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
a period in early childhood 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 with neuropsychological
assessments of anxiety based on daily life experiences to investigate the effects
of anxiety on the brain in 76 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 to 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 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 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.
Key Words
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Article Info
Publication History
Published online: November 25, 2013
Accepted:
October 3,
2013
Received in revised form:
September 4,
2013
Received:
May 23,
2013
Identification
Copyright
© 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
