Attention metaphors: How metaphors guide the cognitive psychology of attention

Abstract

The concept of attention is defined by multiple inconsistent metaphors that scientists use to identify relevant phenomena, frame hypotheses, construct experiments, and interpret data. (1) The Filter metaphor shapes debates about partial vs . complete filtering, early vs . late selection, and information filtering vs. enhancement. (2) The Spotlight metaphor raises the issue of space-vs. object-based selection, and it guides research on the size, shape, and movement of the attentional focus. (3) The Spotlight-in-the-Brain metaphor is frequently used to interpret imaging studies of attention . (4) The debate between supramodal and pre-motor theories of attention replays the dichotomy between the Spotlight and the Vision metaphors of attention . Our analysis reveals the central role of metaphor in scientific theory and research on attention, exposes hidden assumptions behind various research strategies, and shows the need for flexibility in the use of current metaphors.

The structure of the relationship between attention and intelligence

“…There is the possibility to select one of the various approaches of attention research (Fernandez-Duque & Johnson, 1998, 2002 as starting point for the construction of models representing the relationship between attention and intelligence. It is the approach of resource allocation theories which is especially well suited for this purpose because this approach possesses a special advantage: it enables the integration of the processes, which perform the various operations, as resources into the considerations.…”

“…The different types originate from the diversity of attentional phenomena and the approaches which are described by the metaphors of attention (Fernandez-Duque & Johnson, 1998, 2002. The neglect of the differences between the types would mean that one or a few types were taken to represent the whole and that the result of investigating the relationship between attention and intelligence would depend on personal preference for a certain type or chance.…”

Frameworks for Modeling Cognition and Decisions in Institutional Environments

“…Winograd (1980) has focused on the relation of natural language understanding as a cognitive process to be applied to computers. 18 As for language utterance, many studies have been devoted to the nature and use of metaphors (Lakoff and Johnson 1980;Indurkhya 1987;Gerrig 1989;Martin 1992;Clausner and Croft 1997;Fernández-Duque and Johnson 1999), discourse contribution (Clark and Schaefer 1989), 19 the use of referring expressions (Dale and Reiter 1995), the role of emotions in narratives (Dyer 1983a), 20 coreference processing (Gordon and Hendrick 1998), the pragmatics of locative expressions (Herskovits 1985), the relation between discourse processing and conceptual structure (Morrow 1986), and other variables such as interestingness in discourse (Hidi and Baird 1986). …”

Arrow of time: Metaphorical construals of entropy and the second law of thermodynamics

“…The conceptual metaphor perspective has also been applied to technical scientific domains including the theory of natural selection (e.g., Al‐Zahrani, 2008), the scientific concept of energy (Amin, 2009), quantum mechanics and thermodynamics (Brookes, 2006; Brookes & Etkina, 2007), cognitive theories of attention (Fernandez‐Duque & Johnson, 1999, 2002), and scientific problem‐solving using the concept of entropy (Jeppsson, Haglund, Amin, & Strömdahl, submitted), as well as a range of mathematical concepts (Lakoff & Núñez, 1997, 2000). The pervasiveness of implicit conceptual metaphors in technical language is interesting to consider in light of the advantages and challenges of using metaphor in science learning, as discussed in the science education literature.…”