Explaining the variability of antisaccade performance in healthy participants

In the antisaccade task participants are required to saccade to the mirror image location of a sudden onset target. As such, the task provides a powerful tool with which to investigate the cognitive processes underlying goal-directed behaviour. In healthy participants antisaccade errors (prosaccades directed towards the target) occur on approximately 20% of trials, and increased antisaccade error rate is widely used as a measure of “cognitive disinhibition” in clinical settings. One aspect of antisaccade performance that has received relatively little attention is the large variability in error rate typically observed within healthy participants. Whilst there are many studies describing increased antisaccade error rates in patient populations, there has been comparatively little research into what individual differences might underlie the dramatic variations that are observed within healthy participants. This thesis presents five papers, each of which explores potential sources of variability in antisaccade performance in healthy participants. The first paper used a cueing manipulation to explore the extent to which individual differences in the ability to maintain the task goal in mind will influence antisaccade error rate. The second paper addressed the potential role of differences in motivation, by determining the extent to which antisaccade performance is moderated by a range of incentives. In paper 3, the role of strategic influences was investigated by altering the task instructions that participants were given. In paper 4, task instructions and working memory load were manipulated in order to determine their effect on antisaccade error awareness. The final paper, based on data gathered across the preceding experiments, explored the extent to which individual differences in factors such as working memory capacity, processing speed, and personality measures (schizotypy and impulsivity) correlated with antisaccade performance. Across all studies, the data is used to test predictions made by current parallel programming models of antisaccade performance. The data suggests that a range of “top-down” factors can influence antisaccade performance, but that the most important individual difference in explaining antisaccade error rate in healthy participants is prosaccade latency.