Academic journal article Attention, Perception and Psychophysics

Nonindependent and Nonstationary Response Times in Stopping and Stepping Saccade Tasks

Academic journal article Attention, Perception and Psychophysics

Nonindependent and Nonstationary Response Times in Stopping and Stepping Saccade Tasks

Article excerpt

Saccade stop signal and target step tasks are used to investigate the mechanisms of cognitive control. Performance of these tasks can be explained as the outcome of a race between stochastic go and stop processes. The race model analyses assume that response times (RTs) measured throughout an experimental session are independent samples from stationary stochastic processes. This article demonstrates that RTs are neither independent nor stationary for humans and monkeys performing saccade stopping and target-step tasks. We investigate the consequences that this has on analyses of these data. Nonindependent and nonstationary RTs artificially flatten inhibition functions and account for some of the systematic differences in RTs following different types of trials. However, nonindependent and nonstationary RTs do not bias the estimation of the stop signal RT. These results demonstrate the robustness of the race model to some aspects of nonindependence and nonstationarity and point to useful extensions of the model.

(ProQuest: ... denotes formulae omitted.)

Cognitive control is revealed in experiments that require subjects to change their performance in response to changes in their environment (e.g., Logan, 1985). The stop signal task (Logan, 1994; Verbruggen & Logan, 2008b) and the target step task (Camalier et al., 2007; Murthy, Ray, Shorter, Schall, & Thompson, 2009) have been used to examine executive control of saccadic eye movements in humans and macaque monkeys (Camalier et al., 2007; Hanes & Schall, 1995). These tasks present a target for an eye movement and then present either a stop signal, which indicates that the eye movement should be withheld, or a stepped target, which indicates that the eye movement should be directed to a new location. Performance on these tasks can be understood as the outcome of a race between a go process that makes the initial saccade and a stop process that inhibits the initial saccade to maintain fixation or to allow a new saccade to the new location (Camalier et al., 2007; Logan & Cowan, 1984; see also Boucher, Palmeri, Logan, & Schall, 2007). The race model assumes that the finish times for the go and stop processes as a function of trial number are stationary stochastic processes with independence between trials. This article reports data that challenge those assumptions and explores the consequences of those violations for analyses based on the race model. Our goal is not to evaluate the causes of nonindependence and nonstationarity but, rather, to document them in stopping and stepping tasks and evaluate their effects on race model and trial history analyses.

Nonstationarity refers to a stochastic process described by a mean or variance that changes over time. Response times (RTs) gradually becoming longer from the beginning to the end of an experimental session is one example of nonstationarity. Nonindependence refers to statistical dependence across samples in a time series. A correlation in RT between successive trials is one example of nonindependence. A time series that is nonstationary must be nonindependent, but the reverse is not necessarily true (e.g., autoregressive and moving average models; Wagenmakers, Farrell, & Ratcliff, 2004).

The fact that RTs are often nonstationary and nonindependent is well established (e.g., Gilden, 2001; Wagenmakers et al., 2004). For instance, RT on a given trial can vary with the stimulus and response that occurred on the preceding trial (e.g., Fecteau & Munoz, 2003; Luce, 1986). Furthermore, RT can change with arousal, fatigue, learning, and motivation throughout a session (Broadbent, 1971; Freeman, 1933; Welford, 1968, 1980). Several investigators have documented apparently systematic changes in RT during performance of the stop signal task (Cabel, Armstrong, Reingold, & Munoz, 2000; Emeric et al., 2007; Kornylo, Dill, Saenz, & Krauzlis, 2003; Li, Krystal, & Mathalon, 2005; Özyurt, Colonius, & Arndt, 2003; Rieger & Gauggel, 1999; Schachar et al. …

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