Individualizing Representational Similarity Analysis

Abstract

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.

Probing patterns for prognostic potential

“…1e, f ) and, with additional encoding analyses, whether these representations tend to distribute along different dimensions underlying the food representational space. Such approaches could help to unravel how attentional mechanisms may (pathologically) affect cognitive processes related to food in acAN patients and determine whether any individual-level alterations in the representational space have additional prognostic value [ 10 ].…”

Prediction error processing and sharpening of expected information across the face-processing hierarchy

“… 62 . Furthermore, to take into account that individuals may differ in their usage of prior information during ambiguous face identification, we included individual prior weights by contrasting prior-confirming with prior-discarding responses for a face morph in the RSA 30 , 68 , 69 . We show that PE representations dominate along and beyond the face-processing hierarchy, while there was also evidence for the co-existence of sharpened expected face information in early face areas.…”

Qualitative Characters Diversity of Prentul Kediri Cayenne Pepper Mutant (M1) Resulted from Gamma Ray Mutation Induction

“…This happens because of the differences in each plant cell in responding to gamma ray irradiation, giving rise to various new characters. According to (Levine & Schwarzbach, 2021) similarity analysis that provides information based on the phenotype or physical appearance of plants still requires information on the level of similarity based on DNA properties. This is because genotypes that have similarities are often found in plants whose phenotypes look different.…”