title: Sequential effects in two-choice reaction time tasks: decomposition and synthesis of mechanisms.
abstract: 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.
authors: Department of Mechanical and Aerospace Engineering and Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA. juangao@stanford.edu
authors: Juan
authors: J
authors: Gao
authors: Kongfatt
authors: K
authors: Wong-Lin
authors: Philip
authors: P
authors: Holmes
authors: Patrick
authors: P
authors: Simen
authors: Jonathan D
authors: JD
authors: Cohen
mesh_terms: D001332:Automatism; D015982:Bias; D002755:Choice Behavior; D030141:Feedback, Psychological; D006801:Humans; D007266:Inhibition, Psychological; D008433:Mathematics; D008570:Memory, Short-Term / Q000502:physiology; D008960:Models, Psychological; D016571:Neural Networks, Computer; D009483:Neuropsychological Tests; D011930:Reaction Time / Q000502:physiology*; D012691:Serial Learning / Q000502:physiology*; D013997:Time Factors