Sachiko Kiyokawa

Role of selective attention in artificial grammar learning.

To investigate the role of selective attention in artificial grammar (AG) learning, participants were presented with “GLOCAL” strings—that is, chains of compound global and local letters. The global and local levels instantiated different grammars. The results of this experiment revealed that participants learned only the grammar for the level to which they attended. The participants were not even able to choose presented but unattended strings themselves. These results show that selective attention plays a critical role in AG learning.

Cross cultural differences in unconscious knowledge

Previous studies have indicated cross cultural differences in conscious processes, such that Asians have a global preference and Westerners a more analytical one. We investigated whether these biases also apply to unconscious knowledge. In Experiment 1, Japanese and UK participants memorized strings of large (global) letters made out of small (local) letters. The strings constituted one sequence of letters at a global level and a different sequence at a local level. Implicit learning occurred at the global and not the local level for the Japanese but equally at both levels for the English. In Experiment 2, the Japanese preference for global over local processing persisted even when structure existed only at the local but not global level. In Experiment 3, Japanese and UK participants were asked to attend to just one of the levels, global or local. Now the cultural groups performed similarly, indicating that the bias largely reflects preference rather than ability (although the data left room for residual ability differences). In Experiment 4, the greater global advantage of Japanese rather English was confirmed for strings made of Japanese kana rather than Roman letters. That is, the cultural difference is not due to familiarity of the sequence elements. In sum, we show for the first time that cultural biases strongly affect the type of unconscious knowledge people acquire.

Wearing Heavy Iron Clogs Can Inhibit Vection

Visually induced illusory self-motion perception is termed vection. We measured vection strength in participants wearing either wooden or iron clogs together with or without a weight-jacket (four conditions). We hypothesized that the heavier items would inhibit vection more because they make locomotion difficult. Results partially showed that the iron clogs could inhibit vection. We concluded that cognition of the fact that the heavier iron clogs made locomotion difficult might function as an inhibitor of vection, suggesting that cognition can alter vection strength.

Relationship between the diversity of information and idea generation

We attempted to determine whether the provision of diverse information could facilitate creative idea generation. For this purpose, we enlisted 35 students to generate two ideas individually by using the scanning material provided. The results revealed that the participants tended to select similar articles and to reduce their diversity even though diverse materials were provided. Further, the diversity of the materials they used actually was positively correlated with the quality of the generated ideas. We concluded that the diversity of materials that were not provided but nevertheless used had an effect on idea generation.

Modeling high-order human intelligence with intelligence of swarm

Particle Swarm Optimization (PSO) is a type of meta-heuristic optimization method built on the basis of the principle of collective behaviors exhibited by simple organisms. Although PSO is a model of social behaviors, the present research attempts to model learning behaviors of an individual human with PSO in order to evaluate our hypothesis that the dynamics of knowledge that are being acquired and updated in our mind resemble the dynamics of social interactions exhibited by swarms. A simulation study showed that a cognitive model with PSO was able to replicate not only manifested cognitive behaviors but also latent cognitive behaviors, resulting in the acquisition of at least two dissimilar yet functional solutions for a given task.

On the Knowledge Organization in Concept Formation: An Exploratory Cognitive Modeling Study

Recent cognitive modeling studies suggest the effectiveness of meta-heuristic optimization in describing human cognitive behaviors. Such models are built on the basis of population-based algorithm (e.g., genetic algorithm) and thus hold multiple solutions or notions. There are, however, important yet unaddressed issues in cognitive mechanisms associated with possession of multiple notions. The issues we address in the present research is about how multiple notions are organized in our mind. In particular, we paid close attention to how each notion interact with other notions while learning a new concept. In so doing, we incorporated Particle Swarm Optimization in a cognitive model of concept learning. Three PSO-based concept learning models were developed and compared in the present exploratory cognitive modeling study.