The present study investigated attributes of kanji On- and Kun-readings from the perspectives of both statistical prediction and human strategy. In Study 1, discriminant analysis using the stepwise method revealed four significant indicators out of ten kanji characteristics for distinguishing On- and Kun-readings. These indicators are semantic concreteness, naming latency, special sounds and number of strokes. In Study 2, an On- or Kun-reading test is given to 30 native Japanese speakers. The result showed tendencies similar to the accuracy rates of discriminant analysis. After the test, a questionnaire revealed that 6 out of 10 strategies were employed by more than 6 out of the 30 participants. Three of these were congruent with significant indicators specified by discriminant analysis, namely, semantic concreteness, naming latency and special sounds. Despite the significant indicator in Study 1, particular strategies concerning kanji strokes and radical frequency were not used by humans. Native Japanese speakers are likely to use kanji neighborhood, kanji homophones and number of morae. The results between indicators and strategies illustrate a more general point: On- and Kun-readings can be effectively predicted by discriminant analysis on the basis of various kanji characteristics; however, due to a lack of consistency in On- and Kun-readings attached to each kanji, humans can flexibly incorporate a wider variety of strategies when making their determinations.

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We investigated, through a cognitive psychological experiment and its protocol analysis, experts' and novices' interactive process between the mental operation by which participants considered their ideas and the external operations by which they actually produced physical objects in creative activity. In our experiment, the participants were required to build toy robots with creative features with LEGO Mindstorms. The experimental results showed that the experts could create work that fulfilled both high originality and practicality simultaneously. Moreover, the following four points were confirmed as characteristics of the experts' creative process: (1) the experts globally considered their initial ideas, (2) the experts predicted and considered their ideas by focusing on various aspects of important viewpoints, (3) the experts reconstructed their ideas more actively, and (4) the experts reconstructed their ideas by considering comprehensively the relationship among the elements constructing their plans.

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We investigated source-monitoring errors in qualitative and temporal order judgments. In Experiment 1, a group of participants saw pictures on the first day and imagined items on the third day. The order was reversed in the second group. The result showed that the picture-imagined group misattributed new items to the perceived source whereas the imagined-picture group misattributed the new items to the imagined source. These results were consistent with those obtained by Bink, Marsh and Hicks (1999). In Experiment 2 and 3, we investigated the relationship between qualitative and temporal judgments. Participants were presented with pictures and were asked to imagine items on both the first and third days. They tended to misattribute the source of the new items to the first day rather than to the third day. The results further indicated that qualitative judgments were always correct when temporal order judgments were correct. In contrast, correct qualitative judgments did not reliably predict correct temporal order judgments. The results therefore indicated that qualitative judgments rely heavily on temporal order judgments.

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The prefrontal (PF) cortex has long been suspected to play an important role in cognitive control. In this study, we focused on the encoding of rules in the PF cortex. Wallis et al. (2001) explored its neural basis by recording from single neurons in the PF cortex of monkeys trained to use two rules: a ‘match’ rule and a ‘non-match’ rule. The “match” rule required each monkey to release a lever if two successive sample objects were identical, whereas the “non-match” rule required release if the two objects were different. As a result, they found neurons selective for learned rules regardless of samples and cues. However, the mechanism of the rule-guided behaviour is still unknown, and the functional role of rule-selective neurons has not been elucidated. To investigate how the brain may implement a rule-guided behaviour, we simulated physiological results in Wallis et al. (2001) and analyzed the temporal patterns of the model unit and connection weights, and compared the property of the unit with that of biological neurons. Through analysis of the connection weights, we could shed light on the mechanism of the PF cortex performing a rule-guided delayed matching-to-sample task, and elucidate the functional role of the rule-selective neurons.

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RTs (Reaction times) for single-digit addition and multiplication problems are different in each of problem types (cf. problem size effect, tie effect), and this pattern is different in two arithmetic tasks: production and verification. The purpose of this study was which factor contributed to differences of RTs if it was assumed that RTs were the function of the associative strength (AS) and the interference strength (IS). AS and IS for each problem type were evaluated by a experimental method (number-matching task), and solution process in arithmetic tasks was examined. Five experiments and a computational simulation were conducted, and next four conclusions were led. Three of the beginning are related to the production task. First, problem size effect is caused by AS in addition, but by IS in multiplication. Second, tie effect is caused by AS in addition, but mainly by IS in multiplication. Third, the phenomenon which multiplication is solved slower than addition is caused by IS. And forth, in the verification task, difference of RTs in each problem type is caused by AS in both addition and multiplication.

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