A dynamical model of general intelligence: The positive manifold of intelligence by mutualism.

Abstract

Scores on cognitive tasks used in intelligence tests correlate positively with each other, that is, they display a positive manifold of correlations. The positive manifold is often explained by positing a dominant latent variable, the g factor, associated with a single quantitative cognitive or biological process or capacity. In this article, a new explanation of the positive manifold based on a dynamical model is proposed, in which reciprocal causation or mutualism plays a central role. It is shown that the positive manifold emerges purely by positive beneficial interactions between cognitive processes during development. A single underlying g factor plays no role in the model. The model offers explanations of important findings in intelligence research, such as the hierarchical factor structure of intelligence, the low predictability of intelligence from early childhood performance, the integration/differentiation effect, the increase in heritability of g, and the Jensen effect, and is consistent with current explanations of the Flynn effect.

The evolution of primate general and cultural intelligence

“…Here, we show that primate g S correlates with absolute forebrain volume measures and two of the three deployed relative measures, a result mirrored by analyses of laboratory-learning performance [42,66]. Similarly, within humans, g shows a modest correlation with total brain and grey matter volumes [9,11,67,68]. Our data, combined with the multiple studies linking various cognitive measures and brain volume across species [55], and recent findings demonstrating survival pay-offs to brain enlargement [37,69,70], suggests the 'volumetric stance' is warranted: brain component volumes are related to functionally relevant cognitive capacities.…”

“…In common with many human scientists and neuroscientists [1,9,11,65], we note that the mechanisms behind the brain volume-cognition relationship are unknown and require study. It is important to establish if, how and why characteristics such as brain cell composition, connectivity, numerosity and diversity are linked to brain volume, why these characteristics vary across brain regions, how this variation is linked to cognitive function and whether common links between structure and function are found across taxa [65].…”

“…Regarding the mechanisms underlying g S , the observed correlations with brain volume suggest that differences in brain structure underlie g S , but g S could additionally plausibly be a product of positive feedback from niche construction [11,78,79]. For example, individuals from species with a slight g S advantage may be able to inhabit more challenging environments, thus exposing themselves to circumstances favouring the expression of behavioural flexibility and to selection for further increases in flexibility.…”

Statistical models as cognitive models of individual differences in reasoning

“…Returning to the older example introduced earlier of g (Spearman 1904), although the scores from a variety of tasks are positively correlated, this need not imply that the correlations are generated by a single cognitive (or social, or genetic, or whatever) process. The dynamical model proposed by van der Mass et al (2006) shows that correlations can emerge due to mutually beneficial interactions between quite distinct processes.…”

Effects of cognitive training on the structure of intelligence

“…One such class of models involve feedback loops between cognitive processes (e.g., Kovacs & Conway, 2016;Van der Maas et al, 2006). Although these models have their own limitations (see, e.g., Gignac, 2014;Oberauer, 2016;Protzko, 2015), they come with the same magnitude of causal assumptions that may be individually tested.…”