Correlations of movement time and intelligence: Effects of simplifying response requirements

INTELLIGENCE 14, 481-491 (1990)

Correlations of Movement Time and Intelligence: Effects of Simplifying

Response Requirements JOSEPH A. BUCKHALT

Auburn University T. GILMOUR REEVE

Auburn University

LANIE A. DORNIER Texas Tech University

Research indicates that certain response parameters are related consistently to IQ. While explanations of why decision time (DT) and response variability relate to IQ have been presented, no satisfactory explanation of why movement time (MT) should be related to IQ has been advanced. One possible explanation relates to the motor response requirements of the apparatus devised by Jensen (1982). The apparatus controls for movement distance of responses in all conditions, but in some conditions those responses must be made in different directions. Moreover, the responses must be guided to relatively small targets. The present study evaluated the hypothesis that individual differences in guidance of the motor responses may account for a portion of MT-IQ covariance. An apparatus was designed for which the motor response was to a large target and the response was the same distance and direction regardless of decision complexity. For a sample of adolescents, IQ measures were correlated with DT and MT across four levels of task complexity. The MT-IQ correlations were significant and as large as DT-IQ correlations. This finding is interpreted as evidence against the motor guidance hypothesis and suggests that alternate explanations should be investigated.

A number of studies have compared individual differences in intelligence and response decision processes (e.g., Jensen, 1987). Much of this work has evaluated the relationship of performances on standardized intelligence tests and achievement tests to performances on basic choice-reaction tasks. The choicereaction tasks allow for the fractionation of the response into two components: decision time (DT) and movement time (MT). The interval of time from stimulus onset to the release of the "home" button is DT (also termed reaction time in

The assistance of Daniel J. Weeks in apparatus design and Mei-Shio Jang in computer programming is gratefully acknowledged. Correspondence and requests for reprints should be sent to Joseph A. Buckhalt, Department of Counseling and Counseling Psychology, Haley Center 2014, Auburn University, AL 36849. 481

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many instances) and the interval from the release of the "home" button to the depression of a "target" button is MT. Using the Hick paradigm (Hick, 1952), in which task complexity is increased by increasing the number of alternative choices, DT has been found to correlate consistently and negatively with various measures of intelligence and academic achievement. This relationship between DT and intelligence is consistent with the hypothesis that the quickness of cognitive processing (i.e., making choice decisions) is related to intelligence. Because MT involves processes that should be largely independent of the decision processes, the correlation between MT and intelligence should be less than that found for DT and intelligence. However, such an outcome has not been obtained. In fact, in many cases the correlation for MT and intelligence has been as strong as that for DT and intelligence. Summarizing the results from 26 independent samples, Jensen (1987) estimated that correlations (corrected for attenuation due to range restriction and measurement error) of intelligence with DT and with MT were - . 3 2 and - . 3 0 , respectively. Moreover, in a number studies not included in Jensen's summary, MT-IQ correlations have been reported that are higher than the corresponding D T - I Q correlations. These patterns of correlations were found in studies with preschoolers (Telzrow, 1983), 12-yearold children (Buckhalt & Jensen, 1989), young adults (Frearson & Eysenck, 1986), and older adults (Era, Jokela, & Heikkinen, 1986). Unlike the correlation for DT-IQ, a satisfactory explanation for the M T - I Q correlations has been lacking. Jensen (1982) has suggested that M T - I Q correlations may be accounted for by inadequate or incomplete programming of the ballistic response before releasing from the home button by the lower intelligence subjects. In one recent study, Smith and Carew (1987) presented evidence suggesting that for some subjects the decision itself may be incomplete before the motor response is initiated. In their study, Smith and Carew (1987) used a masking condition in which the stimulus lights would go out upon motor response initiation, thus making decisions after response initiation more difficult. They found that some subjects may lift from the home button as rapidly as possible when they detect a stimulus and "hover" momentarily before completing their response decision. A hovering strategy would confound interpretations of the correlations of intelligence with the DT and MT phases. Jensen (1987-) previously considered this possibility, but argued that subjects would be more likely to adopt such a strategy on more complex tasks. If this were the case, within-subject correlations of DT and MT would be negative and increasingly stronger (i.e., closer to - 1 . 0 ) as task complexity increased. Because the predicted relationship was not found in three studies, Jensen concluded that the hovering hypothesis lacked empirical support. It is possible that yet another feature of Jensen's apparatus leads to ambiguity of interpretation of the relationship of MT to intelligence. The apparatus controls for movement length in all conditions by using a semicircular arrangement of

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stimulus/response buttons (i.e,, each response button is the same distance from the home button). However, because of this arrangement, eight different movement directions are required in some conditions. Thus, the uncertainty of one movement parameter (distance) is controlled but the uncertainty of another parameter (direction) is not. Issues related to response parameters such as ann, direction, and extent of movement have long been a concern of motor control researchers (e.g., see Rosenbaum, 1983). By definition, a choice situation involves uncertainty for at least one parameter, and different parameters may have different implications for interpretation of results. For some conditions used with Jensen's apparatus, complexity or difficulty of the motor response is confounded with the demands of decision complexity. In the zero and one-bit conditions (one or two buttons), the response alternatives are in the same approximate direction, but in the three-bit condition (all eight buttons) as well as in the "odd man out" condition (Frearson & Eysenck, 1986), not only is the decision more complex, but the motor programming demands are also more difficult. For some subjects, complete programming of the movement may occur before departure from the home button, while for others directional guidance may continue after departure. Such a possibility provides the hypothesis that brighter subjects complete more programming of the movement during the DT phase, thus reducing the duration of MT and accounting for significant M T - I Q correlations. In his methodological critique of data obtained with Jensen's apparatus, Longstreth (1984) raised questions about response direction (or response "bias") effects. However, Longstreth (1984) failed to provide definitive evidence related to the issue because his apparatus did not separate DT and MT. Two recent studies have addressed the questions raised by Longstreth (1984). In their investigation of procedural effects of the Jensen apparatus, Widaman and Carlson (1989) studied the response bias effect, as well as effects of order, practice, and visual attention. Response direction was experimentally manipulated by using different groupings of response altematives in the Hick paradigm. For example, with the one-bit condition, performances with the conventional adjacent buttons in positions four and five was contrasted with performances in a condition using the two most distant buttons, one and eight. This manipulation allowed for movements in opposite directions while holding decision complexity constant. Widaman and Carlson (1989) reported mixed findings for grouping in that the main effect for grouping was not significant for MT intercept, but was significant (albeit relatively small) for MT slope. They concluded that while substantial order and practice effects pose serious questions for the interpretation of previous results with the Jensen apparatus, problems of response bias did not seem very serious. In another study specifically addressing Longstreth's (1984) methodological concerns, Kranzler, Whang, and Jensen (1988) included an experimental manip-

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ulation similar to Widaman and Carlson (1989). In their study, Kranzler et al. (1988) presented the one-bit task using target buttons one and eight as well as the conventional buttons four and five. While a significant effect was found both for DT and MT, Kranzler et al. (1988) argued that the effect is very small in relation to large amounts of variance in DT and MT accounted for by individual differences. Although the results of these studies suggest that uncertainty of movement direction is not a significant factor in determining the M T - I Q relationship, all of the studies have maintained movement direction as the uncertain parameter. A more direct test of the influence of direction uncertainty requires a situation in which direction uncertainty is eliminated. An additional methodological issue concerns the size of the target buttons. In informal observations of 12-year-old subjects performing on the Jensen apparatus, we noted that subjects were variable in the precision of their depression of the target button. Faster subjects may hit the button at various points "off-center" while slower subjects may make a more deliberate effort to try to "center" their responses. This apparent trade-off between movement precision and movement speed would be consistent with Fitt's law. Fitt's law states that MT is a function of the amplitude and precision of the movement, with MT increasing as amplitude and precision increase (Schmidt, 1988). In other words, subjects' MTs may be affected by differing degrees of precision that they are demanding in their performances. This source of individual differences may also influence the M T IQ correlations. Brighter subjects may realize that the task may be performed faster by hitting the button on any part of its surface, decreasing the precision of the movement, and thus decreasing their MTs. In the present study, an apparatus was constructed that allowed for the presentation of tasks varying in decision complexity, but unlike the Jensen apparatus, movements of the same direction and distance are required across all conditions. For all choice conditions, movements were made with either the left or right arm (arm parameter uncertain) to targets that were directly in front of the subject's hand (direction parameter certain). With this new apparatus, decisions required to resolve stimulus uncertainty also specified the movement parameter for arm. Thus, the movement would be completely parameterized in the DT interval and not in the MT interval. Additionally, large response pads were used instead of small target buttons. The large target pads were intended to decrease the individual differences related to the precision criterion established by the subject for motor control. If the M T - I Q correlations found in previous studies are attributable to the requirement of programming movements in different directions to small targets, we would expect to find much lower M T - I Q correlations in this study. Such a finding would provide evidence for a motor guidance interpretation of the M T - I Q correlations obtained in earlier studies. If the M T - I Q correlations with the new apparatus are comparable to D T - I Q correlations, this finding would provide evidence against the guidance interpretation and altemate explanations must be considered.

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METHOD Subjects Subjects were 43 seventh- and eighth-grade students recruited from a public junior high school in a small Southeastern U.S. town. Twenty-six students were male and 17 were female. Twenty-seven students were white and 16 were black. The mean age was 13 years, 4 months (SD = 6.6 mos.). Informed consent was obtained from participating students and their parents. Subjects were given a movie pass redeemable at a local theater for their participation.

Procedure Intelligence Measures. The measures of intelligence chosen for this study were the British Ability Scales Short-Form (BAS; Elliott, 1983) and the OtisLennon School Ability Test (OLSAT; Otis & Lennon, 1982). The BAS ShortForm for children above age 8 consists of four subtests: Speed of Information Processing, Matrices, Similarities, and Recall of Digits. These subtests were selected for the Short-Form on the basis of their high reliability and their dissimilar requirements for performance (i.e., memory, reasoning, verbal, nonverbal). The BAS Short-Form IQ derived from these subtests has proven to have high reliability and good criterion-related validity. In a validity study of the BAS Short-Form, Buckhalt (1990) reported correlations of .82 with OLSAT School Ability Index and .80 with the Complete Battery Score of the Stanford Achievement Test (SAT). The BAS was administered individually to subjects on the same day they performed the reaction time tasks. Mean BAS Short-Form IQ was 107.7 (SD = 16.9). The OLSAT is a group-administered intelligence test which was administered concurrently with the SAT earlier in the year the present study was conducted. School Ability Index (SAI) scores were obtained from school records with student and parental permission. Mean OLSAT SAI for the sample was 114.2 (SD = 22.5). D T / M T Measures. The apparatus used in the D T - M T component of the study included a stimulus-display panel and a response panel (Fig. l). The display panel had eight equally-spaced, white stimulus lights. The response panel had two response keys and two target pads. With this apparatus, subjects responded with either the left index finger or the fight index finger. Subjects depressed the home response keys before trials and initiated responses by lifting the appropriate finger from one of the keys. A warning signal, which was the onset of all eight lights for an interval of 500 ms, indicated the beginning of each trial. The warning signal and target signal were separated by a foreperiod that varied between 500 ms and 1250 ms. When movements were to be made, they were either to the left target pad for left index finger responses or to the right target pad for right index finger responses.

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Stimuli--

00000000

/

rget Pads I

I

/

Start Keys

FIG. 1. Apparatus used for DT and MT data collection. In one day of testing (total time approximately 25 min), each subject completed two sessions with five blocks of trials. One session required only response decisions in that subjects were simply required to lift the appropriate finger from the home response key (Lift-Only condition). The other condition required the same finger lift response followed by a movement to the corresponding target pad. (Target-Response condition). Thus, the only difference between the two sessions was whether a movement was required following the response decision. The order of presentation of the two sessions was counterbalanced across subjects. For the Lift-Only condition, the five blocks of trials included two simple decision blocks, a two-choice decision block, an eight-item/two-choice decision block, and an odd man decision block. One of the simple decision blocks required the subject to respond to the leftmost stimulus on the display panel and the other block required the subject to respond to the rightmost stimulus. Within each simple decision block, a total of 22 trials were presented, with the first 10 trials considered practice and not included in the data analysis. The order of presentation of these two blocks of trials was counterbalanced. The two-choice decision used the leftmost and rightmost stimulus lights. The stimuli were presented equally often and the subject was to respond by lifting the left or right index finger that corresponded to the same side as the stimulus. A total of 34 trials were presented with the first 10 trials considered practice. Of the last 24 trials, the left and right stimuli were each presented on 12 trials. The order of stimulus presentation was random with the restriction that the stimulus from one side could not be presented on more than three consecutive trials. The 8-stimulus/2-choice decision block was similar to the two-choice task,

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but any of the 8 stimulus lights could be presented on a trial. The subject was to respond with the left or fight index finger depending on whether the stimulus was one of the four leftmost lights or one of the four fightmost lights, respectively. This block included 34 trials, with the first 10 considered practice. Twelve trials (3 for each light) for the four leftmost lights and 12 trials for the four fightmost lights were included in the data analysis. Each light occurred equally often and the order of presentation was random with the restriction that the same stimulus not be presented on two consecutive trials. The odd man out block was a modification of the procedure first described by Frearson and Eysenck (1986). On each trial, three lights were presented, with two of the lights being adjacent on one side of the apparatus and one light on the other side. The subject was to respond with the finger that corresponded to the same side as the stimulus presented alone. All combinations of two adjacent lights from one side and one light from the other side were included, with the exception of the combination for which the two centermost lights on one side were paired with the centermost light from the other side. This unique combination of stimuli would produce three adjacent lights and thus was omitted from the experiment. A total of 11 allowable combinations were possible for the left responses and 11 for the fight responses. Each combination was randomly presented 3 times, making for 66 experimental trials, with an additional 10 trials presented initially for practice. For the Target-Response condition, which included a movement to the target, the same procedures were followed. For these trials, subjects responded by lifting the appropriate index finger and moving the hand forward to strike the target pad. Subjects were encouraged to move quickly and to poke the pad with the index finger. RESULTS AND DISCUSSION Statistical analyses were calculated using DTs and MTs which were averaged across the times from left and fight hand performances of each subject. Mean DTs and MTs are presented in Table 1 (p. 488). As noted previously, the distance and direction of movement are specified in advance for our task, and only the choice of arm used for the response must be specified in the DT interval. Comparing DT means for the Target-Response and Lift-Only conditions gives some indication of the time required for programming the execution of the motor response. While those times are relatively small (mean difference between the two response conditions across all stimulus conditions = 33 ms), an analysis of variance comparing the two conditions yielded a significant (F (1,42) = 10.87, p < .01) main effect for response condition. The main effect for trial blocks was significant (F (3, 126) = 109.87, p < .01), but the interaction of response condition and trial blocks was not significant (F (3, 126) = 2.26, p > .05). By inference, then, we may assume that in the Target-Response condition, a c o m -

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TABLE 1 Mean Decision Time (DT) and Movement Time (MT) by Stimulus and Response Conditions (in ms)

Response Condition

Stimulus Condition 1-bit

2-bits

3-bits

Oddman

DT

322

394

409

596

DT MT

337 235

431 232

468 235

628 251

Lift-Only condition

Target-Response condition

parable period of time is used to program the arm movement for each of the different stimulus conditions. The correlations between the two intelligence measures and DT and MT are shown in Table 2. Of primary interest are the significant correlations between MT and intelligence in all stimulus conditions. Even with short movements of uniform direction which do not require differential directional programming or guidance toward small targets, correlations of MT and intelligence are of considerable magnitude. As has been found in several previous studies, (e.g., Frearson & Eysenck, 1986; Telzrow, 1983; Widaman & Carlson, 1989) these correlations are as strong as D T - I Q correlations. A number of investigators (e.g., Jensen, 1987) have stressed the theoretical implications of the multiple regression of various reaction time measures on intelligence. Although the sample size in the present study was too small for the application of multivariate statistics, one additional analysis was performed to determine if the response measures showed a stronger relationship to intelligence when combined than when considered separately. The response measures (DT and MT) and intelligence measures (BAS and OLSAT) were converted to z scores and then summed for the two sets (DT + MT zs and BAS + OLSAT zs). The correlation obtained between the sum of z scores was - . 4 6 . This value is TABLE 2

Correlations Between Intelligence Measures and Response Speed By Experimental Condition Lift Only Condition

Decision Time

One light Two lights Eight lights Oddman

Target Response Condition Decision Time

Movement Time

BAS

OLSAT

BAS

OLSAT

BAS

OLSAT

-.26 -.26 -.26 - .33

-.28 -.35 -.33 -.46

-.26 - . 17 -.32 - .45

-.30 -.20 -.43 - .51

-.34 -.29 -.36 - .36

-.40 -.39 -.45 - .50

Note. Correlations stronger than - . 2 5 are significant at the p < .05 level (one-tailed).

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consistent with Jensen's (1987) estimate of the multiple correlation of Hick paradigm parameters and intelligence. Using correlations corrected for attenuation and restriction of range in 26 independent samples, Jensen (1987) estimated that the true multiple correlation between Hick parameters and intelligence is between - . 3 5 and - . 5 0 .

Discussion of Theoretical Explanations Much of the theory underlying the recent research that shows significant relationships between Hick paradigm measures and intelligence has assumed that speed of executing the simple cognitive decision is the critical covariate with intelligence. A satisfactory explanation of why MT also should be systematically related to intelligence has not emerged. One explanatory hypothesis that has been offered involves the complexity of motor response programming and execution. However, based on the correlations in the present study, this hypothesis was not supported. M T - I Q correlations were just as large when movement demands were simplified greatly. What reasonable alternative explanations remain? Smith and Carew's (1987) hovering hypothesis seems unlikely, since such a strategy is improbable on our task and would not be advantageous on zero-bit (1 button) conditions even for the Jensen apparatus. Jensen (1987) reviewed eight independent studies which correlated MT and intelligence. He found that MT-IQ correlations did not increase with task complexity, as one might expect if subjects were hovering, but that on the average, M T - I Q correlations became smaller on more complex tasks. In the present study, M T - I Q correlations are relatively constant across task complexity. If more intelligent subjects are executing the movement phase of the response more quickly, a few other reasons are possible. One, brighter subjects may simply be more motivated to respond quickly. This hypothesis is consistent with the finding of Lindley, Smith, and Thomas (1988) that speed in a simple copying task was significantly correlated (r = - . 3 0 , p < .05) with one of the IQ tests for a sample of college students. A second possibility is that a developmental phenomenon is responsible. At the age level of our subjects, higher intelligence may covary with motor development. In commenting that MT-IQ correlations are most often found with children and retarded subjects, Jensen (1987) has suggested this possibility. But this explanation is not wholly satisfactory since the phenomenon is exhibited in a number of studies using adults as subjects (e.g., Era et al., 1986; Frearson & Eysenck, 1986). A third hypothesis is that less intelligent subjects are more mentally "fatigued" by the task demands of attention and cognitive decision and have less energy available to execute a quick target response. Brighter subjects may be able to automatize some task components more easily and have more central attentional resources to devote to other components. Response variability has been shown to bear as strong a relationship to intelligence as DT and MT, and inconsistency across trials in all phases of these tasks by less intelligent subjects

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may reflect less ability to automatize task execution. Widaman and Carlson (1989) have addressed the issue of automaticity in their investigation of practice effects with the Jensen apparatus. They concluded that the DT and MT correlations with intelligence may hold only at early stages of practice. While their hypothesis is most strongly stated for DT, their prediction is that the relationships between both DT and MT will be diminished or nonexistent when sufficient practice allows for full automatization of responses. In the case of the typical study of Hick parameters with the Jensen apparatus, subjects may not have had sufficient practice to automatize MT since different movements are required in every trial block. But in the present study, every trial block had the same movement requirements, yet M T - I Q correlations remain strong across all trial blocks. Moreover, subjects completed a larger number of trials (178) than is typically the case, providing more opportunity to automatize the simple movement required. Jensen has interpreted D T - I Q correlations as supporting the hypothesis that speed of performing very elementary cognitive tasks in the Hick paradigm is a central underlying aspect of general intelligence. Widaman and Carlson's (1989) contention is that the relationship may be due to differential rates of task automatization rather than to a stable "trait-like" characteristic. In either case, however, no suitable explanation remains for the M T - I Q correlations. The same alternative hypotheses may be proposed for MT as for DT. Given the large number of trials with a simple movement requirement in the present study, it seems unlikely that differential rates of automatization of the movement are responsible for the M T - I Q correlations. Still another hypothesis is that brighter persons process information faster and move faster due to central underlying physiological differences affecting both decisions and speed of movement. Vernon and Mori's (1989) evidence that nerve conduction velocity is correlated with speed of information processing and general intelligence is consistent with that hypothesis, but very little research with physiological variables has yet been conducted. In summary, the present results provide no support for the idea that M T - I Q correlations may be accounted for by response complexity confounding (response "bias") or by practice effects. It was found that brighter subjects made their movements faster even when both distance and direction were predetermined across a very large number of trials. The correlations between MT and intelligence are consistent with most previous findings, including those of Widaman and Carlson (1989) who reported correlations between MT and intelligence (Scholastic Aptitude Test scores) that were significant and in many cases stronger than those between DT and intelligence. Theoretical explanations of D T - I Q correlations have received much more attention than have M T - I Q correlations. Several investigations have now addressed possible methodological artifacts due to apparatus design (e.g., Longstreth, 1984) and to procedures such as the number of trials and the order in which trial blocks of differing complexity are administered (Widaman & Carlson, 1989). The collective results of those stud-

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ies, considered with the present results, suggest that MT-IQ relationships may not be artifactual, and that other explanations must be examined. REFERENCES Buckhalt, J.A. (1990). Criterion-related validity of the British Ability Scales Short-Form for black and white students. Psychological Reports, 66, 1059-1066. Buckhalt, J.A., & Jensen, A.R. (1989). The British Ability Scales Speed of Information Processing Subtest: What does it measure? British Journal of Educational Psychology, 59, 100-108. Elliott, C.D. (1983). British Ability Scale Manual 2. Technical handbook. Windsor, England: NFERNelson. Era, P., Jokela, J., & Heikkinen, E. (1986). Reaction and movement times in men of different ages: A population study. Perceptual and Motor Skills, 63, I I I-130. Frearson, W., & Eysenck, H.H. (1986). Intelligence, reaction time (RT) and a new "odd-man-out" RT paradigm. Personality and Individual Differences, 6, 807-817. Hick, W.E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4, 11-26. Jensen, A.R. (1982). The chronometry of intelligence. In R.J. Sternberg (Ed.), Advances in research on intelligence (Vol. 1). Hillsdale, NJ: Erlbaum. Jensen, A.R. (1987). Individual differences in the Hick paradigm. In P.A. Vernon (Ed.), Speed of information processing and intelligence. Norwood, NJ: Ablex. Kranzler, J.H., Whang, P.A., & Jensen, A.R. (1988). Jensen's use of the Hick paradigm: Visual attention and order effects. Intelligence, 12, 379-391. Lindley, R.H., Smith, W.H., & Thomas, T.J. (1988). The relationship between speed of information processing as measured by timed paper-and-pencil tests and psychometric intelligence. Intelligence, 12, 17-25. Longstreth, L.E. (1984). Jensen's reaction time investigations of intelligence: A critique. Intelligence, 8, 139-160. Otis, A.S., & Lennon, R.T. (1982). Otis-Lennon School Ability Test. New York: Psychological Corporation. Rosenbaum, D.A. (1983). The movement precuing technique: Assumptions, applications, and extensions. In R.A. Magill (Ed.), Memory and control of action. Amsterdam: North-Holland. Schmidt, R.A. (1988). Motor control and learning: A behavioral emphasis. Champaign, IL: Human Kinetics. Smith, G.A., & Carew, M. (1987). Decision time unmasked: Individuals adopt different strategies. Australian Journal of Psychology, 39, 339-351. Telzrow, C.F. (1983). Making child neuropsychological appraisal appropriate for children: Alternative to downward extension of adult batteries. Clinical Neuropsychology, 5, 136-141. Vernon, P.A., & Moil, M. (1989, June). Nerve conduction velocity: A correlate of intelligence and speed of information processing. Paper presented of the meeting of the International Society for the Study of Individual Differences, Heidelberg, Germany. Widaman, K.F., & Carlson, J.S. (1989). Procedural effects of performance on the Hick paradigm: Bias in reaction time and movement time parameters. Intelligence, 13, 63-85.