How to produce personality neuroscience research with high statistical power and low additional cost

Raymond A. Mar, R. Nathan Spreng, Colin G. Deyoung

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Personality neuroscience involves examining relations between cognitive or behavioral variability and neural variables like brain structure and function. Such studies have uncovered a number of fascinating associations but require large samples, which are expensive to collect. Here, we propose a system that capitalizes on neuroimaging data commonly collected for separate purposes and combines it with new behavioral data to test novel hypotheses. Specifically, we suggest that groups of researchers compile a database of structural (i.e.; anatomical) and resting-state functional scans produced for other task-based investigations and pair these data with contact information for the participants who contributed the data. This contact information can then be used to collect additional cognitive, behavioral, or individual-difference data that are then reassociated with the neuroimaging data for analysis. This would allow for novel hypotheses regarding brain-behavior relations to be tested on the basis of large sample sizes (with adequate statistical power) for low additional cost. This idea can be implemented at small scales at single institutions, among a group of collaborating researchers, or perhaps even within a single lab. It can also be implemented at a large scale across institutions, although doing so would entail a number of additional complications.

Original languageEnglish (US)
Pages (from-to)674-685
Number of pages12
JournalCognitive, Affective and Behavioral Neuroscience
Volume13
Issue number3
DOIs
StatePublished - Sep 1 2013

Keywords

  • Individual differences
  • Neuroinformatics
  • Neuroscience
  • Personality
  • Sample size
  • Statistical power

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