Wired from the womb: a narrative review of fetal and neonatal connectomics via fMRI and emerging neurotechnologies

Fetal and neonatal connectomics, utilizing functional magnetic resonance imaging (fMRI), offers critical insights into early brain development, with transformative potential for neonatal care. This review synthesizes peer-reviewed research from 2007 to 2025, tracing the historical evolution, methodological advancements, and clinical implications of fMRI-based connectomics in fetuses and neonates. Early studies introduced resting-state fMRI, while initiatives like the Developing Human Connectome Project (dHCP) have expanded the field through large-scale datasets. Methodologies, including resting-state fMRI, independent component analysis, and network modeling, have identified small-world and modular network architectures, with predictive value for cognitive and language outcomes. Despite advantages like non-invasiveness and early disorder detection, challenges include motion artifacts in fMRI data acquisition, blood-oxygen-level-dependent (BOLD) response variability, and sometimes sedation requirements. Future directions involve refining long-term outcome predictions, integrating multimodal imaging (e.g., EEG, NIRS), and developing neonatal intensive care unit (NICU) protocols. This review, drawing on available peer-reviewed sources, highlights the field's growth and limitations, advocating for standardized protocols and interdisciplinary collaboration to bridge research and clinical practice, ultimately improving outcomes for high-risk neonates. IMPACT: This review of fetal and neonatal connectomics adds the following to existing literature. Systematic, historical review of the development of fetal and neonatal connectomics using fMRI. Detailed resources for researchers to utilize existing databases for interpretation of findings as well as describing the technical, biological, and ethical challenges limiting clinical application of these findings. Provides key research gaps in translating connectomics findings into clinical applications as well as suggestions for addressing those gaps.