When memories get complex, sleep comes to their rescue

Here I point to a PNAS article by Lutz et al. and a commentary on the work by Schechtman. Here is the Lutz. et al. abstract:

Significance

Real-life events usually consist of multiple elements such as a location, people, and objects that become associated during the event. Such associations can differ in their strength, and some elements may be associated only indirectly (e.g., via a third element). Here, we show that sleep compared with nocturnal wakefulness selectively strengthens associations between elements of events that were only weakly encoded and of such that were not encoded together, thus fostering new associations. Importantly, these sleep effects were associated with an improved recall of the complete event after presentation of only a single cue. These findings uncover a fundamental role of sleep in the completion of partial information and are critical for understanding how real-life events are processed during sleep.

Abstract

Sleep supports the consolidation of episodic memory. It is, however, a matter of ongoing debate how this effect is established, because, so far, it has been demonstrated almost exclusively for simple associations, which lack the complex associative structure of real-life events, typically comprising multiple elements with different association strengths. Because of this associative structure interlinking the individual elements, a partial cue (e.g., a single element) can recover an entire multielement event. This process, referred to as pattern completion, is a fundamental property of episodic memory. Yet, it is currently unknown how sleep affects the associative structure within multielement events and subsequent processes of pattern completion. Here, we investigated the effects of post-encoding sleep, compared with a period of nocturnal wakefulness (followed by a recovery night), on multielement associative structures in healthy humans using a verbal associative learning task including strongly, weakly, and not directly encoded associations. We demonstrate that sleep selectively benefits memory for weakly associated elements as well as for associations that were not directly encoded but not for strongly associated elements within a multielement event structure. Crucially, these effects were accompanied by a beneficial effect of sleep on the ability to recall multiple elements of an event based on a single common cue. In addition, retrieval performance was predicted by sleep spindle activity during post-encoding sleep. Together, these results indicate that sleep plays a fundamental role in shaping associative structures, thereby supporting pattern completion in complex multielement events.

Brains creating stories of selves: the neural basis of autobiographical reasoning

We all create our experienced selves from autobiographical reasoning based on remembered events in stories from our lives. In the journal Social Cognitive and Affective Neuroscience  D'Argembeau et al.  (open source) do an interesting fMRI study observing brain areas that are active during this process that are not recruited by more simple factual recall of the events.

...A few days before the scanning session, participants selected a set of memories that have been important in developing and sustaining their sense of self and identity (self-defining memories). During scanning, we instructed participants to approach each of their memories in two different ways: in some trials, they had to remember the concrete content of the event in order to mentally re-experience the situation in its original context (autobiographical remembering), whereas in other trials they were asked to reflect on the broader meaning and implications of their memory (autobiographical reasoning). Contrasting the neural activity associated with these two ways of approaching the same self-defining memories allowed us to identify the brain regions specifically involved in the autobiographical reasoning process.

The text of the article notes the functions of the brain areas mentioned in the article abstract (below) and has a nice graphic depiction of areas that were more active during autobiographical remembering compared with autobiographical reasoning versus areas that were more active during autobiographical reasoning compared with autobiographical remembering.  Here is the abstract:

Personal identity critically depends on the creation of stories about the self and one’s life. The present study investigates the neural substrates of autobiographical reasoning, a process central to the construction of such narratives. During functional magnetic resonance imaging scanning, participants approached a set of personally significant memories in two different ways: in some trials, they remembered the concrete content of the events (autobiographical remembering), whereas in other trials they reflected on the broader meaning and implications of their memories (autobiographical reasoning). Relative to remembering, autobiographical reasoning recruited a left-lateralized network involved in conceptual processing [including the dorsal medial prefrontal cortex (MPFC), inferior frontal gyrus, middle temporal gyrus and angular gyrus]. The ventral MPFC—an area that may function to generate personal/affective meaning—was not consistently engaged during autobiographical reasoning across participants but, interestingly, the activity of this region was modulated by individual differences in interest and willingness to engage in self-reflection. These findings support the notion that autobiographical reasoning and the construction of personal narratives go beyond mere remembering in that they require deriving meaning and value from past experiences.

How sleep shapes what we remember and forget.

I have found monitoring the quality of my sleep to be a fascinating and useful activity. I use both the Oura ring and Apple watch to monitor body temperature, body movement, heart rate, and heart rate variability, and then compare their different (but broadly similar) algorithmic estimates of deep sleep, REM sleep, non-REM sleep, and wake periods. I'm on the lookout for articles on sleep during my scans of journals' tables of contents, and have come upon this review by Sakai of what is happening in our sleep to be concise and useful. Below is a more general overview from edited and rearranged clips (The article goes into more electrophysiological and cellular details):

 

(image credit Dave Cutler)

...memory at the beginning of the consolidation process is very much anchored in hippocampal networks, and in the end of this process, it primarily resides in neocortical networks...New memories are rich with contextual clues such as the time, place, and sensory details of an experience...as memories get encoded in the cortex, many of those spatial and temporal details fade...forgetting—through weakening or loss of synapses—seems to play a key role in the process of memory consolidation, especially during sleep... What remains are the elements representing the essential core of the memory. When learning how to drive, for example, the movements needed to steer and brake are critical; the details of avoiding a specific car on a particular outing are not...sleep’s role in memory is not simply about passive storage. Rather..a more active process of consolidation that extracts key information and forms a generalized version of the overall memory that can later be accessed and applied to relevant situations.

Sleep in mammals has distinct phases as characterized by specific EEG patterns. These include brain-wide slow oscillations (less than 1 Hz in frequency), sharp-wave ripples (100-300 Hz) in the hippocampus, and spindles (10-15 Hz), which are related to the firing of neurons in the circuits connecting the thalamus and the cortex. Upon onset of sleep, the brain enters a non-rapid eye movement (non-REM) phase. During non-REM sleep, slow oscillations sweep across large regions of the brain, punctuated by swells of spindles and bursts of sharp wave-ripples. A period of rapid eye movement (REM) sleep follows, with characteristic bursts of its namesake eye movements and low-amplitude theta oscillations around 4-8 Hz. The brain cycles through these phases throughout the sleep period, with slow-wave, non-REM sleep dominating the early hours and REM sleep the late hours.

There are...

...distinct roles of different stages of sleep in memory formation. Non-REM sleep has been shown to be very important for consolidation of declarative memories—those based on recall of information—while REM sleep seems to play a larger part in procedural or task-based memories...this may relate to the degree of synaptic change required. For declarative memories, most of the foundational learning has already taken place; remembering a new fact likely requires only small changes in synaptic strengths. By contrast, procedural memories require a massive amount of synaptic change...If you want to learn how to ride a bike, or how to play capoeira … it's not like learning a new name...I’s weeks, months, years of work. And so it seems like REM sleep is really, really necessary to do this long-term persistent synaptic change.”

A smart phone intervention that enhances memory in older adults.

Martin et al.  offer an open source article that describes a smartphone intervention that enhances real-world memory and promotes differentiation of hippocampal activity in older adults.  I have downloaded the HippoCamera smartphone App described in the text from the Apple App Store, and found a research passcode is required, for which the following clip of text from the article is relevant: "As of the time of writing, this is a research-dedicated application that requires an access code that can be obtained from a corresponding author."

Significance

The ability to vividly recollect our past declines with age, a trend that negatively impacts overall well-being. We show that using smartphone technologies to record and replay brief but rich memory cues from daily life can improve older adults’ ability to reexperience the past. This enhancement was associated with corresponding changes in the way memories were stored in the brain. Functional neuroimaging showed that repeatedly replaying memory cues drove memories apart from one another in the hippocampus, a brain region with well-established links to memory function. This increase in differentiation likely facilitated behavior by strengthening memory and minimizing competition among different memories at retrieval. This work reveals an easy-to-use intervention that helps older adults better remember their personal past.

Abstract

The act of remembering an everyday experience influences how we interpret the world, how we think about the future, and how we perceive ourselves. It also enhances long-term retention of the recalled content, increasing the likelihood that it will be recalled again. Unfortunately, the ability to recollect event-specific details and reexperience the past tends to decline with age. This decline in recollection may reflect a corresponding decrease in the distinctiveness of hippocampal memory representations. Despite these well-established changes, there are few effective cognitive behavioral interventions that target real-world episodic memory. We addressed this gap by developing a smartphone-based application called HippoCamera that allows participants to record labeled videos of everyday events and subsequently replay, high-fidelity autobiographical memory cues. In two experiments, we found that older adults were able to easily integrate this noninvasive intervention into their daily lives. Using HippoCamera to repeatedly reactivate memories for real-world events improved episodic recollection and it evoked more positive autobiographical sentiment at the time of retrieval. In both experiments, these benefits were observed shortly after the intervention and again after a 3-mo delay. Moreover, more detailed recollection was associated with more differentiated memory signals in the hippocampus. Thus, using this smartphone application to systematically reactivate memories for recent real-world experiences can help to maintain a bridge between the present and past in older adults.

The neurophysiology of consciousness - neural correlates of qualia

This is a post for consciousness mavens.Tucker, Luu, and Johnson have offered a neurophyiological model of consciousness, Neurophysiological mechanisms of implicit and explicit memory in the process of consciousness. The open source article has useful summary graphics, and embraces the 'Hard Problem' of consciousness - the nature of 'qualia' (how it feels to see red, eat an apple, etc.) Here I pass on brief, and then more lengthy, paragraphs on what the authors think is new and noteworthy about their ideas.

The process of consciousness, generating the qualia that may appear to be irreducible qualities of experience, can be understood to arise from neurophysiological mechanisms of memory. Implicit memory, organized by the lemnothalamic brain stem projections and dorsal limbic consolidation in REM sleep, supports the unconscious field and the quasi-conscious fringe of current awareness. Explicit memory, organized by the collothalamic midbrain projections and ventral limbic consolidation of NREM sleep, supports the focal objects of consciousness.

Neurophysiological mechanisms are increasingly understood to constitute the foundations of human conscious experience. These include the capacity for ongoing memory, achieved through a hierarchy of reentrant cross-laminar connections across limbic, heteromodal, unimodal, and primary cortices. The neurophysiological mechanisms of consciousness also include the capacity for volitional direction of attention to the ongoing cognitive process, through a reentrant fronto-thalamo-cortical network regulation of the inhibitory thalamic reticular nucleus. More elusive is the way that discrete objects of subjective experience, such as the color of deep blue or the sound of middle C, could be generated by neural mechanisms. Explaining such ineffable qualities of subjective experience is what Chalmers has called “the hard problem of consciousness,” which has divided modern neuroscientists and philosophers alike. We propose that insight into the appearance of the hard problem can be gained through integrating classical phenomenological studies of experience with recent progress in the differential neurophysiology of consolidating explicit versus implicit memory. Although the achievement of consciousness, once it is reflected upon, becomes explicit, the underlying process of generating consciousness, through neurophysiological mechanisms, is largely implicit. Studying the neurophysiological mechanisms of adaptive implicit memory, including brain stem, limbic, and thalamic regulation of neocortical representations, may lead to a more extended phenomenological understanding of both the neurophysiological process and the subjective experience of consciousness.

Sleep preferentially consolidates negative aspects of human emotional memory

The Nov. 1, 2022 issue of PNAS has a special feature on Sleep, Brain, and Cognition. A large body of research suggests that sleep benefits memory, and I want to point in particular to an article by Denis et al. showing that sleep preferentially consolidates negative aspect of emotional memory. They also found that while research participants demonstrated better memory for positive objects compared to their neutral backgrounds, sleep did not modulate this effect.  

Significance

Recent research has called into question whether sleep improves memory, especially for emotional information. However, many of these studies used a relatively small number of participants and focused only on college student samples, limiting both the power of these findings and their generalizability to the wider population. Here, using the well-established emotional memory trade-off task, we investigated sleep’s impact on memory for emotional components of scenes in a large online sample of adults ranging in age from 18 to 59 y. Despite the limitations inherent in using online samples, this well-powered study provides strong evidence that sleep selectively consolidates negative emotional aspects of memory and that this effect generalizes to participants across young adulthood and middle age.

Abstract

Research suggests that sleep benefits memory. Moreover, it is often claimed that sleep selectively benefits memory for emotionally salient information over neutral information. However, not all scientists are convinced by this relationship [e.g., J. M. Siegel. Curr. Sleep Med. Rep., 7, 15–18 (2021)]. One criticism of the overall sleep and memory literature—like other literature—is that many studies are underpowered and lacking in generalizability [M. J. Cordi, B. Rasch. Curr. Opin. Neurobiol., 67, 1–7 (2021)], thus leaving the evidence mixed and confusing to interpret. Because large replication studies are sorely needed, we recruited over 250 participants spanning various age ranges and backgrounds in an effort to confirm sleep’s preferential emotional memory consolidation benefit using a well-established task. We found that sleep selectively benefits memory for negative emotional objects at the expense of their paired neutral backgrounds, confirming our prior work and clearly demonstrating a role for sleep in emotional memory formation. In a second experiment also using a large sample, we examined whether this effect generalized to positive emotional memory. We found that while participants demonstrated better memory for positive objects compared to their neutral backgrounds, sleep did not modulate this effect. This research provides strong support for a sleep-specific benefit on memory consolidation for specifically negative information and more broadly affirms the benefit of sleep for cognition.

Musical rhythm training improves short-term memory for faces

From Zanto et al:  

Significance

Musical training can improve numerous cognitive functions associated with musical performance. Yet, there is limited evidence that musical training may benefit nonmusical tasks and it is unclear how the brain may enable such a transfer of benefit. To address this, nonmusicians were randomized to receive 8 wk of either musical rhythm training or word search training. Memory for faces was assessed pre- and post-training while electroencephalography data were recorded to assess changes in brain activity. Results showed that only musical rhythm training improved face memory, which was associated with increased activity in the superior parietal region of the brain when encoding and maintaining faces. Thus, musical rhythm training can improve face memory by facilitating how the brain encodes and maintains memories.

Abstract

Playing a musical instrument engages numerous cognitive abilities, including sensory perception, selective attention, and short-term memory. Mounting evidence indicates that engaging these cognitive functions during musical training will improve performance of these same functions. Yet, it remains unclear the extent these benefits may extend to nonmusical tasks, and what neural mechanisms may enable such transfer. Here, we conducted a preregistered randomized clinical trial where nonmusicians underwent 8 wk of either digital musical rhythm training or word search as control. Only musical rhythm training placed demands on short-term memory, as well as demands on visual perception and selective attention, which are known to facilitate short-term memory. As hypothesized, only the rhythm training group exhibited improved short-term memory on a face recognition task, thereby providing important evidence that musical rhythm training can benefit performance on a nonmusical task. Analysis of electroencephalography data showed that neural activity associated with sensory processing and selective attention were unchanged by training. Rather, rhythm training facilitated neural activity associated with short-term memory encoding, as indexed by an increased P3 of the event-related potential to face stimuli. Moreover, short-term memory maintenance was enhanced, as evidenced by increased two-class (face/scene) decoding accuracy. Activity from both the encoding and maintenance periods each highlight the right superior parietal lobule (SPL) as a source for training-related changes. Together, these results suggest musical rhythm training may improve memory for faces by facilitating activity within the SPL to promote how memories are encoded and maintained, which can be used in a domain-general manner to enhance performance on a nonmusical task.

Lasting improvements in seniors’ working and long-term memory with repetitive neuromodulation

From Grover et al., an open source article in which details of their transcranial alternating current stimulation (tACS) protocols are given:

The development of technologies to protect or enhance memory in older people is an enduring goal of translational medicine. Here we describe repetitive (4-day) transcranial alternating current stimulation (tACS) protocols for the selective, sustainable enhancement of auditory–verbal working memory and long-term memory in 65–88-year-old people. Modulation of synchronous low-frequency, but not high-frequency, activity in parietal cortex preferentially improved working memory on day 3 and day 4 and 1 month after intervention, whereas modulation of synchronous high-frequency, but not low-frequency, activity in prefrontal cortex preferentially improved long-term memory on days 2–4 and 1 month after intervention. The rate of memory improvements over 4 days predicted the size of memory benefits 1 month later. Individuals with lower baseline cognitive function experienced larger, more enduring memory improvements. Our findings demonstrate that the plasticity of the aging brain can be selectively and sustainably exploited using repetitive and highly focalized neuromodulation grounded in spatiospectral parameters of memory-specific cortical circuitry.

Animals (including us) conjure model-based structures from random events

Superstitious learning is usually thought to be accounted for by conditioned association, but Jin et al. now show that monkeys can develop more complex cognitive structures independent of reinforcement:  

Significance

Past studies on learning and decision-making usually rely on the assumption that the task is learnable. However, humans and other animals often infer spurious relationships from coincidental associations, and it is unknown if this could be achieved without reward conditioning. Here, we exposed monkeys to sets of images that had a hidden hierarchical order and to unordered sets that lacked an underlying structure. Monkeys treated the unordered sets as if they had a hierarchical order even under reward schedules that incentivized random choices. The results cannot be explained by simple associative mechanisms that account for other types of spurious learning, suggesting that when presented with random events animals conjure elaborate model-based structures.

Abstract

Humans and other animals often infer spurious associations among unrelated events. However, such superstitious learning is usually accounted for by conditioned associations, raising the question of whether an animal could develop more complex cognitive structures independent of reinforcement. Here, we tasked monkeys with discovering the serial order of two pictorial sets: a “learnable” set in which the stimuli were implicitly ordered and monkeys were rewarded for choosing the higher-rank stimulus and an “unlearnable” set in which stimuli were unordered and feedback was random regardless of the choice. We replicated prior results that monkeys reliably learned the implicit order of the learnable set. Surprisingly, the monkeys behaved as though some ordering also existed in the unlearnable set, showing consistent choice preference that transferred to novel untrained pairs in this set, even under a preference-discouraging reward schedule that gave rewards more frequently to the stimulus that was selected less often. In simulations, a model-free reinforcement learning algorithm (Q-learning) displayed a degree of consistent ordering among the unlearnable set but, unlike the monkeys, failed to do so under the preference-discouraging reward schedule. Our results suggest that monkeys infer abstract structures from objectively random events using heuristics that extend beyond stimulus–outcome conditional learning to more cognitive model-based learning mechanisms.

Dissecting and improving motor skill acquisition in older adults

 From the introduction of Elvira et al. (open source):

We designed a study intended to identify (i) the main factors leading to differences in motor skill acquisition with aging and (ii) the effect of applying noninvasive brain stimulation during motor training. Comparing different components of motor skill acquisition in young and older adults, constituting the extremes of performance in this study, we found that the improvement of the sequence-tapping task is maximized by the early consolidation of the spatial properties of the sequence in memory (i.e., sequence order), leading to a reduced error of execution, and by the optimization of its temporal features (i.e., chunking). We found the consolidation of spatiotemporal features to occur early in training in young adults, suggesting the emergence of motor chunks to be a direct consequence of committing the sequence elements to memory. This process, seemingly less efficient in older adults, could be partially restored using atDCS by enabling the early consolidation of spatial features, allowing them to prioritize the increase of their speed of execution, ultimately leading to an earlier consolidation of motor chunks. This separate consolidation of spatial and temporal features seen in older adults suggests that the emergence of temporal patterns, commonly identified as motor chunks at a behavioral level, stem from the optimization of the execution of the motor sequence resulting from practice, which can occur only after the sequence order has been stored in memory.

Here is their abstract:

Practicing a previously unknown motor sequence often leads to the consolidation of motor chunks, which enable its accurate execution at increasing speeds. Recent imaging studies suggest the function of these structures to be more related to the encoding, storage, and retrieval of sequences rather than their sole execution. We found that optimal motor skill acquisition prioritizes the storage of the spatial features of the sequence in memory over its rapid execution early in training, as proposed by Hikosaka in 1999. This process, seemingly diminished in older adults, was partially restored by anodal transcranial direct current stimulation over the motor cortex, as shown by a sharp improvement in accuracy and an earlier yet gradual emergence of motor chunks. These results suggest that the emergence of motor chunks is preceded by the storage of the sequence in memory but is not its direct consequence; rather, these structures depend on, and result from, motor practice.

Motor learning without movement

Fascinating work from Kim et al. on the influence of the prediction errors that are essential in calibrating actions of our predictive minds:

Significance

Our brains control aspects of our movements without conscious awareness, allowing many of us to effortlessly pick up a glass of water or wave hello. Here, we demonstrate that this implicit motor system can learn to refine movements that we plan but ultimately decide not to perform. Participants planned to reach to a target but sometimes withheld these reaches while an animation simulated missing the target. Afterward, participants unknowingly reached opposite the direction of the apparent mistake, indicating that the implicit motor system had learned from the animated error. These findings indicate that movement is not strictly necessary for motor adaptation, and we can learn to update our actions without physically performing them.

Abstract

Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to be driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain can generate sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit motor adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for adaptation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial adaptation. Learning following trials without movements persisted even when movement trials had never been paired with errors and when the direction of movement and sensory feedback trajectories were decoupled. These observations indicate that the brain can compute errors that drive implicit adaptation without generating overt movements, leading to the adaptation of motor commands that are not overtly produced.

How the organization of generalized knowledge promotes memory.

From Wing et al.: Significance

What we remember is shaped by what we already know. For example, remembering the angelfish from a recent aquarium visit is easier for those who already know what angelfish are and know things about them. In addition to facilitating memory retrieval of specific items, prior knowledge also supports memory by providing an overarching organizational structure for new information. Here, we show how expert knowledge leads birdwatchers to organize birds based on conceptual features, in contrast to novices who organize birds based on perceptual features. In turn, experts’ organizational structure supports memory by reducing interference typically caused by high overlap among items, even when to-be-remembered birds were unfamiliar species. These findings demonstrate how the organization of generalized knowledge promotes memory.

Abstract

The influence of prior knowledge on memory is ubiquitous, making the specific mechanisms of this relationship difficult to disentangle. Here, we show that expert knowledge produces a fundamental shift in the way that interitem similarity (i.e., the perceived resemblance between items in a set) biases episodic recognition. Within a group of expert birdwatchers and matched controls, we characterized the psychological similarity space for a set of well-known local species and a set of less familiar, nonlocal species. In experts, interitem similarity was influenced most strongly by taxonomic features, whereas in controls, similarity judgments reflected bird color. In controls, perceived episodic oldness during a recognition memory task increased along with measures of global similarity between items, consistent with classic models of episodic recognition. Surprisingly, for experts, high global similarity did not drive oldness signals. Instead, for local birds memory tracked the availability of species-level name knowledge, whereas for nonlocal birds, it was mediated by the organization of generalized conceptual space. These findings demonstrate that episodic memory in experts can benefit from detailed subcategory knowledge, or, lacking that, from the overall relational structure of concepts. Expertise reshapes psychological similarity space, helping to resolve mnemonic separation challenges arising from high interitem overlap. Thus, even in the absence of knowledge about item-specific details or labels, the presence of generalized knowledge appears to support episodic recognition in domains of expertise by altering the typical relationship between psychological similarity and memory.

How exercise supports the brain

From Leiter et al. "Selenium mediates exercise-induced adult neurogenesis and reverses learning deficits induced by hippocampal injury and aging":

Highlights 

• Selenium mediates the exercise-induced increase in adult hippocampal neurogenesis 

• Selenium increases hippocampal precursor proliferation and adult neurogenesis 

• Selenium reverses cognitive decline in aging and in hippocampal injury 

Summary 

Although the neurogenesis-enhancing effects of exercise have been extensively studied, the molecular mechanisms underlying this response remain unclear. Here, we propose that this is mediated by the exercise-induced systemic release of the antioxidant selenium transport protein, selenoprotein P (SEPP1). Using knockout mouse models, we confirmed that SEPP1 and its receptor low-density lipoprotein receptor-related protein 8 (LRP8) are required for the exercise-induced increase in adult hippocampal neurogenesis. In vivo selenium infusion increased hippocampal neural precursor cell (NPC) proliferation and adult neurogenesis. Mimicking the effect of exercise through dietary selenium supplementation restored neurogenesis and reversed the cognitive decline associated with aging and hippocampal injury, suggesting potential therapeutic relevance. These results provide a molecular mechanism linking exercise-induced changes in the systemic environment to the activation of quiescent hippocampal NPCs and their subsequent recruitment into the neurogenic trajectory.

Predictions help neurons, and the brain, learn

From the PNAS Journal Club, a review of a publication by Luczak et. al. that suggest that neurons might be able to predict their own future activity, and learn to improve the accuracy of those predictions. The review expands on the Luczak et al abstract, which I pass on here:

Understanding how the brain learns may lead to machines with human-like intellectual capacities. It was previously proposed that the brain may operate on the principle of predictive coding. However, it is still not well understood how a predictive system could be implemented in the brain. Here we demonstrate that the ability of a single neuron to predict its future activity may provide an effective learning mechanism. Interestingly, this predictive learning rule can be derived from a metabolic principle, whereby neurons need to minimize their own synaptic activity (cost) while maximizing their impact on local blood supply by recruiting other neurons. We show how this mathematically derived learning rule can provide a theoretical connection between diverse types of brain-inspired algorithm, thus offering a step towards the development of a general theory of neuronal learning. We tested this predictive learning rule in neural network simulations and in data recorded from awake animals. Our results also suggest that spontaneous brain activity provides ‘training data’ for neurons to learn to predict cortical dynamics. Thus, the ability of a single neuron to minimize surprise—that is, the difference between actual and expected activity—could be an important missing element to understand computation in the brain.

Unlocking adults’ implicit statistical learning by cognitive depletion

Smalle et al. make the fascinating observation that inhibition of our adult cognitive control system by non-invasive brain stimulation can unleash some of our infant implicit statistical learning abilities - the learning of novel words embedded in a string of spoken syllables. This suggests that adult language learning is antagonized by higher cognitive mechanisms.  

Significance

Statistical learning mechanisms enable extraction of patterns in the environment from infancy to adulthood. For example, they enable segmentation of continuous speech streams into novel words. Adults typically become aware of the hidden words even when passively listening to speech streams. It remains poorly understood how cognitive development and brain maturation affect implicit statistical learning (i.e., infant-like learning without awareness). Here, we show that the depletion of the cognitive control system by noninvasive brain stimulation or by demanding cognitive tasks boosts adults’ implicit but not explicit word-segmentation abilities. These findings suggest that the adult cognitive architecture constrains statistical learning mechanisms that are likely to contribute to early language acquisition and opens avenues to enhance language-learning abilities in adults.

Abstract

Human learning is supported by multiple neural mechanisms that maturate at different rates and interact in mostly cooperative but also sometimes competitive ways. We tested the hypothesis that mature cognitive mechanisms constrain implicit statistical learning mechanisms that contribute to early language acquisition. Specifically, we tested the prediction that depleting cognitive control mechanisms in adults enhances their implicit, auditory word-segmentation abilities. Young adults were exposed to continuous streams of syllables that repeated into hidden novel words while watching a silent film. Afterward, learning was measured in a forced-choice test that contrasted hidden words with nonwords. The participants also had to indicate whether they explicitly recalled the word or not in order to dissociate explicit versus implicit knowledge. We additionally measured electroencephalography during exposure to measure neural entrainment to the repeating words. Engagement of the cognitive mechanisms was manipulated by using two methods. In experiment 1 (n = 36), inhibitory theta-burst stimulation (TBS) was applied to the left dorsolateral prefrontal cortex or to a control region. In experiment 2 (n = 60), participants performed a dual working-memory task that induced high or low levels of cognitive fatigue. In both experiments, cognitive depletion enhanced word recognition, especially when participants reported low confidence in remembering the words (i.e., when their knowledge was implicit). TBS additionally modulated neural entrainment to the words and syllables. These findings suggest that cognitive depletion improves the acquisition of linguistic knowledge in adults by unlocking implicit statistical learning mechanisms and support the hypothesis that adult language learning is antagonized by higher cognitive mechanisms.

Higher performance and fronto-parietal brain activity following active versus passive learning

From a brief open source PNAS report by Stillesjö et al. that has a nice graphic of the fMRI data supporting their observations:

We here demonstrate common neurocognitive long-term memory effects of active learning that generalize over course subjects (mathematics and vocabulary) by the use of fMRI. One week after active learning, relative to more passive learning, performance and fronto-parietal brain activity was significantly higher during retesting, possibly related to the formation and reactivation of semantic representations. These observations indicate that active learning conditions stimulate common processes that become part of the representations and can be reactivated during retrieval to support performance. Our findings are of broad interest and educational significance related to the emerging consensus of active learning as critical in promoting good long-term retention.

Temporal Self-Compression

Brietzke and Meyer (open source) provide behavioral and neural evidence that our past and future selves are compressed as they move away from the present:  

Significance

For centuries, great thinkers have struggled to understand how people represent a personal identity that changes over time. Insight may come from a basic principle of perception: as objects become distant, they also become less discriminable or “compressed.” In Studies 1–3, we demonstrate that people’s ratings of their own personality become increasingly less differentiated as they consider more distant past and future selves. In Study 4, we found neural evidence that the brain compresses self-representations with time as well. When we peer out a window, objects close to us are in clear view, whereas distant objects are hard to tell apart. We provide evidence that self-perception may operate similarly, with the nuance of distant selves increasingly harder to perceive.

Abstract

A basic principle of perception is that as objects increase in distance from an observer, they also become logarithmically compressed in perception (i.e., not differentiated from one another), making them hard to distinguish. Could this basic principle apply to perhaps our most meaningful mental representation: our own sense of self? Here, we report four studies that suggest selves are increasingly non-discriminable with temporal distance from the present as well. In Studies 1 through 3, participants made trait ratings across various time points in the past and future. We found that participants compressed their past and future selves, relative to their present self. This effect was preferential to the self and could not be explained by the alternative possibility that individuals simply perceive arbitrary self-change with time irrespective of temporal distance. In Study 4, we tested for neural evidence of temporal self-compression by having participants complete trait ratings across time points while undergoing functional MRI. Representational similarity analysis was used to determine whether neural self-representations are compressed with temporal distance as well. We found evidence of temporal self-compression in areas of the default network, including medial prefrontal cortex and posterior cingulate cortex. Specifically, neural pattern similarity between self-representations was logarithmically compressed with temporal distance. Taken together, these findings reveal a “temporal self-compression” effect, with temporal selves becoming increasingly non-discriminable with distance from the present.

Drifting nerve assemblies can maintain persistent memories

A prevailing model has been that a memory in our brains is stored in a specific set of nerve connections, that, like a book in a library, stays where it belongs. Over the past few years, however, it has become more and more clear that 'representational plasticity' may be the norm. A recent article by Kossio et al. proposes a contrasting memory model (motivated readers can obtain the whole article from me):

Change is ubiquitous in living beings. In particular, the connectome and neural representations can change. Nevertheless, behaviors and memories often persist over long times. In a standard model, associative memories are represented by assemblies of strongly interconnected neurons. For faithful storage these assemblies are assumed to consist of the same neurons over time. Here we propose a contrasting memory model with complete temporal remodeling of assemblies, based on experimentally observed changes of synapses and neural representations. The assemblies drift freely as noisy autonomous network activity and spontaneous synaptic turnover induce neuron exchange. The gradual exchange allows activity-dependent and homeostatic plasticity to conserve the representational structure and keep inputs, outputs, and assemblies consistent. This leads to persistent memory. Our findings explain recent experimental results on temporal evolution of fear memory representations and suggest that memory systems need to be understood in their completeness as individual parts may constantly change.

Here is an explanatory graphic from the article:

Assembly drift and persistent memory. (A) At two nearby times a similar ensemble of neurons forms the neural representation of, for example, “apple” (compare the blue-colored assembly neurons at the first and the second time point). At distant times the representation consists of completely different ensembles (blue-colored assembly neurons at the first and the third time point). Due to their gradual change, temporally distant representations are indirectly related via ensembles in the time period between them. (B) Parts of a thread possess the same form of indirect relation: Nearby parts are composed of similar ensembles of fibers, while distant ones consist of different ensembles, which are connected by those in between. (C) The complete change of memory representations still allows for stable behavior. In the schematic, a tasty apple is perceived. At different times, this triggers different ensembles that presently form the representation of “apple”; see A. Assembly activation initiates a reaching movement toward the apple, despite the dissimilarity of the activated neuron ensembles. Memory and behavior are conserved because the gradual change of assembly neurons enables the inputs (green) and outputs (orange) to track the neural representation.

People mistake the internet’s knowledge for their own

Fascinating experiments from Adrian Ward:   

Significance

In the current digital age, people are constantly connected to online information. The present research provides evidence that on-demand access to external information, enabled by the internet and search engines like Google, blurs the boundaries between internal and external knowledge, causing people to believe they could—or did—remember what they actually just found. Using Google to answer general knowledge questions artificially inflates peoples’ confidence in their own ability to remember and process information and leads to erroneously optimistic predictions regarding how much they will know without the internet. When information is at our fingertips, we may mistakenly believe that it originated from inside our heads.

Abstract

People frequently search the internet for information. Eight experiments (n = 1,917) provide evidence that when people “Google” for online information, they fail to accurately distinguish between knowledge stored internally—in their own memories—and knowledge stored externally—on the internet. Relative to those using only their own knowledge, people who use Google to answer general knowledge questions are not only more confident in their ability to access external information; they are also more confident in their own ability to think and remember. Moreover, those who use Google predict that they will know more in the future without the help of the internet, an erroneous belief that both indicates misattribution of prior knowledge and highlights a practically important consequence of this misattribution: overconfidence when the internet is no longer available. Although humans have long relied on external knowledge, the misattribution of online knowledge to the self may be facilitated by the swift and seamless interface between internal thought and external information that characterizes online search. Online search is often faster than internal memory search, preventing people from fully recognizing the limitations of their own knowledge. The internet delivers information seamlessly, dovetailing with internal cognitive processes and offering minimal physical cues that might draw attention to its contributions. As a result, people may lose sight of where their own knowledge ends and where the internet’s knowledge begins. Thinking with Google may cause people to mistake the internet’s knowledge for their own.

Watching brain regions that help us anticipate what's going to happen next.

A primary function of the brain is to adaptively use past experience to generate expectations aboutevents that are likely to occur in the future. Lee et al. have used a machine learning model to analyze fMRI measurents made on 30 individuals as they watched repeated viewing of a movie, and a nice summary of this work is presented by the PNAS Journal Club. Areas in the frontal cortex anticipate (possibly foreseeing movie plot changes) up to 15 seconds in advance, while back of the brain cortical areas only anticipate about 1 second ahead. Frontal regions of the brain can keep track of tens of seconds, compared to only a few seconds at the back of the brain. 

Vertical slices of the brain, imaged at different locations, reveal a timescale gradient for anticipation. Timescales are short at the back of the brain (cool blues) and longer at the front (warm reds).

These results demonstrate a hierarchy of anticipatory signals in the human brain and link them to subjective experiences of events...This hierarchical view of the brain is very different from the traditional, modular view,...In the traditional view, there are systems that process raw sensory inputs, such as sights or sounds, and there are separate systems that call up memories or make plans. The latest findings blur the lines between those systems, showing that regions known for processing simple pieces of visual information, such as the visual cortex, can also anticipate what’s coming up soon, even if just by a few seconds.