资源环境科技发展态势分析平台

Our understanding of how human embryos develop before gastrulation, including spatial self-organization and cell type ontogeny, remains limited by available two-dimensional technological platforms(1,2) that do not recapitulate the in vivo conditions(3-5). Here we report a three-dimensional (3D) blastocyst-culture system that enables human blastocyst development up to the primitive streak anlage stage. These 3D embryos mimic developmental landmarks and 3D architectures in vivo, including the embryonic disc, amnion, basement membrane, primary and primate unique secondary yolk sac, formation of anterior-posterior polarity and primitive streak anlage. Using single-cell transcriptome profiling, we delineate ontology and regulatory networks that underlie the segregation of epiblast, primitive endoderm and trophoblast. Compared with epiblasts, the amniotic epithelium shows unique and characteristic phenotypes. After implantation, specific pathways and transcription factors trigger the differentiation of cytotrophoblasts, extravillous cytotrophoblasts and syncytiotrophoblasts. Epiblasts undergo a transition to pluripotency upon implantation, and the transcriptome of these cells is maintained until the generation of the primitive streak anlage. These developmental processes are driven by different pluripotency factors. Together, findings from our 3D-culture approach help to determine the molecular and morphogenetic developmental landscape that occurs during human embryogenesis.

A 3D culture system to model human embryonic development, together with single-cell transcriptome profiling, provides insights into the molecular developmental landscape during human post-implantation embryogenesis.

Primate inferotemporal cortex contains a coarse map of object space consisting of four networks, identified using functional imaging, electrophysiology and deep networks.

The inferotemporal (IT) cortex is responsible for object recognition, but it is unclear how the representation of visual objects is organized in this part of the brain. Areas that are selective for categories such as faces, bodies, and scenes have been found(1-5), but large parts of IT cortex lack any known specialization, raising the question of what general principle governs IT organization. Here we used functional MRI, microstimulation, electrophysiology, and deep networks to investigate the organization of macaque IT cortex. We built a low-dimensional object space to describe general objects using a feedforward deep neural network trained on object classification(6). Responses of IT cells to a large set of objects revealed that single IT cells project incoming objects onto specific axes of this space. Anatomically, cells were clustered into four networks according to the first two components of their preferred axes, forming a map of object space. This map was repeated across three hierarchical stages of increasing view invariance, and cells that comprised these maps collectively harboured sufficient coding capacity to approximately reconstruct objects. These results provide a unified picture of IT organization in which category-selective regions are part of a coarse map of object space whose dimensions can be extracted from a deep network.