Fluid intelligence is supported by the multiple-demand system not the language system. (March 2018)

• Record Type: Journal Article
• Authors: Woolgar, Alexandra; Duncan, John; Manes, Facundo; Fedorenko, Evelina
• Is Part Of: Nature human behaviour. Volume 2:Number 3(2018)
• Page Start: 200
• Page End: 204
• Publication Date: 2018-03
• Subjects: Human behavior -- Periodicals; Psychology -- Periodicals; Sociology -- Periodicals; 300
• DOI: 10.1038/s41562-017-0282-3
• Languages: English
• ISSNs: 2397-3374

Abstract

Abstract A set of frontoparietal brain regions—the multiple-demand (MD) system1, 2 —has been linked to fluid intelligence in brain imaging3, 4 and in studies of patients with brain damage5–7 . For example, the amount of damage to frontal or parietal, but not temporal, cortices predicts fluid intelligence deficit5 . However, frontal and parietal lobes are structurally8 and functionally9, 10 heterogeneous. They contain domain-general regions that respond across diverse tasks11, 12, but also specialized regions that respond selectively during language processing13 . Since language may be critical for complex thought14–24 (compare with refs25, 26 ), intelligence loss following damage to the frontoparietal cortex could have important contributions from damage to language-selective regions. To evaluate the relative contributions of MD versus language-selective regions, we employed large functional magnetic resonance imaging datasets to construct probabilistic maps of the two systems. We used these maps to weigh the volume of lesion (in each of 80 patients) falling within each system. MD-weighted, but not language-weighted, lesion volumes predicted fluid intelligence deficit (with the opposite pattern observed for verbal fluency), indicating that fluid intelligence is specifically tied to the MD system, and undermining claims that language is at the core of complex thought. Using fMRI data from healthy controls, the authors construct probabilistic maps of the multiple-demand and language-selective regions in the brain to classify patient lesions. They find that only multiple-demand-weighted lesion volumes predict deficits in fluid intelligence.