Apparent sequential effects due to trial-to-trial fluctuations in decision criterion

Criterion fluctuations from trial to trial, modeled with SDT, fully explain the repulsive sequential effect of the previous stimulus and substantially reshape choice history bias across 14 empirical datasets.

• Why it matters: Sequential effects are often interpreted as causal updates to decision parameters, but this can confound behavioral and neuroimaging conclusions when slow criterion drift is ignored.
• What they did: Simulations show that history-independent criterion fluctuations generate three sequential effects, and hMFC jointly estimates criterion fluctuations and causal history updating across 14 empirical datasets.
• The result: After accounting for criterion fluctuations, attractive choice-history biases disappeared in four datasets, three revealed masked alternation, and two showed stronger alternation; confidence-modulated choice-history bias was largely unchanged.

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