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Dysregulated behavior has been associated with increased risk for psychopathology (McLaughlin et al., 2011). However, we know relatively little about its neural origins. In adults, the fronto-parietal network and default mode network are implicated in emotion regulation(Pan et al., 2018). However, it remains unclear whether the same neural patterns should be expected in infancy as these connections are still developing. This poster examines associations between resting state functional connectivity (rsFC) and maternal report of dysregulation in infancy.
We collected functional Magnetic Resonance Images (fMRI) in infants at 4 months (Mage= 4.7) while they were in natural sleep to assess rsFC. At a 14-month (Mage= 14.8) behavioral follow-up visit the Infant-Toddler Social and Emotional Assessment (ITSEA) was collected. Here we focus on the dysregulation subscale. Dysregulation is defined as an inappropriate response to a specific situation and is characterized by problem behaviors. 33 infants had both high-quality 4-month MRI data and ITSEA follow-up data. rsFC between 200 regions of interest were extracted and associations between rsFC and scores on the dysregulation subscale were evaluated using enrichment analysis. Enrichment analysis is a statistical method of identifying networks that have an increased density of strong brain-behavior correlations. Statistical thresholding utilized permutation-derived false positive rates.
Results indicated greater maternal report of dysregulation was associated with decreased connectivity between the salience-sensorimotor (p=.021), control-dorsal attention (ps<.026), default-dorsal attention, (p=.020), control-sensorimotor (p=.008), sensorimotor-dorsal attention (p=.003; See Figure 1), and default-salience networks (p=.009) and within the control network (p=.008). Table 1 depicts specific network-network pairs, effect sizes, and p values.
This study suggests that connectivity between control, attention, motor, and default networks may be associated with dysregulation in infancy. Large scale longitudinal studies of network connectivity development are necessary to understand the clinical significance of these relations, as well as to understand how these associations change over time. Follow-up analyses will determine specificity of these effects by testing if similar relations hold with the competence domain of the ITSEA.
Hannah Hardiman, National Institute of Mental Health; University of Maryland - College Park
Presenting Author
Dana Kanel, National Institute of Mental Health; University of Maryland, College Park
Courtney Filippi, New York University School of Medicine
Daniel S. Pine, National Institutes of Health
Nathan A Fox, University of Maryland - College Park