Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input “easy Hi-C” protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology. Display omitted •HiCorr allows robust mapping of sub-TAD chromatin interactions with Hi-C•Low-input “easy Hi-C” protocol compatible with 50–100k cells•Enhancer loops and aggregates are better marks of cell identity than compartments•Chromatin loops outperform eQTLs in defining neurological GWAS target genes Lu et al. developed a rigorous Hi-C bias-correction pipeline to significantly improve the robustness of high-resolution chromatin interaction maps. With a new low-input “easy Hi-C” protocol, they mapped chromatin interactions in neural samples, defined cell-type-specific enhancer loops and aggregates, and concluded that Hi-C outperforms eQTL in explaining GWAS results.