Reconstructing wiring rules of in vivo neural networks using simultaneous single-cell connectomics and transcriptomics

2026-07-22

The brain performs sophisticated functions and complex behaviours, orchestrated by highly specialized cells. Neurons are at the core of the nervous system’s computational capabilities. In recent years, we and others have advanced single-cell RNAseq to reveal their extraordinary molecular diversity in transcriptome-based cell-type taxonomies. It is the unique combinations of circuits that these different neuronal types form – within a practically unlimited space of possible implementations – that encode the large functional repertoire of the nervous system. Although critical, little is known about the basic organizational principles of cells within the circuits – the ‘wiring rules’. This highlights the conceptual challenge to measure connectivity on a systematic and synaptic, single-cell level. What is the topology of networks? What is the relation between network topology and function? How do cell types and gene expression determine wiring? Answering these questions will help resolve nervous system computation at the level of its cellular building blocks. The vision of this proposal is to provide and apply a novel approach that will allow us to investigate neuronal connectivity at large-scale. Two key requirements for such measurements are the ability to measure true synaptic connections, and obtain tens of thousands of datapoints. Further, the concept of cell types is crucial for addressing the connectivity problem, as it allows us to distinguish the network elements and thus assemble a global picture even from fragmented, partial measurements. For this purpose, we will combine transcriptomics and connectomics measurements at the single cell level. The proposed project has enormous potential to systematically (re)address basic functional questions in neuroscience. It can expand our understanding of neural circuits to an unprecedented resolution, with conceivable impact on computational research, such as in vivo inspired neural networks and artificial intelligence.

Israel

2026-02-01