Abstract
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.
Highlights
Everyday life provides many examples of complex behavior
We start with reviewing five computational models that focus on the basal ganglia and cover relevant aspects related to the neuropharmacology of implicit learning: (1) Doya’s computational model of reinforcement learning; (2) Berns and Sejnowskij’s model of sequence production; (3) Frank’s model of probabilistic learning and; (4) Ashby, Ennis and Spiering’s COVIS model of perceptual categorization; and (5) Ashby, Ennis and Spiering’s SPEED model of automaticity in perceptual categorization [43,44,45,46]
One must be careful not to overinterpret simple dissociations such as when explicit but not implicit learning is effected, for example by scopolamine [81, 82], since null effects might be related to low sensitivity in the experimental task chosen to probe a given learning system
Summary
Everyday life provides many examples of complex behavior. One of the most intriguing complex behaviors is perhaps language communication via the exchange of (structured) sentences. We will review some tasks which are commonly conceptualized as procedural learning tasks, including problem solving puzzles like the Tower of Hanoi, London or Toronto [21], mirror reading/drawing, and tracking tasks These tasks do require acquisition of complex sequenced behavior. Procedural learning tasks may be affected by explicit problem solving strategies, especially during the early stage of acquisition Another potential difference is found in mirror reading and trail tracking tasks, where it is not clear whether subjects learn novel information about structured stimuli [see discussion in 4, 15]. We will not review priming studies here, but we will include one implicit memory task [27] since it fulfills the criteria for implicit learning and does not use simple exemplar recognition but rather generation with the instruction to exclude the acquisition set. It has to be kept in mind that full-range dose-response studies are generally lacking
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