Memory consolidation of sequence learning and dynamic adaptation during wakefulness.

Motor learning involves acquiring new movement sequences and adapting motor commands to novel conditions. Labile motor memories, acquired through sequence learning and dynamic adaptation, undergo a consolidation process during wakefulness after initial training. This process stabilizes the new memories, leading to long-term memory formation. However, it remains unclear if the consolidation processes underlying sequence learning and dynamic adaptation are independent and if distinct neural regions underpin memory consolidation associated with sequence learning and dynamic adaptation. Here, we first demonstrated that the initially labile memories formed during sequence learning and dynamic adaptation were stabilized against interference through time-dependent consolidation processes occurring during wakefulness. Furthermore, we found that sequence learning memory was not disrupted when immediately followed by dynamic adaptation and vice versa, indicating distinct mechanisms for sequence learning and dynamic adaptation consolidation. Finally, by applying patterned transcranial magnetic stimulation to selectively disrupt the activity in the primary motor (M1) or sensory (S1) cortices immediately after sequence learning or dynamic adaptation, we found that sequence learning consolidation depended on M1 but not S1, while dynamic adaptation consolidation relied on S1 but not M1. For the first time in a single experimental framework, this study revealed distinct neural underpinnings for sequence learning and dynamic adaptation consolidation during wakefulness, with significant implications for motor skill enhancement and rehabilitation.

Top-down and bottom-up oscillatory dynamics regulate implicit visuomotor sequence learning.

Implicit visuomotor sequence learning is crucial for acquiring skills that result in automated behaviors. The oscillatory dynamics underpinning this learning process are not well understood. To address this gap, the current study employed electroencephalography with a medium-density array (64 electrodes) to investigate oscillatory activity associated with implicit visuomotor sequence learning in the Serial Reaction Time task. In the task, participants unknowingly learn a series of finger movements. Eighty-five healthy adults participated in the study. Analyses revealed that theta activity at the vertex and alpha/beta activity over the motor areas decreased over the course of learning. No associations between alpha/beta and theta power were observed. These findings are interpreted within a dual-process framework: midline theta activity is posited to regulate top-down attentional processes, whereas beta activity from motor areas underlies the bottom-up encoding of sensory information from movement. From this model, we suggest that during implicit visuomotor sequence learning, top-down processes become disengaged (indicated by a reduction in theta activity), and modality specific bottom-up processes encode the motor sequence (indicated by a reduction in alpha/beta activity).

Prior Movement of One Arm Facilitates Motor Adaptation in the Other.

Many movements in daily life are embedded in motion sequences that involve more than one limb, demanding the motor system to monitor and control different body parts in quick succession. During such movements, systematic changes in the environment or the body might require motor adaptation of specific segments. However, previous motor adaptation research has focused primarily on motion sequences produced by a single limb, or on simultaneous movements of several limbs. For example, adaptation to opposing force fields is possible in unimanual reaching tasks when the direction of a prior or subsequent movement is predictive of force field direction. It is unclear, however, whether multilimb sequences can support motor adaptation processes in a similar way. In the present study (38 females, 38 males), we investigated whether reaches can be adapted to different force fields in a bimanual motor sequence when the information about the perturbation is associated with the prior movement direction of the other arm. In addition, we examined whether prior perceptual (visual or proprioceptive) feedback of the opposite arm contributes to force field-specific motor adaptation. Our key finding is that only active participation in the bimanual sequential task supports pronounced adaptation. This result suggests that active segments in bimanual motion sequences are linked across limbs. If there is a consistent association between movement kinematics of the linked and goal movement, the learning process of the goal movement can be facilitated. More generally, if motion sequences are repeated often, prior segments can evoke specific adjustments of subsequent movements.SIGNIFICANCE STATEMENT Movements in a limb's motion sequence can be adjusted based on linked movements. A prerequisite is that kinematics of the linked movements correctly predict which adjustments are needed. We show that use of kinematic information to improve performance is even possible when a prior linked movement is performed with a different limb. For example, a skilled juggler might have learned how to correctly adjust his catching movement of the left hand when the right hand performed a throwing action in a specific way. Linkage is possibly a key mechanism of the human motor system for learning complex bimanual skills. Our study emphasizes that learning of specific movements should not be studied in isolation but within their motor sequence context.

Theta Signal Transfer from Parietal to Prefrontal Cortex Ignites Conscious Awareness of Implicit Knowledge during Sequence Learning.

Unconscious acquisition of sequence structure from experienced events can lead to explicit awareness of the pattern through extended practice. Although the implicit-to-explicit transition has been extensively studied in humans using the serial reaction time (SRT) task, the subtle neural activity supporting this transition remains unclear. Here, we investigated whether frequency-specific neural signal transfer contributes to this transition. A total of 208 participants (107 females) learned a sequence pattern through a multisession SRT task, allowing us to observe the transitions. Session-by-session measures of participants' awareness for sequence knowledge were conducted during the SRT task to identify the session when the transition occurred. By analyzing time course RT data using switchpoint modeling, we identified an increase in learning benefit specifically at the transition session. Electroencephalogram (EEG)/magnetoencephalogram (MEG) recordings revealed increased theta power in parietal (precuneus) regions one session before the transition (pretransition) and a prefrontal (superior frontal gyrus; SFG) one at the transition session. Phase transfer entropy (PTE) analysis confirmed that directional theta transfer from precuneus → SFG occurred at the pretransition session and its strength positively predicted learning improvement at the subsequent transition session. Furthermore, repetitive transcranial magnetic stimulation (TMS) modulated precuneus theta power and altered transfer strength from precuneus to SFG, resulting in changes in both transition rate and learning benefit at that specific point of transition. Our brain-stimulation evidence supports a role for parietal → prefrontal theta signal transfer in igniting conscious awareness of implicitly acquired knowledge.SIGNIFICANCE STATEMENT There exists a pervasive phenomenon wherein individuals unconsciously acquire sequence patterns from their environment, gradually becoming aware of the underlying regularities through repeated practice. While previous studies have established the robustness of this implicit-to-explicit transition in humans, the refined neural mechanisms facilitating conscious access to implicit knowledge remain poorly understood. Here, we demonstrate that prefrontal activity, known to be crucial for conscious awareness, is triggered by neural signal transfer originating from the posterior brain region, specifically the precuneus. By employing brain stimulation techniques, we establish a causal link between neural signal transfer and the occurrence of awareness. Our findings unveil a mechanism by which implicit knowledge becomes consciously accessible in human cognition.

Altered functional connectivity in the hippocampal and striatal systems after motor sequence learning consolidation in medial temporal lobe epilepsy individuals.

Both the hippocampal and striatal systems participate in motor sequence learning (MSL) in healthy subjects, and the prominent role of the hippocampal system in sleep-related consolidation has been demonstrated. However, some pathological states may change the functional dominance between these two systems in MSL consolidation. To better understand the functional performance within these two systems under the pathological condition of hippocampal impairment, we compared the functional differences after consolidation between patients with left medial temporal lobe epilepsy (LmTLE) and healthy control subjects (HCs). We assessed participants' performance on the finger-tapping task (FTT) during acquisition (on day 1) and after consolidation during sleep (on day 2). All participants underwent an MRI scan (T1 and resting state) before each FTT. We found that the LmTLE group showed performance deficits in offline consolidation compared to the HC group. The LmTLE group exhibited structural changes, such as decreased gray matter volume (GMV) in the left hippocampus and increased GMV in the right putamen (striatum). Our results also revealed that whereas the main effect of consolidation was observed in the hippocampus-related functional connection in the HC group, it was only evident in the striatum-related functional loop in the LmTLE group. Our findings indicated that LmTLE patients may rely more on the striatal system for offline consolidation because of structural impairments in the hippocampus. Additionally, this compensatory mechanism may not fully substitute for the role of the impaired hippocampus itself.NEW & NOTEWORTHY Motor sequence learning (MSL) relies on both the hippocampal and striatal systems, but whether functional performance is altered after MSL consolidation when the hippocampus is impaired remains unknown. Our results indicated that whereas the main effect of consolidation was observed in the hippocampus-related functional connection in the healthy control (HC) group, it was only evident in the striatum-related functional loop in the left medial temporal lobe epilepsy (LmTLE) group.

Motor learning alters vision, but vision does not alter motor learning.

During visuomotor learning, improvements in motor performance accompany changes in how people use vision. However, the dependencies between altered visual reliance and improvements in motor skill is unclear. The present studies used an online sequence learning task to quantify how changing the availability of visual information affected motor skill learning (study 1) and how changing motor skill affected visual reliance (study 2). Participants used their keyboard to respond to targets falling vertically down a game screen. In study 1 (n = 49), the availability of visual information was altered by manipulating where the targets were visible on the screen. Three experimental groups practiced the task during full or limited vision conditions (when the targets were only visible in specific areas). We hypothesized that limiting visual information would reduce motor learning (i.e., the rate of improvement during training trial blocks). Instead, although participants performed worse during limited vision trials (P < 0.001), there was no difference in learning rate (P = 0.87). In study 2 (n = 119), all participants practiced the task with full vision and their visual reliance (i.e., their performance change between full and limited vision conditions) was quantified before and after training. We hypothesized that with motor learning, visual reliance on future targets would increase, whereas visual reliance on the current targets would decrease. The results of study 2 partially support our hypotheses with visual reliance decreasing for all visual areas (P < 0.001). Together, the results suggest changing motor skill alters how people use vision, but changing visual availability does not affect motor learning.NEW & NOTEWORTHY Previous research has established how people use visual information changes with motor learning. However, the dependencies of these two processes on each other are unclear. We find that limiting the availability of visual information degrades motor performance but not motor learning. We also find that motor learning reduces the impact of limiting the availability of visual information on motor performance. Together, these results suggest that how people use visual information depends on their motor skill.

Cholinergic modulation of motor sequence learning.

The cholinergic system plays a key role in motor function, but whether pharmacological modulation of cholinergic activity affects motor sequence learning is unknown. The acetylcholine receptor antagonist biperiden, an established treatment in movement disorders, reduces attentional modulation, but whether it influences motor sequence learning is not clear. Using a randomized, double-blind placebo-controlled crossover design, we tested 30 healthy young participants and showed that biperiden impairs the ability to learn sequential finger movements, accompanied by widespread oscillatory broadband power changes (4-25 Hz) in the motor sequence learning network after receiving biperiden, with greater power in the theta, alpha and beta bands over ipsilateral motor and bilateral parietal-occipital areas. The reduced early theta power during a repeated compared with random sequence, likely reflecting disengagement of top-down attention to sensory processes, was disrupted by biperiden. Alpha synchronization during repeated sequences reflects sensory gating and lower visuospatial attention requirements compared with visuomotor responses to random sequences. After biperiden, alpha synchronization was greater, potentially reflecting excessive visuospatial attention reduction, affecting visuomotor responding required to enable sequence learning. Beta oscillations facilitate sequence learning by integrating visual and somatosensory inputs, stabilizing repeated sequences and promoting prediction of the next stimulus. The beta synchronization after biperiden fits with a disruption of the selective visuospatial attention enhancement associated with initial sequence learning. These findings highlight the role of cholinergic processes in motor sequence learning.

Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome.

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.

Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training.

Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.

Does transcranial direct current stimulation of the primary motor cortex improve implicit motor sequence learning in Parkinson's disease?

Implicit motor sequence learning (IMSL) is a cognitive function that is known to be associated with impaired motor function in Parkinson's disease (PD). We previously reported positive effects of transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) on IMSL in 11 individuals with PD with mild cognitive impairments (MCI), with the largest effects occurring during reacquisition. In the present study, we included 35 individuals with PD, with (n = 15) and without MCI (n = 20), and 35 age- and sex-matched controls without PD, with (n = 13) and without MCI (n = 22). We used mixed-effects models to analyze anodal M1 tDCS effects on acquisition (during tDCS), short-term (five minutes post-tDCS) and long-term reacquisition (one-week post-tDCS) of general and sequence-specific learning skills, as measured by the serial reaction time task. At long-term reacquisition, anodal tDCS resulted in smaller general learning effects compared to sham, only in the PD group, p = .018, possibly due to floor effects. Anodal tDCS facilitated the acquisition of sequence-specific learning (M = 54.26 ms) compared to sham (M = 38.98 ms), p = .003, regardless of group (PD/controls). Further analyses revealed that this positive effect was the largest in the PD-MCI group (anodal: M = 69.07 ms; sham: M = 24.33 ms), p < .001. Although the observed effect did not exceed the stimulation period, this single-session tDCS study confirms the potential of tDCS to enhance IMSL, with the largest effects observed in patients with lower cognitive status. These findings add to the body of evidence that anodal tDCS can beneficially modulate the abnormal basal ganglia network activity that occurs in PD.

Temporal cluster-based organization of sleep spindles underlies motor memory consolidation.

Sleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remain unclear. Here, simultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organized patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only. Altogether, our findings suggest that spindles' clustering and rhythmic occurrence during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronized oscillatory activity within a subcortical-cortical network involved during learning.

Chunking as a function of sequence length.

Chunking mechanisms are central to several cognitive processes. During the acquisition of visuo-motor sequences, it is commonly reported that these sequences are segmented into chunks leading to more fluid, rapid, and accurate performances. The question of a chunk's storage capacity has been often investigated but little is known about the dynamics of chunk size evolution relative to sequence length. In two experiments, we studied the dynamics and the evolution of a sequence's chunking pattern as a function of sequence length in a non-human primate species (Guinea baboons, Papio papio). Using an operant conditioning device, baboons had to point on a touch screen to a moving target. In Experiment 1, they had to produce repeatedly the same sequence of 4 movements during 2000 trials. In Experiment 2, the sequence was composed of 5 movements and was repeated 4000 times. For both lengths, baboons initially produced small chunks that became fewer and longer with practice. Moreover, the dynamics and the evolution of the chunking pattern varied as a function of sequence length. Finally, with extended practice (i.e., more than 2000 trials), we observed that the mean chunk size reached a plateau indicating that there are fundamental limits to chunking processes that also depend on sequence length. These data therefore provide new empirical evidence for understanding the general properties of chunking mechanisms in sequence learning.

Motor learning and performance in schizophrenia and aging: two different patterns of decline.

Psychomotor slowing has consistently been observed in schizophrenia, however research on motor learning in schizophrenia is limited. Additionally, motor learning in schizophrenia has never been compared with the waning of motor learning abilities in the elderly. Therefore, in an extensive study, 30 individuals with schizophrenia, 30 healthy age-matched controls and 30 elderly participants were compared on sensorimotor learning tasks including sequence learning and adaptation (both explicit and implicit), as well as tracking and aiming. This paper presents new findings on an explicit motor sequence learning task, an explicit verbal learning task and a simple aiming task and summarizes all previously published findings of this large investigation. Individuals with schizophrenia and elderly had slower Movement Time (MT)s compared with controls in all tasks, however both groups improved over time. Elderly participants learned slower on tracking and explicit sequence learning while individuals with schizophrenia adapted slower and to a lesser extent to movement perturbations in adaptation tasks and performed less well on cognitive tests including the verbal learning task. Results suggest that motor slowing is present in schizophrenia and the elderly, however both groups show significant but different motor skill learning. Cognitive deficits seem to interfere with motor learning and performance in schizophrenia while task complexity and decreased movement precision interferes with motor learning in the elderly, reflecting different underlying patterns of decline in these conditions. In addition, evidence for motor slowing together with impaired implicit adaptation supports the influence of cerebellum and the cerebello-thalamo-cortical-cerebellar (CTCC) circuits in schizophrenia, important for further understanding the pathophysiology of the disorder.

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.

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.

Modality-specific and modality-independent neural representations work in concert in predictive processes during sequence learning.

Probabilistic sequence learning supports the development of skills and enables predictive processing. It remains contentious whether visuomotor sequence learning is driven by the representation of the visual sequence (perceptual coding) or by the representation of the response sequence (motor coding). Neurotypical adults performed a visuomotor sequence learning task. Learning occurred incidentally as it was evidenced by faster responses to high-probability than to low-probability targets. To uncover the neurophysiology of the learning process, we conducted both univariate analyses and multivariate pattern analyses (MVPAs) on the temporally decomposed EEG signal. Univariate analyses showed that sequence learning modulated the amplitudes of the motor code of the decomposed signal but not in the perceptual and perceptual-motor signals. However, MVPA revealed that all 3 codes of the decomposed EEG contribute to the neurophysiological representation of the learnt probabilities. Source localization revealed the involvement of a wider network of frontal and parietal activations that were distinctive across coding levels. These findings suggest that perceptual and motor coding both contribute to the learning of sequential regularities rather than to a neither-nor distinction. Moreover, modality-specific encoding worked in concert with modality-independent representations, which suggests that probabilistic sequence learning is nonunitary and encompasses a set of encoding principles.

Implicit visuospatial sequence representations are accessible in both the practice and the transfer hand.

A serial reaction time task was used to test whether the representations of a probabilistic second-order sequence structure are (i) stored in an effector-dependent, effector-independent intrinsic or effector-independent visuospatial code and (ii) are inter-manually accessible. Participants were trained either with the dominant or non-dominant hand. Tests were performed with both hands in the practice sequence, a random sequence, and a mirror sequence. Learning did not differ significantly between left and right-hand practice, suggesting symmetric intermanual transfer from the dominant to the non-dominant hand and vice versa. In the posttest, RTs were shorter for the practice sequence than for the random sequence, and longest for the mirror sequence. Participants were unable to freely generate or recognize the practice sequence, indicating implicit knowledge of the probabilistic sequence structure. Because sequence-specific learning did not differ significantly between hands, we conclude that representations of the probabilistic sequence structure are stored in an effector-independent visuospatial code.

Anodal transcranial direct current stimulation does not enhance the effects of motor imagery training of a sequential finger-tapping task in young adults.

When applied over the primary motor cortex (M1), anodal transcranial direct current stimulation (a-tDCS) could enhance the effects of a single motor imagery training (MIt) session on the learning of a sequential finger-tapping task (SFTT). This study aimed to investigate the effect of a-tDCS on the learning of an SFTT during multiple MIt sessions. Two groups of 16 healthy young adults participated in three consecutive MIt sessions over 3 days, followed by a retention test 1 week later. They received active or sham a-tDCS during a MIt session in which they mentally rehearsed an eight-item complex finger sequence with their left hand. Before and after each session, and during the retention test, they physically repeated the sequence as quickly and accurately as possible. Both groups (i) improved their performance during the first two sessions, showing online learning; (ii) stabilised the level they reached during all training sessions, reflecting offline consolidation; and (iii) maintained their performance level one week later, showing retention. However, no significant difference was found between the groups, regardless of the MSL stage. These results emphasise the importance of performing several MIt sessions to maximise performance gains, but they do not support the additional effects of a-tDCS.

The complexity of measuring reliability in learning tasks: An illustration using the Alternating Serial Reaction Time Task.

Despite the fact that reliability estimation is crucial for robust inference, it is underutilized in neuroscience and cognitive psychology. Appreciating reliability can help researchers increase statistical power, effect sizes, and reproducibility, decrease the impact of measurement error, and inform methodological choices. However, accurately calculating reliability for many experimental learning tasks is challenging. In this study, we highlight a number of these issues, and estimate multiple metrics of internal consistency and split-half reliability of a widely used learning task on a large sample of 180 subjects. We show how pre-processing choices, task length, and sample size can affect reliability and its estimation. Our results show that the Alternating Serial Reaction Time Task has respectable reliability, especially when learning scores are calculated based on reaction times and two-stage averaging. We also show that a task length of 25 blocks can be sufficient to meet the usual thresholds for minimally acceptable reliability. We further illustrate how relying on a single point estimate of reliability can be misleading, and the calculation of multiple metrics, along with their uncertainties, can lead to a more complete characterization of the psychometric properties of tasks.

Working Memory for Spatial Sequences: Developmental and Evolutionary Factors in Encoding Ordinal and Relational Structures.

Sequence learning is a ubiquitous facet of human and animal cognition. Here, using a common sequence reproduction task, we investigated whether and how the ordinal and relational structures linking consecutive elements are acquired by human adults, children, and macaque monkeys. While children and monkeys exhibited significantly lower precision than adults for spatial location and temporal order information, only monkeys appeared to exceedingly focus on the first item. Most importantly, only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used a chunking strategy to compress sequences in working memory. Monkeys did not detect such relational structures, even after extensive training. Monkey behavior was captured by a conjunctive coding model, whereas a chunk-based conjunctive model explained more variance in humans. These age- and species-related differences are indicative of developmental and evolutionary mechanisms of sequence encoding and may provide novel insights into the uniquely human cognitive capacities.SIGNIFICANCE STATEMENT Sequence learning, the ability to encode the order of discrete elements and their relationships presented within a sequence, is a ubiquitous facet of cognition among humans and animals. By exploring sequence-processing abilities at different human developmental stages and in nonhuman primates, we found that only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used an internal language to compress sequences in working memory. The findings provided insights into understanding the origins of sequence capabilities in humans and how they evolve through development to identify the unique aspects of human cognitive capacity, which includes the comprehension, learning, and production of sequences, and perhaps, above all, language processing.