the shared latent space allowed us to reconstruct a bipartite weighted k - nearest - neighbour ( wknn ) graph between cells in the hnoca and the primary reference atlas, which was used to transfer the ‘ cellclass ’ and ‘ subregion ’ labels, as well as the neurotransmitter transporter ( ntt ) information of neuroblasts and neurons to the hnoca. the transferred labels are strongly consistent with our assigned labels ( extended data fig. 3 ) and allowed us to refine the regional annotation of hnoca non - telencephal ic npcs and neurons, as well as the ntt annotation of the non - telencephal ic neurons ( fig. 2b ), resulting in the final hierarchical hnoca cell type annotation ( extended data fig. 3 ). we also sought to compare organoid cells to stages of human brain development beyond the first trimester. focusing on dorsal telencephalon, we compared the transcriptomic profile of hnoca npcs and neurons with cells in a primary atlas of human cortex development spanning the first trimester to adolescence. we observed a transition from cell states observed in the first trimester to more mature states observed in the second - trimester cortex ( fig. 2c ), and did not detect substantial matching to later stages. we extended the comparison to other brain regions using two primary atlases representing the first and second trimester, respectively. we confirmed increased similarity to second - trimester cell states in older organoids for other brain regions ( extended data fig. 3 ). we evaluated the capacity of each neural organoid protocol to generate neural cells of different brain regions ( fig. 2d, extended data figs. 3 and 4 and supplementary table 2 ). datasets of unguided neural organoids contain cells across all brain regions with proportions varying across datasets, indicating the capacity of unguided protocols to generate many brain regions but with high variability. by contrast, datasets derived from guided organoid protocols are strongly enriched for cells of the targeted brain region, but often show an increased proportion of cells of the brain regions neighbouring the targeted regions. for example, several datasets derived from midbrain organoid protocols also show high proportions of hindbrain neurons, indicating an imprecision of morphogen guidance. to comprehensively evaluate how well organoid protocols represented by the hnoca generate primary brain cell types, we estimated presence scores for every primary cell type in each hnoca dataset ( methods ). a large presence score indicates high frequency and likelihood that cells of a similar type are observed in the hnoca dataset. by normalizing the scores per organoid dataset ( extended data fig. 5 and supplementary table 3 ), we obtained a metric to describe how well each primary cell type is represented in at least one hnoca dataset ( fig. 2d ). this analysis confirmed the absence of erythrocytes, immune cells and vascular endothelial cells in the hnoca, all of which are derived from non - neuroectodermal germ layers ( fig. 2e ). as expected, telencephal ic cell types are most strongly represented in hnoca. by contrast, cell types of the thalamus, midbrain and cerebellum are least represented, including thalamic reticular nucleus gabaergic neurons, dorsal midbrain m1 - derived gabaergic neurons and m1 / m2 - derived glutamatergic neurons, and cerebellar purkinje cells ( fig. 2f, g ). it is worth noting that, even though these cell types are less abundant in hnoca datasets than in the primary atlas, certain organoid protocols can generate some of these under - represented cell types ( for example, purkinje cells in posterior brain organoid protocols ). we next aimed to understand the transcriptomic similarities and differences between organoids generated by distinc t differentiation protocols as well as between organoids and primary brain tissue. we identified differentially expressed genes ( degs ), comparing neural cell types in the hnoca with their primary counterparts ( fig. 3a and supplementary table 4 ). we found that for most neural cell types, more than one - third ( mean 34. 4 %, standard deviation 12. 1 % ) of degs were shared across at least half of the protocols ( protocol - common degs ), suggesting that many transcriptomic differences between organoid and primary cells were independent of organoid protocol ( fig. 3b ). we verified our results using an extra primary human cortex scrna - seq dataset ( extended data fig. 6 and supplementary table 5 ). we next assessed differential transcriptomic programmes that were shared across regional neural cell types, and identified a total of 920 ubiquitous, protocol - common degs ( udegs ) that were differentially expressed in at least 14 out of the 16 neural cell types ( fig. 3c ). these udegs showed consistent fold changes ( r > 0. 8 ) across neuron types and protocols ( fig. 3d ), and represent consistent molecular differences between neurons in organoids and those in primary tissues regardless of protocol or neuronal cell type. out of all 920 udegs, 363 genes were consistently upregulated and 673 genes were consistently downregulated, with only 59 genes ( 6 % ) inconsistently differentially expressed across subtypes or protocols ( fig. 3e ). using gene ontology enrichment analysis on the udegs, we found downregulated udegs enriched in neurodevelopmental processes including neuron cell – cell adhesion and synapse organization ( fig. 3f ). upregulated udegs were enriched in many metabolism - associated terms including mitochondrial atp synthesis - coupled electron transport ( electron transport in short ) and canonical glyco lysis ( fig. 3f ). an enrichment of energy - associated pathways has previously been associated with metabolic changes caused by the limitations of current culture conditions. also, the molecular signatures database gene set hallmark glyco lysis has previously been used to define metabolic states in neural organoids. scoring mitochondrial electron transport, canonical glyco lysis and hallmark glyco lysis gene sets across the hnoca and the primary reference atlas, we found that all three terms showed significant separation of organoid and primary cells ( fig. 3g, h ). using the datasets from refs. and as representative examples, we identified a similar distribution of glyco lysis scores across all neural cell types with an overall increased score in organoid cells ( extended data fig. 7 ). focusing on dorsal telencephal ic neurons, we compared the distribution of glyco lysis scores across organoid differentiation protocols and identified several protocol features that correlated with metabolic cell stress. for instance, the usage of maturation media, slicing or cutting of organoids and, to a lesser extent, shaking or spinning of organoids led to overall lower glyco lysis scores ( fig. 3h ). mean glyco lysis score and transcriptomic similarity of organoid and primary reference cell types across differentiation protocols were negatively correlated. the correlation was significantly reduced when considering only variable transcription factors, indicating that the metabolic changes in organoids have limited impact on the core molecular identity of neuronal cell types ( extended data fig. 7 ). this observation is consistent with previous studies of distinc t metabolic states of cells in neural organoids relative to the primary tissue, which were shown to not affect neuron fate specification and maturation. next, we focused on the expression of 366 variable transcription factors to calculate the correlation between corresponding neuronal cell types in the hnoca datasets and the primary reference atlas. we found that both guided and unguided organoid differentiation protocols generated neuronal cell types with comparable similarity to the corresponding primary reference cell types. however, we observed brain region - dependent differences in transcriptomic similarity.