Early psychologists, including Galton, Cattell, and Spearman, proposed that intelligence and simple sensory discriminations are constrained by common neural processes, predicting a close link between them []. However, strong supporting evidence for this hypothesis remains elusive. Although people with higher intelligence quotients (IQs) are quicker at processing sensory stimuli [], these broadly replicated findings explain a relatively modest proportion of variance in IQ. Processing speed alone is, arguably, a poor match for the information processing demands on the neural system. Our brains operate on overwhelming amounts of information [], and thus their efficiency is fundamentally constrained by an ability to suppress irrelevant information []. Here, we show that individual variability in a simple visual discrimination task that reflects both processing speed and perceptual suppression [] strongly correlates with IQ. High-IQ individuals, although quick at perceiving small moving objects, exhibit disproportionately large impairments in perceiving motion as stimulus size increases. These findings link intelligence with low-level sensory suppression of large moving patterns—background-like stimuli that are ecologically less relevant []. We conjecture that the ability to suppress irrelevant and rapidly process relevant information fundamentally constrains both sensory discriminations and intelligence, providing an information-processing basis for the observed link.

Segregation of object and background motion in visual area MT: effects of microstimulation on eye movements.

Results

31 Axelrod B.N. Validity of the Wechsler abbreviated scale of intelligence and other very short forms of estimating intellectual functioning. 32 Psychological Corporation

WAIS-IV Technical and Interpretive Manual. −9; 95% confidence interval [CI] = [0.55, 0.82]). The observed relationship between SI and IQ is considerably stronger than those reported for other sensory measures [ 2 Jensen A.R. Clocking the Mind: Mental Chronometry and Individual Differences. 3 Deary I.J. Intelligence. 4 Sheppard L.D.

Vernon P.A. Intelligence and speed of information-processing: A review of 50 years of research. 32 Psychological Corporation

WAIS-IV Technical and Interpretive Manual. Figure 2 The Relationship between Spatial Suppression and IQ Show full caption (A and B) The relationship between SI and IQ in two studies. (C) Results of a Monte Carlo simulation showing the distribution of SI-IQ correlations for 9,999 random samples (with n = 15) from the data shown in (B). The triangle indicates median correlation. (D) Combined data from two studies with suppression strength estimated from slope, b, derived from exponential fits (a × ebx) to individual subject’s data. We first tested the hypothesized link between perceptual suppression and IQ in subjects who completed a short-form Wechsler Adult Intelligence Scale III (WAIS-III) []. The results (study 1) revealed a significant correlation between IQ and SI ( Figure 2 A; r = 0.64; p = 0.02). To test the robustness and replicability of this finding, in study 2 we introduced several methodological and stimulus changes ( Supplemental Experimental Procedures ), including the administration of the full-length WAIS-IV []. Again, we found that SI strongly correlates with IQ ( Figure 2 B; r = 0.71; p = 10; 95% confidence interval [CI] = [0.55, 0.82]). The observed relationship between SI and IQ is considerably stronger than those reported for other sensory measures [] and approaches in magnitude correlations between full-scale IQ and WAIS-IV primary indexes (ranging between 0.72 and 0.86) [].

To test the robustness of the SI-IQ link, we carried out a Monte Carlo simulation using study 2 data. We generated 9,999 data sets, each consisting of 15 subjects randomly sampled without replacement, and computed the SI-IQ correlation for each data set. The resultant correlation distribution ( Figure 2 C) is positively skewed with median r = 0.72 (95% CI = [0.43, 0.89]). Notably, nearly all (93.3%) of the obtained correlations were statistically significant, indicating that a relatively small sample size is sufficient to reveal the SI-IQ link.

bx), where the scale parameter, a, determines the lower asymptote, while the slope, b, is an estimate of suppression strength that is not explicitly linked to specific stimulus sizes (−10; 95% CI = [0.53, 0.80]). The two studies presented here differ in methods and stimulus parameters ( Supplemental Experimental Procedures ), yet both reveal strong SI-IQ links. Stimulus size differences ( Figure 1 C), however, preclude a direct comparison of SI values. To circumvent this problem, we fitted each subject’s data with a simple exponential model (a × e), where the scale parameter, a, determines the lower asymptote, while the slope, b, is an estimate of suppression strength that is not explicitly linked to specific stimulus sizes ( Figure 1 C). Importantly, for both data sets, the exponential slope and SI are highly correlated (r > 0.996). The combined distribution of slope estimates again reveals that as the stimulus size increases, high IQ is linked with increasing motion perception impairments ( Figure 2 D; r = 0.68; p = 10; 95% CI = [0.53, 0.80]).

33 Crawford J.R.

Deary I.J.

Allan K.M.

Gustafsson J. Evaluating competing models of the relationship between inspection time and psychometric Intelligence. −3 > p > 10−8). For the purposes of magnitude comparison, we note that these relationships are in the same range as WAIS-IV interindex correlations (ranging between 0.45 and 0.64) [ 32 Psychological Corporation

WAIS-IV Technical and Interpretive Manual. −8), a WAIS-IV measure of general intellectual ability. Overall, we show that SI is strongly linked with a broad range of psychometric indices of intelligence. Next, we examined the relationship between SI and WAIS-IV index scores (study 2). Sensory measures tend to be better predictors of the performance aspects of IQ, often exhibiting weak or no relationship with verbal intelligence []. In contrast, SI is a good predictor of broad intellectual ability: correlations between SI and the Verbal Comprehension, Perceptual Reasoning, Working Memory, and Processing Speed Indices were r = 0.69, 0.47, 0.49, and 0.50, respectively (10> p > 10). For the purposes of magnitude comparison, we note that these relationships are in the same range as WAIS-IV interindex correlations (ranging between 0.45 and 0.64) []. Additionally, SI strongly correlates with the General Ability Index (r = 0.69; p = 10), a WAIS-IV measure of general intellectual ability. Overall, we show that SI is strongly linked with a broad range of psychometric indices of intelligence.

22 Tadin D.

Lappin J.S.

Gilroy L.A.

Blake R. Perceptual consequences of centre-surround antagonism in visual motion processing. 3 Deary I.J. Intelligence. 34 Duckworth A.L.

Quinn P.D.

Lynam D.R.

Loeber R.

Stouthamer-Loeber M. Role of test motivation in intelligence testing. −9) and large-stimulus (−5) thresholds. These results were further supported by a multiple linear regression analysis with thresholds for small and large stimuli as predictors of IQ scores (R2 = 0.52, F 2,50 = 26.7, p = 10−8, variance inflation factor < 1.7). High IQ was associated with lower thresholds for small moving stimuli (β = −0.92, t 50 = −7.2, p = 10−9) and higher thresholds for large moving stimuli (β = 0.72, t 50 = 5.6, p = 10−6). We found analogous results for the four WAIS-IV index scores (all R2 > 0.23, F 2,50 > 7.55, p < 0.001), where high IQ was predicted by lower small-stimulus thresholds (−0.89 < β < −0.58; all p < 0.006) and higher large-stimulus thresholds (0.68 > β > 0.41; all p < 0.011). In conclusion, rather than being linked with an overall speeding of motion perception, we found that high IQ is associated with increasingly selective low-level sensory processing that favors smaller moving stimuli relative to large. Figure 3 The Relationship between Motion Discrimination Thresholds and IQ Show full caption (A and B) The relationship between IQ and duration thresholds for large (♢) and small (■) moving stimuli. Data are represented as mean ± SEM. (C) The relationship between IQ (study 2) and standardized residuals after regressing thresholds for the small stimulus on large-stimulus thresholds. (D) Same as (C), except that thresholds for the large stimulus were regressed on small-stimulus thresholds. What drives the SI-IQ relationship? SI indexes the difference between one’s ability to perceive small and large moving stimuli ( Figure 1 C). Thus, the observed relationship indicates an interactive link between motion perception and IQ. Indeed, correlations between IQ and subjects’ ability to perceive motion of small and large stimuli were significantly different ( Figures 3 A and 3B ; both z > 2.0, p < 0.04). As IQ rises, SI increases because of (1) faster processing of small stimuli coupled with (2) a diminishing ability to perceive large moving stimuli. Neither effect alone was sufficient to account for the observed SI-IQ link; only small-stimulus thresholds in study 2 significantly correlated with IQ (r = −0.46, p = 0.0005), indicating that performance with large stimuli is a key component of the SI-IQ link. Thus, we considered factors that may affect the correlation between IQ and large-stimulus thresholds. The ability to perceive large moving stimuli is determined both by spatial suppression [] and by nonspecific factors (e.g., general motion sensitivity and motivation). Such general factors tend to be positively correlated with IQ [], but they should affect motion perception regardless of stimulus size, allowing us to statistically control for nonspecific effects. First, to control for the shared variance between subjects’ performance with small and large stimuli, we computed semipartial correlations between stimulus thresholds and IQ (study 2). The results revealed significant but opposite correlations between IQ and small-stimulus ( Figure 3 C; sr = −0.71, p = 10) and large-stimulus ( Figure 3 D; sr = 0.55, p = 10) thresholds. These results were further supported by a multiple linear regression analysis with thresholds for small and large stimuli as predictors of IQ scores (R= 0.52, F= 26.7, p = 10, variance inflation factor < 1.7). High IQ was associated with lower thresholds for small moving stimuli (β = −0.92, t= −7.2, p = 10) and higher thresholds for large moving stimuli (β = 0.72, t= 5.6, p = 10). We found analogous results for the four WAIS-IV index scores (all R> 0.23, F> 7.55, p < 0.001), where high IQ was predicted by lower small-stimulus thresholds (−0.89 < β < −0.58; all p < 0.006) and higher large-stimulus thresholds (0.68 > β > 0.41; all p < 0.011). In conclusion, rather than being linked with an overall speeding of motion perception, we found that high IQ is associated with increasingly selective low-level sensory processing that favors smaller moving stimuli relative to large.