Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations.
Performance during instrumental learning is commonly believed to reflect the knowledge that has been acquired up to that point. However, recent work in rodents found that instrumental performance was enhanced during periods when reinforcement was withheld, relative to periods when reinforcement was...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-12-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1010201 |
| _version_ | 1797974023903117312 |
|---|---|
| author | Hannah Kurtenbach Eduard Ort Monja Isabel Froböse Gerhard Jocham |
| author_facet | Hannah Kurtenbach Eduard Ort Monja Isabel Froböse Gerhard Jocham |
| author_sort | Hannah Kurtenbach |
| collection | DOAJ |
| description | Performance during instrumental learning is commonly believed to reflect the knowledge that has been acquired up to that point. However, recent work in rodents found that instrumental performance was enhanced during periods when reinforcement was withheld, relative to periods when reinforcement was provided. This suggests that reinforcement may mask acquired knowledge and lead to impaired performance. In the present study, we investigated whether such a beneficial effect of removing reinforcement translates to humans. Specifically, we tested whether performance during learning was improved during non-reinforced relative to reinforced task periods using signal detection theory and a computational modelling approach. To this end, 60 healthy volunteers performed a novel visual go/no-go learning task with deterministic reinforcement. To probe acquired knowledge in the absence of reinforcement, we interspersed blocks without feedback. In these non-reinforced task blocks, we found an increased d', indicative of enhanced instrumental performance. However, computational modelling showed that this improvement in performance was not due to an increased sensitivity of decision making to learnt values, but to a more cautious mode of responding, as evidenced by a reduction of a general response bias. Together with an initial tendency to act, this is sufficient to drive differential changes in hit and false alarm rates that jointly lead to an increased d'. To conclude, the improved instrumental performance in the absence of reinforcement observed in studies using asymmetrically reinforced go/no-go tasks may reflect a change in response bias rather than unmasking latent knowledge. |
| first_indexed | 2024-04-11T04:13:32Z |
| format | Article |
| id | doaj.art-ee9a6d9ab0834fe896aaca1ba1aca7c9 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-04-11T04:13:32Z |
| publishDate | 2022-12-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-ee9a6d9ab0834fe896aaca1ba1aca7c92023-01-01T05:31:07ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582022-12-011812e101020110.1371/journal.pcbi.1010201Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations.Hannah KurtenbachEduard OrtMonja Isabel FroböseGerhard JochamPerformance during instrumental learning is commonly believed to reflect the knowledge that has been acquired up to that point. However, recent work in rodents found that instrumental performance was enhanced during periods when reinforcement was withheld, relative to periods when reinforcement was provided. This suggests that reinforcement may mask acquired knowledge and lead to impaired performance. In the present study, we investigated whether such a beneficial effect of removing reinforcement translates to humans. Specifically, we tested whether performance during learning was improved during non-reinforced relative to reinforced task periods using signal detection theory and a computational modelling approach. To this end, 60 healthy volunteers performed a novel visual go/no-go learning task with deterministic reinforcement. To probe acquired knowledge in the absence of reinforcement, we interspersed blocks without feedback. In these non-reinforced task blocks, we found an increased d', indicative of enhanced instrumental performance. However, computational modelling showed that this improvement in performance was not due to an increased sensitivity of decision making to learnt values, but to a more cautious mode of responding, as evidenced by a reduction of a general response bias. Together with an initial tendency to act, this is sufficient to drive differential changes in hit and false alarm rates that jointly lead to an increased d'. To conclude, the improved instrumental performance in the absence of reinforcement observed in studies using asymmetrically reinforced go/no-go tasks may reflect a change in response bias rather than unmasking latent knowledge.https://doi.org/10.1371/journal.pcbi.1010201 |
| spellingShingle | Hannah Kurtenbach Eduard Ort Monja Isabel Froböse Gerhard Jocham Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations. PLoS Computational Biology |
| title | Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations. |
| title_full | Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations. |
| title_fullStr | Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations. |
| title_full_unstemmed | Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations. |
| title_short | Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations. |
| title_sort | removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations |
| url | https://doi.org/10.1371/journal.pcbi.1010201 |
| work_keys_str_mv | AT hannahkurtenbach removalofreinforcementimprovesinstrumentalperformanceinhumansbydecreasingageneralactionbiasratherthanunmaskinglearntassociations AT eduardort removalofreinforcementimprovesinstrumentalperformanceinhumansbydecreasingageneralactionbiasratherthanunmaskinglearntassociations AT monjaisabelfrobose removalofreinforcementimprovesinstrumentalperformanceinhumansbydecreasingageneralactionbiasratherthanunmaskinglearntassociations AT gerhardjocham removalofreinforcementimprovesinstrumentalperformanceinhumansbydecreasingageneralactionbiasratherthanunmaskinglearntassociations |