Phd in PHD PROGRAM IN BEHAVIORAL NEUROSCIENCE

Thesis title: Experience with social and non-social cues modulates spatial orienting of attention

During the last decades, attention has been typically described as the result of an interplay between automatic and voluntary mechanisms, elicited by salient characteristics of a stimulus or event, or goal driven. Nevertheless, recent models posit that many factors can modulate how we orient our attention in space. Among these factors, evidence suggests that the probability of an event to occur is implicitly learned, and this learning improves performance when that event must be detected or discriminated. This is known as statistical learning. The aim of the present work was to shed light on how statistical learning influences our attention in the well-known, attentional cueing tasks (Posner, 1980). Previous applications of the Posner task showed that spatial regularities can guide attention even when participants are not informed of them. Here we assessed the effects of cue-target contingencies in the Posner paradigm across seven experiments to investigate how learning effects vary based on the type of cue used. Chapter 1 provides an overview of the theoretical background. Chapter 2 reports a meta-analysis of fMRI studies using non-social (arrow) and social (gaze) stimuli. Chapters 3 to 6 report studies which investigated the role of statistical learning in modulating attention. We showed that when a three-phase design was used to vary cue predictive validity in a Posner cueing task, and when cue predictive validity was associated with a specific spatial location, statistical learning of these regularities improved participants’ performances, and this effect persisted also when cue-target contingencies were removed. This effect was found with different types of cues, namely exogenous (chapter 3), non-social and social cues (chapter 4-5), but only when cognitive resources were fully available (chapter 6). The present research project contributes to enhancing our understanding of the mechanisms that underlie attentional shifts by social and non-social cues, adding new insights to models of attention and guiding future research.