Genome-wide association studies (GWAS) have identified thousands of non-coding variants that contribute to neuropsychiatric disease risks, likely by perturbing cis-regulatory elements (CREs) 1,2 . A significant barrier to understanding the genetic underpinnings of these neuropsychiatric complex diseases is the lack of functional characterization of risk genes and variants in biological systems relevant to human health. Moreover, as the human cortex is complex and heterogeneous3,4 , cell type-specific annotation of the 3D epigenome assists with insights into how non-coding genetic variants contribute to neuropsychiatric disorders. In the Chapter 1, I review how CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) screens can be leveraged to test non-coding variants associated with complex diseases. I first discuss the current challenges of interpreting the function of the non-coding genome and approaches to prioritizing disease-associated variants in the context of the 3D epigenome. Second, I provide a brief overview of high-throughput CRISPRi and CRISPRa screening strategies applicable for characterizing non-coding sequences in appropriate biological systems. Lastly, I discuss the promising prospects of using CRISPR-based technologies to dissect DNA sequences associated with neuropsychiatric diseases. In the Chapter 2, we identified 3,489 and 3,894 functional CREs (fCREs) essential for iPSC fitness and cell survival during neuronal differentiation, respectively. These fCREs display dynamic epigenomic features and exhibit increased numbers and genomic spans of chromatin interactions following terminal neuronal differentiation. Furthermore, fCREs essential for neuronal differentiation show significantly greater enrichment of genetic heritability for neuropsychiatric diseases including schizophrenia (SCZ), autism spectrum disorders (ASD), and post-traumatic stress disorder (PTSD) than non-fCREs. Using high-throughput PRIME editing screens73 , we further identified 19 SCZ risk variants affecting cell survival during neuronal differentiation. ix Lastly, in Chapter 3, I conducted a comprehensive 3D epigenomic analysis of four major glial populations, including ventricular radial glia (vRG), outer radial glia (oRG), oligodendrocyte precursor cells (OPC), and microglia (MG), from the mid-gestational human neocortex. By integrating gene expression, chromatin accessibility, DNA methylation, and 3D chromatin interactions, I identified cell type-specific candidate cCREs and validated their enhancer function using transgenic mouse embryos. Using machine learning, I prioritized 112 SCZ risk variants within glia cCREs and further confirmed the predicted vRG enhancer disruption by rs4449074 risk allele in vivo. Finally, oRG cCREs are enriched for human accelerated regions (HARs) compared to other cCREs and a subset of HARs have predicted activity differences compared to their chimpanzee orthologs that interact with genes involved in neuronal development. In summary, this dissertation outlines the challenges and tools available to functionally evaluate disease associated variants with CRISPRi/a screens, provides a crucial resource for interpreting noncoding risk variants of neuropsychiatric diseases by extensive and in-depth functional annotation of cCREs during neuronal differentiation, and advances the understanding of human-specific gene regulation during corticogenesis