Catecholaminergic Regulation of Learning Rate in a Dynamic Environment.
Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the '...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2016-10-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1005171 |
| _version_ | 1819023006963335168 |
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| author | Marieke Jepma Peter R Murphy Matthew R Nassar Mauricio Rangel-Gomez Martijn Meeter Sander Nieuwenhuis |
| author_facet | Marieke Jepma Peter R Murphy Matthew R Nassar Mauricio Rangel-Gomez Martijn Meeter Sander Nieuwenhuis |
| author_sort | Marieke Jepma |
| collection | DOAJ |
| description | Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change. |
| first_indexed | 2024-12-21T04:32:02Z |
| format | Article |
| id | doaj.art-5204751086604a488fc77f714734c098 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-21T04:32:02Z |
| publishDate | 2016-10-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-5204751086604a488fc77f714734c0982022-12-21T19:15:55ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-10-011210e100517110.1371/journal.pcbi.1005171Catecholaminergic Regulation of Learning Rate in a Dynamic Environment.Marieke JepmaPeter R MurphyMatthew R NassarMauricio Rangel-GomezMartijn MeeterSander NieuwenhuisAdaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change.https://doi.org/10.1371/journal.pcbi.1005171 |
| spellingShingle | Marieke Jepma Peter R Murphy Matthew R Nassar Mauricio Rangel-Gomez Martijn Meeter Sander Nieuwenhuis Catecholaminergic Regulation of Learning Rate in a Dynamic Environment. PLoS Computational Biology |
| title | Catecholaminergic Regulation of Learning Rate in a Dynamic Environment. |
| title_full | Catecholaminergic Regulation of Learning Rate in a Dynamic Environment. |
| title_fullStr | Catecholaminergic Regulation of Learning Rate in a Dynamic Environment. |
| title_full_unstemmed | Catecholaminergic Regulation of Learning Rate in a Dynamic Environment. |
| title_short | Catecholaminergic Regulation of Learning Rate in a Dynamic Environment. |
| title_sort | catecholaminergic regulation of learning rate in a dynamic environment |
| url | https://doi.org/10.1371/journal.pcbi.1005171 |
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