Gray space and default mode network-amygdala connectivity

Julia C Harris; Michael T Liuzzi; Carlos Cardenas-Iniguez; Christine L Larson; Krista M Lisdahl

doi:10.3389/fnhum.2023.1167786

Gray space and default mode network-amygdala connectivity

Front Hum Neurosci. 2023 Aug 30:17:1167786. doi: 10.3389/fnhum.2023.1167786. eCollection 2023.

Authors

Julia C Harris^#¹, Michael T Liuzzi^#¹, Carlos Cardenas-Iniguez², Christine L Larson¹, Krista M Lisdahl¹

Affiliations

¹ Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.
² Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.

^# Contributed equally.

Abstract

Introduction: Aspects of the built environment relate to health factors and equity in living conditions, and may contribute to racial, ethnic, or economic health disparities. For example, urbanicity is linked with negative factors including exposure to gray space (e.g., impervious surfaces such as concrete, streets, or rooftops). While there is existing research on access to green space and urbanicity on some mental health and cognitive outcomes, there is limited research on the presence of gray space linked with cognitive functioning in youth. The goal of this study was to investigate the link between gray space and amygdala-default mode network (DMN) connectivity.

Methods: This study used data from the ABCD Study. Participants (n = 10,144; age M = 119.11 months, female = 47.62%) underwent resting-state fMRI acquisition at baseline. Impervious surfaces (gray space) were measured via the Child Opportunity Index (COI). To examine the relationship between presence of gray space and -amygdala-DMN (left/right) connectivity, we employed linear mixed effects models. Correlations were run between amygdala-DMN connectivity and internalizing and externalizing symptoms. Finally, post hoc sensitivity analyses were run to assess the impact of race.

Results: More gray space, adjusting for age, sex, and neighborhood-level variables, was significantly associated with increased left amygdala-DMN connectivity (p = 0.0001). This association remained significant after sensitivity analyses for race were completed (p = 0.01). No significant correlations were observed between amygdala-DMN and internalizing or externalizing symptoms.

Discussion: Findings suggest gray space was linked with increased left amygdala-DMN connectivity, circuits that have been implicated in affective processing, emotion regulation, and psychopathology. Thus gray space may be related to alterations in connectivity that may enhance risk for emotion dysregulation. Future investigation of these relationships is needed, as neuroimaging findings may represent early dysregulation not yet observed in the behavioral analyses at this age (i.e., the present study did not find significant relationships with parent-reported behavioral outcomes). These findings can help to inform future public policy on improving lived and built environments.

Keywords: amygdala; default mode network; fMRI; gray space; resting state.

Grants and funding

Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development^SM (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The ABCD Study^® is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, and U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from the ABCD 4.0 data release (https://nda.nih.gov/study.html?id=1299). DOIs can be found at 10.15154/1523041. ML was supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant number TL1TR001437. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. Additional support for this work was made possible from NIEHS R01-ES032295 and R01-ES031074. CC-I was also supported by NIEHS P30-ES007048 and T32-ES013678, NINDS R25-NS089462, R25-NS094094, and R25-NS117356.