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Dissecting the parieto-frontal correlates of fluid intelligence: A comprehensive ALE meta-analysis study

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  • Santarnecchi, Emiliano
  • Emmendorfer, Alexandra
  • Pascual-Leone, Alvaro

Abstract

Recent advances in cognitive neuroscience have shown how experience-independent cognitive abilities termed fluid intelligence (Gf) can predict academic achievement, longevity and resilience to neurodegeneration. Therefore, the understanding of the neurobiological underpinnings of Gf becomes a crucial step for the implementation of cognitive rehabilitation as well as enhancement interventions. Here we present the result of a quantitative meta-analysis of available fMRI and PET literature about Gf in humans, including (i) distinct maps for verbal and visuospatial stimuli, (ii) an analysis of brain regions contributing to processing of more complex stimuli as well as (iii) a model-driven distinction of processing stages occurring during Gf-related problem solving. Results highlight the loading of Gf components over functionally defined resting-state fMRI networks, with different degrees of overlap in both hemispheres and subcortical structures. A major role for nodes of the dorsal attention network during both verbal and visuospatial abstract reasoning tasks represents the most consistent correlate of Gf, with additional contributions by regions of the anterior salience and left fronto-parietal control network. Increase in trial difficulty elicits a more pronounced engagement of the language and left fronto-parietal control networks, while inferring the rules subtending a given Gf task relies on a different anatomo-functional substrate than producing novel solutions. Current findings might allow a clearer association between Gf-related activity and brain connectivity, also providing quantitative ALE maps to be used in network-based brain stimulation and cognitive training interventions.

Suggested Citation

  • Santarnecchi, Emiliano & Emmendorfer, Alexandra & Pascual-Leone, Alvaro, 2017. "Dissecting the parieto-frontal correlates of fluid intelligence: A comprehensive ALE meta-analysis study," Intelligence, Elsevier, vol. 63(C), pages 9-28.
    • Handle: RePEc:eee:intell:v:63:y:2017:i:c:p:9-28
    DOI: 10.1016/j.intell.2017.04.008
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    2. Ünal, Zehra E. & Kartal, Gamze & Ulusoy, Serra & Ala, Aslı M. & Yilmaz, Munube & Geary, David C., 2023. "Relative contributions of g and basic domain-specific mathematics skills to complex mathematics competencies," Intelligence, Elsevier, vol. 101(C).
    3. 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).
    4. Zurrin, Riley & Wong, Samantha Tze Sum & Roes, Meighen M. & Percival, Chantal M. & Chinchani, Abhijit & Arreaza, Leo & Kusi, Mavis & Momeni, Ava & Rasheed, Maiya & Mo, Zhaoyi & Goghari, Vina M. & Wood, 2024. "Functional brain networks involved in the Raven's standard progressive matrices task and their relation to theories of fluid intelligence," Intelligence, Elsevier, vol. 103(C).
    5. Bruton, Oliver J., 2021. "Is there a “g-neuron”? Establishing a systematic link between general intelligence (g) and the von Economo neuron," Intelligence, Elsevier, vol. 86(C).
    6. Hilger, Kirsten & Spinath, Frank M. & Troche, Stefan & Schubert, Anna-Lena, 2022. "The biological basis of intelligence: Benchmark findings," Intelligence, Elsevier, vol. 93(C).
    7. Jastrzębski, Jan & Ciechanowska, Iwona & Chuderski, Adam, 2018. "The strong link between fluid intelligence and working memory cannot be explained away by strategy use," Intelligence, Elsevier, vol. 66(C), pages 44-53.
    8. Ociepka, Michał & Kałamała, Patrycja & Chuderski, Adam, 2022. "High individual alpha frequency brains run fast, but it does not make them smart," Intelligence, Elsevier, vol. 92(C).

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