Picture Theory, Tacit Knowledge or Vividness-Core? Three Hypotheses on the Mind's Eye and Its Elusive Size

In this study, we compared hypotheses derived from our interpretation of three imagery theories - picture theory, tacit knowledge and vividness-core. Participants were asked to generate "small" (1.2o), "medium" (11o or 16o), or "large" (91o) images of concrete, everyday objects. Image size varied between subjects in Experiment 1, and within subjects in Experiment 2. Vividness ratings and image latency were measured. According to picture theory, vividness should increase directly with latency, and both should increase continuously with size, in both Experiments. According to tacit knowledge theory, such a continuous increase will occur only in Experiment 2 when the full range of sizes is known to the subjects. According to vividness-core theory, latency and vividness should be inversely related in both experiments, and latency should increase with size in Experiment 1 but not in Experiment 2. Results support vividness-core. Images, we conclude, are primarily derived from memories whose latent activation is reflected in reported vividness, as specified by vividness-core theory. In the recently revived "imagery debate", one contention has been that tacit knowledge can explain the classic findings on the effects of manipulating the size of mental images without the need of postulating visual mental imagery or pictorial representations (Pylyshyn, 2002). In the classic study, Kosslyn (1975) verbally cued participants to imagine an animal (e.g., tiger) so that the entire visual image would fill one of four randomly presented squares of different areas. Latencies were longer for generating images that filled larger squares, suggesting to Kosslyn that more time was consumed to "fill out" the larger images with the imaged object parts, and, hence, with more details. According to Kosslyn's (1994) picture theory, images are depictive representations formed in a structure (visual buffer) that has space limits, which constrain image resolution. If the object is imagined so small (or so large) that one cannot appropriately represent a part in which a given detail belongs, then the detail will not be incorporated. As size increases within an optimal range, it will offer progressively more locations for representing details of the imaged object, thereby requiring continuously more time to be completely fleshed out. However, this direct relationship between size and