Visual word recognition: Attention, intention, context, and processing dynamics.

Abstract

The notion that some mental processes are "automatic" while others are "controlled" is a distinction that appears in virtually all cognition textbooks, as well as in thousands of papers and book chapters. Indeed, so entrenched is the automatic side of this distinction that various leading computational accounts make no mention of it, but instead assume it implicitly. These models, and the field more generally, assume that processing is stimulus triggered and does not need any form of attention or an intention as a preliminary. Further, the fundamental processing dynamics underlying such automatic processing is widely seen as consisting of interactive activation and autonomous in that it unfolds in the same way across contexts. I review a number of findings from my lab that lead me to a different conclusion. Visual word recognition requires a consideration and integrated understanding of automaticity, attention, intention, context, and cognitive processing. I present various findings that challenge the preeminent role ascribed to interactive activation as implemented in the dominant computational models. I conclude that, going forward, the time is due for computational models of visual word recognition (and researchers in the field more generally) to acknowledge that the findings reported here constitute benchmarks that constrain theory and present opportunities for making meaningful advances in our understanding of visual word recognition (and perhaps of cognition more generally). A few proposals for how we might think about some of these processes are offered. (PsycInfo Database Record (c) 2022 APA, all rights reserved).