Stimulus repetition and sample size considerations in item-level representational similarity analysis

ABSTRACT

In studies using representational similarity analysis (RSA) of fMRI data, the reliability of the neural representational dissimilarity matrix (RDM) is a limiting factor in the ability to detect neural correlates of a model. A common strategy for boosting neural RDM reliability is to employ repeated presentations of the stimulus set across imaging runs or sessions. However, little is known about how the benefits of stimulus repetition are affected by repetition suppression, or how they compare with the benefits of increasing the number of participants. We examined the effects of these design parameters in two large data sets where participants performed a semantic decision task on visually presented words. We found that reliability gains from stimulus repetition were strongly affected by repetition suppression, both within and across scanning sessions separated by multiple weeks. The results provide new insights into these experimental design choices, particularly for item-level RSA studies of semantic cognition.

KEYWORDS:

• Representational similarity analysis
• fMRI
• sample size
• reliability
• semantic cognition

Acknowledgements

The authors thank Volkan Arpinar, Elizabeth Awe, Joseph Heffernan, Steven Jankowski, Jedidiah Mathis, and Megan LeDoux for technical assistance.

Data availability statement

The neural RDMs as well as code to generate all figures are available at the following GitHub repository: https://github.com/smazurchuk/rsa_reliability

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Institute on Deafness and Other Communication Disorders (NIDCD) grant R01 DC016622.