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.
Year
DOI
Venue
2009
10.1162/neco.2009.09-08-866
Neural Computation
Keywords
Field
DocType
first-and higher-order sequential effect,previous trial,higher-order af,neural decision unit,strategic expectancy,first-order af,residual decision unit activity,cost-benefit mode,two-choice reaction time task,benefit-only mode,connectionist network,mathematics,automatism,reaction time,higher order,first order
Expectancy theory,Neurophysiology,Facilitation,Models of neural computation,Priming (psychology),Algorithm,Artificial neural network,Mathematics,Connectionism,Alternation (linguistics)
Journal
Volume
Issue
ISSN
21
9
0899-7667
Citations 
PageRank 
References 
7
0.66
6
Authors
5
Name
Order
Citations
PageRank
Juan Gao170.66
KongFatt Wong-Lin24611.52
Philip Holmes321526.66
Patrick Simen4377.82
Jonathan D Cohen529265.10