Consolidation of human skill linked to waking hippocampo-neocortical replay

Construction of ThermoMaze

Physiological changes during awake immobility-related brain states remain one of the great unexplored behavioral states. Controlling periods of awake immobility is challenging because restraining the animal is stressful and is accompanied by altered physiological states. Here, we describe the ThermoMaze, a behavioral paradigm that allows for the collection of large amounts of physiological data while the animal rests at distinct experimenter-determined locations. We found that the paradigm generated long periods of immobility and did not alter the brain temperature. We combined the ThermoMaze with electrophysiology recordings in the CA1 region of the hippocampus and found a location-specific distribution of sharp-wave ripple events. We describe the construction of the ThermoMaze with the intention that it helps enable large-scale data recordings on immobility-related brain states. Key features • Controlling periods of awake immobility in rodents. • Electronic-friendly analog of the Morris water maze.

Recognizing ideas generated in a creative task: the roles of the hippocampus and medial prefrontal cortex in facilitating self-generated learning

Creative idea generation plays an important role in promoting successful memory formation. Yet, its underlying neural correlates remain unclear. We investigated the self-generated learning of creative ideas motivated by the schema-linked interactions between medial prefrontal and medial temporal regions framework. This was achieved by having participants generate ideas in the alternative uses task, self-evaluating their ideas based on novelty and source (i.e. new or old), and then later being tested on the recognition performance of the generated ideas. At the behavioral level, our results indicated superior performances in discriminating novel ideas, highlighting the novelty effect on memory. At the neural level, the regions-of-interest analyses revealed that successful recognition of novel ideas was associated with greater activations in the hippocampus (HPC) and medial prefrontal cortex (mPFC) during ideation. However, only activation in the right HPC was positively related to the successful recognition of novel ideas. Importantly, the weaker the connection between the right HPC and left mPFC, the higher the recognition accuracy of novel ideas. Moreover, activations in the right HPC and left mPFC were both effective predictors of successful recognition of novel ideas. These findings uniquely highlight the role of novelty in promoting self-generated learning of creative ideas.

Rest to Promote Learning: A Brain Default Mode Network Perspective

The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning.

Maintenance of Procedural Motor Memory across Brief Rest Periods Requires the Hippocampus

Research on the role of the hippocampus in memory acquisition has generally focused on active learning. But to understand memory, it is at least as important to understand processes that happen offline, during both wake and sleep. In a study of patients with amnesia, we previously demonstrated that although a functional hippocampus is not necessary for the acquisition of procedural motor memory during training session, it is required for its offline consolidation during sleep. Here, we investigated whether an intact hippocampus is also required for the offline consolidation of procedural motor memory while awake. Patients with amnesia due to hippocampal damage (n = 4, all male) and demographically matched controls (n = 10, 8 males) trained on the finger tapping motor sequence task. Learning was measured as gains in typing speed and was divided into online (during task execution) and offline (during interleaved 30 s breaks) components. Amnesic patients and controls showed comparable total learning, but differed in the pattern of performance improvement. Unlike younger adults, who gain speed across breaks, both groups gained speed only while typing. Only controls retained these gains over the breaks; amnesic patients slowed down and compensated for these losses during subsequent typing. In summary, unlike their peers, whose motor performance remained stable across brief breaks in typing, amnesic patients showed evidence of impaired access to motor procedural memory. We conclude that in addition to being necessary for the offline consolidation of motor memories during sleep, the hippocampus maintains access to motor memory across brief offline periods during wake.

Micro-consolidation occurs when learning an implicit motor sequence, but is not influenced by HIIT exercise

We investigated if micro-consolidation, a phenomenon recently discovered during the brief rest periods between practice when learning an explicit motor sequence, generalises to learning an implicit motor sequence task. We demonstrate micro-consolidation occurs in the absence of explicit sequence awareness. We also investigated the effect of a preceding bout of high-intensity exercise, as exercise is known to augment the consolidation of new motor skills. Micro-consolidation was not modified by exercise.

Comparison of online, offline, and hybrid hypotheses of motor sequence learning using a quantitative model that incorporate reactive inhibition

Two hypotheses have been advanced for when motor sequence learning occurs: offline between bouts of practice or online concurrently with practice. A third possibility is that learning occurs both online and offline. A complication for differentiating between those hypotheses is a process known as reactive inhibition, whereby performance worsens over consecutively executed sequences, but dissipates during breaks. We advance a new quantitative modeling framework that incorporates reactive inhibition and in which the three learning accounts can be implemented. Our results show that reactive inhibition plays a far larger role in performance than is appreciated in the literature. Across four groups of participants in which break times and correct sequences per trial were varied, the best overall fits were provided by a hybrid model. The version of the offline model that does not account for reactive inhibition, which is widely assumed in the literature, had the worst fits. We discuss implications for extant hypotheses and directions for future research.

Functional connectivity via the dorsolateral prefrontal cortex in the late phase of rest periods predicts offline learning

The relationship between offline learning gains and functional connectivity (FC) has been investigated in several studies. They have focused on average motor task performance and resting-state FC across subjects. Generally, individual differences are seen in both offline learning gain and neurophysiological profiles in resting-state FC. However, few studies have focused on the relationship between individual differences in offline learning gain and temporal characteristics of resting-state FC. The present study aimed to clarify this relationship between the two profiles. Thirty-four healthy right-handed participants performed a force-controlled motor task. Electroencephalography was performed during the 15-minute wakeful rest period between tasks. The results revealed a significant correlation between offline learning gain and FC between the contralateral dorsolateral prefrontal cortex (DLPFC) and contralateral primary motor cortex (M1), and ipsilateral primary somatosensory cortex (S1) during late phase of the rest interval. These results are consistent with the findings of previous studies showing the FC between M1, which is necessary for awake offline learning, and DLPFC, which is related to motor control. Additionally, sensory feedback related to force control may be caused by the interaction between contralateral DLPFC and ipsilateral S1. Our study shed light on the temporal profiles of resting-state FC associated with individual differences in offline learning.

Effect of cognitive load on time spent offline during wakefulness

Humans continuously alternate between online attention to the current environment and offline attention to internally generated thought and imagery. This may be a fundamental feature of the waking brain, but remains poorly understood. Here, we took a data-driven approach to defining online and offline states of wakefulness, using machine learning methods applied to measures of sensory responsiveness, subjective report, electroencephalogram (EEG), and pupil diameter. We tested the effect of cognitive load on the structure and prevalence of online and offline states, hypothesizing that time spent offline would increase as cognitive load of an ongoing task decreased. We also expected that alternation between online and offline states would persist even in the absence of a cognitive task. As in prior studies, we arrived at a three-state model comprised of one online state and two offline states. As predicted, when cognitive load was high, more time was spent online. Also as predicted, the same three states were present even when participants were not performing a task. These observations confirm our method is successful at isolating seconds-long periods of offline time. Varying cognitive load may be a useful way to manipulate time spent in at least one of these offline states in future experimental studies.

Early excitatory-inhibitory cortical modifications following skill learning are associated with motor memory consolidation and plasticity overnight

Consolidation of motor memories is vital to offline enhancement of new motor skills and involves short and longer-term offline processes following learning. While emerging evidence link glutamate and GABA dynamics in the primary motor cortex (M1) to online motor skill practice, its relationship with offline consolidation processes in humans is unclear. Using two-day repeated measures of behavioral and multimodal neuroimaging data before and following motor sequence learning, we show that short-term glutamatergic and GABAergic responses in M1 within minutes after learning were associated with longer-term learning-induced functional, structural, and behavioral modifications overnight. Furthermore, Glutamatergic and GABAergic modifications were differentially associated with different facets of motor memory consolidation. Our results point to unique and distinct roles of Glutamate and GABA in motor memory consolidation processes in the human brain across timescales and mechanistic levels, tying short-term changes on the neurochemical level to overnight changes in macroscale structure, function, and behavior.

Efficient, continual, and generalized learning in the brain - neural mechanism of Mental Schema 2.0

There has been tremendous progress in artificial neural networks (ANNs) over the past decade; however, the gap between ANNs and the biological brain as a learning device remains large. With the goal of closing this gap, this paper reviews learning mechanisms in the brain by focusing on three important issues in ANN research: efficiency, continuity, and generalization. We first discuss the method by which the brain utilizes a variety of self-organizing mechanisms to maximize learning efficiency, with a focus on the role of spontaneous activity of the brain in shaping synaptic connections to facilitate spatiotemporal learning and numerical processing. Then, we examined the neuronal mechanisms that enable lifelong continual learning, with a focus on memory replay during sleep and its implementation in brain-inspired ANNs. Finally, we explored the method by which the brain generalizes learned knowledge in new situations, particularly from the mathematical generalization perspective of topology. Besides a systematic comparison in learning mechanisms between the brain and ANNs, we propose "Mental Schema 2.0," a new computational property underlying the brain's unique learning ability that can be implemented in ANNs.

Theta EEG neurofeedback promotes early consolidation of real life-like episodic memory

Theta oscillations are believed to coordinate neuronal activity related to human cognition, especially for memory functions. Theta power during learning and retrieval has been found to correlate with memory performance success. Additionally, up-regulating theta oscillations during a post-encoding epoch crucial for memory consolidation was previously shown to benefit long-term memory for acquired motor sequences, pictures, and object-location associations. However, it remains to be determined whether such effects would be found for more ecological aspects of long-term episodic memory. Therefore, the current study assessed neurofeedback-based theta upregulation effects on movie memory. After viewing a 15-minute silent, narrative movie, participants engaged in neurofeedback-based theta/beta up-regulation, neurofeedback beta/theta up-regulation as an active control condition, or an unrelated passive control task. Memory was tested three times: once immediately after watching the movie (as baseline); 24 hours thereafter; and once again 1 week later. Memory performance 1 week after encoding was significantly enhanced in the theta/beta up-regulation group compared with the other groups. Additionally, changes in neurofeedback theta/beta ratio from baseline EEG recordings correlated with long-term memory gains in retrieving the movie's content. These findings highlight the relationship between post-learning theta oscillations and the consolidation of episodic memory for a naturalistic event.

Brain plasticity underlying sleep-dependent motor consolidation after motor imagery

Motor imagery can, similarly to physical practice, improve motor performance through experience-based plasticity. Using magnetoencephalography, we investigated changes in brain activity associated with offline consolidation of motor sequence learning through physical practice or motor imagery. After an initial training session with either physical practice or motor imagery, participants underwent overnight consolidation. As control condition, participants underwent wake-related consolidation after training with motor imagery. Behavioral analyses revealed that overnight consolidation of motor learning through motor imagery outperformed wake-related consolidation (95% CI [0.02, 0.07], P < 0.001, RP2 = 0.05). As regions of interest, we selected the generators of event-related synchronization/desynchronization of alpha (8-12 Hz) and beta (15-30 Hz) oscillations, which predicted the level of performance on the motor sequence. This yielded a primary sensorimotor-premotor network for alpha oscillations and a cortico-cerebellar network for beta oscillations. The alpha network exhibited increased neural desynchronization after overnight consolidation compared to wake-related consolidation. By contrast, the beta network exhibited an increase in neural synchronization after wake-related consolidation compared to overnight consolidation. We provide the first evidence of parallel brain plasticity underlying behavioral changes associated with sleep-dependent consolidation of motor skill learning through motor imagery and physical practice.

Generalization of procedural motor sequence learning after a single practice trial

When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments (N = 2095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0-30 s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill.

Prefrontal stimulation as a tool to disrupt hippocampal and striatal reactivations underlying fast motor memory consolidation

BACKGROUND

Recent evidence suggests that hippocampal replay in humans support rapid motor memory consolidation during epochs of wakefulness interleaved with task practice.

OBJECTIVES/HYPOTHESES

The goal of this study was to test whether such reactivation patterns can be modulated with experimental interventions and in turn influence fast consolidation. We hypothesized that non-invasive brain stimulation targeting hippocampal and striatal networks via the prefrontal cortex would influence brain reactivation and the rapid form of motor memory consolidation.

METHODS

Theta-burst stimulation was applied to a prefrontal cluster functionally connected to both the hippocampus and striatum of young healthy participants before they learned a motor sequence task in a functional magnetic resonance imaging (fMRI) scanner. Neuroimaging data acquired during task practice and the interleaved rest epochs were analyzed to comprehensively characterize the effect of stimulation on the neural processes supporting fast motor memory consolidation.

RESULTS

Our results collectively show that active, as compared to control, theta-burst stimulation of the prefrontal cortex hindered fast motor memory consolidation. Converging evidence from both univariate and multivariate analyses of fMRI data indicate that active stimulation disrupted hippocampal and caudate responses during inter-practice rest, presumably altering the reactivation of learning-related patterns during the micro-offline consolidation episodes. Last, stimulation altered the link between the brain and the behavioral markers of the fast consolidation process.

CONCLUSION

These results suggest that stimulation targeting deep brain regions via the prefrontal cortex can be used to modulate hippocampal and striatal reactivations in the human brain and influence motor memory consolidation.

Engram neurons: Encoding, consolidation, retrieval, and forgetting of memory

Tremendous strides have been made in our understanding of the neurobiological substrates of memory - the so-called memory "engram". Here, we integrate recent progress in the engram field to illustrate how engram neurons transform across the "lifespan" of a memory - from initial memory encoding, to consolidation and retrieval, and ultimately to forgetting. To do so, we first describe how cell-intrinsic properties shape the initial emergence of the engram at memory encoding. Second, we highlight how these encoding neurons preferentially participate in synaptic- and systems-level consolidation of memory. Third, we describe how these changes during encoding and consolidation guide neural reactivation during retrieval, and facilitate memory recall. Fourth, we describe neurobiological mechanisms of forgetting, and how these mechanisms can counteract engram properties established during memory encoding, consolidation, and retrieval. Motivated by recent experimental results across these four sections, we conclude by proposing some conceptual extensions to the traditional view of the engram, including broadening the view of cell-type participation within engrams and across memory stages. In collection, our review synthesizes general principles of the engram across memory stages, and describes future avenues to further understand the dynamic engram.

Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit

Once formed, the fate of memory is uncertain. Subsequent offline interactions between even different memory types (actions versus words) modify retention.^1,2,3,4,5,6 These interactions may occur due to different oscillations functionally linking together different memory types within a circuit.^{7,8,9,10,11,12,13} With memory processing driving the circuit, it may become less susceptible to external influences.¹⁴ We tested this prediction by perturbing the human brain with single pulses of transcranial magnetic stimulation (TMS) and simultaneously measuring the brain activity changes with electroencephalography (EEG^15,16,17). Stimulation was applied over brain areas that contribute to memory processing (dorsolateral prefrontal cortex, DLPFC; primary motor cortex, M1) at baseline and offline, after memory formation, when memory interactions are known to occur.^1,4,6,10,18 The EEG response decreased offline (compared with baseline) within the alpha/beta frequency bands when stimulation was applied to the DLPFC, but not to M1. This decrease exclusively followed memory tasks that interact, revealing that it was due specifically to the interaction, not task performance. It remained even when the order of the memory tasks was changed and so was present, regardless of how the memory interaction was produced. Finally, the decrease within alpha power (but not beta) was correlated with impairment in motor memory, whereas the decrease in beta power (but not alpha) was correlated with impairment in word-list memory. Thus, different memory types are linked to different frequency bands within a DLPFC circuit, and the power of these bands shapes the balance between interaction and segregation between these memories.

Human motor sequence learning drives transient changes in network topology and hippocampal connectivity early during memory consolidation

In the last decade, the exclusive role of the hippocampus in human declarative learning has been challenged. Recently, we have shown that gains in performance observed in motor sequence learning (MSL) during the quiet rest periods interleaved with practice are associated with increased hippocampal activity, suggesting a role of this structure in motor memory reactivation. Yet, skill also develops offline as memory stabilizes after training and overnight. To examine whether the hippocampus contributes to motor sequence memory consolidation, here we used a network neuroscience strategy to track its functional connectivity offline 30 min and 24 h post learning using resting-state functional magnetic resonance imaging. Using a graph-analytical approach we found that MSL transiently increased network modularity, reflected in an increment in local information processing at 30 min that returned to baseline at 24 h. Within the same time window, MSL decreased the connectivity of a hippocampal-sensorimotor network, and increased the connectivity of a striatal-premotor network in an antagonistic manner. Finally, a supervised classification identified a low-dimensional pattern of hippocampal connectivity that discriminated between control and MSL data with high accuracy. The fact that changes in hippocampal connectivity were detected shortly after training supports a relevant role of the hippocampus in early stages of motor memory consolidation.

Breaking the barriers to designing online experiments: A novel open-source platform for supporting procedural skill learning experiments

BACKGROUND

Motor learning experiments are typically performed in laboratory environments, which can be time-consuming and require dedicated equipment/personnel, thus limiting the ability to gather data from large samples. To address this problem, some researchers have transitioned to unsupervised online experiments, showing advantages in participant recruitment without losing validity. However, most online platforms require coding experience or time-consuming setups to create and run experiments, limiting their usage across the field.

METHOD

To tackle this issue, an open-source web-based platform was developed (https://experiments.neurro-lab.engin.umich.edu/) to create, run, and manage procedural skill learning experiments without coding or setup requirements. The feasibility of the platform and the comparability of the results between supervised (n = 17) and unsupervised (n = 24) were tested in 41 naive right-handed participants using an established sequential finger tapping task. The study also tested if a previously reported rapid form of offline consolidation (i.e., microscale learning) in procedural skill learning could be replicated with the developed platform and evaluated the extent of interlimb transfer associated with the finger tapping task.

RESULTS

The results indicated that the performance metrics were comparable between the supervised and unsupervised groups (all p's > 0.05). The learning curves, mean tapping speeds, and micro-scale learning were similar to previous studies. Training led to significant improvements in mean tapping speed (2.22 ± 1.48 keypresses/s, p < 0.001) and a significant interlimb transfer of learning (1.22 ± 1.43 keypresses/s, p < 0.05).

CONCLUSIONS

The results show that the presented platform may serve as a valuable tool for conducting online procedural skill-learning experiments.

How our understanding of memory replay evolves

Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.

Reactivation-induced motor skill modulation does not operate at a rapid micro-timescale level

Abundant evidence shows that consolidated memories are susceptible to modifications following their reactivation. Processes of memory consolidation and reactivation-induced skill modulation have been commonly documented after hours or days. Motivated by studies showing rapid consolidation in early stages of motor skill acquisition, here we asked whether motor skill memories are susceptible to modifications following brief reactivations, even at initial stages of learning. In a set of experiments, we collected crowdsourced online motor sequence data to test whether post-encoding interference and performance enhancement occur following brief reactivations in early stages of learning. Results indicate that memories forming during early learning are not susceptible to interference nor to enhancement within a rapid reactivation-induced time window, relative to control conditions. This set of evidence suggests that reactivation-induced motor skill memory modulation might be dependent on consolidation at the macro-timescale level, requiring hours or days to occur.

Manipulating the Rapid Consolidation Periods in a Learning Task Affects General Skills More than Statistical Learning and Changes the Dynamics of Learning

Memory consolidation processes have traditionally been investigated from the perspective of hours or days. However, recent developments in memory research have shown that memory consolidation processes could occur even within seconds, possibly because of the neural replay of just practiced memory traces during short breaks. Here, we investigate this rapid form of consolidation during statistical learning. We aim to answer (1) whether this rapid consolidation occurs in implicit statistical learning and general skill learning, and (2) whether the duration of rest periods affects these two learning types differently. Human participants performed a widely used statistical learning task-the alternating serial reaction time (ASRT) task-that enables us to measure implicit statistical and general skill learning separately. The ASRT task consisted of 25 learning blocks with a rest period between the blocks. In a between-subjects design, the length of the rest periods was fixed at 15 or 30 s, or the participants could control the length themselves. We found that the duration of rest periods does not affect the amount of statistical knowledge acquired but does change the dynamics of learning. Shorter rest periods led to better learning during the learning blocks, whereas longer rest periods promoted learning also in the between-block rest periods, possibly because of the higher amount of replay. Moreover, we found weaker general skill learning in the self-paced group than in the fixed rest period groups. These results suggest that distinct learning processes are differently affected by the duration of short rest periods.

Cortical-hippocampal coupling during manifold exploration in motor cortex

Systems consolidation-a process for long-term memory stabilization-has been hypothesized to occur in two stages1-4. Whereas new memories require the hippocampus5-9, they become integrated into cortical networks over time10-12, making them independent of the hippocampus. How hippocampal-cortical dialogue precisely evolves during this and how cortical representations change in concert is unknown. Here, we use a skill learning task13,14 to monitor the dynamics of cross-area coupling during non-rapid eye movement sleep along with changes in primary motor cortex (M1) representational stability. Our results indicate that precise cross-area coupling between hippocampus, prefrontal cortex and M1 can demarcate two distinct stages of processing. We specifically find that each animal demonstrates a sharp increase in prefrontal cortex and M1 sleep slow oscillation coupling with stabilization of performance. This sharp increase then predicts a drop in hippocampal sharp-wave ripple (SWR)-M1 slow oscillation coupling-suggesting feedback to inform hippocampal disengagement and transition to a second stage. Notably, the first stage shows significant increases in hippocampal SWR-M1 slow oscillation coupling in the post-training sleep and is closely associated with rapid learning and variability of the M1 low-dimensional manifold. Strikingly, even after consolidation, inducing new manifold exploration by changing task parameters re-engages hippocampal-M1 coupling. We thus find evidence for dynamic hippocampal-cortical dialogue associated with manifold exploration during learning and adaptation.

Applied strategies of neuroplasticity

Various levels of somatotopic organization are present throughout the human nervous system. However, this organization can change when needed based on environmental demands, a phenomenon known as neuroplasticity. Neuroplasticity can occur when learning a new motor skill, adjusting to life after blindness, or following a stroke. Following an injury, these neuroplastic changes can be adaptive or maladaptive, and often occur regardless of whether rehabilitation occurs or not. But not all movements produce neuroplasticity, nor do all rehabilitation interventions. Here, we focus on research regarding how to maximize adaptive neuroplasticity while also minimizing maladaptive plasticity, known as applied neuroplasticity. Emphasis is placed on research exploring how best to apply neuroplastic principles to training environments and rehabilitation protocols. By studying and applying these principles in research and clinical practice, it is hoped that learning of skills and regaining of function and independence can be optimized.

Robust enhancement of motor sequence learning with 4 mA transcranial electric stimulation

BACKGROUND AND OBJECTIVES

Motor learning experiments with transcranial direct current stimulation (tDCS) at 2 mA have produced mixed results. We hypothesize that tDCS boosts motor learning provided sufficiently high field intensity on the motor cortex.

METHODS

In a single-blinded design, 108 healthy participants received either anodal (N = 36) or cathodal (N = 36) tDCS at 4 mA total, or no stimulation (N = 36) while they practiced a 12-min sequence learning task. Anodal stimulation was delivered across four electrode pairs (1 mA each), with anodes above the right parietal lobe and cathodes above the right frontal lobe. Cathodal stimulation, with reversed polarities, served as an active control for sensation, while the no-stimulation condition established baseline performance. fMRI-localized targets on the primary motor cortex in 10 subjects were used in current flow models to optimize electrode placement for maximal field intensity. A single electrode montage was then selected for all participants.

RESULTS

We found a significant difference in performance with anodal vs. cathodal stimulation (Cohen's d = 0.71) and vs. no stimulation (d = 0.56). This effect persisted for at least 1 h, and subsequent learning for a new sequence and the opposite hand also improved. Sensation ratings were comparable in the active groups and did not exceed moderate levels. Current flow models suggest the new electrode montage can achieve stronger motor cortex polarization than alternative montages.

CONCLUSION

The present paradigm shows a medium to large effect size and is well-tolerated. It may serve as a go-to experiment for future studies on motor learning and tDCS.

Dissipation of reactive inhibition is sufficient to explain post-rest improvements in motor sequence learning

The prevailing hypothesis for observed post-rest motor reaction time improvements is offline consolidation. In the present study, we present evidence for an alternate account involving the accrual and dissipation of reactive inhibition. Four groups of participants (N = 159) performed a finger-tapping task involving either massed (30 s per trial) or spaced (10 s per trial) training, and with one of two break intervals between each trial: 10 s or 30 s. After 360 s of training in each group, there was a 300 s rest period followed by a final test on the same task. The results show that the smaller the ratio of break time to on-task trial time during training, the larger the improvement in reaction time after the rest period. Those results are fully consistent with a model that assumes no facilitating offline consolidation, but rather learning that is concurrent with performance and reactive inhibition that builds during performance and dissipates during breaks.

Sustained upregulation of widespread hippocampal-neocortical coupling following memory encoding

Systems consolidation of new experiences into lasting episodic memories involves hippocampal-neocortical interactions. Evidence of this process is already observed during early post-encoding rest periods, both as increased hippocampal coupling with task-relevant perceptual regions and reactivation of stimulus-specific patterns following intensive encoding tasks. We investigate the spatial and temporal characteristics of these hippocampally anchored post-encoding neocortical modulations. Eighty-nine adults participated in an experiment consisting of interleaved memory task- and resting-state periods. We observed increased post-encoding functional connectivity between hippocampus and individually localized neocortical regions responsive to stimuli encountered during memory encoding. Post-encoding modulations were manifested as a nearly system-wide upregulation in hippocampal coupling with all major functional networks. The configuration of these extensive modulations resembled hippocampal-neocortical interaction patterns estimated from active encoding operations, suggesting hippocampal post-encoding involvement exceeds perceptual aspects. Reinstatement of encoding patterns was not observed in resting-state scans collected 12 h later, nor when using other candidate seed regions. The similarity in hippocampal functional coupling between online memory encoding and offline post-encoding rest suggests reactivation in humans involves a spectrum of cognitive processes engaged during the experience of an event. There were no age effects, suggesting that upregulation of hippocampal-neocortical connectivity represents a general phenomenon seen across the adult lifespan.

Effects of virtual body-representation on motor skill learning

Motor learning is often hindered or facilitated by visual information from one's body and its movement. However, it is unclear whether visual representation of the body itself facilitates motor learning. Thus, we tested the effects of virtual body-representation on motor learning through a virtual reality rotary pursuit task. In the task, visual feedback on participants' movements was identical, but virtual body-representation differed by dividing the experimental conditions into three conditions: non-avatar, non-hand avatar, and hand-shaped avatar. We measured the differences in the rate of motor learning, body-ownership, and sense of agency in the three conditions. Although there were no differences in body-ownership and sense of agency between the conditions, the hand-shaped avatar condition was significantly superior to the other conditions in the rate of learning. These findings suggest that visually recognizing one's body shape facilitates motor learning.

Wakeful resting and listening to music contrast their effects on verbal long-term memory in dependence on word concreteness

Wakeful resting and listening to music are powerful means to modulate memory. How these activities affect memory when directly compared has not been tested so far. In two experiments, participants encoded and immediately recalled two word lists followed by either 6 min wakefully resting or 6 min listening to music. The results of Experiment 1 show that both post-encoding conditions have a similar effect on memory after 1 day. In Experiment 2, we explored the possibility that less concrete words, i.e. lower in imageability than in Experiment 1, are differently affected by the two post-encoding conditions. The results of Experiment 2 show that, when words are less concrete, more words are retained after 1 day when encoding is followed by wakeful resting rather than listening to music. These findings indicate that the effects of wakeful resting and listening to music on memory consolidation are moderated by the concreteness of the encoded material.

Somatosensory targeted memory reactivation enhances motor performance via hippocampal-mediated plasticity

Increasing evidence suggests that reactivation of newly acquired memory traces during postlearning wakefulness plays an important role in memory consolidation. Here, we sought to boost the reactivation of a motor memory trace during postlearning wakefulness (quiet rest) immediately following learning using somatosensory targeted memory reactivation (TMR). Using functional magnetic resonance imaging, we examined the neural correlates of the reactivation process as well as the effect of the TMR intervention on brain responses elicited by task practice on 24 healthy young adults. Behavioral data of the post-TMR retest session showed a faster learning rate for the motor sequence that was reactivated as compared to the not-reactivated sequence. Brain imaging data revealed that motor, parietal, frontal, and cerebellar brain regions, which were recruited during initial motor learning, were specifically reactivated during the TMR episode and that hippocampo-frontal connectivity was modulated by the reactivation process. Importantly, the TMR-induced behavioral advantage was paralleled by dynamical changes in hippocampal activity and hippocampo-motor connectivity during task practice. Altogether, the present results suggest that somatosensory TMR during postlearning quiet rest can enhance motor performance via the modulation of hippocampo-cortical responses.

Modulation of neural co-firing to enhance network transmission and improve motor function after stroke

Stroke is a leading cause of disability. While neurotechnology has shown promise for improving upper limb recovery after stroke, efficacy in clinical trials has been variable. Our central thesis is that to improve clinical translation, we need to develop a common neurophysiological framework for understanding how neurotechnology alters network activity. Our perspective discusses principles for how motor networks, both healthy and those recovering from stroke, subserve reach-to-grasp movements. We focus on neural processing at the resolution of single movements, the timescale at which neurotechnologies are applied, and discuss how this activity might drive long-term plasticity. We propose that future studies should focus on cross-area communication and bridging our understanding of timescales ranging from single trials within a session to across multiple sessions. We hope that this perspective establishes a combined path forward for preclinical and clinical research with the goal of more robust clinical translation of neurotechnology.

Time Is of the Essence: Neural Codes, Synchronies, Oscillations, Architectures

Time is of the essence in how neural codes, synchronies, and oscillations might function in encoding, representation, transmission, integration, storage, and retrieval of information in brains. This Hypothesis and Theory article examines observed and possible relations between codes, synchronies, oscillations, and types of neural networks they require. Toward reverse-engineering informational functions in brains, prospective, alternative neural architectures incorporating principles from radio modulation and demodulation, active reverberant circuits, distributed content-addressable memory, signal-signal time-domain correlation and convolution operations, spike-correlation-based holography, and self-organizing, autoencoding anticipatory systems are outlined. Synchronies and oscillations are thought to subserve many possible functions: sensation, perception, action, cognition, motivation, affect, memory, attention, anticipation, and imagination. These include direct involvement in coding attributes of events and objects through phase-locking as well as characteristic patterns of spike latency and oscillatory response. They are thought to be involved in segmentation and binding, working memory, attention, gating and routing of signals, temporal reset mechanisms, inter-regional coordination, time discretization, time-warping transformations, and support for temporal wave-interference based operations. A high level, partial taxonomy of neural codes consists of channel, temporal pattern, and spike latency codes. The functional roles of synchronies and oscillations in candidate neural codes, including oscillatory phase-offset codes, are outlined. Various forms of multiplexing neural signals are considered: time-division, frequency-division, code-division, oscillatory-phase, synchronized channels, oscillatory hierarchies, polychronous ensembles. An expandable, annotative neural spike train framework for encoding low- and high-level attributes of events and objects is proposed. Coding schemes require appropriate neural architectures for their interpretation. Time-delay, oscillatory, wave-interference, synfire chain, polychronous, and neural timing networks are discussed. Some novel concepts for formulating an alternative, more time-centric theory of brain function are discussed. As in radio communication systems, brains can be regarded as networks of dynamic, adaptive transceivers that broadcast and selectively receive multiplexed temporally-patterned pulse signals. These signals enable complex signal interactions that select, reinforce, and bind common subpatterns and create emergent lower dimensional signals that propagate through spreading activation interference networks. If memory traces share the same kind of temporal pattern forms as do active neuronal representations, then distributed, holograph-like content-addressable memories are made possible via temporal pattern resonances.

Reward timing matters in motor learning

Reward timing, that is, the delay after which reward is delivered following an action is known to strongly influence reinforcement learning. Here, we asked if reward timing could also modulate how people learn and consolidate new motor skills. In 60 healthy participants, we found that delaying reward delivery by a few seconds influenced motor learning. Indeed, training with a short reward delay (1 s) induced continuous improvements in performance, whereas a long reward delay (6 s) led to initially high learning rates that were followed by an early plateau in the learning curve and a lower performance at the end of training. Participants who learned the skill with a long reward delay also exhibited reduced overnight memory consolidation. Overall, our data show that reward timing affects the dynamics and consolidation of motor learning, a finding that could be exploited in future rehabilitation programs.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.