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

2016 ◽  
Vol 116 (3) ◽  
pp. 1239-1249 ◽  
Author(s):  
Eugene Poh ◽  
Timothy J. Carroll ◽  
Jordan A. Taylor
Keyword(s):  
Implicit Learning ◽  
Neural Representation ◽  
Coordinate Frame ◽  
Explicit Learning ◽  
Verbal Reports ◽  
Visuomotor Rotation ◽  
Left And Right ◽  
Task Conditions ◽  
Opposite Limb ◽  
Implicit And Explicit

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.

scholarly journals Flexible explicit but rigid implicit learning in a visuomotor adaptation task

2015 ◽  
Vol 113 (10) ◽  
pp. 3836-3849 ◽  
Author(s):  
Krista M. Bond ◽  
Jordan A. Taylor
Keyword(s):  
Implicit Learning ◽  
Computational Models ◽  
Visuomotor Adaptation ◽  
Task Demands ◽  
Similar Degree ◽  
Explicit Learning ◽  
Prediction Errors ◽  
Visuomotor Rotation ◽  
Indirect Measures ◽  
Task Conditions

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.

Re-evaluating Dissociations between Implicit and Explicit Category Learning: An Event-related fMRI Study

2011 ◽  
Vol 23 (7) ◽  
pp. 1697-1709 ◽  
Author(s):  
Todd M. Gureckis ◽  
Thomas W. James ◽  
Robert M. Nosofsky
Keyword(s):  
Implicit Learning ◽  
Category Learning ◽  
Neural Activity ◽  
Incidental Learning ◽  
Brain Activity ◽  
Neural Systems ◽  
Explicit Learning ◽  
Learning Condition ◽  
Perceptual Category Learning ◽  
Implicit And Explicit

Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of these factors on the recruitment of alternate neural systems. Consistent with previous reports, following incidental learning in a dot-pattern classification task, participants showed decreased neural activity in occipital visual cortex (extrastriate region V3, BA 19) in response to novel exemplars of a studied category compared to members of a foil category, but did not show this decreased neural activity following explicit learning. Crucially, however, our results show that this pattern was primarily modulated by aspects of the stimulus-encoding instructions provided at the time of study. In particular, when participants in an implicit learning condition were encouraged to evaluate the overall shape and configuration of the stimuli during study, we failed to find the pattern of brain activity that has been taken to be a signature of implicit learning, suggesting that activity in this area does not uniquely reflect implicit memory for perceptual categories but instead may reflect aspects of processing or perceptual encoding strategies.

scholarly journals A locomotor learning paradigm using distorted visual feedback elicits strategic learning

2018 ◽  
Vol 120 (4) ◽  
pp. 1923-1931 ◽  
Author(s):  
Margaret A. French ◽  
Susanne M. Morton ◽  
Charalambos C. Charalambous ◽  
Darcy S. Reisman
Keyword(s):  
Upper Extremity ◽  
Implicit Learning ◽  
Visual Feedback ◽  
Explicit Learning ◽  
Strategic Learning ◽  
Overground Walking ◽  
Visuomotor Rotation ◽  
Small Component ◽  
Walking Pattern ◽  
Do So

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.

Implicit versus explicit: An act-r learning perspective

1999 ◽  
Vol 22 (5) ◽  
pp. 785-786 ◽  
Author(s):  
Niels A. Taatgen
Keyword(s):  
Implicit Learning ◽  
Explicit Memory ◽  
Explicit Knowledge ◽  
Cognitive Architecture ◽  
Explicit Learning ◽  
Implicit And Explicit Memory ◽  
The Difference ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

Dienes & Perner propose a theory of implicit and explicit knowledge that is not entirely complete. It does not address many of the empirical issues, nor does it explain the difference between implicit and explicit learning. It does, however, provide a possible unified explanation, as opposed to the more binary theories like the systems and the processing theories of implicit and explicit memory. Furthermore, it is consistent with a theory in which implicit learning is viewed as based on the mechanisms of the cognitive architecture, and explicit learning as strategies that exploit these mechanisms.

Implicit and explicit learning in a hybrid architecture of cognition

1999 ◽  
Vol 22 (5) ◽  
pp. 772-773
Author(s):  
Christian Lebiere ◽  
Dieter Wallach
Keyword(s):  
Implicit Learning ◽  
Conceptual Analysis ◽  
Human Cognition ◽  
Explicit Learning ◽  
Hybrid Architecture ◽  
Integrated Architecture ◽  
The Common ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning ◽  
Analysis Of Knowledge

We present a theoretical account of implicit and explicit learning in terms of act-r, an integrated architecture of human cognition as a computational supplement to Dienes & Perner's conceptual analysis of knowledge. Explicit learning is explained in act-r by the acquisition of new symbolic knowledge, whereas implicit learning amounts to statistically adjusting subsymbolic quantities associated with that knowledge. We discuss the common foundation of a set of models that are able to explain data gathered in several signature paradigms of implicit learning.

An algebraic perspective on implicit and explicit knowledge

2016 ◽  
Vol 3 (1) ◽  
pp. 151-162 ◽  
Author(s):  
Omid Khatin Zadeh ◽  
Sedigheh Vahdat ◽  
Babak Yazdani Fazlabadi
Keyword(s):  
Implicit Learning ◽  
Infinite Number ◽  
Explicit Knowledge ◽  
Algebraic Groups ◽  
The Other ◽  
Explicit Learning ◽  
Abstract Group ◽  
Abstract Structure ◽  
The Mind ◽  
Implicit And Explicit

The isomorphic relationship between an infinite number of concrete algebraic groups and the existence of a single abstract group that underlies all these concrete groups is one of the most fundamental subjects in Abstract Algebra. Looking at the process of explicit learning from a mathematical perspective, this article suggests that explicit knowledge of a certain concrete structure can be viewed as consciousness of an abstract algebraic structure that underlies that structure. On the other hand, implicit knowledge can be regarded as knowing something without being conscious of the abstract structure that underlies that knowledge. Explicit knowledge enables the learner to know what features are shared by these concrete groups or structures. These shared features are the defining elements of underlying abstract structure. The abstract structure is constructed in the mind by the suppression of irrelevant data. Therefore, it is suggested that while implicit learning is a receiving-oriented mode of learning, explicit learning is a suppression-oriented one. The sub-process of suppression enables the cognitive system to focus on abstract structure and its defining features, making the process of explicit learning deeper.

scholarly journals Acquisition of skilled finger movements is accompanied by reorganization of the corticospinal system

2018 ◽  
Vol 119 (2) ◽  
pp. 573-584 ◽  
Author(s):  
Masato Hirano ◽  
Shinji Kubota ◽  
Shinichi Furuya ◽  
Yoshiki Koizume ◽  
Shinya Tanaka ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Sequence Learning ◽  
Explicit Learning ◽  
Voluntary Movements ◽  
Finger Movements ◽  
Corticospinal System ◽  
Learning Conditions ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning ◽  
Coordination Patterns

Dexterous finger movements are often characterized by highly coordinated movements. Such coordination might be derived from reorganization of the corticospinal system. In this study, we investigated 1) the manner in which finger movement covariation patterns are acquired, by examining the effects of the implicit and explicit learning of a serial reaction time task (SRTT), and 2) how such changes in finger coordination are represented in the corticospinal system. The subjects learned a button press sequence in both implicit and explicit learning conditions. In the implicit conditions, they were naive about what they were learning, whereas in the explicit conditions the subjects consciously learned the order of the sequence elements. Principal component analysis decomposed both the voluntary movements produced during the SRTT and the passive movements evoked by transcranial magnetic stimulation (TMS) over the primary motor cortex into a set of five finger joint covariation patterns. The structures of the voluntary and passive TMS-evoked movement patterns were reorganized by implicit learning but not explicit learning. Furthermore, in the implicit learning conditions the finger covariation patterns derived from the TMS-evoked and voluntary movements spanned similar movement subspaces. These results provide the first evidence that skilled sequential finger movements are acquired differently through implicit and explicit learning, i.e., the changes in finger coordination patterns induced by implicit learning are accompanied by functional reorganization of the corticospinal system, whereas explicit learning results in faster recruitment of individual finger movements without causing any changes in finger coordination. NEW & NOTEWORTHY Skilled sequential multifinger movements are characterized as highly coordinated movement patterns. These finger coordination patterns are represented in the corticospinal system, yet it still remains unclear how these patterns are acquired through implicit and explicit motor sequence learning. A direct comparison of learning-related changes between actively generated finger movements and passively evoked finger movements by TMS provided evidence that finger coordination patterns represented in the corticospinal system are reorganized through implicit, but not explicit, sequence learning.

scholarly journals Implicit and Explicit Learning of Temporal Sequences Studied With the Process Dissociation Procedure

2008 ◽  
Vol 100 (2) ◽  
pp. 733-739 ◽  
Author(s):  
Anke Karabanov ◽  
Fredrik Ullén
Keyword(s):  
Implicit Learning ◽  
Serial Recall ◽  
Explicit Knowledge ◽  
Stimulus Presentation ◽  
Explicit Learning ◽  
Process Dissociation ◽  
Process Dissociation Procedure ◽  
Significant Difference ◽  
Implicit And Explicit ◽  
Temporal Sequences

We studied whether temporal sequences can be learned implicitly using a process dissociation procedure (PDP). Participants performed repeated serial recalls of sequential stimuli with a random ordinal structure and fixed temporal structure. Explicit knowledge was evaluated through verbal questions and PDP analysis of two generation tasks (inclusion and exclusion). Participants were divided into two groups: in the Ordinal group, stimulus presentation was visual and the participants were instructed to repeat the ordinal structure; in the Temporal+Ordinal group, stimulus presentation was audio-visual and the participants were instructed to repeat temporal and ordinal structure. We expected predominantly implicit learning in the Ordinal group and explicit learning in the Temporal+Ordinal group. This was supported by two findings. First, a significant difference between inclusion and exclusion performance was seen only in the Temporal+Ordinal group. Second, in both groups, a negative relation was found between the degree of improvement during serial recall and a measure of explicit knowledge in the generation tasks. This relation was independent of the final level of performance during serial recall. These findings suggest that distinct implicit and explicit systems may exist for learning of temporal sequences: implicit learning is gradual and gives rise to knowledge that is inaccessible to conscious control while the explicit system is fast and results in representations that can be used to control performance in inclusion and exclusion tasks.

Complementary Category Learning Systems Identified Using Event-Related Functional MRI

2000 ◽  
Vol 12 (6) ◽  
pp. 977-987 ◽  
Author(s):  
Howard J. Aizenstein ◽  
Angus W. MacDonald ◽  
V. Andrew Stenger ◽  
Robert D. Nebes ◽  
Jeris K. Larson ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Category Learning ◽  
Medial Temporal Lobe ◽  
Learning Task ◽  
Neural Systems ◽  
Explicit Learning ◽  
Imaging Data ◽  
Activation Patterns ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

Event-related fMRI was used to dissociate the neural systems involved in category learning with and without awareness. Ten subjects performed a speeded response category learning task. Functional MR images were acquired during both explicit and implicit learning conditions. Behavioral data showed evidence of learning in both conditions. Functional imaging data showed different activation patterns in implicit and explicit trials. Decreased activation in extrastriate region V3 was found with implicit learning, and increased activation in V3, the medial temporal lobe, and frontal regions were found with explicit learning. These results support the theory that implicit and explicit learning utilize dissociable neural systems. Moreover, in both the implicit and explicit conditions a similar pattern of decreased activation was found in parietal regions. This commonality suggests that these dissociable systems also operate in parallel.

scholarly journals Human Learning: implicit and explicit

2015 ◽  
Vol 40 (3) ◽  
pp. 809-823 ◽  
Author(s):  
Peter Jarvis
Keyword(s):  
Tacit Knowledge ◽  
Implicit Learning ◽  
Conscious Experience ◽  
Human Learning ◽  
Explicit Learning ◽  
Tacit Dimension ◽  
Implicit And Explicit

Building on Polanyi's insight in The Tacit Dimension that we know more than we can tell, this paper argues that we actually experience more of reality than that of which we are conscious. Our conscious experience becomes the basis of explicit learning but that which we experience but of which we are not conscious is the basis of implicit learning and tacit knowledge.

Sign in / Sign up

Export Citation Format

Share Document