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Network connectivity correlates of variability in fluid intelligence performance

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  • Santarnecchi, Emiliano
  • Emmendorfer, Alexandra
  • Tadayon, Sayedhedayatollah
  • Rossi, Simone
  • Rossi, Alessandro
  • Pascual-Leone, Alvaro

Abstract

reasoning requires a pattern of spatial and temporal coordination among regions across the entire brain. Recent evidence suggests a very high similarity between spontaneous and evoked brain activity in humans, implying that a fine characterization of brain dynamics recorded during resting-state might be informative for the understanding of evoked behavior. In a recent work, we listed and detailed the sets of regions showing robust co-activation during the solution of fluid intelligence (gf) tasks, decomposing such meta-analytic maps in stimulus- and reasoning stage-specific sub-maps. However, while anatomical overlap with well-known resting-state fMRI networks (RSNs) has been documented, we here propose a quantitative validation of such findings via functional connectivity analysis in a sample of healthy participants. Results highlight a striking degree of similarity between the connectivity profile of the gf network and that of the dorsal attention network, with additional overlap with the left and right fronto-parietal control networks. Interestingly, a strong negative correlation with structures of the default mode network (DMN) was also identified. Results of regression models built on two independent fMRI datasets confirmed the negative correlation between gf regions and medial prefrontal structures of the DMN as a significant predictor of individual gf scores. These might suggest a framework to interpret previously reported aging-related decline in both gf and the correlation between “task-positive” networks and DMN, possibly pointing to a common neurophysiological substrate.

Suggested Citation

  • Santarnecchi, Emiliano & Emmendorfer, Alexandra & Tadayon, Sayedhedayatollah & Rossi, Simone & Rossi, Alessandro & Pascual-Leone, Alvaro, 2017. "Network connectivity correlates of variability in fluid intelligence performance," Intelligence, Elsevier, vol. 65(C), pages 35-47.
  • Handle: RePEc:eee:intell:v:65:y:2017:i:c:p:35-47
    DOI: 10.1016/j.intell.2017.10.002
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    References listed on IDEAS

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    1. Ian Deary, 2008. "Why do intelligent people live longer?," Nature, Nature, vol. 456(7219), pages 175-176, November.
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    Cited by:

    1. Fraenz, Christoph & Schlüter, Caroline & Friedrich, Patrick & Jung, Rex E. & Güntürkün, Onur & Genç, Erhan, 2021. "Interindividual differences in matrix reasoning are linked to functional connectivity between brain regions nominated by Parieto-Frontal Integration Theory," Intelligence, Elsevier, vol. 87(C).
    2. Koch, Marco & Becker, Nicolas & Spinath, Frank M. & Greiff, Samuel, 2021. "Assessing intelligence without intelligence tests. Future perspectives," Intelligence, Elsevier, vol. 89(C).
    3. Fernandes, Heitor B.F. & Peñaherrera-Aguirre, Mateo & Woodley of Menie, Michael A. & Figueredo, Aurelio José, 2020. "Macroevolutionary patterns and selection modes for general intelligence (G) and for commonly used neuroanatomical volume measures in primates," Intelligence, Elsevier, vol. 80(C).

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