Visualising mental representations: A primer on noise-based reverse correlation in social psychology

L. Brinkman, A. Todorov, R. Dotsch

Research output: Contribution to journalArticlepeer-review

72 Scopus citations


With the introduction of the psychophysical method of reverse correlation, a holy grail of social psychology appears to be within reach – visualising mental representations. Reverse correlation is a data-driven method that yields visual proxies of mental representations, based on judgements of randomly varying stimuli. This review is a primer to an influential reverse correlation approach in which stimuli vary by applying random noise to the pixels of images. Our review suggests that the technique is an invaluable tool in the investigation of social perception (e.g., in the perception of race, gender and personality traits), with ample potential applications. However, it is unclear how these visual proxies are best interpreted. Building on advances in cognitive neuroscience, we suggest that these proxies are visual reflections of the internal representations that determine how social stimuli are perceived. In addition, we provide a tutorial on how to perform reverse correlation experiments using R.

Original languageEnglish (US)
Pages (from-to)333-361
Number of pages29
JournalEuropean Review of Social Psychology
Issue number1
StatePublished - Jan 1 2017

All Science Journal Classification (ASJC) codes

  • Social Psychology


  • Classification image
  • Predictive coding
  • Reverse correlation
  • Social perception
  • Top-down biases


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