Cerebral correlates of explicit sequence learning

Reward actively engages both implicit and explicit components in dual force field adaptation

Motor learning occurs through multiple mechanisms, including unsupervised, supervised (error based), and reinforcement (reward based) learning. Although studies have shown that reward leads to an overall better motor adaptation, the specific processes by which reward influences adaptation are still unclear. Here, we examine how the presence of reward affects dual adaptation to novel dynamics and distinguish its influence on implicit and explicit learning. Participants adapted to two opposing force fields in an adaptation/deadaptation/error-clamp paradigm, where five levels of reward (a score and a digital face) were provided as participants reduced their lateral error. Both reward and control (no reward provided) groups simultaneously adapted to both opposing force fields, exhibiting a similar final level of adaptation, which was primarily implicit. Triple-rate models fit to the adaptation process found higher learning rates in the fast and slow processes and a slightly increased fast retention rate for the reward group. Whereas differences in the slow learning rate were only driven by implicit learning, the large difference in the fast learning rate was mainly explicit. Overall, we confirm previous work showing that reward increases learning rates, extending this to dual-adaptation experiments and demonstrating that reward influences both implicit and explicit adaptation. Specifically, we show that reward acts primarily explicitly on the fast learning rate and implicitly on the slow learning rates.NEW & NOTEWORTHY Here we show that rewarding participants' performance during dual force field adaptation primarily affects the initial rate of learning and the early timescales of adaptation, with little effect on the final adaptation level. However, reward affects both explicit and implicit components of adaptation. Whereas the learning rate of the slow process is increased implicitly, the fast learning and retention rates are increased through both implicit components and the use of explicit strategies.

Involvement of the prefrontal cortex in motor sequence learning: A functional near-infrared spectroscopy (fNIRS) study

Our previous functional near-infrared spectroscopy (fNIRS) study on motor sequence learning (Polskaia et al., 2020) did not detect the same decrease in activity in the left dorsolateral prefrontal cortex (DLPFC) associated with movement automaticity, as reported by Wu et al. (2004). This was partly attributed to insufficient practice time to reach neural efficiency. Therefore, we sought to expand on our previous work to better understand the contribution of the prefrontal cortex (PFC) to motor sequence learning by examining learning across a longer period of time. Participants were randomly assigned to one of two groups: control or trained. fNIRS was acquired at three time points: pre-test, post-test, and retention. Participants performed four sequences (S1, S2, S3, and S4) of right-hand finger tapping. The trained group also underwent four days of practice of S1 and S2. No group differences in the left DLPFC and ventrolateral (VLPFC) were found between sessions for S1 and S2. Our findings revealed increased contribution from the right VLPFC in post-test for the trained group, which may reflect the active retrieval of explicit information from long-term memory. Our results suggest that despite additional practice time, explicit motor sequence learning requires the continued involvement of the PFC.

Does a Cognitive Task Promote Implicit or Explicit Motor Learning?

This study examined whether use of an N-back task could promote implicit and explicit motor learning. In Experiment 1, 30 healthy adults were assigned to an N-back task group (NTG) or a control task group (CG). All participants performed the serial reaction time task (SRTT) and generation task after either the N-back or control tasks. The results did not reveal whether the N-back task promoted implicit or explicit motor learning because participants in the NTG noticed a hidden loop in the SRTT and this "awareness" made it difficult to interpret the results in Experiment 1. In Experiment 2, we examined whether the N-back task promoted explicit motor learning only using a modified SRTT. Thirty healthy adults were assigned to the NTG or the CG. On day 1, all participants performed the modified SRTT after either the N-back or control tasks. On day 7, all participants repeated the modified SRTT. As a result, the performance on the modified SRTT was faster in the NTG than in the CG on days 1 and 7. In summary, although the N-back task might promote explicit motor learning, the present study could not clearly conclude whether the N-back task promoted implicit and explicit motor learning.

Enhancement of prefrontal area excitability induced by a cognitive task: Impact on subsequence visuomotor task performance

Cognitive tasks may have the potential to improve visuomotor task performance; however, the reason for this is unclear. If this can be clarified, it may be possible to develop clinically valuable outcomes, such as promotion of motor learning though cognitive tasks. The present study aimed to investigate whether changes in prefrontal area excitability induced by cognitive tasks, especially within the dorsolateral prefrontal cortex (DLPFC), influenced the speed of improvement during visuomotor task performance. Twenty young healthy adults were recruited. The serial reaction time task (SRTT) was used to assess visuomotor task performance. Cognitive tasks included an adjusted N-back task, a non-adjusted N-back task, and a control task, which were evaluated on different days. Additionally, we measured cerebral hemodynamic activity using near-infrared spectroscopy while each cognitive task was being performed. We observed that the adjusted N-back task significantly enhanced the speed of improvement during the SRTT performance compared to the control task. However, there was no relationship between the speed of improvement during the SRTT performance and changes in prefrontal area excitability induced by the cognitive tasks. Our findings contribute towards developing an effective method that uses cognitive tasks to promote visuomotor learning.

Differential effects of left and right prefrontal cortex anodal transcranial direct current stimulation during probabilistic sequence learning

Left and right prefrontal cortex and the primary motor cortex (M1) are activated during learning of motor sequences. Previous literature is mixed on whether prefrontal cortex aids or interferes with sequence learning. The present study investigated the roles of prefrontal cortices and M1 in sequence learning. Participants received anodal transcranial direct current stimulation (tDCS) to right or left prefrontal cortex or left M1 during a probabilistic sequence learning task. Relative to sham, the left prefrontal cortex and M1 tDCS groups exhibited enhanced learning evidenced by shorter response times for pattern trials, but only for individuals who did not gain explicit awareness of the sequence (implicit). Right prefrontal cortex stimulation in participants who did not gain explicit sequence awareness resulted in learning disadvantages evidenced by slower overall response times for pattern trials. These findings indicate that stimulation to left prefrontal cortex or M1 can lead to sequence learning benefits under implicit conditions. In contrast, right prefrontal cortex tDCS had negative effects on sequence learning, with overall impaired reaction time for implicit learners. There was no effect of tDCS on accuracy, and thus our reaction time findings cannot be explained by a speed-accuracy tradeoff. Overall, our findings suggest complex and hemisphere-specific roles of left and right prefrontal cortices in sequence learning. NEW & NOTEWORTHY Prefrontal cortices are engaged in motor sequence learning, but the literature is mixed on whether the prefrontal cortices aid or interfere with learning. In the current study, we used anodal transcranial direct current stimulation to target left or right prefrontal cortex or left primary motor cortex while participants performed a probabilistic sequence learning task. We found that left prefrontal and motor cortex stimulation enhanced implicit learning whereas right prefrontal stimulation negatively impacted performance.

Spontaneous eyeblinks are sensitive to sequential learning

Although sequential learning and spontaneous eyeblink rate (EBR) have both been shown to be tightly related to cerebral dopaminergic activity, they have never been investigated at the same time. In the present study, EBR, taken as an indirect marker of dopaminergic activity, was investigated in two resting state conditions, both before and after visuomotor sequence learning in a serial reaction time task (SRT) and during task practice. Participants' abilities to produce and manipulate their knowledge about the sequential material were probed in a generation task. We hypothesized that the time course of spontaneous EBR might follow the progressive decrease of RTs during the SRT session. Additionally, we manipulated the structure of the transfer blocks as well as their respective order, assuming that (1) fully random trials might generate a larger psychophysiological response than an unlearned but structured material, and (2) a second (final) block of transfer might give rise to larger effects given that the sequential material was better consolidated after further practice. Finally, we tentatively hypothesized that, in addition to their online version, spontaneous EBR recorded during the pre- and post-learning resting sessions might be predictive of (1) the SRT learning curve, (2) the magnitude of the transfer effects, and (3) performance in the generation task. Results showed successful sequence learning with decreased accuracy and increased reaction times (RTs) in transfer blocks featuring a different material (random trials or a structured, novel sequence). In line with our hypothesis that EBR reflects dopaminergic activity associated with sequential learning, we observed increased EBR in random trials as well as when the second transfer block occurred at the end of the learning session. There was a positive relationship between the learning curve (RTs) and the slope of EBR during the SRT session. Additionally, inter-individual differences in resting and real-time EBR predicted the magnitude of accuracy and RTs transfer effects, respectively, but they were not related to participants' performances during the generation task. Notwithstanding, our results suggest that the degree of explicit sequential knowledge modulates the association between the magnitude of the transfer effect in EBR and SRT performance. Overall, the present study provides evidence that EBR may represent a valid indirect psychophysiological correlate of dopaminergic activity coupled to sequential learning.

Dissociable roles of medial and lateral PFC in rule learning

INTRODUCTION

Although the neural basis of rule learning is of great interest to cognitive neuroscientists, the pattern of transient brain activation during rule discovery remains to be investigated.

METHOD

In this study, we measured event-related functional magnetic resonance imaging (fMRI) during distinct phases of rule learning. Twenty-one healthy human volunteers were presented with a series of cards, each containing a clock-like display of 12 circles numbered sequentially. Participants were instructed that a fictitious animal would move from one circle to another either in a regular pattern (according to a rule hidden in consecutive trials) or randomly. Participants were then asked to judge whether a given step followed a rule.

RESULTS

While the rule-search phase evoked more activation in the posterior lateral prefrontal cortex (LPFC), the rule-following phase caused stronger activation in the anterior medial prefrontal cortex (MPFC). Importantly, the intermediate phase, the rule-discovery phase evoked more activations in MPFC and dorsal anterior cingulate cortex (dACC) than rule search, and more activations in LPFC than rule following.

CONCLUSION

Therefore, we can conclude that the medial and lateral PFC have dissociable contributions in rule learning.

Awareness of sensorimotor adaptation to visual rotations of different size

Previous studies on sensorimotor adaptation revealed no awareness of the nature of the perturbation after adaptation to an abrupt 30° rotation of visual feedback or after adaptation to gradually introduced perturbations. Whether the degree of awareness depends on the magnitude of the perturbation, though, has as yet not been tested. Instead of using questionnaires, as was often done in previous work, the present study used a process dissociation procedure to measure awareness and unawareness. A naïve, implicit group and a group of subjects using explicit strategies adapted to 20°, 40° and 60° cursor rotations in different adaptation blocks that were each followed by determination of awareness and unawareness indices. The awareness index differed between groups and increased from 20° to 60° adaptation. In contrast, there was no group difference for the unawareness index, but it also depended on the size of the rotation. Early adaptation varied between groups and correlated with awareness: The more awareness a participant had developed the more the person adapted in the beginning of the adaptation block. In addition, there was a significant group difference for savings but it did not correlate with awareness. Our findings suggest that awareness depends on perturbation size and that aware and strategic processes are differentially involved during adaptation and savings. Moreover, the use of the process dissociation procedure opens the opportunity to determine awareness and unawareness indices in future sensorimotor adaptation research.

Motor learning in individuals with autism spectrum disorder: activation in superior parietal lobule related to learning and repetitive behaviors

Motor-linked implicit learning is the learning of a sequence of movements without conscious awareness. Although motor symptoms are frequently reported in individuals with autism spectrum disorder (ASD), recent behavioral studies have suggested that motor-linked implicit learning may be intact in ASD. The serial reaction time (SRT) task is one of the most common measures of motor-linked implicit learning. The present study used a 3T functional magnetic resonance imaging scanner to examine the behavioral and neural correlates of real-time motor sequence learning in adolescents and adults with ASD (n = 15) compared with age- and intelligence quotient-matched individuals with typical development (n = 15) during an SRT task. Behavioral results suggested less robust motor sequence learning in individuals with ASD. Group differences in brain activation suggested that individuals with ASD, relative to individuals with typical development, showed decreased activation in the right superior parietal lobule (SPL) and right precuneus (Brodmann areas 5 and 7, and extending into the intraparietal sulcus) during learning. Activation in these areas (and in areas such as the right putamen and right supramarginal gyrus) was found to be significantly related to behavioral learning in this task. Additionally, individuals with ASD who had more severe repetitive behavior/restricted interest symptoms demonstrated greater decreased activation in these regions during motor learning. In conjunction, these results suggest that the SPL may play an important role in motor learning and repetitive behavior in individuals with ASD.

Strengthening Procedural Memories by Reactivation in Sleep

There is robust evidence that sleep facilitates procedural memory consolidation. The exact mechanisms underlying this process are still unclear. We tested whether an active replay of prior experience can underlie sleep effects on procedural memory. Participants learned a finger-tapping task in which key presses were associated with tones during practice. Later, during a consolidation interval spent either sleeping or awake, we presented auditory cues to reactivate part of the learned sequence. We show that reactivation strengthens procedural memory formation during sleep, but not during wakefulness. The improvement was restricted to those finger transitions that were cued. Thus, reactivation is a very specific process underpinning procedural memory consolidation. When comparing periods of sleep with and without reactivation, we find that it is not the time spent in a specific stage of sleep per se, but rather the occurrence of reactivation that mediates the effect of sleep on memory consolidation. Our data show that longer sleep time as well as additional reactivation by cueing during sleep can enhance later memory performance.

Specific early vulnerability of high-order executive function to focal brain lesions and long-term impact on educational persistence: Sparing of incidental episodic memory

OBJECTIVE

We investigated mental functions expected to remain impaired or not ain adulthood following childhood-onset brain lesions.

METHODS

Thirty unilaterally lesioned young adults were tested a decade after lesion onset with an effort-demanding complex executive function (EF) task as well as a task of incidental declarative retrospective episodic recognition memory (IRM). Thirty neurotypical participants were also tested.

RESULTS

The EF task was significantly impaired in the lesion group and significantly more so than the IRM task. Regarding the lesioned cases, performance on EF, but not IRM, was significantly positively correlated with long-term educational persistence (EP). Both EF and EP but not IRM were significantly positively correlated with the age of onset of the lesion. Severity of neurological impairment was unrelated to any variable.

CONCLUSION

Mental abilities acquired through early schooling remain impaired into adulthood when early schooling is disturbed, not everyday memory which does not depend on schooling.

Interaction between hippocampal and striatal systems predicts subsequent consolidation of motor sequence memory

The development of fast and reproducible motor behavior is a crucial human capacity. The aim of the present study was to address the relationship between the implementation of consistent behavior during initial training on a sequential motor task (the Finger Tapping Task) and subsequent sleep-dependent motor sequence memory consolidation, using functional magnetic resonance imaging (fMRI) and total sleep deprivation protocol. Our behavioral results indicated significant offline gains in performance speed after sleep whereas performance was only stabilized, but not enhanced, after sleep deprivation. At the cerebral level, we previously showed that responses in the caudate nucleus increase, in parallel to a decrease in its functional connectivity with frontal areas, as performance became more consistent. Here, the strength of the competitive interaction, assessed through functional connectivity analyses, between the caudate nucleus and hippocampo-frontal areas during initial training, predicted delayed gains in performance at retest in sleepers but not in sleep-deprived subjects. Moreover, during retest, responses increased in the hippocampus and medial prefrontal cortex in sleepers whereas in sleep-deprived subjects, responses increased in the putamen and cingulate cortex. Our results suggest that the strength of the competitive interplay between the striatum and the hippocampus, participating in the implementation of consistent motor behavior during initial training, conditions subsequent motor sequence memory consolidation. The latter process appears to be supported by a reorganisation of cerebral activity in hippocampo-neocortical networks after sleep.

An analysis of rat prefrontal cortex in mediating executive function

While it is acknowledged that species specific differences are an implicit condition of comparative studies, rodent models of prefrontal function serve a significant role in the acquisition of converging evidence on prefrontal function across levels of analysis and research techniques. The purpose of the present review is to examine whether the prefrontal cortex (PFC) in rats supports a variety of processes associated with executive function including working memory, temporal processing, planning (prospective coding), flexibility, rule learning, and decision making. Therefore, in this review we examined changes associated with working memory processes for spatial locations, visual objects, odors, tastes, and response domains or attributes, temporal processes including temporal order, sequence learning, prospective coding, behavioral flexibility associated with reversal learning and set shifting, paired associate learning, and decision making based on effort, time discounting, and uncertainty following damage to the PFC in rats. In addition, potential parallel processes of executive function in monkeys and humans based on several theories of subregional differentiation within the PFC will be presented. Specifically, theories based on domain or attribute specificity (Goldman-Rakic, 1996), level of processing (Petrides, 1996), rule learning based on complexity (Wise, Murray, & Gerfen, 1996), executive functions based on connectivity with other brain regions associated with top-down control (Miller & Cohen, 2001), are presented and applied to PFC function in rats with the aim of understanding subregional specificity in the rat PFC. The data suggest that there is subregional specificity within the PFC of rats, monkey and humans and there are parallel cognitive functions of the different subregions of the PFC in rats, monkeys and humans.

Intact first- and second-order implicit sequence learning in secondary-school-aged children with developmental dyslexia

We examined the influence of task complexity on implicit sequence learning in secondary-school-aged children with developmental dyslexia (DD). This was done to determine whether automatization problems in reading extend to the automatization of all skill and depend on the complexity of the to-be-learned skill. A total of 28 dyslexic children between 12 and 15 years and 28 matched control children carried out two serial reaction time tasks using a first-order conditional (FOC) and second-order conditional (SOC) sequence. In both tasks, children incidentally learned a sequence of hidden target positions, but whereas FOC sequence learning could be based on knowledge about the immediate preceding position, SOC sequence learning required more complex knowledge about the previous two positions. The results demonstrated that sequence learning was highly comparable in dyslexic and control children, regardless of the sequence complexity. This shows that implicit sequence learning, as manifested in the present study, is maintained in DD and is unrelated to task complexity. We suggest that previous reports of sequence-learning deficits in DD can be accounted for by attenuated explicit sequence learning, possibly related to malfunctions in prefrontal processing. The present findings indicate that deficits in skill learning and automatization in DD are not general in nature, but task dependent.

Social cognition and the brain: a meta-analysis

This meta-analysis explores the location and function of brain areas involved in social cognition, or the capacity to understand people's behavioral intentions, social beliefs, and personality traits. On the basis of over 200 fMRI studies, it tests alternative theoretical proposals that attempt to explain how several brain areas process information relevant for social cognition. The results suggest that inferring temporary states such as goals, intentions, and desires of other people-even when they are false and unjust from our own perspective--strongly engages the temporo-parietal junction (TPJ). Inferring more enduring dispositions of others and the self, or interpersonal norms and scripts, engages the medial prefrontal cortex (mPFC), although temporal states can also activate the mPFC. Other candidate tasks reflecting general-purpose brain processes that may potentially subserve social cognition are briefly reviewed, such as sequence learning, causality detection, emotion processing, and executive functioning (action monitoring, attention, dual task monitoring, episodic memory retrieval), but none of them overlaps uniquely with the regions activated during social cognition. Hence, it appears that social cognition particularly engages the TPJ and mPFC regions. The available evidence is consistent with the role of a TPJ-related mirror system for inferring temporary goals and intentions at a relatively perceptual level of representation, and the mPFC as a module that integrates social information across time and allows reflection and representation of traits and norms, and presumably also of intentionality, at a more abstract cognitive level.

Sleep transforms the cerebral trace of declarative memories

After encoding, memory traces are initially fragile and have to be reinforced to become permanent. The initial steps of this process occur at a cellular level within minutes or hours. Besides this rapid synaptic consolidation, systems consolidation occurs within a time frame of days to years. For declarative memory, the latter is presumed to rely on an interaction between different brain regions, in particular the hippocampus and the medial prefrontal cortex (mPFC). Specifically, sleep has been proposed to provide a setting that supports such systems consolidation processes, leading to a transfer and perhaps transformation of memories. Using functional MRI, we show that postlearning sleep enhances hippocampal responses during recall of word pairs 48 h after learning, indicating intrahippocampal memory processing during sleep. At the same time, sleep induces a memory-related functional connectivity between the hippocampus and the mPFC. Six months after learning, memories activated the mPFC more strongly when they were encoded before sleep, showing that sleep leads to long-lasting changes in the representation of memories on a systems level.

The basal ganglia in human learning

For many years, the basal ganglia were described in anatomy courses as strictly motor structures. Certainly, some of the most obvious and debilitating symptoms shown by persons with basal ganglia disorders are problems in motor control. However, the basal ganglia are not limited to motoric aspects of behavior: recent research shows that they are involved in most areas of cognitive and emotional functioning, consistent with their anatomical connections with all areas of the cortex. This review will focus on the roles of the basal ganglia in human learning, particularly sequence learning and category learning. Current areas of research that are discussed include the differing roles of different basal ganglia regions, patterns of interaction between the cortex and basal ganglia, differences in positive and negative association learning, effects of dopaminergic medication on learning, whether basal ganglia-mediated learning is implicit or explicit, and how the basal ganglia learning systems interact with other learning systems, particularly within the medial temporal lobe.

CAP, epilepsy and motor events during sleep: the unifying role of arousal

Arousal systems play a topical neurophysiologic role in protecting and tailoring sleep duration and depth. When they appear in NREM sleep, arousal responses are not limited to a single EEG pattern but are part of a continuous spectrum of EEG modifications ranging from high-voltage slow rhythms to low amplitude fast activities. The hierarchic features of arousal responses are reflected in the phase A subtypes of CAP (cyclic alternating pattern) including both slow arousals (dominated by the <1Hz oscillation) and fast arousals (ASDA arousals). CAP is an infraslow oscillation with a periodicity of 20-40s that participates in the dynamic organization of sleep and in the activation of motor events. Physiologic, paraphysiologic and pathologic motor activities during NREM sleep are always associated with a stereotyped arousal pattern characterized by an initial increase in EEG delta power and heart rate, followed by a progressive activation of faster EEG frequencies. These findings suggest that motor patterns are already written in the brain codes (central pattern generators) embraced with an automatic sequence of EEG-vegetative events, but require a certain degree of activation (arousal) to become visibly apparent. Arousal can appear either spontaneously or be elicited by internal (epileptic burst) or external (noise, respiratory disturbance) stimuli. Whether the outcome is a physiologic movement, a muscle jerk or a major epileptic attack will depend on a number of ongoing factors (sleep stage, delta power, neuro-motor network) but all events share the common trait of arousal-activated phenomena.

Oculomotor and manual indexes of incidental and intentional spatial sequence learning during middle childhood and adolescence

The goal of this study was to examine incidental and intentional spatial sequence learning during middle childhood and adolescence. We tested four age groups (8-10 years, 11-13 years, 14-17 years, and young adults [18+ years]) on a serial reaction time task and used manual and oculomotor measures to examine incidental sequence learning. Participants were also administered a trial block in which they were explicitly instructed to learn a sequence. Replicating our previous study with adults, oculomotor anticipations and response times showed learning effects similar to those in the manual modality. There were few age-related differences in the sequence learning indexes during incidental learning, but intentional learning yielded differences on all indexes. Results indicate that the search for regularities and the ability to learn a sequence rapidly under incidental conditions are mature by 8 to 10 years of age. In contrast, the ability to learn a sequence intentionally, which requires cognitive resources and strategies, continues to develop through adolescence.

Cerebral correlates of delta waves during non-REM sleep revisited

We aimed at characterizing the neural correlates of delta activity during Non Rapid Eye Movement (NREM) sleep in non-sleep-deprived normal young adults, based on the statistical analysis of a positron emission tomography (PET) sleep data set. One hundred fifteen PET scans were obtained using H(2)(15)O under continuous polygraphic monitoring during stages 2-4 of NREM sleep. Correlations between regional cerebral blood flow (rCBF) and delta power (1.5-4 Hz) spectral density were analyzed using statistical parametric mapping (SPM2). Delta power values obtained at central scalp locations negatively correlated during NREM sleep with rCBF in the ventromedial prefrontal cortex, the basal forebrain, the striatum, the anterior insula, and the precuneus. These regions embrace the set of brain areas in which rCBF decreases during slow wave sleep (SWS) as compared to Rapid Eye Movement (REM) sleep and wakefulness (Maquet, P., Degueldre, C., Delfiore, G., Aerts, J., Peters, J.M., Luxen, A., Franck, G., 1997. Functional neuroanatomy of human slow wave sleep. J. Neurosci. 17, 2807-S2812), supporting the notion that delta activity is a valuable prominent feature of NREM sleep. A strong association was observed between rCBF in the ventromedial prefrontal regions and delta power, in agreement with electrophysiological studies. In contrast to the results of a previous PET study investigating the brain correlates of delta activity (Hofle, N., Paus, T., Reutens, D., Fiset, P., Gotman, J., Evans, A.C., Jones, B.E., 1997. Regional cerebral blood flow changes as a function of delta and spindle activity during slow wave sleep in humans. J. Neurosci. 17, 4800-4808), in which waking scans were mixed with NREM sleep scans, no correlation was found with thalamus activity. This latter result stresses the importance of an extra-thalamic delta rhythm among the synchronous NREM sleep oscillations. Consequently, this rCBF distribution might preferentially reflect a particular modulation of the cellular processes involved in the generation of cortical delta waves during NREM sleep.

The neural correlates of implicit and explicit sequence learning: Interacting networks revealed by the process dissociation procedure

In two H2(15)O PET scan experiments, we investigated the cerebral correlates of explicit and implicit knowledge in a serial reaction time (SRT) task. To do so, we used a novel application of the Process Dissociation Procedure, a behavioral paradigm that makes it possible to separately assess conscious and unconscious contributions to performance during a subsequent sequence generation task. To manipulate the extent to which the repeating sequential pattern was learned explicitly, we varied the pace of the choice reaction time task-a variable that is known to have differential effects on the extent to which sensitivity to sequence structure involves implicit or explicit knowledge. Results showed that activity in the striatum subtends the implicit component of performance during recollection of a learned sequence, whereas the anterior cingulate/mesial prefrontal cortex (ACC/MPFC) supports the explicit component. Most importantly, we found that the ACC/MPFC exerts control on the activity of the striatum during retrieval of the sequence after explicit learning, whereas the activity of these regions is uncoupled when learning had been essentially implicit. These data suggest that implicit learning processes can be successfully controlled by conscious knowledge when learning is essentially explicit. They also supply further evidence for a partial dissociation between the neural substrates supporting conscious and nonconscious components of performance during recollection of a learned sequence.

Neural correlates of encoding and expression in implicit sequence learning

In the domain of motor learning it has been difficult to separate the neural substrate of encoding from that of change in performance. Consequently, it has not been clear whether motor effector areas participate in learning or merely modulate changes in performance. Here, using a variant of the serial reaction time task that dissociated these two factors, we report that encoding during procedural motor learning does engage cortical motor areas and can be characterized by distinct early and late encoding phases. The highest correlation between activation and subsequent changes in motor performance was seen in the motor cortex during early encoding, and in the basal ganglia during the late encoding phase. Our results show that rapid encoding during procedural motor learning involves several distinct processes, and is represented primarily within motor system structures.

Learning and production of movement sequences: behavioral, neurophysiological, and modeling perspectives

A wave of recent behavioral studies has generated a new wealth of parametric observations about serial order behavior. What was a trickle of neurophysiological studies has grown to a steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we review major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2 x N, discrete sequence production, and serial reaction time. These tasks populate a continuum from higher to lower degrees of internal control of sequential organization and probe important contemporary issues such as the nature of working-memory representations for sequential behavior, and the development and role of chunks in hierarchical control. The main movement classes reviewed are speech and keypressing, both involving small amplitude movements amenable to parametric study. A synopsis of serial order models, vis-a-vis major empirical findings leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been complemented by successful prediction of distinctively patterned electrophysiological recordings. In lateral prefrontal cortex, parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model--the N-STREAMS neural network model--exemplifies ongoing attempts to accommodate a broad range of both behavioral and neurobiological data within a CQ-consistent theory.

Computational correlates of consciousness

Over the past few years numerous proposals have appeared that attempt to characterize consciousness in terms of what could be called its computational correlates: Principles of information processing with which to characterize the differences between conscious and unconscious processing. Proposed computational correlates include architectural specialization (such as the involvement of specific regions of the brain in conscious processing), properties of representations (such as their stability in time or their strength), and properties of specific processes (such as resonance, synchrony, interactivity, or information integration). In exactly the same way as one can engage in a search for the neural correlates of consciousness, one can thus search for the computational correlates of consciousness. The most direct way of doing is to contrast models of conscious versus unconscious information processing. In this paper, I review these developments and illustrate how computational modeling of specific cognitive processes can be useful in exploring and in formulating putative computational principles through which to capture the differences between conscious and unconscious cognition. What can be gained from such approaches to the problem of consciousness is an understanding of the function it plays in information processing and of the mechanisms that subtend it. Here, I suggest that the central function of consciousness is to make it possible for cognitive agents to exert flexible, adaptive control over behavior. From this perspective, consciousness is best characterized as involving (1) a graded continuum defined over quality of representation, such that availability to consciousness and to cognitive control correlates with properties of representation, and (2) the implication of systems of meta-representations.

Methods for studying unconscious learning

One has to face numerous difficulties when trying to establish a dissociation between conscious and unconscious knowledge. In this paper, we review several of these problems as well as the different methodological solutions that have been proposed to address them. We suggest that each of the different methodological solutions offered refers to a different operational definition of consciousness, and present empirical examples of sequence learning studies in which these different procedures were applied to differentiate between implicit and explicit knowledge acquisition. We also show how the use of a sensitive behavioral method, the process dissociation procedure, confers a distinctive advantage in brain-imaging studies when aiming to delineate the neural correlates of conscious and unconscious processes in sequence learning.

[Dream, memory and Freud's reconciliation with the brain]

What is the function of dreaming? The vast contribution on dreams made by Freud and Jung has been largely ignored by science, which harshly criticized their approach for the lack of a quantitative method and of testable hypotheses. Here I review a series of experimental results that corroborate two important psychoanalytical insights regarding dreams: 1) that dreams often contain a "day residue" of the preceding waking experience, and 2) that such "residue" includes cognitive and mnemonic activities, therefore leading to a facilitation of learning. In particular, recent data suggests that dreams may play an essential role in memory consolidation, allowing recently-acquired memories to exit the hippocampus and settle in the neocortex. Taken together, these results call for a comprehensive scientific reassessment of the psychoanalytical legacy.