Neural representations in MPFC and Insula encode individual differences in preference estimation

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Abstract Submission 

Hyeran Kang¹, Kun Il Kim¹, Jinhee Kim¹, Hackjin Kim¹

¹Korea University, Seoul, Korea, Republic of

Hyeran Kang  
Korea University
Seoul, Korea, Republic of

Kun Il Kim  
Korea University
Seoul, Korea, Republic of

Jinhee Kim  
Korea University
Seoul, Korea, Republic of

Hackjin Kim  
Korea University
Seoul, Korea, Republic of

In human society, successful social interactions hinge on appropriate reactions achieved through accurate estimation of other's perspectives, often necessitating the consideration of contextual information. The study delves into the neural mechanism underpinning this cognitive capacity, employing a preference estimation task.

Task-based functional MRI data were collected using the 3T Siemens Trio scanner while 38 healthy female participants performed the preference estimating task. In this task, participants, upon seeing the target's face, were tasked with predicting the extent to which the target would prefer a given item. Preference estimation accuracy is quantified by the percentage of correct guesses, aligning with the target's preferences on a 4-point Likert scale. In the first-level, preprocessed functional images were modeled using a general linear model, incorporating the self-trial and the target-trial at the face and item phase. In the group-level, we adapted both univariate and multivariate approach to reveal the neural activity as well as the neural representation associated with the individual difference in preference estimation. In univariate approach, to identify brain regions associated with individual preference estimation accuracy, we performed a linear regression analysis with individual accuracy score as covariates. In multivariate approach, to identify brain regions associated with variability in preference estimation accuracy, we performed inter-subject representational similarity analysis (IS-RSA).

Univariate findings reveal the involvement of subregions of the medial prefrontal cortex (mPFC) in precisely assessing others' preferences. Multivariate results, utilizing inter-subject representational similarity analysis (IS-RSA), demonstrate that the multi-voxel patterns in the pregenual anterior cingulate cortex (pgACC) and the anterior insula (AI) predict individual variability in preference estimation accuracy. This implies that the diverse behavioral patterns among participants in inferring others' preferences were mirrored in the multivariate neural representations in these areas, both of which are strongly associated with individual differences in interoception and context-dependent ambiguous facial emotion estimation.

The present study suggests that the mPFC and AI play a pivotal role in accurately estimating others' preferences with minimal information. The application of multivariate pattern analysis unveils insights beyond the scope of traditional approaches, shedding light on the intricate neural processes involved in this social cognitive task.

Social Cognition ²

Social Neuroscience Other ¹

Multivariate Approaches

Univariate Modeling

FUNCTIONAL MRI

Other - Inter-subject Representational Analysis; Medial Prefrontal Cortex; Insula; Preference Estimation; Social Cognition