Autonomic Imbalance across the Brain-Heart Axis in Children with Autism
Poster No:
681
Submission Type:
Abstract Submission
Authors:
Jellina Prinsen1, Nicky Daniels2, Matthijs Moerkerke1, Jean Steyaert1, Bart Boets1, Kaat Alaerts1
Institutions:
1KU Leuven, Leuven, 2KU Leuven, Leuven,
First Author:
Co-Author(s):
Introduction:
Because of its negative link to stress and anxiety, as well as its positive link to a wide range of positive psychological outcomes, heart rate variability (HRV) is increasingly considered as a marker of mental health and homeostasis (Schaffer & Ginsberg, 2017). In healthy adult subjects, HRV has also been shown to covary with changes in connectivity between brain regions of the central autonomic network (CAN), demonstrating a functional integration between cardiac and neural systems for maintaining and regulating homeostasis (Thayer et al., 2012). The high-frequency component of HRV (HF-HRV) in particular, exclusively denoting parasympathetic ("vagal") outflow, is associated with increased functional coupling between the medial prefrontal cortex (mPFC) and amygdala, thought to reflect a prefrontal top-down inhibition of amygdala-centered circuits. In children with ASD, extremely high prevalence rates of anxiety and autonomic stress are noted (Arora et al., 2021). Furthermore, hyperarousal at the level of the heart, caused by vagal withdrawal during prolonged stress is often reported (Cheng et al., 2020), yet its extent, functional relevance and the role of the CAN network herein remain undetermined. Here, we aim to investigate the occurrence of cardiac autonomic (im)balance as well as associated differences in intrinsic CAN connectivity in 59 school-aged children with ASD (8-12 y/o) compared to 39 age- and IQ-matched typically developing (TD) children.
Methods:
Cardiac monitoring was performed during concurrent resting-state 3T fMRI neuroimaging while at rest. We focused on the HF-HRV component - defined within the 0.24-1.04 Hz) frequency band in children - as an index of cardiac vagal tone. Besides addressing functional connectivity between core CAN brain regions (bilateral amygdala, mPFC, anterior cingulate cortex (ACC)), spectral dynamic causal modelling (spDCM) was adopted to specifically delineate effective connectivity between these region. As such, we can explicitly model the influence that one region (mPFC) exerts over another (amygdala) within a network model of causal neural dynamics. Parametric empirical Bayes (PEB) procedures were used to test how individual (within-subject) neural connections within the CAN relate to different between-subjects effects (group, HF-HRV%, parent-reported SRS scores).
Results:
At the group level, we show similar band power in the HF-HRV frequency band in children with and without ASD, denoting similar levels of cardiac vagal tone during rest. Yet lower parasympathetic outflow at the level of the heart was found in ASD children with more severe ASD symptomatology, indicative of vagal withdrawal and higher autonomic arousal in these children. No group differences in CAN functional connectivity could be detected, but the effective connectivity analyses demonstrated increased excitatory feed-forward connections between bilateral amygdala and ACC in ASD children, combined with active inhibition of the mPFC by the amygdalae. Neuro-cardiac integration between functional amygdala-mPFC connectivity and HF-HRV was only shown in TD (r = -.36, p = .03), but not in ASD children (all p > .38). The spDCM analysis in combination with PEB estimation did show however that with increasing HF-HRV band power, the role of the mPFC becomes more prominent and exerts an inhibition over the amygdala, as proposed by the theory of neuro-cardiac integration (Thayer et al., 2012).
·Parametric Empirical Bayes estimates for effective connectivity between regions of the CAN network.
Conclusions:
Despite no overall differences in cardiac vagal tone between TD vs. ASD children, the effective connectivity analyses demonstrated increased excitatory feed-forward amygdala-centered connections within the CAN network in children with ASD. Most importantly, higher cardiac vagal tone was related to lower ASD symptomatology and a more prominent top-down inhibition from the mPFC over the amygdala, providing further evidence for a functionally integrative brain-heart system that can be addressed as a marker of disrupted homeostasis in children ASD.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Keywords:
Autism
FUNCTIONAL MRI
Modeling
Psychiatric Disorders
1|2Indicates the priority used for review
Provide references using author date format
Cheng et al. (2020). Heart rate variability in individuals with autism spectrum disorders: A meta-analysis. Neuroscience & Biobehavioral Reviews, 118, 463–471.
Patriquin et al. (2019). Autonomic response in autism spectrum disorder: Relationship to social and cognitive functioning. Biological Psychology, 145, 185–197.
Shaffer & Ginsberg (2017). An Overview of Heart Rate Variability Metrics and Norms. Frontiers in Public Health, 5.
Thayer et al. (2012). A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience and Biobehavioral Reviews, 36(2), 747–756.