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Gabard-Durnam, L.

Publications and source records attributed to Gabard-Durnam, L..

3 recordsLinked to original sources

Microbiome-behavior coupling shapes infant adaptation to early maternal unpredictability

We asked whether infant microbiome composition, together with infants behavioral responses to early maternal unpredictability, can offer novel mechanistic insights into behavioral phenotypic variation in human development. Maternal unpredictability was computed as the entropy rate of transitions among maternal sensory signals during naturalistic mother-infant interaction (n=256 dyads; 2-6 months). Infant visual orienting behavior (VOB) was indexed by infants simultaneous gaze shifts to and from the mother. Higher maternal unpredictability predicted more frequent VOB shifts, indicating a mature-for-age profile, and longitudinally forecast poorer inhibitory control at 19-28 months. A subgroup of infants with high maternal unpredictability and high VOB had inhibitory control outcomes closer to those of infants who experienced low maternal unpredictability, suggesting VOB strategy might buffer against the effects of high maternal unpredictability. In participants with metagenomic data (n=93), VOB was associated with taxonomic and functional gut microbial profiles along a Bifidobacterium breve to Bifidobacterium longum axis. Neuroactive gene-set enrichment analysis linked VOB to increase in tryptophan synthesis and glutamate synthesis genes. In contrast, maternal unpredictability showed depletions of GABA and tryptophan synthesis in the unique-effects model and, when VOB and the maternal unpredictability by VOB term were included, enrichment of acetate synthesis and quinolinic acid degradation. Notably, the maternal unpredictability by VOB interactions for tryptophan and glutamate were negative, indicating that the VOB-pathway coupling attenuates as unpredictability increases. Together, these findings support a framework in which maternal unpredictability is the environmental challenge, infant VOB expresses the behavioral strategy, and microbial metabolism modulates whether that strategy is biochemically feasible. TeaserInfant gut microbiome is linked to infant behavioral responses to maternal unpredictability, which in turn impacts how they learn to control their actions.

neuroscience↗

Spatiotemporal dynamics of EEG microstate networks over the first two years of life: A multi-cohort longitudinal study

The first two years of life are marked by rapid development of large-scale brain networks that support emerging cognition and behavior. Magnetic-resonance approaches have revealed much about largescale networks in sleep, but very little is known about functional network dynamics in awake, behaving infants during this period of substantial development. Microstates are brief instances of distinct spatial topographies of largescale neural activity measured with electroencephalography (EEG) that offer a novel approach to studying whole-brain network dynamics at sub-second scale in awake infants by capturing their temporally coherent brain activity. While emerging literature is leveraging microstate dynamics in adults to understand mature largescale network function, developmental trajectories during networks rapid construction in infancy remain uncharacterized. In this study, we leveraged longitudinal resting-state EEG data from 854 infants across two geoculturally diverse cohorts to explore largescale network development through EEG microstates over the first two years of life. We provide evidence for conserved emergence of various network configurations (microstate classes A-G) through infancy across cohorts using data-driven clustering analyses. We also demonstrate significant longitudinal changes in microstate dynamics during this period, characterized by more numerous and more rapid transitions between largescale configurations, especially over early infancy. While patterns of sensory microstate development were largely consistent between cohorts, higher-order cognitive microstates showed context-specific developmental trends. Together these results provide novel insights into how large-scale brain networks functionally develop and organize across the first two years of life.

neuroscience↗

Age-related change in task-evoked amygdala-prefrontal circuitry: a multiverse approach with an accelerated longitudinal cohort aged 4-22 years

The amygdala and its connections with medial prefrontal cortex (mPFC) play central roles in the development of emotional processes. While several studies have suggested that this circuitry exhibits functional changes across the first two decades of life, findings have been mixed - perhaps resulting from differences in analytic choices across studies. Here we used multiverse analyses to examine the robustness of task-based amygdala-mPFC function findings to analytic choices within the context of an accelerated longitudinal design (4-22 years- old; N=98; 183 scans; 1-3 scans/participant). Participants, recruited from the greater Los Angeles area, completed an event-related emotional face (fear, neutral) task. Parallel analyses varying in preprocessing and modeling choices found that age-related change estimates for amygdala reactivity were more robust than task-evoked amygdala-mPFC functional connectivity to varied analytical choices. Specification curves indicated evidence for age-related decreases in amygdala reactivity to faces, though within-participant changes in amygdala reactivity could not be differentiated from between-participant differences. In contrast, amygdala--mPFC functional connectivity results varied across methods much more, and evidence for age-related change in amygdala-mPFC connectivity was not consistent. Generalized psychophysiological interaction (gPPI) measurements of connectivity were especially sensitive to whether a deconvolution step was applied. Our findings demonstrate the importance of assessing the robustness of findings to analysis choices, although the age-related changes in our current work cannot be overinterpreted given low test-retest reliability. Together, these findings highlight both the challenges in estimating developmental change in longitudinal cohorts and the value of multiverse approaches in developmental neuroimaging for assessing robustness of results. (Preprint: https://www.biorxiv.org/content/10.1101/2021.10.08.463601v1). Key PointsO_LIMultiverse analyses applied to fMRI data are valuable for determining the robustness of findings to varied analytical choices C_LIO_LIIn the current study, age-related change estimates for amygdala reactivity were relatively robust to analytical decisions, though gPPI functional connectivity analyses were much more sensitive, leading some estimates to flip sign C_LIO_LIBoth test-retest reliability and robustness to analytical choices are important considerations for developmental research C_LI

neuroscience↗