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This paper examines the causes of dual-task interference in a time pressured dynamic environment. Resource sharing theories are often used as a theoretical framework to understand dual-task interference. These frameworks propose that resources from a limited pool of information-processing capacity is reallocated towards the primary task as task load increases, and as a result, secondary-task performance declines if the total demand exceeds capacity limit. However, tests of resource models have relied on behavioral results that could be due to a number of different cognitive processes, including changes in response caution, rate of information processing, non-decision processes and response biases. We applied evidence-accumulation models to quantify the cognitive processes underlying performance in a dual-task paradigm in order to examine the causes underlying dual-task interference. We fit performance in time-pressured environment on both a primary classification task and a secondary detection task using evidence-accumulation models. Under greater time pressure, the rate of information processing increased for the primary task while response caution decreased, whereas the rate of information processing for the secondary task declined with greater time pressure. Assuming the rate of evidence accumulation is proportional to available capacity these results are consistent with resource theory and highlight the value of evidence-accumulation models for understanding the complex set of processes underlying dual-task interference.
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