a, SPRING plots visualizing the kNN networks of human (10,063) and chimpanzee (5,612) pseudocells, and macaque cells (6,580), which represent NPCs and neurons of different brain regions. Cortical NPCs and neurons are coloured by their pseudotimes. b, Ratios of upper layer (UL) to deeper layer (DL) neuron marker expression in human (black), chimpanzee (dark grey) and macaque (light grey) organoids. The dashed line indicates the cut-off applied to human pseudocells to filter out those representing UL neurons. c, Truncated dynamic time warping (DTW)-based alignment was applied to align human, chimpanzee and macaque cortical pseudotime courses. Two support vector regression models were trained to predict chimpanzee (top) and macaque (bottom) pseudotimes of human pseudocells. A constrained B-splines regression model was fitted to determine the trimming point at the chimpanzee and macaque pseudotime courses, respectively. An end-to-end DTW-based alignment was applied to the human pseudotime course to the trimmed chimpanzee and macaque pseudotime courses for the final alignments (middle). d, Pseudotemporal expression profiles of GLI3, EOMES and BCL11B along the human, chimpanzee and macaque cortical pseudotimes, before (left) and after (right) the pseudotime alignment procedures. e, Robustness and false-positive rate of differential pseudotemporal expression between human and chimpanzee based on the number of cell lines involved in the analysis with constrained replaceable pseudocell subsampling. In each subsampling, pseudocells representing cells from a certain number of human lines were sampled in a replaceable manner to recapitulate pseudocell distribution along pseudotime course of the chimpanzee pseudocells. Differential expression analysis was applied to compare all chimpanzee pseudocells and the sampled human pseudocells to estimate robustness to cell line numbers (dark grey boxes), and to compare sampled human pseudocells to human pseudocells from another two lines sampled with the same procedure to estimate false-positive rate (light grey boxes). In box plots, boxes represent 100 times of subsampling IQR, the line represents 1.5 × IQR and dots represent outliers. f, Robustly detected human–chimpanzee differentially expressed genes (robust DE genes) are defined as the non-ribosomal genes which were detected as DE in at least 80% of the subsampling-based human–chimpanzee DE analysis using any number of human lines (black). The dendrogram shows the hierarchical clustering of robust DE genes, based on their human–chimpanzee pseudotemporal DE patterns along the aligned pseudotimes of cortical organoid pseudocells, resulting in eight clusters of robust DE genes. g, Pseudotemporal differential expression patterns between human and chimpanzee (without including macaque cells) of the eight clusters of genes along the pseudotimes of cortical organoid pseudocells with 50% and 95% confidence intervals shown in dark and light grey, respectively. Numbers of genes in each cluster are shown in parenthesis. h, Number of differentially expressed genes in chimpanzee versus human and macaque comparison grouped by gain or loss of expression in chimpanzees. A gain of expression specifically in chimpanzees is more likely than a loss of expression pattern conserved in the other primates. i, Comparison of the reported human–chimpanzee pseudotemporal differential expression based on 10x Genomics data with the Fluidigm C1-based scRNA-seq data of human and chimpanzee cerebral organoids. The two rows show the results based on C1 data generated in this manuscript and combined with data from refs. 11,15,16. The first two columns show estimated human–chimpanzee differential expression directionality and magnitude in the reported droplet-based scRNA-seq data and the C1-based measurement, with the first column presenting the generalized differential expression along the whole cortical pseudotimes, and the second column presenting the maximum differential expression along the pseudotimes. The red dots represent consistently differentially expressed genes, which have consistent differential expression directionalities in the two datasets. The right panel shows pseudotime intervals with the largest human–chimpanzee differential expression in the two datasets in comparison to the consistent differentially expressed genes. Dot sizes represent frequencies. j, Comparison of the estimated human–macaque differential expression directionality and magnitude of the human-specific differentially expressed genes using human and macaque fetal prefrontal cortex scRNA-seq data16,19. k, Functional annotations of genes with human-specific expression patterns based on GO annotations related to brain development and neurogenesis. Only the human-specific differentially expressed genes with consistent human–chimpanzee or human–macaque differential expression detected in at least one of the three C1-based scRNA-seq datasets are shown. l, Ventral telencephalon cell heterogeneity in organoids was investigated by t-SNE embeddings with RSS profiles of human (3,385) and chimpanzee ventral (773) pseudocells combined as the input. Pseudocell clusters were annotated on the basis of marker gene expression. Pseudocells were also coloured by species and diffusion map based on MGE neuron developmental pseudotimes. m, t-SNE plots coloured by marker gene expression and in situ hybridization images from the Allen Developing Mouse Brain Atlas (available from https://developingmouse.brain-map.org/) showing expression of Dlx5, Isl1 and Sox6 in the mouse developing ventral forebrain embryonic day 13.5 (E13.5). n, Human–chimpanzee ventral differentially expressed genes are largely shared along the dorsal forebrain developmental trajectories. o, Human–chimpanzee DE directionalities and magnitudes and DE gene detection rates on the two trajectories. DE directionalities and magnitudes are consistent on the dorsal and MGE trajectories, with most of the shared DE genes showing the highest human–chimpanzee expression divergence at NPC. DE genes specifically detected on one trajectory have the tendency of higher detection rates on the trajectory where human–chimpanzee differential expression is detected.