Prenatal drug exposure affects neonatal brain functional connectivity

Abstract

Prenatal drug exposure, particularly prenatal cocaine exposure (PCE), incurs great public and scientific interest because of its associated neurodevelopmental consequences. However, the neural underpinnings of PCE remain essentially uncharted, and existing studies in school-aged children and adolescents are confounded greatly by postnatal environmental factors. In this study, leveraging a large neonate sample (N = 152) and non-invasive resting-state functional magnetic resonance imaging, we compared human infants with PCE comorbid with other drugs (such as nicotine, alcohol, marijuana, and antidepressant) with infants with similar non-cocaine poly drug exposure and drug-free controls. We aimed to characterize the neural correlates of PCE based on functional connectivity measurements of the amygdala and insula at the earliest stage of development. Our results revealed common drug exposure-related connectivity disruptions within the amygdala-frontal, insula-frontal, and insula-sensorimotor circuits. Moreover, a cocaine-specific effect was detected within a subregion of the amygdala-frontal network. This pathway is thought to play an important role in arousal regulation, which has been shown to be irregular in PCE infants and adolescents. These novel results provide the earliest human-based functional delineations of the neural-developmental consequences of prenatal drug exposure and thus open a new window for the advancement of effective strategies aimed at early risk identification and intervention.

Keywords: amygdala; fMRI; functional connectivity; infant; insula; prenatal drug exposure.

Figure 1.

Comparison of motion scrubbing parameters across neonatal groups. A, Number of volumes removed. B, Residual framewise displacement (FD). Data are plotted as mean ± SEM. For both motion parameters, the neonatal groups were statistically indistinguishable (p > 0.05, ANOVA).

Figure 2.

Visualization of functional connectivity for left amygdala and left insula seed regions across neonatal groups. Top row, PCE; middle row, NCOC; bottom row, CTR; left column, amygdala; right column, insula. Significant connectivity (α = 0.05) is pseudocolored based on the Fisher's Z-transformed correlation measure (see color bar, bottom right) generated from the connectivity analysis. Data are visualized on the partially inflated surface model. Asterisks show the approximate locations of the seed regions. Arrows highlight regions of dissimilarity across groups.

Figure 3.

Visualization of functional connectivity for right amygdala and right insula seed regions across neonatal groups. Top row, PCE; middle row, NCOC; bottom row, CTR; left column, amygdala; right column, insula. Significant connectivity (α = 0.05) is pseudocolored based on the Fisher's Z-transformed correlation measure (see color bar, bottom right) generated from the connectivity analysis. Data visualized on a partially inflated surface model. Asterisks show the approximate locations of the seed regions.

Figure 4.

Visualization of groupwise differences in seed-based functional connectivity. Top row, PCE; middle row, NCOC; bottom row, CTR. Columns are labeled as “seed location [cluster location]”: left, left amygdala [frontal]; middle, left insula [frontal]; right, left insula [sensorimotor]. Three significant clusters (α = 0.05, controlling for participant characteristics) are pseudocolored based on the Fisher's Z-transformed correlation measures (see color bar, bottom right) generated in the connectivity analysis. Data are visualized on the inflated surface model. Note that the surface view is slightly tilted compared with those in Figure 2 to better show the clusters. LH, Left hemisphere; RH, right hemisphere.

Figure 5.

Post hoc comparisons of functional connectivity by group within the detected group-level significant clusters. Plots are labeled as “seed location [cluster location].” Seed regions were located in the left hemisphere. *p ≤ 0.05, pairwise differences between groups (Dunn–Sidak corrected). Data are plotted for all subjects as mean ± SEM.

Figure 6.

Cocaine-specific effect within the amygdala frontal subcluster. A, Visualization of the subcluster (highlighted in red with the original cluster in blue). B, Post hoc comparison of functional connectivity by group within the detected subcluster. *p ≤ 0.05, pairwise differences between groups (Dunn–Sidak corrected). Data are plotted as mean ± SEM.

Figure 7.

Relationship between functional connectivity (Z) and average cocaine usage per trimester for the amygdala frontal subcluster. Data points (open circles) correspond to individual subjects. The dashed line is the best linear fit (R² = 7.26E⁻⁰⁶, p = 0.987).

Figure 8.

Post hoc comparisons within previously established group-level significant clusters using functional connectivity measures generated from visual cortex or control seed regions. A, Main clusters. B, Subcluster. Data are plotted as mean ± SEM. No significant group-level effects (p > 0.05, ANOVA) were detected within the pre-established clusters (originally defined using left hemisphere seeds) using the visual cortex connectivity measures.

Figure 9.

Post hoc comparisons within group-level significant clusters without GSR. A, Main clusters. B, Subcluster. Plots are labeled as “seed location [cluster location].” All seed regions were located in the left hemisphere. *p ≤ 0.05, pairwise differences between groups (Dunn–Sidak corrected). Data are plotted as mean ± SEM.