Open Access 11.08.2017 | Original Article

# The corpus callosum as anatomical marker of intelligence? A critical examination in a large-scale developmental study

Erschienen in: Brain Structure and Function | Ausgabe 1/2018

## Abstract

## Introduction

## Methods

### Participants

### Intelligence assessment

^{2}= 0.37 for the prediction of v-IQ, R

^{2}= 0.35 for the prediction of p-IQ, and R

^{2}= 0.31 for the prediction of fs-IQ. At follow-up testing (n = 239), it was R

^{2}= 0.26 for v-IQ, R

^{2}= 0.42 for p-IQ, and R

^{2}= 0.31 for the prediction of fs-IQ. Across all analyses both the linear (all regression weights positive) and quadratic predictors (all negative regression weights) were significant (all p < 0.05), except for the v-RS analysis at follow-up testing in which the quadratic prediction was not significant (p = 0.41). This overall pattern of association underlines the expected non-equivalence of RS and deviation IQ in a developmental sample (Neisser 1997). Thus, in accordance with the objectives of the present study we focused on the raw test scores for further analyses.

_{Age}= 0.049; t

_{731}= 47.3, p < 0.0001; p-RS: β

_{Age}= 0.061; t

_{731}= 37.8, p < 0.0001) and Age-squared (v-RS: β

_{Age squared}= −0.0025; t

_{731}= −14.4, p < 0.0001; p-RS: β

_{Age squared}= −0.0036; t

_{731}= −13.8, p < 0.0001) contributed significantly to the prediction, together describing the monotonous increase of level of performance which flattens towards young adulthood (see Fig. 1).

### MRI acquisition

^{3}, a field view of 240 × 240 mm

^{2}and a 192 × 192 scan matrix. The data acquisition for the MOBA participants was done using a parallel imaging technique (iPAT, GRAPPA factor 2) acquiring multiple (between 2 and 4) T1 volumes in a short scan time (4 min and 18 s per volume). Of the final 734 datasets 542 datasets were acquired in Oslo and 192 in Trondheim. Raw image quality was assessed based on visual inspection and performed by two experienced examiners (D.A.R., S.K.K.) and the best dataset was used for the analysis.

### Measurement of callosal thickness

### Measurement of brain compartment volume

### Statistical analysis

^{2}) as relative measure.

^{2}= 0.024 and f

^{2}= 0.034, for 0.80 and 0.95 test power, respectively (only marginally differing from step 1 to step 3, with 5–9 predictors, respectively) which is equivalent to an explained variance of ω

^{2}= 0.023–0.033. That is, population effects larger than 2.3 or 3.3% can be excluded for non-significant associations.

## Results

^{2}= 0.07 (β

_{p-RS}= 1.00; t

_{728}= 5.01, p < 0.0001, see Fig. 4). Comparably, for v-RS the strongest association was also found in segment 57 (β

_{v-RS}= 1.01; t

_{728}= 5.03, p < 0.0001; ω

^{2}= 0.07, see Fig. 4). The v-RS analysis additionally revealed a negative association in the genu of the corpus callosum, that is, in segment 13 (β

_{v-RS}= −0.55; t

_{728}= −3.14, p = 0.0018, ω

^{2}= 0.03, see Fig. 2). In addition to the main effect, both analyses also revealed a significant interaction of test score and Sex indicating differences in the slope of the association between the sexes. In the p-RS analysis the interaction was found in extended areas in the genu as well as in the truncus region with the maximum effect being located in segment 9 (β

_{p-RS*Sex}= 1.44; t

_{728}= 4.12, p < 0.0001, ω

^{2}= 0.05). Across all significant segments, the interaction was driven by a more positive slope in female than in male participants (see Fig. 4d). In the v-RS analysis the area of significant interactions was restricted to the genu region with the maximum being located in segment 12 (β

_{v-RS*Sex}= 1.09; t

_{728}= 4.17, p < 0.0001, ω

^{2}= 0.05). Also here the interaction was driven by a more positive slope in female than male participants (see Fig. 4b).

_{v-RS}= 1.13; t

_{727}= 5.54, p < 0.0001; ω

^{2}= 0.09, see Fig. 5) and in segment 58 for the p-RS analysis (for p-RS: β

_{p-RS}= 1.07; t

_{727}= 5.36, p < 0.0001; ω

^{2}= 0.08). However, including TIV in the model, the interaction of Sex and Test Score was no longer significant (for v-RS all |β

_{v-RS*Sex}| < 0.51; all |t

_{727}| < 1.66; and for p-RS all |β

_{p-RS*Sex}| < 0.69; all |t

_{727}| < 2.08; all non-significant using FDR correction).

_{v-RS}| < 1.04, all |t

_{724}| < 2.41; for p-RS all |β

_{p-RS}| < 0.76, all |t

_{724}| < 2.00; all non-significant using FDR correction) for both p-RS and v-RS analyses. In addition, the interaction of test score and Sex did not reach significance (for v-RS all |β

_{v-RS*Sex}| < 0.47, all |t

_{724}| < 1.53; and for p-RS all |β

_{p-RS*Sex}| < 0.70, all |t

_{724}| < 2.11). In neither of the two analyses a significant interaction of Test Score and Age was found (for v-RS all |β

_{v-RS*Age}| < 0.20, all |t

_{724}| < 2.72; and for p-RS all |β

_{p-RS*Age}| < 0.22, all |t

_{724}| < 2.52; all non-significant using FDR correction, see Fig. 6), that is, the association of intelligence and callosal thickness was not significantly modulated by Age.