Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-30T21:17:16.591Z Has data issue: false hasContentIssue false
  • English
  • Français

Cognitive representations and the predictive brain depend heavily on the environment

Published online by Cambridge University Press:  19 June 2020

Klaus Fiedler Open the ORCID record for Klaus Fiedler [Opens in a new window]
Klaus Fiedler*
Affiliation:
Psychology Department, Heidelberg University, 69117 Heidelberg, Germany. [email protected] https://www.psychologie.uni-heidelberg.de/ae/crisp/staff/fiedler.html
Get access Rights & Permissions [Opens in a new window]

Abstract

In their scholarly target article, Gilead et al. explain how abstract mental representations and the predictive brain enable prospection and time-traveling. However, their exclusive focus on intrapsychic capacities misses an important point, namely, the degree to which mind and brain are tuned by the environment. This neglected aspect of adaptive cognition is discussed and illustrated from a cognitive-ecological perspective.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 43 , 2020 , e132
Check for updates
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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

Dehaene, S. (2003) The neural basis of the Weber–Fechner law: A logarithmic mental number line. Trends in Cognitive Sciences 7(4):145–47.CrossRefGoogle ScholarPubMed
Fiedler, K. (2014) From intrapsychic to ecological theories in social psychology: Outlines of a functional theory approach. European Journal of Social Psychology 44(7):657–70.CrossRefGoogle Scholar
Fiedler, K., Bluemke, M., Freytag, P., Unkelbach, C. & Koch, S. (2008) A semiotic approach to understanding the role of communication in stereotyping. In: Stereotype dynamics: Language-based approaches to the formation, maintenance, and transformation of stereotypes, ed. Kashima, Y., Fiedler, K., Freytag, P., pp. 95–116. Erlbaum.Google Scholar
Fiedler, K., Jung, J., Wänke, M., Alexopoulos, T. & de Molière, L. (2015) Toward a deeper understanding of the ecological origins of distance construal. Journal of Experimental Social Psychology 57:78–86.CrossRefGoogle Scholar
Konovalova, E. & Le Mens, G. (2020) An information sampling explanation for the in-group heterogeneity effect. Psychological Review 127(1):47–73. https://doi.org/10.1037/rev0000160.CrossRefGoogle ScholarPubMed
Liberman, N. & Trope, Y. (2014) Traversing psychological distance. Trends in Cognitive Sciences 18(7):364–69. Available at: http://doi.org/10.1016/j.tics.2014.03.001.CrossRefGoogle Scholar
Linville, P. W., Fischer, G. W. & Yoon, C. (1996) Perceived covariation among the features of ingroup and outgroup members: The outgroup covariation effect. Journal of Personality and Social Psychology 70(3):421–36.CrossRefGoogle Scholar
Parducci, A. (1965) Category judgment: A range-frequency model. Psychological Review 72(6):407–418.CrossRefGoogle ScholarPubMed
Pleskac, T. J. & Hertwig, R. (2014) Ecologically rational choice and the structure of the environment. Journal of Experimental Psychology: General 143(5):2000–2019.CrossRefGoogle ScholarPubMed
Proctor, R. W. & Cho, Y. S. (2006) Polarity correspondence: A general principle for performance of speeded binary classification tasks. Psychological Bulletin 132(3):416–42.CrossRefGoogle ScholarPubMed
Trope, Y. & Liberman, N. (2010) Construal-level theory of psychological distance. Psychological Review 117(2):440–63.CrossRefGoogle ScholarPubMed