The cortical thickness of the area PF of the left inferior parietal cortex mediates technical-reasoning skills

Abstract

Most recent research highlights how a specific form of causal understanding, namely technical reasoning, may support the increasing complexity of tools and techniques developed by humans over generations, i.e., the cumulative technological culture (CTC). Thus, investigating the neurocognitive foundations of technical reasoning is essential to comprehend the emergence of CTC in our lineage. Whereas functional neuroimaging evidence started to highlight the critical role of the area PF of the left inferior parietal cortex (IPC) in technical reasoning, no studies explored the links between the structural characteristics of such a brain region and technical reasoning skills. Therefore, in this study, we assessed participants' technical-reasoning performance by using two ad-hoc psycho-technical tests; then, we extracted from participants' 3 T T1-weighted magnetic-resonance brain images the cortical thickness (i.e., a volume-related measure which is associated with cognitive performance as reflecting the size, density, and arrangement of cells in a brain region) of all the IPC regions for both hemispheres. We found that the cortical thickness of the left area PF predicts participants' technical-reasoning performance. Crucially, we reported no correlations between technical reasoning and the other IPC regions, possibly suggesting the specificity of the left area PF in generating technical knowledge. We discuss these findings from an evolutionary perspective, by speculating about how the evolution of parietal lobes may have supported the emergence of technical reasoning in our lineage.

Figure 1

The area PF of the left inferior parietal cortex and technical-reasoning skills. (A) The left and right inferior parietal cortex (both highlighted in light orange), including the area PF (highlighted in orange), according to the 2016 Glasser et al.’s brain atlas. The images were devised by generating a volumetric mesh with SurfIce (https://www.nitrc.org/projects/surfice). (B) Pearson’s correlation between the technical reasoning performance index (TRPI) and the normalized cortical thickness of the area PF of the left IPC (R = 0.34, p < 0.001). (C) GLM mediation analysis, which included Physical Understanding as the dependent variable, Visuospatial Imagery as the endogenous modulator and the Left PF Cortical Thickness as the independent predictor (β = 0.2; p < 0.001). (A–C) *p < 0.05; **p < 0.01.

Figure 2

Psycho-technical assessment. (A) One of the 24 items we used to evaluate participants’ understanding of physical properties. In the example depicted, participants were asked to select which of the four nails were hammered more easily. (B) One of the 38 items we used to evaluate participants’ visuospatial-imagery skills. Participants were asked to identify which of the four 3D figures showed on the right corresponded to the 2D pattern on the left. Both the subtests were extracted from the NV7 battery.