Implicit Motor Learning Strategies Benefit Dual-Task Performance in Patients with Stroke

Background and Objectives: In stroke rehabilitation, the use of either implicit or explicit learning as a motor learning approach during dual tasks is common, but it is unclear which strategy is more beneficial. This study aims to determine the benefits of implicit versus explicit motor learning approaches in patients with stroke. Materials and Methods: Seventeen patients with stroke and 21 control participants were included. Motor learning was evaluated using the Serial Reaction Time Task (SRTT) in the context of dual-task conditions. The SRTT was conducted on two separate days: one day for implicit learning conditions and the other day for explicit learning conditions. Under the explicit learning conditions, a task rule was given to the participants before they started the task, but not under the implicit learning conditions. Learning scores were calculated for both implicit and explicit learning, and these scores were then compared within groups for patients with stroke and controls. We calculated the difference in learning scores between implicit and explicit learning and conducted a correlation analysis with the Trail Making Test (TMT) Parts A and B. Results: Learning scores on the SRTT were not different between implicit and explicit learning in controls but were significantly greater in patients with stroke for implicit learning than for explicit learning. The difference in learning scores between implicit and explicit learning in patients with stroke was correlated with TMT-A and showed a correlation trend with TMT-B. Conclusions: Implicit learning approaches may be effective in the acquisition of motor skills with dual-task demands in post-stroke patients with deficits in attention and working memory.

Optimal Training for Movement Acquisition and Transfer: Does "Externally Focused" Visual Biofeedback Promote Implicit Motor Learning?

CONTEXT

Visual biofeedback has been shown to facilitate injury-resistant movement acquisition in adolescent athletes. Visual biofeedback is typically thought to foster implicit learning by stimulating athletes to focus attention externally (on movement outcome). However, biofeedback may also induce explicit learning if the athlete uses the visual information to consciously guide movement execution (via an internal focus).

OBJECTIVE

To determine the degree to which athletes reported statements indicating implicit or explicit motor learning after engaging in a visual biofeedback intervention.

DESIGN

Prospective cohort study.

SETTING

Three-dimensional motion-analysis laboratory.

PATIENTS OR OTHER PARTICIPANTS

Twenty-five adolescent female soccer athletes (age = 15.0 ± 1.5 years, height = 165.7 ± 5.9 cm, mass = 59.4 ± 10.6 kg).

INTERVENTIONS

Standard 6-week neuromuscular training intervention (three 90-minute sessions/wk), with added visual biofeedback sessions (2 sessions/wk). For the biofeedback training, participants performed squatting and jumping movements while interacting with a visual rectangular stimulus that mapped key parameters associated with injury risk. After the last biofeedback session in each week, participants answered open-ended questions to probe learning strategies.

MAIN OUTCOME MEASURE(S)

Responses to the open-ended questions were categorized as externally focused (ie, on movement outcome, suggestive of implicit learning), internally focused (ie, on movement itself, suggestive of explicit learning), mixed focus, or other.

RESULTS

A total of 171 open-ended responses were collected. Most of the responses that could be categorized (39.2%) were externally focused (41.8%), followed by mixed (38.8%) and internally focused (19.4%). The frequency of externally focused statements increased from week 1 (18%) to week 6 (50%).

CONCLUSIONS

Although most statements were externally focused (suggesting implicit learning), the relatively large proportion of internal- and mixed-focus statements suggested that many athletes also engaged in explicit motor learning, especially in early practice sessions. Therefore, biofeedback may affect motor learning through a mixture of implicit and explicit learning.

Implicit learning of the one-back reinforcement matching-mismatching task by pigeons

Humans can learn tasks explicitly, as they can often describe the rules they have used to learn the task.^1,2,3 Animals, however, are thought to learn tasks implicitly (i.e., purely associatively).^2,3 That is, they gradually learn the correlation or association between the stimulus (or response) and the outcome. Both humans and pigeons can learn matching, where a sample stimulus indicates which one of two stimuli matches the sample. The 1-back reinforcement task is a difficult version of matching in which a correct response on trial N is rewarded only following a response on trial N + 1 (independent of the response on trial N + 1),⁴ and the correct response on trial N + 1 indicates whether a reward will occur on trial N + 2, and so forth. Humans do not appear to be able to learn the 1-back rule.⁵ Pigeons, however, do show 1-back reinforcement learning,^6,7 and they appear to do so implicitly by gradually learning the correlation between their response on one trial and the outcome on the next trial (because all other relations are uncorrelated with the outcome). They learn the task slowly and to a level below what would be expected had they learned it explicitly. The present results, together with research with humans,⁷ suggest that there are times when human explicit learning may interfere with the ability of humans to learn. Pigeons, however, are not "distracted" by attempts at explicit learning, and thus they are able to learn this and other similar tasks.^6,7,8.

Aging effects and feasibility of statistical learning tasks across modalities

Knowledge on statistical learning (SL) in healthy elderly is scarce. Theoretically, it is not clear whether aging affects modality-specific and/or domain-general learning mechanisms. Practically, there is a lack of research on simplified SL tasks, which would ease the burden of testing in clinical populations. Against this background, we conducted two experiments across three modalities (auditory, visual and visuomotor) in a total of 93 younger and older adults. In Experiment 1, SL was induced in all modalities. Aging effects appeared in the tasks relying on an explicit posttest to assess SL. We hypothesize that declines in domain-general processes that predominantly modulate explicit learning mechanisms underlie these aging effects. In Experiment 2, more feasible tasks were developed for which the level of SL was maintained in all modalities, except the auditory modality. These tasks are more likely to successfully measure SL in elderly (patient) populations in which task demands can be problematic.

Explicit Instructions Do Not Enhance Auditory Statistical Learning in Children With Developmental Language Disorder: Evidence From Event-Related Potentials

A current issue in psycholinguistic research is whether the language difficulties exhibited by children with developmental language disorder [DLD, previously labeled specific language impairment (SLI)] are due to deficits in their abilities to pick up patterns in the sensory environment, an ability known as statistical learning (SL), and the extent to which explicit learning mechanisms can be used to compensate for those deficits. Studies designed to test the compensatory role of explicit learning mechanisms in children with DLD are, however, scarce, and the few conducted so far have led to inconsistent results. This work aimed to provide new insights into the role that explicit learning mechanisms might play on implicit learning deficits in children with DLD by resorting to a new approach. This approach involved not only the collection of event-related potentials (ERPs), while preschool children with DLD [relative to typical language developmental (TLD) controls] were exposed to a continuous auditory stream made of the repetition of three-syllable nonsense words but, importantly, the collection of ERPs when the same children performed analogous versions of the same auditory SL task first under incidental (implicit) and afterward under intentional (explicit) conditions. In each of these tasks, the level of predictability of the three-syllable nonsense words embedded in the speech streams was also manipulated (high vs. low) to mimic natural languages closely. At the end of both tasks' exposure phase, children performed a two-alternative forced-choice (2-AFC) task from which behavioral evidence of SL was obtained. Results from the 2-AFC tasks failed to show reliable signs of SL in both groups of children. The ERPs data showed, however, significant modulations in the N100 and N400 components, taken as neural signatures of word segmentation in the brain, even though a detailed analysis of the neural responses revealed that only children from the TLD group seem to have taken advantage of the previous knowledge to enhance SL functioning. These results suggest that children with DLD showed deficits both in implicit and explicit learning mechanisms, casting doubts on the efficiency of the interventions relying on explicit instructions to help children with DLD to overcome their language difficulties.

Competition between parallel sensorimotor learning systems

Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error.

Separation of multiple motor memories through implicit and explicit processes

Acquisition of multiple motor skills without interference is a remarkable ability in daily life. During adaptation to opposing perturbations, a common paradigm to study this ability, each perturbation can be successfully learned when a contextual follow-through movement is associated with the direction of the perturbation. It is still unclear, however, to what extent this learning engages the cognitive explicit process and the implicit process. Here, we untangled the individual contributions of the explicit and implicit components while participants learned opposing visuomotor perturbations, with a second unperturbed follow-through movement. In Exp. 1 we replicated previous adaptation results and showed that follow-through movements also allow learning for opposing visuomotor rotations. For one group of participants in Exp. 2 we isolated strategic explicit learning, while for another group we isolated the implicit component. Our data showed that opposing perturbations could be fully learned by explicit strategies; but when strategy was restricted, distinct implicit processes contributed to learning. In Exp.3, we examined whether learning is influenced by the disparity between the follow-through contexts. We found that the location of follow-through targets had little effect on total learning, yet it led to more instances in which participants failed to learn the task. In Exp. 4, we explored the generalization capability to untrained targets. Participants showed near-flat generalization of the implicit and explicit processes. Overall, our results indicate that follow-through contextual cues might activate, in part, top-down cognitive factors that influence not only the dynamics of the explicit learning, but also the implicit process.

Implicit motor learning in primary school children: A systematic review

The aim of this study was to assess the current state of evidence and methodological quality of studies on implicit and explicit motor learning in both typically developing children and children with developmental disorders. A systematic literature review was conducted on the experimental literature published up to April 2020. A total of 25 studies were included. Studies were evaluated on methodological quality, paradigm used, and level of evidence. The results showed that implicit paradigms are as effective as explicit paradigms in both groups of children. Studies are predominantly experimental in nature involving mostly upper limb aiming tasks. The few studies that were performed outside the lab (n = 5) suggest superior efficacy of the implicit paradigm. Methodological quality varied between studies and was not always of sufficient standard to allow conclusions. In particular, manipulation checks were only performed in 13 studies (52% of all studies), limiting conclusions. Further progress can be made by focussing on improving methodological quality through retention testing by the inclusion of a control group, by the inclusion of a manipulation check, and via assessment of relevant co-variables, such as working memory, age, and motor competence.

Taking aim at the perceptual side of motor learning: exploring how explicit and implicit learning encode perceptual error information through depth vision

Motor learning in visuomotor adaptation tasks results from both explicit and implicit processes, each responding differently to an error signal. Although the motor output side of these processes has been extensively studied, the visual input side is relatively unknown. We investigated if and how depth perception affects the computation of error information by explicit and implicit motor learning. Two groups of participants made reaching movements to bring a virtual cursor to a target in the frontoparallel plane. The Delayed group was allowed to reaim and their feedback was delayed to emphasize explicit learning, whereas the camped group received task-irrelevant clamped cursor feedback and continued to aim straight at the target to emphasize implicit adaptation. Both groups played this game in a highly detailed virtual environment (depth condition), leveraging a cover task of playing darts in a virtual tavern, and in an empty environment (no-depth condition). The delayed group showed an increase in error sensitivity under depth relative to no-depth. In contrast, the clamped group adapted to the same degree under both conditions. The movement kinematics of the delayed participants also changed under the depth condition, consistent with the target appearing more distant, unlike the Clamped group. A comparison of the delayed behavioral data with a perceptual task from the same individuals showed that the greater reaiming in the depth condition was consistent with an increase in the scaling of the error distance and size. These findings suggest that explicit and implicit learning processes may rely on different sources of perceptual information.NEW & NOTEWORTHY We leveraged a classic sensorimotor adaptation task to perform a first systematic assessment of the role of perceptual cues in the estimation of an error signal in the 3-D space during motor learning. We crossed two conditions presenting different amounts of depth information, with two manipulations emphasizing explicit and implicit learning processes. Explicit learning responded to the visual conditions, consistent with perceptual reports, whereas implicit learning appeared to be independent of them.

Use of explicit processes during a visually guided locomotor learning task predicts 24-h retention after stroke

Implicit and explicit processes can occur within a single locomotor learning task. The combination of these learning processes may impact how individuals acquire/retain the task. Because these learning processes rely on distinct neural pathways, neurological conditions may selectively impact the processes that occur, thus, impacting learning and retention. Thus, our purpose was to examine the contribution of implicit and explicit processes during a visually guided walking task and characterize the relationship between explicit processes and performance/retention in stroke survivors and age-matched healthy adults. Twenty chronic stroke survivors and twenty healthy adults participated in a 2-day treadmill study. Day 1 included baseline, acquisition1, catch, acquisition2, and immediate retention phases, and day 2 included 24-h retention. During acquisition phases, subjects learned to take a longer step with one leg through distorted visual feedback. During catch and retention phases, visual feedback was removed and subjects were instructed to walk normally (catch) or how they walked during the acquisition phases (retention). Change in step length from baseline to catch represented implicit processes. Change in step length from catch to the end of acquisition2 represented explicit processes. A mixed ANOVA found no difference in the type of learning between groups (P = 0.74). There was a significant relationship between explicit processes and 24-h retention in stroke survivors (r = 0.47, P = 0.04) but not in healthy adults (r = 0.34, P = 0.15). These results suggest that stroke may not affect the underlying learning mechanisms used during locomotor learning, but that these mechanisms impact how well stroke survivors retain the new walking pattern.NEW & NOTEWORTHY This study found that stroke survivors used implicit and explicit processes similar to age-matched healthy adults during a visually guided locomotion learning task. The amount of explicit processes was related to how well stroke survivors retained the new walking pattern but not to how well they performed during the task. This work illustrates the importance of understanding the underlying learning mechanisms to maximize retention of a newly learned motor behavior.

Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning

Statistical learning (SL), the process of extracting regularities from the environment, is a fundamental skill of our cognitive system to structure the world regularly and predictably. SL has been studied using mainly behavioral tasks under implicit conditions and with triplets presenting the same level of difficulty, i.e., a mean transitional probability (TP) of 1.00. Yet, the neural mechanisms underlying SL under other learning conditions remain largely unknown. Here, we investigated the neurofunctional correlates of SL using triplets (i.e., three-syllable nonsense words) with a mean TP of 1.00 (easy "words") and 0.50 (hard "words") in an SL task performed under incidental (implicit) and intentional (explicit) conditions, to determine whether the same core mechanisms were recruited to assist learning. Event-related potentials (ERPs) were recorded while participants listened firstly to a continuous auditory stream made of the concatenation of four easy and four hard "words" under implicit instructions, and subsequently to another auditory stream made of the concatenation of four easy and four hard "words" drawn from another artificial language under explicit instructions. The stream in each of the SL tasks was presented in two consecutive blocks of ~3.5-min each (~7-min in total) to further examine how ERP components might change over time. Behavioral measures of SL were collected after the familiarization phase of each SL task by asking participants to perform a two-alternative forced-choice (2-AFC) task. Results from the 2-AFC tasks revealed a moderate but reliable level of SL, with no differences between conditions. ERPs were, nevertheless, sensitive to the effect of TPs, showing larger amplitudes of N400 for easy "words," as well as to the effect of instructions, with a reduced N250 for "words" presented under explicit conditions. Also, significant differences in the N100 were found as a result of the interaction between TPs, instructions, and the amount of exposure to the auditory stream. Taken together, our findings suggest that triplets' predictability impacts the emergence of "words" representations in the brain both for statistical regularities extracted under incidental and intentional instructions, although the prior knowledge of the "words" seems to favor the recruitment of different SL mechanisms.

Adaptive Changes in the Dynamics of Visual Attention With Extended Practice

Previous research indicates that visual attention can adapt to temporal stimulus patterns utilizing the rapid serial visual presentation (RSVP) task. However, how the temporal dynamics of an attentional pulse adapt to temporal patterns has not been explored. We addressed this question by conducting an attentional component analysis on RSVP performance and explored whether changes in attentional dynamics were accompanied by explicit learning about predictable target timing. We utilized an RSVP task in which a target letter appeared either in two possible RSVP positions in fixed-timing conditions or in random positions over 1, 2, or 3 days of training. In a transfer phase, the target appeared in previously presented or new positions. Over 3 days of practice the target identification rate, efficacy, and precision of a putative attentional pulse increased. These changes reflected general learning in the RSVP task resulting in attentional dynamics more efficiently focused on the target. Although group performance effects did not support learning of fixed target positions, target identification rates and the measure of the efficacy of an attentional pulse at these positions were positively associated with explicit learning. The current study is the first to provide a detailed description of practice related adaptation of attentional dynamics and suggests that timing specific changes might be mediated by explicit temporal learning.

Treatment of agrammatism in oral and written production in patients with Broca's aphasia The use of implicit and explicit learning

Several approaches to the rehabilitation of agrammatism use implicit and explicit learning methods.

Verbal Instructions and Motor Learning: How Analogy and Explicit Instructions Influence the Development of Mental Representations and Tennis Serve Performance

To better understand the benefits of using analogy and explicit instructions, the underlying cognitive mechanism remains to be explored. The concept of chunking provides a promising approach to the cognitive mechanism of instructions and can be approximated by analyzing athletes’ mental representations. The purpose of this study was to investigate the influence of analogy and explicit instructions on performance and the cognitive representations of the tennis serve in intermediate participants over the course of a 5-week training period. Junior tennis players (N = 44; M = 11.5 years) were tested on their tennis serve and, based on their initial performance and their individual error patterns, assigned to one of three groups: an analogy group (N = 15), an explicit group (N = 15), or a control group (N = 14). Their performance and their mental representation structures were assessed prior to and after the 5-week training period and again after a retention period of 14 days. Independent of group, findings demonstrated higher velocity from pretest to posttest. Participants in both the analogy and the explicit group showed enhanced accuracy over time and more functional mental representation structures. Thus, both analogy instruction and explicit instruction helped to structure mental representations in their long-term memory.

Eye Movements during Visuomotor Adaptation Represent Only Part of the Explicit Learning

Visuomotor rotations are learned through a combination of explicit strategy and implicit recalibration. However, measuring the relative contribution of each remains a challenge and the possibility of multiple explicit and implicit components complicates the issue. Recent interest has focused on the possibility that eye movements reflects explicit strategy. Here we compared eye movements during adaptation to two accepted measures of explicit learning: verbal report and the exclusion test. We found that while reporting, all subjects showed a match among all three measures. However, when subjects did not report their intention, the eye movements of some subjects suggested less explicit adaptation than what was measured in an exclusion test. Interestingly, subjects whose eye movements did match their exclusion could be clustered into the following two subgroups: fully implicit learners showing no evidence of explicit adaptation and explicit learners with little implicit adaptation. Subjects showing a mix of both explicit and implicit adaptation were also those where eye movements showed less explicit adaptation than did exclusion. Thus, our results support the idea of multiple components of explicit learning as only part of the explicit learning is reflected in the eye movements. Individual subjects may use explicit components that are reflected in the eyes or those that are not or some mixture of the two. Analysis of reaction times suggests that the explicit components reflected in the eye movements involve longer reaction times. This component, according to recent literature, may be related to mental rotation.

Variable Neural Contributions to Explicit and Implicit Learning During Visuomotor Adaptation

We routinely make fine motor adjustments to maintain optimal motor performance. These adaptations have been attributed to both implicit, error-based mechanisms, and explicit, strategy-based mechanisms. However, little is known about the neural basis of implicit vs. explicit learning. Here, we aimed to use anodal transcranial direct current stimulation (tDCS) to probe the relationship between different brain regions and learning mechanisms during a visuomotor adaptation task in humans. We hypothesized that anodal tDCS over the cerebellum (CB) should increase implicit learning while anodal tDCS over the dorsolateral prefrontal cortex (dlPFC), a region associated with higher-level cognition, should facilitate explicit learning. Using a horizontal visuomotor adaptation task that measures explicit/implicit contributions to learning (Taylor et al., 2014), we found that dlPFC stimulation significantly improved performance compared to the other groups, and weakly increased explicit learning. However, CB stimulation had no effects on either target error or implicit learning. Previous work showed variable CB stimulation effects only on a vertical visuomotor adaptation task (Jalali et al., 2017), so in Experiment 2, we conducted the same study using a vertical context to see if we could find effects of CB stimulation. We found only weak effects of CB stimulation on target error and implicit learning, and now the dlPFC effect did not replicate. To resolve this discrepancy, in Experiment 3, we examined the effect of context (vertical vs. horizontal) on implicit and explicit contributions and found that individuals performed significantly worse and used greater implicit learning in the vertical screen condition compared to the horizontal screen condition. Across all experiments, however, there was high inter-individual variability, with strong influences of a few individuals, suggesting that these effects are not consistent across individuals. Overall, this work provides preliminary support for the idea that different neural regions can be engaged to improve visuomotor adaptation, but shows that each region's effects are highly context-dependent and not clearly dissociable from one another. This holds implications especially in neurorehabilitation, where an intact neural region could be engaged to potentially compensate if another region is impaired. Future work should examine factors influencing interindividual variability during these processes.

A locomotor learning paradigm using distorted visual feedback elicits strategic learning

Distorted visual feedback (DVF) during locomotion has been suggested to result in the development of a new walking pattern in healthy individuals through implicit learning processes. Recent work in upper extremity visuomotor rotation paradigms suggest that these paradigms involve implicit and explicit learning. Additionally, in upper extremity visuomotor paradigms, the verbal cues provided appear to impact how a behavior is learned and when this learned behavior is used. Here, in two experiments in neurologically intact individuals, we tested how verbal instruction impacts learning a new locomotor pattern on a treadmill through DVF, the transfer of that pattern to overground walking, and what types of learning occur (i.e., implicit vs. explicit learning). In experiment 1, we found that the instructions provided impacted the amount learned through DVF, but not the size of the aftereffects or the amount of the pattern transferred to overground walking. Additionally, the aftereffects observed were significantly different from the baseline walking pattern, but smaller than the behavior changes observed during learning, which is uncharacteristic of implicit sensorimotor adaptation. Thus, experiment 2 aimed to determine the cause of these discrepancies. In this experiment, when VF was not provided, individuals continued using the learned walking pattern when instructed to do so and returned toward their baseline pattern when instructed to do so. Based on these results, we conclude that DVF during locomotion results in a large portion of explicit learning and a small portion of implicit learning. NEW & NOTEWORTHY The results of this study suggest that distorted visual feedback during locomotor learning involves the development of an explicit strategy with only a small component of implicit learning. This is important because previous studies using distorted visual feedback have suggested that locomotor learning relies primarily on implicit learning. This paradigm, therefore, provides a new way to examine a different form of learning in locomotion.

Chunking, Conscious Processing, and EEG During Sequence Acquisition and Performance Pressure: A Comprehensive Test of Reinvestment Theory

This study was designed to test the theorized link between reinvestment, motor chunks, and conscious processing, to provide a thorough examination of reinvestment theory. The authors measured electroencephalographic power and connectivity alongside self-reported conscious processing and behavioral indices of chunking in a 2 (group) × 5 (block) mixed-model design. A total of 55 individuals acquired a motor sequence (blocks A1, A2, A3, and A4) by relatively explicit (errorful) or implicit (errorless) paradigms. Then they performed in a pressure condition (block T). Results confirmed that chunking characterizes both modes of acquisition. However, explicit acquisition resulted in quicker chunking, reduced conscious processing, and increased cortical efficiency (left-temporal high-alpha power). In support of reinvestment theory, self-reported conscious processing tended to increase under pressure among explicit trainees only. In contrast to reinvestment theory, this had no adverse effect on performance. The results endorse explicit acquisition as an effective mode of training and provide a new neurophysiological explanation of this phenomenon.

The Effects of Implicit and Explicit Motor Learning in Gait Rehabilitation of People After Stroke: Protocol for a Randomized Controlled Trial

Background

A significant part of neurological rehabilitation focuses on facilitating the learning of motor skills. Training can adopt either (more) explicit or (more) implicit forms of motor learning. Gait is one of the most practiced motor skills within rehabilitation in people after stroke because it is an important criterion for discharge and requirement for functioning at home.

Objective

The aim of this study was to describe the design of a randomized controlled study assessing the effects of implicit motor learning compared with the explicit motor learning in gait rehabilitation of people suffering from stroke.

Methods

The study adopts a randomized, controlled, single-blinded study design. People after stroke will be eligible for participation when they are in the chronic stage of recovery (>6 months after stroke), would like to improve walking performance, have a slow walking speed (<1 m/s), can communicate in Dutch, and complete a 3-stage command. People will be excluded if they cannot walk a minimum of 10 m or have other additional impairments that (severely) influence gait. Participants will receive 9 gait-training sessions over a 3-week period and will be randomly allocated to an implicit or explicit group. Therapists are aware of the intervention they provide, and the assessors are blind to the intervention participants receive. Outcome will be assessed at baseline (T0), directly after the intervention (T1), and after 1 month (T2). The primary outcome parameter is walking velocity. Walking performance will be assessed with the 10-meter walking test, Dynamic Gait Index, and while performing a secondary task (dual task). Self-reported measures are the Movement Specific Reinvestment Scale, verbal protocol, Stroke and Aphasia Quality of Life Scale, and the Global Perceived Effect scale. A process evaluation will take place to identify how the therapy was perceived and identify factors that may have influenced the effectiveness of the intervention. Repeated measures analyses will be conducted to determine significant and clinical relevant differences between groups and over time.

Results

Data collection is currently ongoing and results are expected in 2019.

Conclusions

The relevance of the study as well as the advantages and disadvantages of several aspects of the chosen design are discussed, for example, the personalized approach and choice of measurements.

Trial Registration

Netherlands Trial Register NTR6272; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=6272 (Archived by WebCite http://www.webcitation.org/6ytA937m5)

Registered Report Identifier

RR1-10.2196/9595

Working Memory Capacity Limits Motor Learning When Implementing Multiple Instructions

Although it is generally accepted that certain practice conditions can place large demands on working memory (WM) when performing and learning a motor skill, the influence that WM capacity has on the acquisition of motor skills remains unsubstantiated. This study examined the role of WM capacity in a motor skill practice context that promoted WM involvement through the provision of explicit instructions. A cohort of 90 children aged 8 to 10 years were assessed on measures of WM capacity and attention. Children who scored in the lowest and highest thirds on the WM tasks were allocated to lower WM capacity (n = 24) and higher WM capacity (n = 24) groups, respectively. The remaining 42 participants did not participate in the motor task. The motor task required children to practice basketball shooting for 240 trials in blocks of 20 shots, with pre- and post-tests occurring before and after the intervention. A retention test was administered 1 week after the post-test. Prior to every practice block, children were provided with five explicit instructions that were specific to the technique of shooting a basketball. Results revealed that the higher WM capacity group displayed consistent improvements from pre- to post-test and through to the retention test, while the opposite effect occurred in the lower WM capacity group. This implies that the explicit instructions had a negative influence on learning by the lower WM capacity children. Results are discussed in relation to strategy selection for dealing with instructions and the role of attention control.

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly (experiment 1) or gradually (experiment 2). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability (experiment 3). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials.NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory prediction errors to update an internal model. Here we show that these individuals also have difficulty in discovering an aiming solution to overcome their adaptation deficit, suggesting a new role for the cerebellum in sensorimotor adaptation tasks.

A Comparison of Implicit and Explicit Motor Sequence Learning in Patients with Relapsing-Remitting Multiple Sclerosis

This study tends to assess implicit and explicit types of motor learning in patients with Multiple Sclerosis (MS) and normal peers by means of a serial reaction time. Sample size was 15 for each group and Samples included 30 patients with MS and 30 normal peers and were assigned to implicit and explicit learning groups. A repeated measures ANOVA was used for measuring reaction time and response error, and a paired samples t-test was used to compare regular and irregular sequence data in each group. Comparison of these two types of learning in speed (response time) and accuracy (number of errors) showed the number of errors (P = 0.012) and response time (P = 0.012) in the implicit motor learning group of MS patients and the number of errors (P = 0.096) and response time (P = 0.954) in the explicit motor learning group of MS patients. Moreover, comparison showed the number of errors (P = 0.008) and response time (P = 0.05) in the implicit group of normal peers and the number of errors (P = 0.011) and response time (P = 0.442) in the explicit group of normal peers. The results showed that explaining and describing the task is less effective at training the motor sequence of MS patients and that these patients benefit more from implicit learning.

Implications of plan-based generalization in sensorimotor adaptation

Generalization is a fundamental aspect of behavior, allowing for the transfer of knowledge from one context to another. The details of this transfer are thought to reveal how the brain represents what it learns. Generalization has been a central focus in studies of sensorimotor adaptation, and its pattern has been well characterized: Learning of new dynamic and kinematic transformations in one region of space tapers off in a Gaussian-like fashion to neighboring untrained regions, echoing tuned population codes in the brain. In contrast to common allusions to generalization in cognitive science, generalization in visually guided reaching is usually framed as a passive consequence of neural tuning functions rather than a cognitive feature of learning. While previous research has presumed that maximum generalization occurs at the instructed task goal or the actual movement direction, recent work suggests that maximum generalization may occur at the location of an explicitly accessible movement plan. Here we provide further support for plan-based generalization, formalize this theory in an updated model of adaptation, and test several unexpected implications of the model. First, we employ a generalization paradigm to parameterize the generalization function and ascertain its maximum point. We then apply the derived generalization function to our model and successfully simulate and fit the time course of implicit adaptation across three behavioral experiments. We find that dynamics predicted by plan-based generalization are borne out in the data, are contrary to what traditional models predict, and lead to surprising implications for the behavioral, computational, and neural characteristics of sensorimotor adaptation.NEW & NOTEWORTHY The pattern of generalization is thought to reveal how the motor system represents learned actions. Recent work has made the intriguing suggestion that maximum generalization in sensorimotor adaptation tasks occurs at the location of the learned movement plan. Here we support this interpretation, develop a novel model of motor adaptation that incorporates plan-based generalization, and use the model to successfully predict surprising dynamics in the time course of adaptation across several conditions.

Estimating the implicit component of visuomotor rotation learning by constraining movement preparation time

When sensory feedback is perturbed, accurate movement is restored by a combination of implicit processes and deliberate reaiming to strategically compensate for errors. Here, we directly compare two methods used previously to dissociate implicit from explicit learning on a trial-by-trial basis: 1) asking participants to report the direction that they aim their movements, and contrasting this with the directions of the target and the movement that they actually produce, and 2) manipulating movement preparation time. By instructing participants to reaim without a sensory perturbation, we show that reaiming is possible even with the shortest possible preparation times, particularly when targets are narrowly distributed. Nonetheless, reaiming is effortful and comes at the cost of increased variability, so we tested whether constraining preparation time is sufficient to suppress strategic reaiming during adaptation to visuomotor rotation with a broad target distribution. The rate and extent of error reduction under preparation time constraints were similar to estimates of implicit learning obtained from self-report without time pressure, suggesting that participants chose not to apply a reaiming strategy to correct visual errors under time pressure. Surprisingly, participants who reported aiming directions showed less implicit learning according to an alternative measure, obtained during trials performed without visual feedback. This suggests that the process of reporting can affect the extent or persistence of implicit learning. The data extend existing evidence that restricting preparation time can suppress explicit reaiming and provide an estimate of implicit visuomotor rotation learning that does not require participants to report their aiming directions.NEW & NOTEWORTHY During sensorimotor adaptation, implicit error-driven learning can be isolated from explicit strategy-driven reaiming by subtracting self-reported aiming directions from movement directions, or by restricting movement preparation time. Here, we compared the two methods. Restricting preparation times did not eliminate reaiming but was sufficient to suppress reaiming during adaptation with widely distributed targets. The self-report method produced a discrepancy in implicit learning estimated by subtracting aiming directions and implicit learning measured in no-feedback trials.

Different Effects of Implicit and Explicit Motor Sequence Learning on Latency of Motor Evoked Potential Evoked by Transcranial Magnetic Stimulation on the Primary Motor Cortex

Motor training induces plastic changes in the primary motor cortex (M1). However, it is unclear whether and how the latency of motor-evoked potentials (MEP) and MEP amplitude are affected by implicit and/or explicit motor learning. Here, we investigated the changes in M1 excitability and MEP latency induced by implicit and explicit motor learning. The subjects performed a serial reaction time task (SRTT) with their five fingers. In this task, visual cues were lit up sequentially along with a predetermined order. Through training, the subjects learned the order of sequence implicitly and explicitly. Before and after the SRTT, we recorded MEP at 25 stimulation points around the hot spot for the flexor pollicis brevis (FPB) muscle. Although no changes in MEP amplitude were observed in either session, we found increases in MEP latency and changes in histogram of MEP latency after implicit learning. Our results suggest that reorganization across the motor cortices occurs during the acquisition of implicit knowledge. In contrast, acquisition of explicit knowledge does not appear to induce the reorganization based on the measures we recorded. The fact that the above mentioned increases in MEP latency occurred without any alterations in MEP amplitude suggests that learning has different effects on different physiological signals. In conclusion, our results propose that analyzing a combination of some indices of M1 excitability, such as MEP amplitude and MEP latency, is encouraged in order to understand plasticity across motor cortices.

Effect of coordinate frame compatibility on the transfer of implicit and explicit learning across limbs

Insights into the neural representation of motor learning can be obtained by investigating how learning transfers to novel task conditions. We recently demonstrated that visuomotor rotation learning transferred strongly between left and right limbs when the task was performed in a sagittal workspace, which afforded a consistent remapping for the two limbs in both extrinsic and joint-based coordinates. In contrast, transfer was absent when performed in horizontal workspace, where the extrinsically defined perturbation required conflicting joint-based remapping for the left and right limbs. Because visuomotor learning is thought to be supported by both implicit and explicit forms of learning, however, it is unclear to what extent these distinct forms of learning contribute to interlimb transfer. In this study, we assessed the degree to which interlimb transfer, following visuomotor rotation training, reflects explicit vs. implicit learning by obtaining verbal reports of participants' aiming direction before each movement. We also determined the extent to which these distinct components of learning are constrained by the compatibility of coordinate systems by comparing transfer between groups of participants who reached to targets arranged in the horizontal and sagittal planes. Both sagittal and horizontal conditions displayed complete transfer of explicit learning to the untrained limb. In contrast, transfer of implicit learning was incomplete, but the sagittal condition showed greater transfer than the horizontal condition. These findings suggest that explicit strategies developed with one limb can be fully implemented in the opposite limb, whereas implicit transfer depends on the degree to which new sensorimotor maps are spatially compatible for the two limbs.

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning.

Facial beauty affects implicit and explicit learning of men and women differently

The present work explores the unconscious and/or conscious nature of learning attractive faces of same and opposite sex, that is, of stimuli that experimental and neuroimaging research has shown to be rewarding and thus highly motivating. To this end, we examined performance of men and women while classifying strings of average and attractive faces for grammaticality in the experimental task of artificial grammar learning (AGL), which reflects both conscious and unconscious processes. Subjective measures were used to assess participants' conscious and unconscious knowledge. It was found that female attractiveness impaired performance in male participants. In particular, male participants demonstrated the lowest accuracy while classifying beautiful faces of women. Conversely, female attractiveness facilitated performance in female participants. The pattern was similar for conscious and unconscious knowledge. Presumably, objects with high incentive salience, as are beautiful faces, captured resources, which were used in task relevant versus task irrelevant ways by women versus men. The present findings shed light on the relation of conscious and unconscious processing with affective and reward-related stimuli, as well as on gender differences underlying this relation.

The Structural Relationship Between Two Motor Sequences Practiced Close in Time Impacts Offline Facilitation

Robust offline gains occur during explicit motor sequence learning. However practice of a motor sequence, other than the target sequence, within 4-6 hr after initial practice interferes with these gains. This work assessed if experiencing supplemental practice of spatially or motorically similar sequences influenced the extent of offline gain. A contemporary model of sequence learning assumes that exposure to a spatially but not motor-related sequence would not compromise stabilization of the memory for the target sequence, thus, would have minimal impact on the resultant offline gain and possibly amplify overnight gains. As anticipated, a reliable offline improvement was observed for the target motor sequence in the absence of practice with an alternative motor sequence. This gain was significantly reduced when the learner experienced additional practice with either a novel or motorically similar sequence. There was no evidence of heightened overnight gain for the target sequence from intervening practice with a spatially similar sequence. Thus, the expression of offline improvement is not necessarily eliminated if practice of an alternative motor sequence is encountered shortly after a target sequence. However, the structure of the motor sequence faced during intervening practice can impact the resultant postpractice consolidation processes reflected in the eventual expression of offline facilitation.

Flexible explicit but rigid implicit learning in a visuomotor adaptation task

There is mounting evidence for the idea that performance in a visuomotor rotation task can be supported by both implicit and explicit forms of learning. The implicit component of learning has been well characterized in previous experiments and is thought to arise from the adaptation of an internal model driven by sensorimotor prediction errors. However, the role of explicit learning is less clear, and previous investigations aimed at characterizing the explicit component have relied on indirect measures such as dual-task manipulations, posttests, and descriptive computational models. To address this problem, we developed a new method for directly assaying explicit learning by having participants verbally report their intended aiming direction on each trial. While our previous research employing this method has demonstrated the possibility of measuring explicit learning over the course of training, it was only tested over a limited scope of manipulations common to visuomotor rotation tasks. In the present study, we sought to better characterize explicit and implicit learning over a wider range of task conditions. We tested how explicit and implicit learning change as a function of the specific visual landmarks used to probe explicit learning, the number of training targets, and the size of the rotation. We found that explicit learning was remarkably flexible, responding appropriately to task demands. In contrast, implicit learning was strikingly rigid, with each task condition producing a similar degree of implicit learning. These results suggest that explicit learning is a fundamental component of motor learning and has been overlooked or conflated in previous visuomotor tasks.

Self-insight in probabilistic category learning

The Weather Prediction (WP) task is one of the most extensively used Probabilistic Category Learning tasks. Although it has been usually treated as an implicit task, its implicit nature has been questioned with focus on the structural knowledge of the acquired information. The goal of the current studies is to test if participants acquire explicit knowledge on the WP task. Experiment 1 addresses this question directly with the help of a subjective measure on self-insight in two groups: an experimental group facing the WP task and a control group with a task lacking predictive structure. Participants in the experimental group produced more explicit reports than the control group, and only on trials with explicit knowledge was their performance higher. Experiment 2 provided further evidence against the implicitness of the task by showing that decreasing stimulus presentation times extends the learning process, but does not result in more implicit processes.

Statistical learning under incidental versus intentional conditions

Statistical learning (SL) studies have shown that participants are able to extract regularities in input they are exposed to without any instruction to do so. This and other findings, such as the fact that participants are often unable to verbalize their acquired knowledge, suggest that SL can occur implicitly or incidentally. Interestingly, several studies using the related paradigms of artificial grammar learning and serial response time tasks have shown that explicit instructions can aid learning under certain conditions. Within the SL literature, however, very few studies have contrasted incidental and intentional learning conditions. The aim of the present study was to investigate the effect of having prior knowledge of the statistical regularities in the input when undertaking a task of visual sequential SL. Specifically, we compared the degree of SL exhibited by participants who were informed (intentional group) versus those who were uninformed (incidental group) about the presence of embedded triplets within a familiarization stream. Somewhat surprisingly, our results revealed that there were no statistically significant differences (and only a small effect size) in the amount of SL exhibited between the intentional versus the incidental groups. We discuss the ways in which this result can be interpreted and suggest that short presentation times for stimuli in the familiarization stream in our study may have limited the opportunity for explicit learning. This suggestion is in line with recent research revealing a statistically significant difference (and a large effect size) between intentional versus incidental groups using a very similar visual sequential SL task, but with longer presentation times. Finally, we outline a number of directions for future research.

Rule-based and information-integration perceptual category learning in children with attention-deficit/hyperactivity disorder

OBJECTIVE

Suboptimal functioning of the basal ganglia is implicated in attention-deficit/hyperactivity disorder (ADHD). These structures are important to the acquisition of associative knowledge, leading some to theorize that associative learning deficits might be expected, despite the fact that most extant research in ADHD has focused on effortful control. We present 2 studies that examined the acquisition of explicit rule-based (RB) and associative information integration (II) category learning among school-age children with ADHD.

METHOD AND RESULTS

In Study 1, we found deficits in both RB and II category learning tasks among children with ADHD (n = 81) versus controls (n = 42). Children with ADHD tended to sort by the more salient but irrelevant dimension (in the RB paradigm) and were unable to acquire a consistent sorting strategy (in the II paradigm). To disentangle whether the deficit was localized to II category learning versus a generalized inability to consider more than 1 stimulus dimension, in Study 2 children completed a conjunctive RB paradigm that required consideration of 2 stimulus dimensions. Children with ADHD (n = 50) continued to underperform controls (n = 33).

CONCLUSIONS

Results provide partial support for neurocognitive developmental theories of ADHD that suggest that associative learning deficits should be found, and highlight the importance of using analytic approaches that go beyond asking whether an ADHD-related deficit exists to why such deficits exist.

Self-insight in probabilistic categorization - not implicit in children either

The weather prediction (WP) task is a probabilistic category learning task that was designed to be implicit/procedural. In line with this claim, early results showed that patients with amnesia perform comparably to healthy participants. On the other hand, later research on healthy adult participants drew attention to the fact that the WP task is not necessarily implicit. There have been results showing that participants can access structural information acquired during the task. Participants also report that their responses are based on memories and rule knowledge. The contradictory results may be reconciled by assuming that while explicit learning occurs on the WP task in case of adults, in children the learning process is implicit. The present study aims at testing this hypothesis. Primary school children completed the WP task; the experimental group performed the original task, whereas in the control group cues and outcomes were associated on a random basis, hence their version of the WP task lacked a predictive structure. After each item, participants were asked whether they relied on guessing, intuition, “I think I know the answer” type of knowledge, memories of previous items, or knowledge of rules. Self-insight reports of the experimental group were compared to a control group. Results showed that children learn similarly to adults: they mostly (but not completely) rely on explicit, and not on implicit processes.

Towards mastery of complex visuo-motor transformations

In this paper we review and integrate a set of findings on learning the transformation of a sliding first-order lever, a type of tool with a prominent role in minimal access surgery. Its kinematic transformation is characterized by the so-called fulcrum effect, the inversion of the movement direction of the tip of the lever relative to that of the hand for rotations. A second characteristic is gain anisotropy, which results in curved paths of the tip of the lever for straight paths of the hand and vice versa. An internal model of the kinematic transformation is acquired during practice, the accuracy of which can be assessed in visual open-loop test trials. The accuracy of the acquired internal model is enhanced when visual closed-loop control during practice is impeded, and the accuracy of the internal model is reduced when closed-loop control during practice is facilitated. The internal model consists of a rapidly acquired line-symmetric approximation to the transformation of the sliding lever and a slowly acquired fine tuning. The fine tuning is local, that is, it is specific for the region of the workspace encountered during practice. The internal model is transferred to other regions of the workspace, but not adjusted to the fine tuning appropriate for these regions. Whereas the symmetry approximation is most likely explicit, the fine tuning seems to be represented implicitly. Findings on the straightness of the paths of the tip of the lever and the hand suggest that the internal model of the transformation is confined to initial and final positions of aimed movements, whereas their path is not strictly controlled, but affected by the dynamic transformation of the tool. Only when visual closed-loop control is possible, the path of the effective part of the tool is straightened. These characteristics of the internal model of the sliding first-order lever and its acquisition may be partly specific to sufficiently complex extrinsic transformations that arise from mechanical or electronic extensions of the body.

The Movement Kinematics and Learning Strategies Associated with Adopting Different Foci of Attention during Both Acquisition and Anxious Performance

Research suggests that implicit strategies adopted during learning help prevent breakdown of automatic processes and subsequent performance decrements associated with the presence of pressure. According to the Constrained Action Hypothesis, automaticity of movement is promoted when adopting an external focus of attention. The purpose of the current experiment was to investigate if learning with an external focus of attention can enhance performance under subsequent pressure situations through promoting implicit learning and automaticity. Since previous research has generally used outcome measures of performance, the current study adopted measures of movement production. Specifically, we calculated within-subject variability in trajectory velocity and distance traveled every 10% of movement time. This detailed kinematic analysis allowed investigation into some of the previously unexplored mechanisms responsible for the benefits of adopting an external focus of attention. Novice participants performed a 2.5 m golf putt. Following a pre-test, participants were randomly assigned to one of three focus groups (internal, external, control). Participants then completed 400 acquisition trials over two consecutive days before being subjected to both a low anxiety and high anxiety (HA) transfer test. Dependent variables included variability, number of successful putts and mean radial error. Results revealed that variability was greater in the internal compared to the external and control groups. Putting performance revealed that all groups increased performance following acquisition. However, only the control group demonstrated a decrement in performance in the HA transfer test. These findings suggest that adopting an appropriate focus of attention during learning can prevent choking; with an external focus inhibiting the breakdown of automatic processes and an internal focus acting as a self-focus learning strategy and thus desensitizing individuals to anxiety effects.

Development of implicit and explicit category learning

We present two studies that examined developmental differences in the implicit and explicit acquisition of category knowledge. College-attending adults consistently outperformed school-age children on two separate information-integration paradigms due to children's more frequent use of an explicit rule-based strategy. Accuracy rates were also higher for adults on a unidimensional rule-based task due to children's more frequent use of the irrelevant dimension to guide their behavior. Results across these two studies suggest that the ability to learn categorization structures may be dependent on a child's ability to inhibit output from the explicit system.

ACL injury prevention, more effective with a different way of motor learning?

PURPOSE

What happens to the transference of learning proper jump-landing technique in isolation when an individual is expected to perform at a competitive level yet tries to maintain proper jump-landing technique? This is the key question for researchers, physical therapists, athletic trainers and coaches involved in ACL injury prevention in athletes. The need for ACL injury prevention is clear, however, in spite of these ongoing initiatives and reported early successes, ACL injury rates and the associated gender disparity have not diminished. One problem could be the difficulties with the measurements of injury rates and the difficulties with the implementation of thorough large scale injury prevention programs. A second issue could be the transition from conscious awareness during training sessions on technique in the laboratory to unexpected and automatic movements during a training or game involves complicated motor control adaptations. The purpose of this paper is to highlight the issue of motor learning in relation to ACL injury prevention and to post suggestions for future research.

CONCLUSION

ACL injury prevention programs addressing explicit rules regarding desired landing positions by emphasizing proper alignment of the hip, knee, and ankle are reported in the literature. This may very well be a sensible way, but the use of explicit strategies may be less suitable for the acquisition of the control of complex motor skills (Maxwell et al. J Sports Sci 18:111-120, 2000). Sufficient literature on motor learning and it variations point in that direction.

Distinct neural mechanisms for repetition effects of visual objects

Repetition of visually common objects was examined in relation to prior intentional learning and memory status using a delayed match-to-sample task in humans. Both response time and two temporally separate event-related potential (ERP) components indexed repetition. The early repetition effect ( approximately 200-550 ms) evoked more ERP responses for repeated visual objects, and was diminished by prior intentional learning (old/new) or being maintained in working memory (targets/distracters). In contrast, the late repetition effect (after approximately 550 ms) evoked reduced ERP activation for repeated items, and was not affected by prior learning or working memory status. Our source localization results indicate that the late and posterior repetition effect in visual cortex is consistent with repetition suppression results reported in monkey physiology and human fMRI studies. Meanwhile, the early and anterior repetition effect, in temporal pole and frontal cortices, is modulated by explicit memory mechanisms.