Interference during the implicit learning of two different motor sequences

It has been demonstrated that learning a second motor task after having learned a first task may interfere with the long-term consolidation of the first task. However, little is known about immediate changes in the representation of the motor memory in the early acquisition phase within the first minutes of the learning process. Therefore, we investigated such early interference effects with an implicit serial reaction time task in 55 healthy subjects. Each subject performed either a sequence learning task involving two different sequences, or a random control task. The results showed that learning the first sequence led to only a slight, short-lived interference effect in the early acquisition phase of the second sequence. Overall, learning of neither sequence was impaired. Furthermore, the two processes, sequence-unrelated task learning (i.e. general motor training) and the sequence learning itself did not appear to interfere with each other. In conclusion, although the long-term consolidation of a motor memory has been shown to be sensitive to other interfering memories, the present study suggests that the brain is initially able to acquire more than one new motor sequence within a short space of time without significant interferenc

Развитие частотно-временного обеспечения объектов наземной космической инфраструктуры на примере разработки системы единого времени космодрома «Восточный»

Under certain circumstances, implicit, automatic learning may be attenuated by explicit memory processes. We explored the brain basis of this phenomenon in a functional magnetic resonance imaging (fMRI) study of motor sequence learning. Using a factorial design that crossed subjective intention to learn (explicit versus implicit) with sequence difficulty (a standard versus a more complex alternating sequence), we show that explicit attempts to learn the difficult sequence produce a failure of implicit learning and, in a follow-up behavioural experiment, that this failure represents a suppression of learning itself rather than of the expression of learning. This suppression is associated with sustained right frontal activation and attenuation of learning-related changes in the medial temporal lobe and the thalamus. Furthermore, this condition is characterized by a reversal of the fronto-thalamic connectivity observed with unimpaired implicit learning. The findings demonstrate a neural basis for a well-known behavioural effect: the deleterious impact of an explicit search upon implicit learning

Dual enhancement mechanisms for overnight motor memory consolidation

Our brains are constantly processing past events<sup>1</sup>. These offline processes consolidate memories, leading in the case of motor skill memories to an enhancement in performance between training sessions. A similar magnitude of enhancement develops over a night of sleep following an implicit task, in which a sequence of movements is acquired unintentionally, or following an explicit task, in which the same sequence is acquired intentionally<sup>2</sup>. What remains poorly understood, however, is whether these similar offline improvements are supported by similar circuits, or through distinct circuits. We set out to distinguish between these possibilities by applying transcranial magnetic stimulation over the primary motor cortex (M1) or the inferior parietal lobule (IPL) immediately after learning in either the explicit or implicit task. These brain areas have both been implicated in encoding aspects of a motor sequence and subsequently supporting offline improvements over sleep<sup>3,​4,​5</sup>. Here we show that offline improvements following the explicit task are dependent on a circuit that includes M1 but not IPL. In contrast, offline improvements following the implicit task are dependent on a circuit that includes IPL but not M1. Our work establishes the critical contribution made by M1 and IPL circuits to offline memory processing, and reveals that distinct circuits support similar offline improvements

Cerebellar contributions to visuomotor adaptation and motor sequence learning: an ALE meta-analysis

Cerebellar contributions to motor learning are well-documented. For example, under some conditions, patients with cerebellar damage are impaired at visuomotor adaptation and at acquiring new action sequences. Moreover, cerebellar activation has been observed in functional MRI (fMRI) investigations of various motor learning tasks. The early phases of motor learning are cognitively demanding, relying on processes such as working memory, which have been linked to the cerebellum as well. Here, we investigated cerebellar contributions to motor learning using activation likelihood estimation (ALE) meta-analysis. This allowed us to determine, across studies and tasks, whether or not the location of cerebellar activation is constant across differing motor learning tasks, and whether or not cerebellar activation in early learning overlaps with that observed for working memory. We found that different regions of the anterior cerebellum are engaged for implicit and explicit sequence learning and visuomotor adaptation, providing additional evidence for the modularity of cerebellar function. Furthermore, we found that lobule VI of the cerebellum, which has been implicated in working memory, is activated during the early stages of explicit motor sequence learning. This provides evidence for a potential role for the cerebellum in the cognitive processing associated with motor learning. However, though lobule VI was activated across both early explicit sequence learning and working memory studies, there was no spatial overlap between these two regions. Together, our results support the idea of modularity in the formation of internal representations of new motor tasks in the cerebellum, and highlight the cognitive processing relied upon during the early phases of motor skill learning

Implicit cognition is impaired and dissociable in a head-injured group with executive deficits

Implicit or non-conscious cognition is traditionally assumed to be robust to pathology but Gomez-Beldarrain et al (1999, 2002) recently showed deficits on a single implicit task after head injury. Laboratory research suggests that implicit processes dissociate. This study therefore examined implicit cognition in 20 head-injured patients and age- and I.Q.-matched controls using a battery of four implicit cognition tasks: a Serial Reaction Time task (SRT), mere exposure effect task, automatic stereotype activation and hidden co-variation detection. Patients were assessed on an extensive neuropsychological battery, and MRI scanned. Inclusion criteria included impairment on at least one measure of executive function. The patient group was impaired relative to the control group on all the implicit cognition tasks except automatic stereotype activation. Effect size analyses using the control mean and standard deviation for reference showed further dissociations across patients and across implicit tasks. Patients impaired on implicit tasks had more cognitive deficits overall than those unimpaired, and a larger Dysexecutive Self/Other discrepancy (DEX) score suggesting greater behavioural problems. Performance on the SRT task correlated with a composite measure of executive function. Head-injury thus produced heterogeneous impairments in the implicit acquisition of new information. Implicit activation of existing knowledge structures appeared intact. Impairments in implicit cognition and executive function may interact to produce dysfunctional behaviour after head-injury. Future comparisons of implicit and explicit cognition should use several measures of each function, to ensure that they measure the latent variable of interest

Network constraints on learnability of probabilistic motor sequences

Human learners are adept at grasping the complex relationships underlying incoming sequential input. In the present work, we formalize complex relationships as graph structures derived from temporal associations in motor sequences. Next, we explore the extent to which learners are sensitive to key variations in the topological properties inherent to those graph structures. Participants performed a probabilistic motor sequence task in which the order of button presses was determined by the traversal of graphs with modular, lattice-like, or random organization. Graph nodes each represented a unique button press and edges represented a transition between button presses. Results indicate that learning, indexed here by participants' response times, was strongly mediated by the graph's meso-scale organization, with modular graphs being associated with shorter response times than random and lattice graphs. Moreover, variations in a node's number of connections (degree) and a node's role in mediating long-distance communication (betweenness centrality) impacted graph learning, even after accounting for level of practice on that node. These results demonstrate that the graph architecture underlying temporal sequences of stimuli fundamentally constrains learning, and moreover that tools from network science provide a valuable framework for assessing how learners encode complex, temporally structured information.Comment: 29 pages, 4 figure

Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more 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 summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein 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-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.Defense Advanced Research Projects Agency/Office of Naval Research (N00014-95-1-0409); National Institute of Mental Health (R01 DC02852

Investigation of sequence processing: A cognitive and computational neuroscience perspective

Serial order processing or sequence processing underlies many human activities such as speech, language, skill learning, planning, problem-solving, etc. Investigating the neural bases of sequence processing enables us to understand serial order in cognition and also helps in building intelligent devices. In this article, we review various cognitive issues related to sequence processing with examples. Experimental results that give evidence for the involvement of various brain areas will be described. Finally, a theoretical approach based on statistical models and reinforcement learning paradigm is presented. These theoretical ideas are useful for studying sequence learning in a principled way. This article also suggests a two-way process diagram integrating experimentation (cognitive neuroscience) and theory/ computational modelling (computational neuroscience). This integrated framework is useful not only in the present study of serial order, but also for understanding many cognitive processes

From creation to consolidation: a novel framework for memory processing

Long after playing squash, your brain continues to process the events that occurred during the game, thereby improving your game, and more generally, enhancing adaptive behavior. Understanding these mysterious processes may require novel theories

Learning curve assessment of rule use provides evidence for spared implicit sequence learning in a mouse model of mental retardation

Humans with Fragile X Syndrome (FXS) have a mental retardation of which a notable characteristic is a weakness in recalling sequences of information. A mouse model of the disorder exists which exhibits behavioral and neurologic changes, but cognitive testing has not revealed learning deficits seemingly comparable in magnitude to that seen in the human condition. A working memory task for olfactory sequences was employed to test learning set acquisition in mice, half of which had a disruption of the gene responsible for FXS in humans. The task protected against reward detection artifact and demonstrated stringency-dependent task acquisition. A comparable image-based sequence learning set task was used to test humans. The performances of human subjects who did and did not report consciously acquiring the task rules were used as positive and negative controls to assess the mouse learning curves. Learning curve plateau error fluctuation for individual mice was comparable to that of human subjects who never acquired an explicit rule to perform the task, but different from those of human subjects who could state a rule to solve the problem. Sliding window error plots and nonparametric statistical analysis discriminated between the consciously rule-based human performances and that of the mice and humans who did not explicitly obtain the rule. Based on comparison to the human results, wild-type and FX mouse learning curves with a continuingly variable terminal plateau error rate in sliding epochs were classified as “implicit”. Although a moderately large difference in performance of the olfactory task was observed among mouse strains, there was no significant effect of FX genotype. The wild-type performance of the FX mice in this sequence task suggests that implicit learning may be relatively spared in FXS