ramified state of microglia will promote structural and synaptic plasticity essential for cognitive functions [120]. They also proffer the idea that a change from their ramified state and function could lead to a disruption in the normal synaptic function which is characteristic of neurodegenerative diseases like Alzheimer’s disease and Parkinson’s disease.

Microglia cells also play a key role in synaptic pruning which occurs when synaptic elimination occurs at a faster rate than synaptic formation [120]. An important study has demonstrated that synaptic elimination occurs during contextual fear conditioning when neurons in the hippocampus are activated [127]. From a study investigating the effects of chondroitinase ABC (ChABC), it was observed that intra‐amygdalar injection of ChABC made subsequently acquired fear memories prone to erasure [128]. A similarly interesting finding from another study also showed that intra‐amygdalar injections of ChABC promoted the extinction of heroin‐ and cocaine‐seeking behavior and prevented the drug‐induced reinstatement of such behavior, or basically relapse [129]. From the results from the experimental study by Inman et al. [30], it was posited that briefly stimulating the amygdala triggered some molecular cascades associated with synaptic plasticity, explaining the enhancement of memory over a long period of time. The assumption is that increased glutamate release triggers the upregulation of the induction of some key synaptic molecular changes at amygdalohippocampal synapses.

Also, the plasticity of the ECM affords ECM molecules derived from neuronal and glial cells the ability to modulate synaptic plasticity. These ECM molecules may serve as fine targets for synapse‐plasticizing drugs with the potential to enhance memory and learning or to restore certain cognitive functions. The dysregulation of these ECM molecules has also been implicated in some psychiatric and cognitive disorders [130]. Perineuronal nets (an organization of chondroitin sulfate proteoglycans) and tenascin‐R are important ECM structures. The chondroitin sulfate proteoglycans (CSPGs) that form perineuronal nets (PNNs) in the amygdala are associated with the fear memory formation [128, 130]. The importance of the ECM to memory and learning functions and processes simply cannot be overstated, as ECM digestion has been shown to impair memory acquisition and is also capable of boosting reversal learning [130]. The removal of the ECM did, however, not seem to influence initial learning or already established memory [131].

Currently, there is some evidence that the elevation of brain magnesium may significantly influence learning and memory positively, in a study by Slutsky et al. performed on rats [132]. The focus of the study was on how nutritional and environmental conditions affect cognitive functions of learning and memory. A significant improvement in learning abilities, working memory and long‐term memory was observed when rats were treated with magnesium‐L‐threonate (MgT). This was due to the burgeoning of functional presynaptic release sites in a manner that selectively enhanced the synaptic transmission for burst inputs, subsequently resulting in the enhancement of synaptic plasticity by the correlated inputs through the combined effects of short‐term synaptic facilitation and long‐term potentiation.

As far as the probable role of protein kinase M‐ζ (PKM‐ζ) in the promotion of long‐term memory is concerned, the activation of PKM‐ζ, an isoform of protein kinase C (PKC) in the brain was previously thought to mediate the maintenance of LTP and long‐term memory [133] due to findings which affirmed this assumption based on the observed in vivo and in vitro reversal of established LTP stemming from the use of a synthetic zeta inhibitory peptide (ZIP) to inhibit the activity of PKM‐ζ. It was, however, not until later that a finding by Volk et al. [134] was able to establish that the reversal of LTP was more likely influenced by the ZIP rather than PKM‐ζ as there were no deficits observed the hippocampal‐dependent learning and memory tasks in both normal and conditional PKC‐ζ/PKM‐ζ knockout mice. Also, ZIP still had a reversal effect on LTP even in the PKC‐ζ/PKM‐ζ knockout mice.

Interestingly, through synaptic plasticity induced by intracellular mechanisms, drug‐induced signals like dopamine release can be transformed into long‐term neural functional changes and hence result in remodeled neuronal circuits [135, 136]. Essentially, the drug cues and behavior get encoded and consolidated into LTM. Aside pre‐drug use cues that could trigger relapse, stress could also trigger relapse. Since stress and essentially stress hormones influence the reward pathways, they can trigger dopamine just as addictive drugs can [137]. The “pathological learning model of addiction” seems to be compelling in showing how the behavior of addicts can be associated with the reward‐related learning that is mediated by dopamine. [138, 139].

Neuroplasticity has afforded specifically designed cognitive training programs the ability to address the problem of waning cognitive functions in older or aging people, as demonstrated in a randomized, control study by Manhcke et al., where the subjects showed an enhancement in learning and memory after the training program which engaged brain plasticity, while the control group of subjects exhibited no significant change in memory function [140]. However, some of these training programs may only elicit effects that are not very long term, thereby somewhat impugning their efficacy. Interestingly, the findings from a study by Zehnder et al. who were investigating the effects of plasticity‐based memory training programs for old aged people evinced that there are limitations and uncertainties with regards to how effective memory training programs for older people really are [141].

3 Challenges and prospects

3.1 Brain stimulation

Inasmuch as brain stimulation can be used to enhance memory, direct stimulation of the hippocampus is known to be capable of disrupting memory [142 –144]. This may however be likely to happen when the stimulation of many hippocampal neurons exceeds the acceptable threshold, negatively impacting the hippocampal neural circuitry that mediate learning and memory [142,143]. The nature of the stimulation rather than the number of neurons stimulated could also be responsible for the apparent disruption in memory [31]. Suthana and Fried proposed that future studies have to determine the maximal level of hippocampal neuronal populations that need to be stimulated without exceeding the threshold to offset the chances of counterproductively disrupting memory [31].

There are also challenges with the feasibility of hippocampal or MTL‐stimulation with non‐invasive brain stimulating techniques. One challenge with TMS and tDCS as noninvasive electrical brain stimulation techniques is that they seem to be limited to just large cortical surfaces such that it can sometimes be unclear the specific neural mechanisms that are elicited in response to the stimulation as seen in the work by Nitsche et al. where a large area like the temporal lobe was apparently stimulated by the tDCS [145]. Future work with these techniques ought to improve on focal modalities [31].

Also, although there is precedence for the use of brain‐stimulating implants for therapeutic effects of safely treating some neurological disorders [30], there is apparently inconclusive data on the general practicality and effectiveness of such an approach for the enhancement of human cognitive functions of learning and memory [33, 38, 146 –148], although that is not to say it is impossible. Interestingly, despite being a potent tool for studying brain function and being useful in brain stimulation studies, the combination of EEG and fMRI has also proven to be technically challenging [149].

3.2 Effects of sleep

Memory reactivation during sleep can be enhanced by certain external cues. This is practically beneficial, as learning with some background (olfactory or auditory) stimuli like some particular smell or sounds could help bias memory replay during sleep when there is re‐exposure to those stimuli which act as memory cues [34, 150 –153]. These memory reactivation cues could, however, have a counterproductive effect when re‐exposed to the individual during wakefulness rather than during sleep, as they have the potential to render the memory trace labile [154]. To optimize the beneficial effect of sleep on learning and memory, the interval between learning and sleep should be shorter rather than longer.

Another challenge faced by researchers in optimizing the effects of sleep to enhance memory processing during sleep is that approaches that seek to go beyond the certain boundaries primarily face the restraints of ethics and methodology that have been outlined by Diekelmann [155].

3.3 Effects of stress and emotion

This approach of learning and memory enhancement faces a key challenge with regards to the translational gaps that exist in relating the findings in tested rodents to human memory that is not necessarily hippocampus‐dependent. Examining the human response to stress to enhance declarative memory and the measurement of such memory presents a focus for prospective studies. [90]. This will be essential for optimally leveraging stress effects on memory to inform effective memory enhancement interventions.

Some of the challenges associated with adding an emotional component to the neutral learning material for students as suggested by Vogel and Schwabe [82] is that it may condition the student to be biased towards that route of memory consolidation. This may, as a result, lead to an increased susceptibility to the effects of PTSD [156], as the individual may struggle to lose such stressful and traumatic memories.

Despite the availability of knowledge on the impact stress has on learning and memory, deeper insights are still needed on the finer details. It is still unclear how or whether different types or intensities of stressors elicit different effects on the modulation of memory. Also, the clear distinction between the effects of stress on the various types of long‐term memory is yet to be established. It is also quite important to conclusively establish how long the effects of stress on memory lasts, and what could account for the variations from person to person.

Finally, since acute stress is known to have the potential of either enhancing or impairing the cognitive functions of learning and memory, caution must be taken to always ensure the avoidance of counterproductive outcomes for stress effects to have any useful bearing.

3.4 Synaptic plasticity

Experimental assessments of synaptic plasticity have over the years mainly focused on in vitro preparations. Another problem has been that of extreme inconsistency in results from these experiments stemming from the difficulty of perfectly recreating the various conditions in the brains of behaving animals [119]. That is however not to say that the in vitro experiments serve no purpose. It is simply expedient that prospective work focusses more on in vivo experiments for the determination of synaptic plasticity rules and their modifications during learning [119].

Despite knowing that ECM digestion can lead to the inhibition of the acquisition of new memories and that even a partial disassembly of ECM aggregates could also result in the same condition [130], it is however difficult to tell whether this observation is particularly as a result of the loss of a target molecule or its binding partners, therefore making it necessary to have rescue experiments involving the reintroduction of the target molecule [157] or its functional domains.

Morris et al. also proffer that prospective research into learning and memory should focus on the role of microglia at synapses [120]. And such, research should ideally employ cellular, molecular, physiological and behavioral approaches alongside neuroimaging techniques to establish a causal relationship between the role of microglia and cognitive brain function and neurological disorders. The roles of microglia and astrocytes in the brain and in the mechanisms of synaptic plasticity that underpin learning and memory should be explored in both the healthy and diseased brains. Through the release of tumor necrosis factor (TNF), human astrocytes have the potential to better enhance cognitive functions than other mammalian astrocytes [158]. They also have been shown to create a feedback loop on synaptic transmission through their continual increase in the intracellular concentration of Ca²⁺ in response to synaptic transmission [159].

4 Conclusions

Human learning and memory are undoubtedly essential cognitive functions. Fortunately, thanks to scientific research, we have some level of understanding today of how these cognitive functions work and how they can be enhanced. Despite looking very promising, the four broad areas for the study and enhancement of human learning and memory that have been discussed in this review can be counterproductive by impairing memory or simply be ineffective if certain optimal conditions are not met.

Rather than view these avenues as isolated areas, their effectiveness would be better appreciated when cognizance is taken of the apparent interplay among them. For instance, brain stimulation and the emotionality of learning content can positively influence sleep‐dependent consolidation of memory which in turn is also dependent on synaptic potentiation in the brain during sleep. Also, the role of sleep in the downscaling and renormalizing of synaptic weights, the role of emotion in establishing relevance of learning material to promote sleep‐dependent consolidation of memory, the pharmacological use of cortisol, a stress hormone, to boost memory of emotional content, and the triggering of molecular cascades associated with synaptic plasticity in response to amygdalar stimulation reveal the interconnectedness of these avenues in promoting learning and memory.

Adequate and uninterrupted sleep shortly following learning, the incorporation of emotional content into neutral learning material, learning with some background stimuli and making subsequent use of such non‐disturbing stimuli as memory cues during sleep, the use of safe and effective drugs designed to target ECM molecules to promote LTP, the use of an effective and appropriately‐designed amygdala‐stimulating apparatus, and many more specific approaches could be employed in a selective yet integrative manner that may proffer maximal and optimal benefits to an individual with respect to the enhancement of learning and memory. Despite the obvious challenges with some of the outlined approaches, we can be hopeful of making some significant progress in the years ahead.

Footnotes

Conflict of interests

The contributing author reports no conflict of interests in this work.

Funding

There is no funding support for this article.

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Advances in the understanding and enhancement of the human cognitive functions of learning and memory

Abstract

Keywords

1 Introduction

2 What we know so far

2.1 Brain stimulation

2.2 Effects of sleep

2.3 Effects of stress and emotion

2.4 Synaptic plasticity

3 Challenges and prospects

3.1 Brain stimulation

3.2 Effects of sleep

3.3 Effects of stress and emotion

3.4 Synaptic plasticity

4 Conclusions

Footnotes

Conflict of interests

Funding

References