4.8 Article

Neural signatures of evidence accumulation in temporal decisions

Journal

CURRENT BIOLOGY
Volume 32, Issue 18, Pages 4093-+

Publisher

CELL PRESS
DOI: 10.1016/j.cub.2022.08.006

Keywords

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Funding

  1. James McDonnell Scholar Award in Understanding Human Cognition, ISF [958/16]
  2. European Research Council (ERC) under the European Union [852387]
  3. European Research Council (ERC) [852387] Funding Source: European Research Council (ERC)

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This study investigates the cognitive processes underlying temporal decisions using a combination of behavior, EEG, and modeling. The neural responses of participants were measured during a temporal bisection task, and a drift-diffusion model was used to relate these responses to the underlying cognitive processes. The study found that EEG responses at the offset of stimulus presentation marked the distance of the accumulator from the decision threshold.
Cognitive models of interval timing can be formulated as an accumulation-to-bound process.1-5 However, the physiological manifestation of such processes has not yet been identified. We used electroencephalography (EEG) to measure the neural responses of participants while they performed a temporal bisection task in which they were requested to categorize the duration of visual stimuli as short or long.6 We found that the stimulus -offset and response-locked activity depends on both stimulus duration and the participants' decision. To relate this activity to the underlying cognitive processes, we used a drift-diffusion model.7 The model includes a noisy accumulator starting with the stimulus onset and a decision threshold. According to the model, a stimulus duration will be categorized as longif the accumulator reaches the threshold during stimulus presentation. Otherwise, it will be categorized as short.We found that at the offset of stimulus presentation, an EEG response marks the distance of the accumulator from the threshold. Therefore, this model offers an accurate description of our behavioral data as well as the EEG response using the same two model parameters. We then replicated this finding in an identical experiment conducted in the tactile domain. We also extended this finding to two different temporal ranges (sub-and supra-second). Taken together, the work provides a new way to study the cognitive processes underlying temporal decisions, using a combination of behavior, EEG, and modeling.

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