Every person develops brain regions to recognize people, places and things; these regions end up in similar locations across brains. However, people who played Pokémon extensively as children also have a region that responds more to Pokémon than anything else, and its location is likely determined by the size of the Pokémon on the video game player’s screen.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
A self-supervised domain-general learning framework for human ventral stream representation
Nature Communications Open Access 25 January 2022
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Gomez, J., Barnett, M. & Grill-Spector, K. Nat. Hum. Behav. https://doi.org/10.1038/s41562-019-0592-8 (2019).
Dehaene-Lambertz, G., Monzalvo, K. & Dehaene, S. PLoS Biol. 16, e2004103 (2018).
Srihasam, K., Mandeville, J. B., Morocz, I. A., Sullivan, K. J. & Livingstone, M. S. Neuron 73, 608–619 (2012).
Konkle, T. & Oliva, A. Neuron 74, 1114–1124 (2012).
Hasson, U., Levy, I., Behrmann, M., Hendler, T. & Malach, R. Neuron 34, 479–490 (2002).
Malach, R., Levy, I. & Hasson, U. Trends Cogn. Sci. 6, 176–184 (2002).
Srihasam, K., Vincent, J. L. & Livingstone, M. S. Nat. Neurosci. 17, 1776–1783 (2014).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Rights and permissions
About this article
Cite this article
Janini, D., Konkle, T. A Pokémon-sized window into the human brain. Nat Hum Behav 3, 552–553 (2019). https://doi.org/10.1038/s41562-019-0594-6
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41562-019-0594-6
This article is cited by
-
A self-supervised domain-general learning framework for human ventral stream representation
Nature Communications (2022)