Journal article
Quantifying decision-making in dynamic, continuously evolving environments
- Abstract:
- During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear. Here, we use a novel continuous task design to study how the centroparietal positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests that these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 2.9MB, Terms of use)
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- Publisher copy:
- 10.7554/eLife.82823
Authors
- Publisher:
- eLife Sciences Publications
- Journal:
- eLife More from this journal
- Volume:
- 12
- Article number:
- e82823
- Place of publication:
- England
- Publication date:
- 2023-10-26
- Acceptance date:
- 2023-10-13
- DOI:
- EISSN:
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2050-084X
- Language:
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English
- Keywords:
- Pubs id:
-
1560278
- Local pid:
-
pubs:1560278
- Deposit date:
-
2023-11-08
Terms of use
- Copyright holder:
- Ruesseler et al.
- Copyright date:
- 2023
- Rights statement:
- © 2023, Ruesseler, Weber et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
- Notes:
- For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
- Licence:
- CC Attribution (CC BY)
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