Some mechanisms responsible for the vividness of mental imagery : suppressor, closer, and other functions

In this paper, studies concerned with the vividness of imagery are reviewed to elucidate the characteristics of vivid imagery, the mechanisms responsible for the vividness of imagery, and the factors that affect those mechanisms. From this review, the following characteristics of imagery can be identified: (a) imagery vividness can be defined by the amount of information in the image, and more perceptual information is in vivid than in dim imagery; (b) information structure in long-term memory (LTM) consists of meaning, affective information, perceptual information, and motoric information, and those components are interconnected; (c) imagery is generated in the image construction stages using perceptual information; (d) a mechanism called the Suppressor controls the channel capacity, or the flow of perceptual information from LTM to the image construction stages; (e) the degree of this suppression is affected by the emotional value of imagery computed on the basis of affective information stored in LTM; (f) motoric information in LTM also influences vividness by acting on the image construction stages. Given these characteristics, we propose a model of imagery processes in order to explain how a certain level of vividness is established for the visual mental image. Finally, some neural correlates of the model are described based on results from our latest fMRI studies, and problems remaining for further development of the model are discussed. Keywords: Imagery Vividness; Suppressor; Closer; Affection; Motor Activity Address correspondence to Shinsuke Hishitani, Department of Psychology, Graduate School of Letters, Hokkaido University, Sapporo 060-0810, Japan. E-mail: hishitani@let.hokudai. ac.jp The second and third authors contributed equally to writing this paper and are listed in alphabetical order. 2 Hishitani, Miyazaki, and Motoyama In the present paper, we propose a hypothetical model of the mechanisms that explain how visual mental imagery achieves a certain vividness. Since mental imagery is a basic building-block of consciousness (Marks, 1999), it is one of the indispensable subjects of scientific research on consciousness. Mental imagery is a quasi-perceptual subjective experience, and this "quasi-perceptuality" is the most salient characteristic that differentiates imagery from other forms of conscious experience. In other words, subjective sensory-like aspects of experience, namely experiences of qualia, are central to mental imagery (Hubbard, 1996). Therefore, the most important measure that represents the quality of imagery is its vividness, which is measured in terms of its similarity to perceptual experience. The mechanisms that determine and evaluate imagery vividness have not yet been elucidated, but it is expected that solving this problem would give us an essential clue to the scientific study of conscious experience. Most imagery researchers agree about the process through which conscious mental imagery is represented in the image construction stage via transformations applied to the information retrieved from long-term memory (LTM) (e.g., Kosslyn, 1980; Kosslyn, Thompson, & Ganis, 2006; Pearson, 2001; Pearson, Logie, & Gilhooly, 1999; Pearson, Logie, & Green, 1996). Some researchers call the image construction stage the visual buffer, which is assumed to be in the early visual areas, and others identify it as visuo-spatial working memory. The relationship between the former and the latter has not necessarily been specified. Moreover, Kosslyn et al. (2006) suggest that high-resolution imagery is represented in the visual buffer, but not low-resolution imagery. At this time, one specific image construction stage has not been identified, but almost all imagery researchers admit that it is an indispensable, effective construct for research. Thus, it is possible that there are multiple image construction stages that are used in accordance with the situation. Accordingly, we outline an image generation process in which information is retrieved from LTM and transferred to the proper image construction stage (or stages), where conscious mental imagery is formed. We adopt this process as a framework for our research on imagery vividness and consider the following topics in turn. First, we discuss the characteristics of vivid imagery and suggest that imagery vividness can be defined by the amount of information the image contains. Second, we propose a mechanism that represents interpersonal variations in imagery vividness to explain individual differences in imagery vividness or imagery ability. Third, we discuss affect as a factor that causes intrapersonal variations in imagery vividness, and we expand on the mechanism mentioned above. Fourth, we argue for a model of interand intrapersonal variations in imagery vividness in terms of the information structure in LTM. Fifth, we identify the neural correlates of the proposed model based on results from our latest functional magnetic resonance imaging (fMRI) studies. Finally, we MECHANISMS FOR IMAGERY VIVIDNESS 3 discuss some problems to consider in further development of the model. The Characteristics of Vivid Imagery In the visual imagery questionnaires that have been developed so far, imagery vividness has been measured in terms of relative clarity in comparison with perception (e.g., Betts, 1909; Marks, 1973; Sheehan, 1967). This method, in which vividness is measured based on the similarity between imagery and perception, corresponds to a phenomenalistic definition of imagery: specifically, a quasi-perceptual experience without a perceptual stimulus (e.g., Bugelski, 1970; Richardson, 1969). It is assumed that a mental image contains perceptual information, and that more vivid images include more information. In fact, some studies that employ imagery vividness and/or individual differences in vividness as experimental variables support these assumptions. These studies have shown directly and indirectly that vivid images contain more information than dim images, and that the subjective vividness of an image is determined by the amount of information it includes (Denis, 1979). For example, Cornoldi et al. (1991) examined the characteristics that influence the vividness of imagery. They interviewed participants and found that the following six characteristics may influence the vividness of imagery: color, richness of context, salient features, richness of details, well-defined shape and contour, and generality of the represented object. Next, they examined the characteristics that have greater relevance in evaluating the vividness of voluntarily generated imagery. First, their participants constructed an image of a presented noun and evaluated its vividness; then, they rated to what extent the six characteristics existed in the image. Stepwise multiple regression analysis revealed that the vividness ratings were significantly influenced by five characteristics: shape and contour, color, details, generality, and salience. Seligman and Yellen (1987) reported that the vivid involuntary imagery of dreams has the same characteristics as voluntarily generated imagery. In their experiment, they asked participants to describe their dreams from the previous night and to evaluate the vividness of the images in these dreams. Judges who were blind to the content and vividness of the dreams examined the characteristics of the images that were extracted from the dreams on the basis of the participants' descriptions. Vivid imagery was found to be more detailed and colorful than dim imagery. Participants were also asked to report the size of their images, and the more vivid images were found to be larger in size. These studies directly investigated the characteristics of vivid imagery based mainly on the participants' introspection, and they all found that vivid images contained more perceptual information than dim ones. Other studies indirectly support this finding. For example, Finke and Schmidt (1978) found that when vivid imagers visualized black stripes on a colored background and then observed only the black stripes, they could see a 4 Hishitani, Miyazaki, and Motoyama complementary color between the stripes (i.e., an imagery-induced McCollough effect). This complementary color after-effect induced by imagery arose only at chance levels in non-vivid imagers. Further, Richardson and Patterson (1986) reported that, in comparison with dim imagery, vivid imagery induced a stronger physiological response corresponding to the content of the imagery, for example, saliva secretion while forming an image of lemons. Since vivid imagery includes much more perceptual information and has a stronger resemblance to what is imaged than dim imagery, it should function as a better substitute for a perceptual stimulus and should also function as a more effective mental stimulus in problem solving. Hishitani (1991) examined this prediction and found that a shorter time was required to find a target item in a vivid image than in a dim image. Consequently, it was concluded that an image that includes more perceptual information will be more vivid and that differences in vividness are directly related to the amount of information transferred from LTM to the image construction stage(s) (Hishitani, 1993). Hishitani (1985) also examined the characteristics of vivid imagery, employing individual differences in vividness as the experimental variables. He gave vivid and non-vivid imagers three concrete nouns (e.g., a night stall [booth], a small bird, and a railroad), and asked them to generate and describe an integrated image scene (e.g., The street along the railroad is alive with a row of night stalls, and a night-stall vendor is calling out that small birds are for sale. The street is crowded with people.). The number of objects, people, animals, and so on that appeared in the image and the number of simple sentences that were obtained by parsing the description were calculated. Ther