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The neuropharmacology of implicit learning

MPG-Autoren
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Uddén,  Julia
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Unification, MPI for Psycholinguistics, Max Planck Society;
Cognitive Neurophysiology Research Group, Stockholm Brain Institute, Karolinska Institutet, Stockholm, Sweden;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Folia,  Vasiliki
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Unification, MPI for Psycholinguistics, Max Planck Society;
Cognitive Neurophysiology Research Group, Stockholm Brain Institute, Karolinska Institutet, Stockholm, Sweden;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

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Petersson,  Karl Magnus
Neurobiology of Language Group, MPI for Psycholinguistics, Max Planck Society;
Unification, MPI for Psycholinguistics, Max Planck Society;
Cognitive Neurophysiology Research Group, Stockholm Brain Institute, Karolinska Institutet, Stockholm, Sweden;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;
Cognitive Neuroscience Research Group, Institute of Biotechnology & Bioengineering/CBME, Universidade do Algarve, Faro, Portugal;

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Zitation

Uddén, J., Folia, V., & Petersson, K. M. (2010). The neuropharmacology of implicit learning. Current Neuropharmacology, 8, 367-381. doi:10.2174/157015910793358178.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0012-9E26-C
Zusammenfassung
Two decades of pharmacologic research on the human capacity to implicitly acquire knowledge as well as cognitive skills and procedures have yielded surprisingly few conclusive insights. We review the empirical literature of the neuropharmacology of implicit learning. We evaluate the findings in the context of relevant computational models related to neurotransmittors such as dopamine, serotonin, acetylcholine and noradrenalin. These include models for reinforcement learning, sequence production, and categorization. We conclude, based on the reviewed literature, that one can predict improved implicit acquisition by moderately elevated dopamine levels and impaired implicit acquisition by moderately decreased dopamine levels. These effects are most prominent in the dorsal striatum. This is supported by a range of behavioral tasks in the empirical literature. Similar predictions can be made for serotonin, although there is yet a lack of support in the literature for serotonin involvement in classical implicit learning tasks. There is currently a lack of evidence for a role of the noradrenergic and cholinergic systems in implicit and related forms of learning. GABA modulators, including benzodiazepines, seem to affect implicit learning in a complex manner and further research is needed. Finally, we identify allosteric AMPA receptors modulators as a potentially interesting target for future investigation of the neuropharmacology of procedural and implicit learning.