Confidence predicts speed-accuracy tradeoff for subsequent decisions in humans
Abstract
When external feedback about decision outcomes is lacking, agents need to adapt their decision policies based on an internal estimate of the correctness of their choices (i.e., decision confidence). We hypothesized that agents use confidence to continuously update the tradeoff between the speed and accuracy of their decisions: When confidence is low in one decision, the agent needs more evidence before committing to a choice in the next decision, leading to slower but more accurate decisions. We tested this hypothesis by fitting a bounded accumulation decision model to behavioral data from three different perceptual choice tasks. Decision bounds indeed depended on the reported confidence on the previous trial, independent of objective accuracy. This increase in decision bound was predicted by a centro-parietal EEG component sensitive to confidence. We conclude that internally computed neural signals of confidence predict the ongoing adjustment of decision policies.
Data availability
All data has been deposited online and can be freely accessed (https://osf.io/83x7c/ and https://github.com/AnnikaBoldt/Boldt_Yeung_2015). All analysis code is available on GitHub.
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Dataset: Post-decisional sense of confidence shapes speed-accuracy tradeoff for subsequent choicesOpen Science Framework, osf.io/83x7c/.
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Shared Neural Markers of Decision Confidence and Error DetectionGithub, AnnikaBoldt/Boldt_Yeung_2015.
Article and author information
Author details
Funding
Fonds Wetenschappelijk Onderzoek (FWO [PEGASUS]² Marie Skłodowska-Curie fellow)
- Kobe Desender
Economic and Social Research Council (PhD studentship)
- Annika Boldt
Wellcome (Sir Henry Wellcome Postdoctoral Fellowship)
- Annika Boldt
Deutsche Forschungsgemeinschaft (DO 1240/2-1)
- Tobias H Donner
Deutsche Forschungsgemeinschaft (DO 1240/3-1)
- Tobias H Donner
Fonds Wetenschappelijk Onderzoek (G010419N)
- Kobe Desender
- Tom Verguts
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Written informed consent and consent to publish was obtained prior to participiation. All procedures were approved by the local ethics committee of the University Medical Center, Hamburg-Eppendorf (PV5512).
Copyright
© 2019, Desender et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Neuroscience
When navigating environments with changing rules, human brain circuits flexibly adapt how and where we retain information to help us achieve our immediate goals.
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- Neuroscience
Human-specific cognitive abilities depend on information processing in the cerebral cortex, where the neurons are significantly larger and their processes longer and sparser compared to rodents. We found that, in synaptically connected layer 2/3 pyramidal cells (L2/3 PCs), the delay in signal propagation from soma to soma is similar in humans and rodents. To compensate for the longer processes of neurons, membrane potential changes in human axons and/or dendrites must propagate faster. Axonal and dendritic recordings show that the propagation speed of action potentials (APs) is similar in human and rat axons, but the forward propagation of excitatory postsynaptic potentials (EPSPs) and the backward propagation of APs are 26 and 47% faster in human dendrites, respectively. Experimentally-based detailed biophysical models have shown that the key factor responsible for the accelerated EPSP propagation in human cortical dendrites is the large conductance load imposed at the soma by the large basal dendritic tree. Additionally, larger dendritic diameters and differences in cable and ion channel properties in humans contribute to enhanced signal propagation. Our integrative experimental and modeling study provides new insights into the scaling rules that help maintain information processing speed albeit the large and sparse neurons in the human cortex.