Investigating Emotional Similarity: A Comment on Riberto, Pobric, and Talmi (2019)

Levine, Seth M.; Wackerle, Anja

doi:10.1007/s10548-020-00766-5

Cited by 1 publication

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“…The resulting averaged behavioral RDM from the "free-arrangement" sample resembled the behavioral RDM from the sample that arranged the images according to the similarity of their functions. This finding raises the question of what "default" information underlies representations in the absence of specific task demands, and how not controlling for this default processing may lead to neural representations that contain (possibly fluctuating) subjective biases toward the stimuli (53), thereby reducing the statistical power of the RSA. This issue is especially pronounced given that individuals have different attentional biases (54)(55)(56)(57)(58) and fluctuate between different mental states in an individualized manner (59)(60)(61)(62).…”

Section: When Acquiring Behavioral and Neural Datamentioning

confidence: 99%

Individualizing Representational Similarity Analysis

Levine

Schwarzbach

2021

Front. Psychiatry

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Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.

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