Periodic Reporting for period 3 - TYPEWIRE (Reconstructing wiring rules of in vivo neural networks using simultaneous single-cell connectomics and transcriptomics)
Reporting period: 2023-01-01 to 2024-06-30
The brain performs sophisticated functions and complex behaviours, orchestrated by highly specialized cells. Neurons are the cells at the core of the nervous system’s computational capabilities. In recent years, we and others have advanced single-cell RNA-sequencing 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. However, little is known about the basic organizational principles of cells within the circuits – the ‘wiring rules’: 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 understand nervous system computation at the level of its cellular building blocks. But we face a conceptual challenge to measure connectivity on a large scale, with resolution to single cells. The vision of this proposal is to develop and apply a new approach that will allow us to investigate neuronal connectivity: We aim to measure synaptic connections, across tens of thousands of neurons, with known cell type identity. The proposed project has the 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.
Answering these questions will help understand nervous system computation at the level of its cellular building blocks. But we face a conceptual challenge to measure connectivity on a large scale, with resolution to single cells. The vision of this proposal is to develop and apply a new approach that will allow us to investigate neuronal connectivity: We aim to measure synaptic connections, across tens of thousands of neurons, with known cell type identity. The proposed project has the 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.
In the past funding period, we have focused our efforts on establishing several of the challenging techniques required to measure neuronal connections both by fluorescence microscopy, and by RNA-sequencing. Based on our initial, sometimes surprising results, we were also inspired to develop other, parallel approaches that may help address some quantitative aspects of neuronal connectivity. We targeted a number of regions in the brain concerned with spatial navigation, learning and memory, or social behaviors. We are beginning to learn of some differences between wiring in male and female mice, but mostly, have gained many important insights into the possibilities – and limits – of our method and model system.
In the coming years, we initially aim to simultaneously acquire several nodes of information about neurons participating in a network: their spatial location, their numbers, and their molecular description; and how these features may differ between regions executing different functions. Eventually. we want to achieve step-wise improved resolution of the networks we measure, down to the level of the single neurons inputting to each other.