<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
pmid: 15746411
The elegant computational model of addiction described by A. D. Redish in his Report “Addiction as a computational process gone awry” (10 Dec. 2004, p. [1944][1]) has the potential to provide an explanation for the placebo effect. In the temporal-difference reinforcement learning model (TDRL),
Reward, Substance-Related Disorders, Dopamine, Models, Neurological, Humans, Learning, Cues, Placebo Effect, Reinforcement, Psychology, Synaptic Transmission
Reward, Substance-Related Disorders, Dopamine, Models, Neurological, Humans, Learning, Cues, Placebo Effect, Reinforcement, Psychology, Synaptic Transmission
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |