INFORMACIÓN GRÁFICA

According to goal activation accounts, successful antisaccade performance requires the ability to maintain and manipulate task-relevant information in mind (working memory), whilst simultaneously ignoring task-irrelevant information and over-riding prepotent responses (inhibition). These two functions suggest a close relationship between goal activation and working memory. Some studies that support a goal activation account of antisaccade performance have used „dual task paradigms‟ to investigate the role of working memory in antisaccade performance (e.g. Claeys et al., 1999; Mitchell, McCrae, & Gilchrist, 2002; Roberts et al., 1994). In a dual task paradigm, participants perform antisaccades whilst simultaneously performing a concurrent task. In an interesting study, Stuyven, Van der Goten, Vandierendonck, Claeys, & Crevits (2000) investigated the effects of cognitive load on antisaccade performance. The authors wanted to know whether a possible effect of cognitive load on antisaccade performance could be due to a central cognitive component, a motor

component, or simply to the fact that two tasks have to be performed at the same time. In their first experiment, participants completed a block of antisaccades, a block of antisaccades with the Random time Interval Generation (RIG) task (Vandierendonck, De Vooght, & Van der Goten, 1998) and a block of antisaccades with a fixed tapping task. The RIG task required participants to tap an unpredictable rhythm on the zero key of the computer keyboard at an average rate of one keystroke per second. Repetition of a pattern was not allowed. The requirement to be random and to avoid automaticity loads the central executive (De Rammelaere, Stuyven, & Vandierendonck, 2001). For the fixed tapping task, participants were instructed to hit zero on the keyboard at a rate of one tap per second. In addition, participants performed a block of prosaccades, a block of prosaccades with the RIG and a block of prosaccades with the fixed tapping task. The fixed tapping task was included as an additional control condition for the RIG as it requires the same motor actions, but presumably does not require as much

executive functioning resources. Compared to when antisaccades were performed alone, antisaccade errors and correct antisaccade latencies were increased when antisaccades were performed with fixed tapping. Similarly, errors and latencies were increased when antisaccades were performed with the RIG task. A similar pattern of results was found for prosaccades, except that the fixed tapping task did not alter prosaccade errors, suggesting that cognitive load impacted more on antisaccades. Participants made more antisaccade errors when performing the RIG task compared to fixed tapping, but there

were no differences in latencies between these conditions. The authors argued that more antisaccade errors were made when antisaccades were performed with the RIG task than the fixed tapping task because the RIG task required working memory processes that would otherwise have been devoted to antisaccade performance. In terms of goal activation accounts of antisaccade performance, it would seem that the RIG task disrupted goal activation more than the fixed planning task. This is presumably due to the increased monitoring demands that are required in the RIG task (i.e. constantly checking that the taps are random) compared to the fixed tapping task.

The relationship between goal activation, working memory and antisaccade performance has also been investigated in studies that have explored individual differences in working memory capacity (the ability to maintain memory

representations in the face of concurrent processing, distraction, and/or attention shifts Shah & Miyake, 1999) as a possible predictor of antisaccade performance. One

common individual difference that has been used in these studies is participants‟ scores on the operation span task, a measure that indicates whether a participant has high or low working memory capacity (e.g. Kane, Bleckley, Conway, & Engle, 2001; Unsworth et al., 2004). These studies will be discussed in more detail in the 5th paper of this thesis, where an attempt will be made to find potential sources that can account for the large variability in antisaccade performance in healthy participants.

One relatively unexplored area of antisaccade performance is the degree to which a participant‟s motivation impacts on error rate and correct latencies. Previous studies have addressed this to some extent, by using incentives as a tool with which to measure motivation. Typically, the type of incentive used is monetary reward, and previous research has found mixed results when looking at the effects of monetary reward on antisaccade performance in healthy participants (e.g. Blaukopf & Di Girolamo, 2006; Hardin, Schroth, Pine, & Ernst, 2007; Jazbec et al., 2006). If

antisaccade error rate is reduced by monetary reward, then it can be assumed that the incentive increases activation of the task goal, in line with goal activation accounts. The influence of motivation (using incentives) on antisaccade performance will be explored in more detail in the 2nd paper of this thesis.

The preceding discussion has outlined several key issues concerning antisaccade performance that still remain unclear. The most prominent of these issues is that

variability in antisaccade error rate can be enormously large and it is unclear why these individual differences in antisaccade performance exist? Additionally, the extent to

which antisaccade performance can be explained by predictions of recent competitive race model and goal activation accounts remains under researched. The following section, will outline the aims and hypotheses of this thesis based on predictions of current models of antisaccade performance.