Sequential effects in two-choice reaction time tasks: decomposition and synthesis of mechanisms

Juan Gao, KongFatt Wong-Lin, Philip Holmes, Patrick Simen, Jonathan Cohen

    Research output: Contribution to journalArticlepeer-review

    55 Citations (Scopus)
    67 Downloads (Pure)


    Performance on serial tasks is influenced by first- and higher-order sequential effects, respectively, due to the immediately previous and earlier trials. As response-to-stimulus interval (RSI) increases, the pattern of reaction times transits from a benefit-only mode, traditionally ascribed to automatic facilitation (AF), to a cost-benefit mode, due to strategic expectancy (SE). To illuminate the sources of such effects, we develop a connectionist network of two mutually inhibiting neural decision units subject to feedback from previous trials. A study of separate biasing mechanisms shows that residual decision unit activity can lead to only first-order AF, but higher-order AF can result from strategic priming mediated by conflict monitoring, which we instantiate in two distinct versions. A further mechanism mediates expectation-related biases that grow during RSI toward saturation levels determined by weighted repetition (or alternation) sequence lengths. Equipped with these mechanisms, the network, consistent with known neurophysiology, accounts for several sets of behavioral data over a wide range of RSIs. The results also suggest that practice speeds up all the mechanisms rather than adjusting their relative strengths.
    Original languageEnglish
    Pages (from-to)2407-2436
    JournalNeural Computation
    Issue number9
    Publication statusPublished (in print/issue) - 24 Sept 2009


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