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      Intention to learn modulates the impact of reward and punishment on sequence learning

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          Abstract

          In real-world settings, learning is often characterised as intentional: learners are aware of the goal during the learning process, and the goal of learning is readily dissociable from the awareness of what is learned. Recent evidence has shown that reward and punishment (collectively referred to as valenced feedback) are important factors that influence performance during learning. Presently, however, studies investigating the impact of valenced feedback on skill learning have only considered unintentional learning, and therefore the interaction between intentionality and valenced feedback has not been systematically examined. The present study investigated how reward and punishment impact behavioural performance when participants are instructed to learn in a goal-directed fashion (i.e. intentionally) rather than unintentionally. In Experiment 1, participants performed the serial response time task with reward, punishment, or control feedback and were instructed to ignore the presence of the sequence, i.e., learn unintentionally. Experiment 2 followed the same design, but participants were instructed to intentionally learn the sequence. We found that punishment significantly benefitted performance during learning only when participants learned unintentionally, and we observed no effect of punishment when participants learned intentionally. Thus, the impact of feedback on performance may be influenced by goal of the learner.

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          Most cited references42

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          Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism.

          Dopamine (DA) depletion in the basal ganglia (BG) of Parkinson's patients gives rise to both frontal-like and implicit learning impairments. Dopaminergic medication alleviates some cognitive deficits but impairs those that depend on intact areas of the BG, apparently due to DA ''overdose.'' These findings are difficult to accommodate with verbal theories of BG/DA function, owing to complexity of system dynamics: DA dynamically modulates function in the BG, which is itself a modulatory system. This article presents a neural network model that instantiates key biological properties and provides insight into the underlying role of DA in the BG during learning and execution of cognitive tasks. Specifically, the BG modulates the execution of ''actions'' (e.g., motor different parts of the frontal cortex. Phasic changes in DA, which occur during error feedback, dynamically modulate the BG threshold for facilitating/suppressing a cortical command in response to particular stimuli. Reduced dynamic range of DA explains Parkinson and DA overdose deficits with a single underlying dysfunction, despite overall differences in raw DA levels. Simulated Parkinsonism and medication effects provide a theoretical basis for behavioral data in probabilistic classification and reversal tasks. The model also provides novel testable predictions for neuropsychological and pharmacological studies, and motivates further investigation of BG/DA interactions with the prefrontal cortex in working memory.
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            The Role of GABA in Human Motor Learning

            Results There is considerable variability in motor learning behavior across individuals [7], and the present study aimed to test whether some of this variability could be explained by variation in responsiveness of the GABA system, because GABA modulation plays an important role in learning [1–4]. As a measure of GABA responsiveness, we used magnetic resonance spectroscopy (MRS) to quantify changes in GABA concentration following anodal transcranial direct current stimulation (tDCS), a noninvasive technique that decreases GABA within the motor cortex [5], increases cortical excitability [8], and enhances short-term learning [9]. We predicted that individuals who show less tDCS-mediated GABA modulation would show less behavioral evidence of motor learning and less modulation of fMRI responses during learning. Subjects participated in three experimental sessions on different days. The first two sessions were MRS sessions, during which GABA-edited spectra were acquired before and after 10 min of tDCS. In the third session, subjects performed an explicit sequence learning task during fMRI, and no tDCS was applied. Motor Behavior Motor learning was assessed via change in reaction times to a visually cued explicit sequence learning task performed with the four fingers of the right hand during fMRI acquisition in session 3. All subjects showed a significant reduction in reaction times across successive learning blocks (Figure 1A; repeated-measures analysis of variance, main effect of BLOCK F(15,150) = 19.95; p  2.0 and a (corrected) cluster significance threshold of p = 0.01.
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              Motor Learning.

              Motor learning encompasses a wide range of phenomena, ranging from relatively low-level mechanisms for maintaining calibration of our movements, to making high-level cognitive decisions about how to act in a novel situation. We survey the major existing approaches to characterizing motor learning at both the behavioral and neural level. In particular, we critically review two long-standing paradigms used in motor learning research-adaptation and sequence learning. We discuss the extent to which these paradigms can be considered models of motor skill acquisition, defined as the incremental improvement in our ability to rapidly select and then precisely execute appropriate actions, and conclude that they fall short of doing so. We then discuss two classes of emerging research paradigms-learning of arbitrary visuomotor mappings de novo and learning to execute movements with improved acuity-that more effectively address the acquisition of motor skill. Future work will be needed to determine the degree to which laboratory-based studies of skill, as described in this review, will relate to true expertise, which is likely dependent on the effects of practice on multiple cognitive processes that go beyond traditional sensorimotor neural architecture. © 2019 American Physiological Society. Compr Physiol 9:613-663, 2019.
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                Author and article information

                Contributors
                adamdanielsteel@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 June 2020
                1 June 2020
                2020
                : 10
                : 8906
                Affiliations
                [1 ]GRID grid.497865.1, Wellcome Trust Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, ; Oxford, UK
                [2 ]ISNI 0000 0004 0464 0574, GRID grid.416868.5, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, ; Bethesda, MD 20814 USA
                [3 ]GRID grid.497865.1, Oxford Centre for Human Brain Activity (OHBA), Wellcome Trust Centre for Integrative Neuroimaging, University Department of Psychiatry, University of Oxford, ; Oxford, UK
                Author information
                http://orcid.org/0000-0001-8876-933X
                http://orcid.org/0000-0001-6861-8964
                Article
                65853
                10.1038/s41598-020-65853-w
                7264311
                32483289
                7bfac74d-00a8-46f6-a6ac-7da5e317d3df
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 September 2019
                : 20 April 2020
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                © The Author(s) 2020

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                learning and memory,motivation
                Uncategorized
                learning and memory, motivation

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