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Nettelbeck and Lally (1976) reported the first correlations between IT and IQ. They obtained a correlation of -0.92 (p<0.01) between the Performance Scale of the WAIS and IT, and a correlation of -0.41 ( not significant) between the Verbal Scale of the WAIS and IT, using a subject sample of ten adults. Lally and Nettelbeck (1977) and Brand (1980) reported equally high correlation coefficients. These high correlations inspired a great deal of research attempting to replicate these results. In further studies, correlations ranged between -0.2 and -0.9 (Nettelbeck, Hirons &Wilson, 1984; Nettelbeck, 1982; Lally & Nettelbeck, 1980). Brand and Deary (1982) obtained correlations between -0.04 and -0.09. However, methodological flaws limit the usefulness of these studies (e.g. small sample sizes and huge ranges of IQ, and inclusion of subjects with mental retardation). Hunt (1980), reviewing the evidence, concluded that most results have been significant, but that correlations are low, (typically under -0.3). Some studies which excluded subjects with mental retardation found low or insignificant correlations (Hulme & Tumbell, 1983; Irwin, 1984).

In a review of 29 theses and published articles, Nettelbeck (1987) found a reliable relationship between IT and IQ. The best estimate of the strength of the association across the full range of IQ is -0.5 according to his results. This coefficient, however, has been corrected for restriction of variability, the raw coefficient being -0.35. Kranzler and Jensen (1989) conducted a meta-analysis of 25 studies including measures of general intelligence. Although a negative relationship between IT and IQ was always obtained, the 95% confidence interval for each correlation contained zero. Kranzler and Jensen (1989) then corrected the coefficients for the effects of sampling error, attenuation and range restriction, arriving at a best estimate of -0.54 for the correlation between IT and IQ for adults. The raw correlation coefficient ( i.e. before correction ) was -0.30, and the correlation with Performance IQ was strongest.

Most studies suggest that correlations between verbal IQ and IT are lower than between performance IQ and IT. Nettelbeck (1987) concluded that there is “confusing contradiction” with regard to the verbal IQ- IT relationship, with few studies reaching significance. The higher correlation with performance IQ could be viewed within the model of crystallized and fluid intelligence, originally proposed by Cattell (Cattell, 1963; Horn & Cattell, 1966). Fluid intelligence is a concept much like ‘g’, a stable characteristic that does not include knowledge acquisition. Deary (1993) found in a confirmatory factor analysis that fluid intelligence declines with old age, whereas crystallised intelligence seemed to be stable across the life span. The Performance scale of the WISC or WAIS has been thought to reflect primarily fluid intelligence, whereas the Verbal Scale reflects mainly crystallized intelligence (Sternberg, 1990). The finding that IT is correlated more consistently and strongly with performance IQ than verbal IQ supports Sattler’s (1982) suggestion that fluid intelligence is more akin to a biological parameter of the brain, and may decline with age. It is interesting to note that Nettelbeck and Rabbitt (1992) found a decline in IT in old age.

A correlation of -0.5 attributes 25% of the variance in IQ test scores to differences in speed of the BPM as reflected in inspection time. Most researchers regard this as a high proportion considering that IT reflects just a single low-level parameter (Anderson, 1992). The inspection time task has the advantage that it does not penalize for differences in knowledge acquisition, unlike most of the standard intelligence measures which require knowledge to varying extents. It is

thus thought to be suitable for groups of children that have deficits in particular cognitive areas that may prevent the development of some language abilities, but who nevertheless may have intact basic processing mechanisms.

Method

Procedure

The IT task was presented in the form of a computer game specially devised for children. The stimulus shown was a line-drawn alien with two antennae which were either the same or different lengths. Four variations (both antennae short, both antennae long, left antenna longer, right antenna longer) were randomly presented. The subject’s task was to make a two choice discrimination between same or different length antennae. Stimulus duration was controlled by a mask. Subjects were warned that the alien would appear for a very brief period before hiding behind a bush (the backward mask). After presentation of a stimulus the subject had to press one of two buttons on a simple purpose-made box to indicate their choices between same or different length antennae. The button for ‘Same’ was on the left and a picture of an alien with two equally long antennae was displayed on the left of the computer screen. The same arrangement applied to the button for ‘Different’ on the right. Each correct response was followed by a ‘beep’. After each button press the subject pressed the space bar to initiate the next stimulus.

Stimulus exposure duration was controlled by varying the stimulus onset asynchrony (SOA) of the stimulus and a backward mask, using a PEST procedure (Taylor & Creelman, 1967) designed to estimate 70% accuracy of responding. The PEST algorithm calculates whether a given SOA results in accuracy greater or less than 70%. If so, the SOA is increased or decreased as appropriate by a given step-size. This step-size is halved for every change of direction in the performance staircase (increasing SOA to decreasing SOA or vice versa), and in this way the PEST procedure homes in on the SOA required for the desired level of accuracy. The initial exposure duration used by the PEST procedure was 568 ms (40 VDU screen-frames), the initial step-size was 114 ms

(8 frames) and the final step-size was 14.2 msec (1 frame), which is the shortest SOA possible. The SO As of the last four turns or reversals in the performance staircase were used to calculate a subject’s IT. A trial consisted of four blocks, each of 25 stimulus presentations.

The IT programme was run on a Toshiba laptop computer, with stimuli displayed on a 12 inch VGA monochrome monitor (brightness held constant across test sessions). A response box with two differently coloured buttons was held by the subject, with right and left thumb or index finger operating the right and left buttons, respectively.

All subjects were seen individually in a quiet place at school. The subjects were first introduced to the task during a practice session with feed­ back. All subjects were taken through the IT task twice, the testing session lasting approximately half an hour. This was done to obtain optimal performance in the clinical groups, and to ameliorate possible effects of poor comprehension of instructions, attention, or motivation.