Human fetal brain development is marked by the rapid growth of connections between brain structures during the last trimester of pregnancy. Crucially, data processing of fetal rs-functional scans (rs-fMRI) results largely affected by high degrees of movement, which impose severe constraints on interpretation of functional activation patterns leading to potentially biased results. In this work we present a standardized yet flexible preprocessing and normalization procedure allowing for data loss minimization (i.e. allowing to preserve the highest amount of volumes while consistently excluding outliers) and thus fostering reliable group-level inferences.
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