Inference-driven Mechanisms of Attentional Orienting

Contents

In this paper we present some empirical data in support of a new view of attentional orienting, according to which (a) some basic mechanisms of attentional deployment (i.e. its high efficiency in dealing with expected and unexpected in- puts) meet the requirements of the inferential system, and have possibly evolved to support its functioning; and (b) these orienting mechanisms function in very similar ways in different domains, i.e. in perceptual tasks and in symbolic tasks. After sketching the basics of the model and of its spe- cific predictions, we report the results of 3 behavioral experiments where participants tracked visual trajectories (Ex- periments 1 and 3) or arithmetic series (Experiments 2 and 3), responding to the onset of a target event (e.g., to a specific number) and to the repetition of an event (e.g., a number ap- pearing twice consecutively). Target events could be antici- pated when they were embedded in regular series/trajectories; they could be anticipated, with the anticipation later discon- firmed, when a regular series/trajectory was abruptly inter- rupted before the target event occurred; and could not be an- ticipated when the series/trajectory was random. Repeated events could not be anticipated. Results show a very similar pattern of allocation in tracking visual trajectories and arith- metic series: attention is focused on anticipated events, it is defocused and redistributed when an anticipation is not con- firmed by ensuing events, while performance decreases when dealing with random series/trajectory, i.e. in absence of anticipations. The behavioral results were later supported by an electrophysiological investigation using Event Related Po- tentials. In our view, this pattern of allocation of attention is due to the fact that confirmed and disconfirmed anticipations are crucial events for knowledge revision, i.e. the fine tuning of the inferential system to the environment; attentional mechanisms have developed so as to enhance detection of these events, possibly at all levels of inferential processing.