Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-29T00:24:15.946Z Has data issue: false hasContentIssue false

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 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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