Linking brain networks and social networks: connectomic correlates of empathy and closeness

Presented During: Poster Session
Thursday, June 13, 2019: 12:45 PM - 02:45 PM

Poster No:

Th892 

Submission Type:

Abstract Submission 

Authors:

Olusola Ajilore1, Alex Leow1, Sylvia Morelli1

Institutions:

1University of Illinois at Chicago, Chicago, United States

Introduction:

Recent work in social cognition has demonstrated that empathy is a characteristic of people central in social networks defined by trust (Morelli et al, 2017) and brain regions involved in mentalizing are activated when subjects perceive persons of high social value within a community (Morelli et al, 2018). However, it is unclear whether global brain network characteristics of people within a community reflect the social network properties of that community. To answer this question, the present study used a data-driven whole-brain network approach to determine connectomic correlates of empathy and closeness in a social network.

Methods:

Participants:
As part of a larger study on social networks (Morelli et al, 2017), 52 college students were recruited from two freshman-only dormitories at Stanford University.

Social Network Determination
To assess social ties in the dorm, we asked participants to nominate up to eight people in their dormitory in response to each of nine prompts (in the listed order): (1) "Who are your closest friends?" (2) "Whom do you spend the most time with?" (3) "Whom have you asked for advice about your social life?" (4) "Who do you turn to when something bad happens?" (5) "Whom do you share good news with?" (6) "Who makes you feel supported and cared for?" (7) "Who is the most empathetic?" (8) "Who usually makes you feel positive (e.g., happy, enthusiastic)?" and (9) "Who usually makes you feel negative (e.g., stressed, angry, sad)? For each participant, the following measures of centrality were calculated for each question: indegree, outdegree, betweenness, and closeness centrality. 

fMRI Tasks:
Participants completed the following tasks: Face-Viewing Task: The face-viewing task was modified from a study by Zerubavel and colleagues (Zerubavel etl al, 2015); Relationship-Rating Task: In the relationship-rating task, participants were asked to think about how close they felt to each pictured person; Trait-Rating Task: The trait-rating task had the same design as the relationship-rating task, with the same number of trials, trial components, randomization, and timing. However, participants saw the question "How empathetic?" under each photo and were instead instructed to think about this trait when viewing photos.

Task-based Connectome Analysis:
Data from the tasks above were analyzed with the CONN toolbox (Whitfield-Gabrieli and Nieto-Castanon, 2012) to create task-based connectomes representing face-viewing, closeness, and empathy networks. Edge strength differences between networks were analyzed in a pairwise fashion controlling for multiple comparisons using the false discovery rate (FDR). Betweenness and eigenvector centrailty of all nodes in empathy and closeness brain networks were correlated with participants' betweenness centrality in their social network.

Results:

Comparing connections in the closeness and empathy brain networks with the face viewing network revealed a subnetwork with reduced connectivity containing brain regions involved in face processing and increased connectivity between the default mode and salience network. Additionally, betweenness centrality in the closeness social network correlated most significantly with left planum temporale betweenness centrality (r = .48, p = .0003).

Conclusions:

The results of our data-driven analysis demonstrate that empathy and closeness networks have increased connectivity between the default mode network and salience networks compared to face-viewing networks. This is consistent with the literature suggesting that the salience network is associated with constructs of empathy and closeness (i.e. socioemotional sensitivity and emotional contagion). Furthermore, participants with higher centrality in their social network defined by closeness had higher centrality of the left planum temporale in their brain networks. This region is typically associated with language function but has been recently identified as an important region for social cognition (McDonald et al, 2018).

Provide references using author date format

McDonald S, Dalton KI, Rushby JA, Landin-Romero R. (2018) Loss of white matter connections after severe traumatic brain injury (TBI) and its relationship to social cognition. Brain Imaging Behav. doi: 10.1007/s11682-018-9906-0.

Morelli, S. A., Ong, D. C., Makati, R., Jackson, M. O., & Zaki, J. (2017). Empathy and well-being correlate with centrality in different social networks. Proceedings of the National Academy of Sciences, 114(37), 9843-9847. 

Morelli SA, Leong YC, Carlson RW, Kullar M, Zaki J. (2018) Neural detection of socially valued community members. Proc Natl Acad Sci U S A. 115(32):8149-8154.

Whitfield-Gabrieli, S., and Nieto-Castanon, A. (2012). Conn: A functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity. doi:10.1089/brain.2012.0073

Zerubavel, N., Bearman, P. S., Weber, J., & Ochsner, K. N. (2015). Neural mechanisms tracking popularity in real-world social networks. Proceedings of the National Academy of Sciences, 112(49), 15072-15077.