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Research Article
DaHui Wang
Beijing Normal University
Corresponding Author
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Human and many animals can asses the confidence of their decisions. However, little has been known about the underlying neural substrate and mechanism. Here we proposed a computational model consisting of one group of ’confidence neurons’ with adaptation, which is able to asses the confidence of decision by detecting the slope of ramping activities of decision neurons. The simulated activities of ’confidence neurons’ in our simple model capture the typical features of confidence in human and animals experiments. Our results indicate that confidence could be online formed along with the decision formation and the adaptation properties could be used to monitor the decision confidence in artificial intelligence.
Keywords
substrate, neurons, artificial intelligence, adaptation
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The full text of this article is available to read as a PDF.
No competing interests reported.
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View the published article at Scientific Reports.
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Editorial decision: Major revision
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On 23 Jun, 2021
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On 16 Jun, 2021
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A new preprint design is coming!
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See the published version of this preprint at Scientific Reports.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
DaHui Wang
Beijing Normal University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Scientific Reports.
Version 1
Posted 03 Jun, 2021
No community comments so far
Editorial decision: Major revision
On 13 Aug, 2021
Reviews received
Received 12 Aug, 2021
Reviewers agreed
On 10 Aug, 2021
Reviews received
Received 09 Jul, 2021
Reviewers agreed
On 23 Jun, 2021
Reviewers agreed
On 16 Jun, 2021
Reviewers invited
Invitations sent on 09 Jun, 2021
Editor assigned
On 09 Jun, 2021
Editor invited
On 28 May, 2021
Submission checks complete
On 28 May, 2021
First submitted
On 25 May, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Scientific Reports.
Human and many animals can asses the confidence of their decisions. However, little has been known about the underlying neural substrate and mechanism. Here we proposed a computational model consisting of one group of ’confidence neurons’ with adaptation, which is able to asses the confidence of decision by detecting the slope of ramping activities of decision neurons. The simulated activities of ’confidence neurons’ in our simple model capture the typical features of confidence in human and animals experiments. Our results indicate that confidence could be online formed along with the decision formation and the adaptation properties could be used to monitor the decision confidence in artificial intelligence.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
The full text of this article is available to read as a PDF.
No competing interests reported.
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