The preceding review makes it obvious that there is no consistent view of how experts construct mental imagery representations. The imagery processes described above do not provide a detailed description of the mechanisms underlying the task used in Studies I-IV: that is, when experts incrementally construct a mental representation. The tasks that experts are able to perform are complex and require capacity surpassing WM limits.
Therefore, associative memory and conceptual knowledge may have a greater role than in the simpler imagery tasks studied earlier. The Studies IV-V also investigated the domain of music, where auditory imagery has a greater role than visual imagery. There is presently no clear picture of the general principles that underlie imagery in different sense modalities in the complex images that experts are able to construct.
There are, however, striking similarities between the main questions of imagery research and research on expert memory: in both fields the roles of perceptual and conceptual knowledge are debated. In the imagery literature, the disagreement about whether perceptual properties are the core of mental imagery or whether interpretations are tied to the imagery representations is an important issue. In expert memory research, the dichotomy between perceptual chunking as the main mechanism underlying expert memory and the crucial role of higher-order knowledge and conceptual chunking is also essential. Furthermore, several theories of expert memory imply that mental imagery has an important role when experts construct representations. The chunking and template theories propose a visuo-spatial system, a mind’s eye, as the foundation of chess players’ thinking. The LTWM theory suggests spatial retrieval structures for several task environments. Thus, although the imagery research and the expert memory research represent different traditions, the dichotomy of perceptual and conceptual knowledge is found in both.
What, then, could be the mechanisms underlying experts’ mental imagery? The importance of perceptual properties is evident in the concept of ‘mind’s eye’ introduced in expert memory research. The patterns in the mind’s eye are constructed from external stimuli and from LTM. These descriptions are in line with the suggestions of imagery research. Kosslyn’s (1994) theory on visual mental imagery, and research findings on visuo-spatial WM (Logie, 1995) further suggest several processes and components that are required in the generation, maintenance, and manipulation of images. Furthermore, the chunking and template theories of expert memory stress that the pattern-recognition processes are automatic and unconscious, and operate on both the perceived stimulus and the internal image (Campitelli & Gobet, 2005; Gobet & Simon, 1996a). These assumptions lead
to the hypothesis that the main mechanism underlying skilled imagery is perceptual chunking.
However, expert imagery is a very complex phenomenon and, therefore, it is possible that the perceptual imagery processes that have been demonstrated in knowledge-poor tasks are not sufficient in explaining expert imagery. There is evidence that, at least in some cases, interpretation is tied to mental imagery and that conceptual knowledge plays a major role (Chambers & Reisberg, 1992; Reisberg, 1996; Reisberg, Smith, Baxter, &
Sonenshine, 1989). There is also preliminary evidence for the claim that the level of LTM knowledge and skills and the ability to overcome WM limitations contribute to how experts construct mental images (Saariluoma, 1991). Furthermore, theories of expert memory stressing the role of higher-level conceptual knowledge suggest that constructing skilled images can be a slow problem solving process rather than fast automatic pattern recognition.
If this is the case, mental imagery could offer a special kind of system for encoding and retrieving information deliberately and consciously. These assumptions lead to the hypothesis that skilled imagery is not solely based on perceptual chunking and that conceptual chunking also plays an important role.
One reason for the lack of consensus among mental imagery researchers and among expert memory researchers is the great variety of empirical methods used to study the basic issues in these research fields. In imagery research, the main problem in developing a consensus between theorists is that the current views on imagery are based on a mixture of behavioural and brain research studies, as well as on introspective and intuitive notions (Pylyshyn, 2002). Therefore, the empirical results are not strictly comparable. For example, in some studies the mental images result from an immediately prior visual stimulus but in some cases the images are constructed from LTM. However, results concerning sensory images are often interpreted as being evidence for the perceptual properties of mental images although it is unclear whether the images following sensory stimuli and those constructed from memory actually reflect the same phenomenon.
In the expert memory research, empirical methods vary from brief-exposure techniques customarily employed by researchers of perceptual chunking, to memory tasks, verbal protocols, and long-range learning tasks used by other researchers (Gobet, 1998). In this situation, the empirical data on expert memory are disconnected and difficult to compare between several domains, and even within a single domain.
In the present research, a method was developed for use across a variety of domains. This method can provide empirical data relevant to the further development of the current theories on mental imagery and expert memory.
The research method was developed from an application of blindfold chess (Saariluoma, 1991). In blindfold chess, players do not see the chess board
but have to imagine the moves of the pieces that are described to them verbally. In the present studies, representations were constructed from successively presented stimuli for problem solving or immediate recall.
Thus, the participants did not see whole stimuli patterns, such as all the pieces of a chess position or every street name of the list or all the notes of the pattern. This method makes it possible to tease out the process of representation construction, since experts are not familiar with this kind of task; thus the process cannot be fully automatic, and therefore its mechanisms can be caught.
Since an equivalent experimental method was applied to every domain investigated in the present studies, it was possible to compare results from the different domains. This approach addressed general cognitive principles that underlie skilled imagery in several domains. In this sense it resembles the approaches of LTWM and the constraint attunement hypothesis. The domains of chess, taxi driving, and music were studied. In these domains memorising is not an intrinsic task, but a contrived task, an issue considered important in the template theory and the constraint attunement hypothesis.
That is, although chess players, taxi drivers, and musicians have to memorise games, routes, and melodies, the defining feature of these domains of expertise is not memorising the stimuli; exceptional memory and imagery are by-products of expertise.
At the same time, the present studies concentrated on a specific process in expert imagery: the incremental construction of mental representations.
Therefore, the approach also resembles that of template theory, where the focus is on a specific task and the aim is to understand specific mechanisms.
Thus it was possible to clarify both the general aspects of expert memory and imagery across three domains, and the specific mechanisms underlying the process of incremental construction of mental imagery.
In the representation construction task used in the present study, the role of WM is crucial: a person has to maintain the presented items in WM in order to construct a global representation and to connect individual items into chunks. This process is subject to decay and interference. The main question is how pre-learned knowledge and skills that experts have acquired contributes to this process and how experts are able to overcome the limitations of WM. What is at issue is the role of automatic pattern matching in image construction, and whether experts are also able to use higher-level knowledge and conceptual chunking.