In case of both children and adults, the effects of time and space on velocity estimation in the field of motion perception are generally as follows: In constant physical velocity, subjective velocity increases with decrease in physical and/or phenomenal time and space (see Table 1). These effects may be tentatively explained by the neurophysiological adaptation hypothesis. Findings for the basis of the hypothesis are as follows. It has been reported that in comparatively primitive vertebrates such as frogs and rabbits, some ganglion cells in the retina respond only to a moving stimulus with certain direction, that when such cells are stimulated continuously by the moving stimulus, frequency of the neural discharge declines very quickly, and that in such cells the relation between frequency of the neural discharge and the angular velocity is expressed as an exponential function. These facts suggest that in pursuit movement of the eye a moving stimulus of a certain physical velocity with long exposure time raises sensory adaptation of certain directionally sensitive cells in the retina more strongly and frequency of the neuronal discharge in the cells accordingly decreases and then perceived velocity becomes lower than in the case of a moving stimulus of the same physical velocity but with short exposure time. But in higher mammals any such directionally sensitive cells have scarcely been found in the retina. Whereas those cells have, been found in the visual cortex of cats and monkys. It is therefore assumed that the same kind of neurophysiological adaptation for the moving stimulus might occur also in those cells in human visual cortex.
Now, we have made sure that effects of time, space and velocity on time and space estimations in the field of motion perception may be explained by the hypothesis of sets to choose cues in estimation. The present experiment is so designed as to make clear that in stead of the above hypothesis the neurophysiological adaptation hypothesis might hold better for velocity estimation.
For velocity estimation reproduction method was used. Standard stimuli shown in Table 2 consisted of the four series, each of which contained five standard velocities common to all series. In each series the condition of standard velocity 6.1cm/sec was the main condition and the other four were the additional conditions to a certain set. As the main condition and one of the additional conditions were alternately presented, reproduced velocities were obtained in four times for the main condition and only one reproduced velocity was obtained for each additional condition, in each subject.
The age and number of subjects are designated in Table 3.
The main results ware as follows:
1. Not only reproduced velocities under the main condition of the series TLL were lower than those under the series TSS for both children and adult, but also reproduced velocities under the main condition of the series ELL were lower than those under the series ESS for both children and adult (see Fig. 1, and Tables 4 and 5).
2. Ratios of reproduced velocities to standard velocities under the series TLL and TSS increased as standard velocities were higher, and those under the series ELL and ESS decreased a little as standard velocities were higher (see Fig. 2, and Tables 7 and 8).
These findings never agree with the estimates from the hypothesis of sets to choose cues in velocity estimation, but agrees pretty well with the estimates from the neurophysiological adaptation hypotheses.

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1) This study is aimed at research into the problem of whether heredity has an effect on school marks or not, and if it has, on which subjects it has the most powerful influence or the least one.
2) Method i) Subjects were as shown in Table 1. ii) The method of measurement on inheritance: 4 indexes; D₁, D₂, D², r in Table 2. iii) The criteria of interpretation of inheritance: a) The smaller the average intra-pair differences (D₁, D₂, D²) for the MZ in a school subject are, the more powerful the inheritance is, but in the case of (r), it is converse. b) The larger the differences between the DZ and the MZ are, the more powerful the inheritance is. This is the same in the case of the ratio H (Heredity)/E (Environment). iv) The zygocity diagnosis of twins: 18 kinds of morphological similarity diagnosis were used.
3) Results and discussion i) The differences between any two groups of 4 twin groups (MZ, DZ, OZ, SB) were generally significant as in Table 3. ii) In Table 2, the rankings of arithmetic were distinctly higher than the other subjects with regard to D₁, D₂, D², r for the MZ, but in Table 4, the rankings of arithmetic were lower conversely on primary school level. The rankings of arithmetic in these two tables were not similar to each other, and the differences between all subjects in Table 2 were not significant. Ida Frischeisen-Köhler and T. Iwashita argued that arithmetic marks were most influenced by the environment, because of the agreement of the results which were gained upon two criteria of the interpretation of inheritance in their studies. These results were not fully applicable to their results, but only in the criteria (a), which were almost similar. iii) In Table 5, the rankings of mathematics were generally higher than the other subjects for the MZ on junior high school level. The tendency of these rankings were identical with these in Table 6. These results were applicable to the results of the two authors above. But, the differences between all subjects were not significant, still the differences (D₁) were nearly significant as in Table 5.
4) Conclusion i) Without doubt, school marks were influenced by heredity on primary and junior high school level, ii) There was a faint indication of the more powerful effect of environment in arithmetic above all the other school subjects on the primary school level, but we could not conclude anything from this finding. iii) On the junior high school level, the mathematics marks seemed to be more influenced by environment than in primary school but it could not be concluded statistically. iv) These results were comparatively similar to the results of Ida Frischeisen-Köhler and T. Iwashita, but quite different to those of Torsten Husén.

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The present study reports three experiments designed to investigate the effects of drive on performance in selective learning.
In Exp. I, twelve rats were run to reversed goal each day, receiving 5 trials per day for 20 days in a T-maze. After 10-day training Ss were satiated and then given drive-test for 10 days. On the first day of the drive-test Ss received satiated trials, next 7 days they were deprived of all food except rewards in the goal and on the last two days satiated again. During the drive-test the percentage of correct responses was an inverted U-function of drive (Fig. 2). The performance under 48-hrs of food deprivation was significantly better than under both 0-hr and 96-hrs. The mean log running time was computed separately for positive and negative runs to confirm Reynolds' R-hypothesis (Fig. 3). It appeared that the differences between the positive and negative mean log running time varied with the percentage of correct responses.
In Exp. II, high drive group of 24 Ss and low drive group of 23 Ss received 5 trials per day for 10 days using a T-maze. Each drive group was divided into two groups: one given a choice cue and the other not. The difference between two drive groups was significant in the mean log running time but not in the number of correct responses. The choice cue had no effect on mean log running time but some effect on the choice (Table 1, 2 and Fig. 5). The drive effect on performance seemed to be greater under the no-cue condition than under the cue condition. The differences in mean log running time between the positive and negative runs were shown in Fig. 4, revealing some relation between these differences and z-values of the percentage correct.
In Exp. III, two drive groups of 22 Ss (18-hrs and 42-hrs of food deprivation) were run for 14 cycles of 12 trials each, using a Y-type discrimination apparatus in which the positive side had a curtain but the negative side did not. The number of positive and negative responses was equated by means of forced trials. Curves of percentage of correct choices showed some difference in favor of the 18-hr group (Fig. 6), but the drive effect was not significant (Table 5). The 42-hr group was significantly superior in speed to the 12-hr group and the interaction of drive with discriminanda (curtain) was significant (Fig. 6 and Table 4). The z-values of the percentage of correct choices were positive functions of the differences in the mean log running time again (Fig. 7).
Thus, drive effects on choice behavior were related to the effect of drive on response speed. And these results of three experiments were interpreted as supporting the R-hypothesis. However, the interference of high drive with choice performance was explained by the drive-disinhibition hypothesis, proposing that drive released negative response tendency from conditioned inhibition. After all, many conflicting results of drive/learning experiments would be explained by both the R-hypothesis and the drive-disinhibition hypothesis.

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Monopolar occipital recordings were obtained in 5 adults with flickering stimuli of 8, 10, 12, 16 and 25Hz and without flickers (NF), either with eyes closed, resting (EC), mental calculation (MC), or eyes opened, resting (EO) for a total session period of 1hr, Observations were repeated several days later. Similarly, another group of 3 adults were later tested 3 times under EC and EO. Intra- and inter-subject variations of EEG patterns under varing conditions were measured in terms of rank order correlations between a set of 5 integrated band-values per 10sec, in which the respective flicker frequencies were included.
When EEG patterns were computed based on group means as in ordinary experiments, their consistencies across sessions as measured by correlations were highest under EC and lowest under EO; in addition, the EEG pattern was considerably reduced with 25Hz lights under EO (Figs. 1, 2 and Table 1), When the same inter-session were computed per S and then averaged, the result was similar but, as a whole, correlations were lower compared with those based on group means (0.87 vs. 0.80) (Table 2). Moreover, these intra-subject correlations were almost identical even when they were computed within the session (Table 3).
Contrary to the intra-subject correlations, the mean inter-subject correlations within the session were in average lower and in particular markedly reduced with 25Hz lights under EC than under EO (Table 4). Thus greater individual differences were suggested under EC than under EO. No group differences (groups with 5 and 3 adults) were found.
Individual differences in EEG patterns especially with respects to alpha responses have been well-recognized since Walter and the present findings suggested that these individual-specific or internal factors are naturally more dominant with eyes closed (EC) than with eyes opened (EO), when external or environmental factors are more effective.
The flickering stimuli had both frequency-specific photic driving effects and nonspecific alpha-blocking effects. The former effects were dominant over the latter with stimuli of 8 to 16Hz, while the reverse was true with 25Hz lights and this would explain the lowest intra-subject correlations with these high-frequenecy lights. Similarly, the intra-subject correlations would be decreased by a house light of 50Hz, or of much faster frequency, that is under the EO conditions.
In addition, the depressant effects of 25Hz stimuli upon alpha responses were considerably different from individual to individual when alpha responses are otherwise not blocked, that is under EC, and thus inter-subject correlations would be greatly decreased with 25Hz flickering stimuli with eyes closed (EC).
Lastly, it was interesting to note that intra-subject correlations in EEG patterns were relatively independent of time intervals between observations and that the results under MC were closer to those under EC than those under EO; thus even dark illumination (EO) was more effective in altering EEG patterns than simple mental calculation.

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