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Evolution, brain size, and variations in intelligence

Published online by Cambridge University Press:  15 August 2017

Louis D. Matzel
Affiliation:
Department of Psychology, Program in Behavioral and Systems Neuroscience, Rutgers University, Piscataway, NJ [email protected]@rutgers.eduhttps://www.researchgate.net/profile/Louis_Matzelhttps://www.researchgate.net/profile/Bruno_Sauce
Bruno Sauce
Affiliation:
Department of Psychology, Program in Behavioral and Systems Neuroscience, Rutgers University, Piscataway, NJ [email protected]@rutgers.eduhttps://www.researchgate.net/profile/Louis_Matzelhttps://www.researchgate.net/profile/Bruno_Sauce

Abstract

Across taxonomic subfamilies, variations in intelligence (G) are sometimes related to brain size. However, within species, brain size plays a smaller role in explaining variations in general intelligence (g), and the cause-and-effect relationship may be opposite to what appears intuitive. Instead, individual differences in intelligence may reflect variations in domain-general processes that are only superficially related to brain size.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2017 

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References

Aiello, L. C. & Dean, M. C. (1990) An introduction to human evolutionary anatomy. Academic Press.Google Scholar
Banks, W. E., d'Errico, F., Peterson, A. T., Kageyama, M., Sima, A. & Sanchez-Goni, M. F. (2008) Neanderthal extinction by competitive exclusion. PLoS One 3(12):e3972. doi: 10.1371/journal.pone.0003972.Google Scholar
Clayton, N. S. (2001) Hippocampal growth and maintenance depend on food-caching experience in juvenile mountain chickadees (Poecile gambeli). Behavioral Neuroscience. 115(3):614–25.Google Scholar
Diekamp, B., Kalt, T. & Gunturkun, O. (2002) Working memory neurons in pigeons. Journal of Neuroscience 22(4):RC210.Google Scholar
Gilpin, W., Feldman, M. W. & Aoki, K. (2016) An ecocultural model predicts Neanderthal extinction through competition with modern humans. Proceedings of the National Academy of Sciences USA 113(8):2134–39. doi: 10.1073/pnas.1524861113.CrossRefGoogle ScholarPubMed
Gunturkun, O. (2012) The convergent evolution of neural substrates for cognition. Psychological Research 76(2):212–19. doi: 10.1007/s00426-011-0377-9.CrossRefGoogle ScholarPubMed
Gunturkun, O. & Kroner, S. (1999) A polysensory pathway to the forebrain of the pigeon: The ascending projections of the nucleus dorsolateralis posterior thalami (DLP). European Journal of Morphology 37(2–3):185–89.CrossRefGoogle Scholar
Karakuyu, D., Herold, C., Gunturkun, O. & Diekamp, B. (2007) Differential increase of extracellular dopamine and serotonin in the “prefrontal cortex” and striatum of pigeons during working memory. European Journal of Neuroscience 26(8):2293–302.CrossRefGoogle ScholarPubMed
Karten, H. J. (2015) Vertebrate brains and evolutionary connectomics: On the origins of the mammalian “neocortex”. Philosophical Transactions of the Royal Society of London B: Biological Sciences 370(1684). doi: 10.1098/rstb.2015.0060.Google Scholar
Kolata, S., Light, K., Wass, C. D., Colas-Zelin, D., Roy, D. & Matzel, L. D. (2010) A dopaminergic gene cluster in the prefrontal cortex predicts performance indicative of general intelligence in genetically heterogeneous mice. PLoS One 5(11):e14036.Google Scholar
Light, K. R., Grossman, Y., Kolata, S., Wass, C. D. & Matzel, L. D. (2011) General learning ability regulates exploration through its influence on rate of habituation. Behavioral Brain Research 223:297309.Google Scholar
Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S. & Frith, C. D. (2000) Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences USA 97(8):4398–403.CrossRefGoogle ScholarPubMed
Matzel, L. D., Sauce-Silva, B. & Wass, C. (2013) The architecture of intelligence: Converging evidence from studies of humans and animals. Current Directions in Psychological Science 22:342–48.Google Scholar
Matzel, L. D., Townsend, D. A., Grossman, H., Han, Y. R., Hale, G., Zappulla, M., Light, K. & Kolata, S. (2006) Exploration in outbred mice covaries with general learning abilities irrespective of stress reactivity, emotionality, and physical attributes. Neurobiology of Learning and Memory 86:228–40.Google Scholar
McDaniel, M. A. (2005) Big-brained people are smarter: A meta-analysis of the relationship between in vivo brain volume and intelligence. Intelligence 33:337–46.CrossRefGoogle Scholar
McNab, F., Varrone, A., Farde, L., Jucaite, A., Bystritsky, P., Forssberg, H. & Klingberg, T. (2009) Changes in cortical dopamine D1 receptor binding associated with cognitive training. Science 323(5915):800802.CrossRefGoogle ScholarPubMed
Miller, E. K. & Cohen, J. D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience 24:167202. doi: 10.1146/annurev.neuro.24.1.167.Google Scholar
Rosenzweig, M. R. & Bennett, E. L. (1996) Psychobiology of plasticity: Effects of training and experience on brain and behavior. Behavioral Brain Research 78(1):5765.Google Scholar
Seashore, C. E. (1923) Introduction to psychology. Macmillan.Google Scholar
van Leeuwen, M., Peper, J. S. & van den Berg, S. M. (2009) A genetic analysis of brain volumes and IQ in children. Intelligence 37:417–24.CrossRefGoogle Scholar
van Praag, H., Kempermann, G. & Gage, F. H. (2000) Neural consequences of environmental enrichment. Nature Reviews Neuroscience 1(3):191–98.Google Scholar
van Schaik, C. P., Isler, K. & Burkart, J. M. (2012) Explaining brain size variation: From social to cultural brain. Trends in Cognitive Sciences 16:277–84.CrossRefGoogle ScholarPubMed
Van Valen, L. (1974) Brain size and intelligence in man. American Journal of Physical Anthropology 40:417–24.Google Scholar
Veit, L., Hartmann, K. & Nieder, A. (2014) Neuronal correlates of visual working memory in the corvid endbrain. Journal of Neuroscience 34(23):7778–86. doi: 10.1523/JNEUROSCI.0612-14.2014.CrossRefGoogle ScholarPubMed
Wass, C., Pizzo, A., Sauce, B., Kawasumi, Y., Sturzoiu, T., Ree, F., Otto, T. & Matzel, L. D. (2013) Dopamine D1 sensitivity in the prefrontal cortex predicts general cognitive abilities and is modulated by working memory training. Learning & Memory 20(11):617–27.CrossRefGoogle ScholarPubMed
Wickett, J. C., Verbnon, P. A. & Lee, D. H. (2000) Relationships between factors of intelligence and brain volume. Personality and Individual Differences 29:1095–122.CrossRefGoogle Scholar
Will, B., Galani, R., Kelche, C. & Rosenzweig, M. R. (2004) Recovery from brain injury in animals: Relative efficacy of environmental enrichment, physical exercise or formal training (1990–2002). Progress in Neurobiology 72(3):167–82. doi: 10.1016/j.pneurobio.2004.03.001.CrossRefGoogle ScholarPubMed