Amygdala Subregional Structure and Intrinsic Functional Connectivity Predicts Individual Differences in Anxiety During Early Childhood

Abstract

Background Early childhood anxiety has been linked to an increased risk for developing mood and anxiety disorders. Little, however, is known about its effect on the brain during early childhood – a period when anxiety-related traits begin to be reliably identifiable. Even less is known about the neurodevelopmental origins of individual differences in childhood anxiety. Methods We combined structural and functional magnetic resonance imaging (fMRI) with neuropsychological assessment of anxiety based on daily life experiences to investigate the effects of anxiety on the brain in seventy-six young children. We then used machine learning algorithms with balanced cross-validation to examine brain-based predictors of individual differences in childhood anxiety. Results Even in children as young as ages 7–9, high childhood anxiety is associated with enlarged amygdala volume and this enlargement is localized specifically to the basolateral amygdala. High childhood anxiety is also associated with increased connectivity between the amygdala and distributed brain systems involved in attention, emotion perception and regulation, and these effects are most prominent effect in basolateral amygdala. Critically, machine learning algorithms revealed that levels of childhood anxiety could be reliably predicted by amygdala morphometry and intrinsic functional connectivity, with the left basolateral amygdala emerging again as the strongest predictor. Conclusions Individual differences in anxiety can be reliably detected with high predictive value in amygdala-centric emotion circuits at a surprisingly young age. Our study provides important new insights into the neurodevelopmental origins of anxiety, and has significant implications for the development of predictive biomarkers to identify children at-risk for anxiety disorders.

Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct‐disordered juvenile offenders

“…Given apparent lateralization effects in amygdalar functionality and subregional connectivity [Aghajani et al 2016, 2016; Baas et al, 2004; Brown et al, 2014; Gabard‐Durnam et al, 2014; Qin et al, 2014; Sergerie et al, 2008; Styliadis et al, 2014], and in line with recent work [Aghajani et al, 2016; Qin et al, 2012, 2014], BLA and CMA region of interest (ROI) masks were created in each hemisphere (see Supporting Information), and used to extract individual participant's mean time series within BLA and CMA complexes. Seed‐based whole‐brain iFC analysis implemented within FSL FEAT [Jenkinson et al, 2012], was then employed to reveal BLA and CMA connectivity patterns [Fox and Raichle, 2007].…”

Development of White Matter Microstructure and Intrinsic Functional Connectivity Between the Amygdala and Ventromedial Prefrontal Cortex: Associations With Anxiety and Depression

“…However, even within a single disorder, results are conflicting, some reporting hypo-connectivity while others find hyper-connectivity(8;40;48;49). Discrepancy in amygdala-vmPFC connectivity findings may be due to differences in age ranges examined (50;51), not addressing developmental effects (52;53), and the specific amygdala and vmPFC subregions examined.…”

Developmental Resting State Functional Connectivity for Clinicians

“…They found that adults showed greater connectivity between the task-positive network and dorsolateral prefrontal cortex and stronger anti-correlations between the “task negative” network and anterior insula, parietal and posterior cingulate cortices [23]. Chai and colleagues also examined the development of anti-correlated networks in 8-24 year-olds [24] and found that as age increased, anti-correlations also increased between networks (i.e., medial and dorsolateral prefrontal cortex, and between lateral parietal and supramarginal gyrus and precuneus). Authors noted that the correlation between regions in these networks was positive in childhood but negative in adults, with adolescent connectivity levels falling in the middle [24].…”

“…Chai and colleagues also examined the development of anti-correlated networks in 8-24 year-olds [24] and found that as age increased, anti-correlations also increased between networks (i.e., medial and dorsolateral prefrontal cortex, and between lateral parietal and supramarginal gyrus and precuneus). Authors noted that the correlation between regions in these networks was positive in childhood but negative in adults, with adolescent connectivity levels falling in the middle [24]. …”

“…Gender differences have received little experimental attention, but do appear to be present in studies that examined them [21]. Finally, anti-correlated networks have been reproduced in several studies as markers of more advanced, adult-like development [23, 24]. All of the studies reviewed here have had the limitation of cross-sectional designs and concerns for the impact of head motion on findings.…”