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WIREs Cogn Sci

Socioeconomic status and cognitive functioning: moving from correlation to causation

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A growing body of cognitive research uses sophisticated behavioral and neuroimaging measurements to demonstrate associations between family socioeconomic status (SES) and specific cognitive functions. We argue for the value in these kinds of studies of increased sophistication in the measurement and modeling of SES. With regard to measurement, SES combines several components, each of which represents distinct resources that might benefit children's cognitive development in different ways. Policy implications of studies using omnibus SES composites are problematic because there are no ‘treatments’ for enhancing overall SES, although policies abound for enhancing specific components of SES such as family income. Past literature offers guidance regarding how best to measure each of the SES components. With regard to modeling, we point out that the manipulability of economic, educational, and occupational components of SES varies, which provides opportunities for generating experimental or quasi‐experimental variation in some components but not others. Evidence on the causal connections between SES components and child outcomes is summarized. Both experimental and quasi‐experimental studies involving manipulation of family income have demonstrated consistent associations with a number of cognitive measures. Quasi‐experimental increases in maternal education have also shown associations with child achievement. We end with a discussion of useful directions in SES‐related cognitive research. WIREs Cogn Sci 2012, 3:377–386. doi: 10.1002/wcs.1176

Figure 1.

School achievement and engagement gaps between low‐, middle‐ and high‐SES kindergarteners. (Reprinted with permission from Ref 52. Copyright 2011 Russell Sage Foundation). Based on data from the ECLS‐K. ‘Low’, ‘medium’, and ‘high’ refer to quintiles of the SES distribution.

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Konrad Körding

Konrad Körding

Konrad Körding is Assistant Professor of Physiology and Physical Medicine and Rehabilitation at the Rehabilitation Institute of Chicago, part of Northwestern University. Before joining Northwestern in 2006, Professor Körding worked in three different research groups, most recently in 2004-2005 at MIT, studying machine learning and hierarchical Bayesian models.


Professor Körding is a member of the Swiss Society for Neuroscience, the German Society for Neuroscience, the Society for Neuroscience (USA) and the Electronic Frontier Foundation.

Professor Körding’s current research with the Bayesian Behavior group aims to improve rehabilitation procedures through a greater understanding of motor learning. In order to do this the team studies how people move, and how these movements are affected by uncertainty.

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