Occupational Attributes relate to Large-Scale Brain Network Organization

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

H. Moriah Sokolowski^1,2 (hm.sokolowski@torontomu.ca), Ju-Chi Yu³, Devin Sodums², Herve Abdi⁴, Brian Levine^2,5,6; ¹Department of Psychology, Toronto Metropolitan University, Toronto, ON, Canada, ²Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, ³Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada, ⁴School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, USA, ⁵Department of Psychology, University of Toronto, Toronto, ON, Canada, ⁶Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada

Individuals invest a significant portion of their daily lives in their professions, implicating occupations as influential in cognitive functioning. Diverse jobs require distinct knowledge, skills, and abilities, contributing to a multifaceted, lifelong experience that likely shapes bidirectional influences on brain development. While prior studies have predominantly focused on specific occupational factors causing focal brain changes, this approach may underestimate the impact of large-scale brain network organization. Additionally, characterizing occupations nominally limits hypothesis testing and data analysis. The current study explores how brain network organization correlates with continuous occupation scores across three dimensions: 1) occupational complexity, 2) alignment with science, technology, engineering, and mathematical (STEM) disciplines, and 3) emphasis on computational versus health knowledge. Participants (N = 403, ages 18-85 years) from the Nathan Kline Institute-Rockland Sample were utilized. Occupation scores, derived via a validated method converting free-entry occupations into continuous dimensions, were related to brain network organization, measured by the strength of within-network versus between-network connections (i.e., network segregation). Multivariate analyses revealed associations between network segregation and occupational scores. Specifically, individuals in occupations that required computational (versus health) knowledge, exhibited more network segregation in their salience ventral attention network. Notably, men, but not women, in these computational occupations also displayed increased segregation in their visual and control systems. These findings underscore the intricate relationship between large-scale brain organization and occupations, emphasizing gender-specific variations. These results not only shed light on neural measures warranting further exploration but also emphasize the need to understand and address gender disparities in STEM disciplines.

Topic Area: OTHER