Cell types, connectivity, and computation: reconstructing molecularly annotated connectome of the mouse visual cortex

architecture of functional neural networks? To overcome this bottleneck, evolution has endowed animal brains with specialised neuronal cell types that follow different rules in selecting their synaptic partners and therefore play distinct roles in the circuit. The neocortex contains ~14 distinct cell types, conserved across cortical areas and further divisible into fine-grained transcriptional subclasses whose composition varies across the cortex[1], suggesting that they may support different specialised computations.

We use the mouse visual cortex as a model[2, 3] and apply a range of tools to link the in vivo properties, connectivity and gene expression of cortical neurons. Central to this effort is Barcoded Rabies In Situ Connectomics (BRISC)[4], a method we recently developed that uses rabies viruses expressing molecular barcodes to trace thousands of synaptic connections in a matter of weeks, read out by in situ sequencing alongside endogenous gene expression. Within this framework, we are especially interested in understanding how visual cortical circuits enable animals to process the three-dimensional organisation of visual scenes.

The details of the project will be tailored to the interests of the successful candidate. Projects below provide examples of possible research directions.

Connectomics and transcriptomics of cortical wiring

This project will map the connectivity of cortical neurons at unprecedented scale, asking how inputs onto single neurons are organised and how the connectivity of individual cells relates to their gene expression. It will use BRISC together with in situ sequencing to read out input connectivity and transcriptional identity in the same cells, and develop data-driven models that bridge gene expression and circuit architecture. It offers a unique opportunity to work at the intersection of barcoded neuroanatomy, spatial transcriptomics and computational modelling.

Cell types and the cortical representation of depth

To guide behaviour, the brain must infer the structure of the world from the two-dimensional images formed on the retinae. Depth perception is innate in most mammals, does not require visual experience, and does not depend on binocular vision; visual motion is instead thought to be an essential depth cue. Building on our discovery that neurons in mouse primary visual cortex show widespread depth selectivity driven by motion parallax[5], we hypothesise that this innate capacity is mediated by specialised, hardwired cell types. This project will ask how the cell types of the cortical microcircuit respond to three-dimensional visual stimuli and how inputs onto single depth-selective neurons shape their responses, reconstructing a molecularly annotated connectome of the visual cortex in mice navigating virtual reality. It combines multiphoton calcium imaging, correlative in situ sequencing and molecular connectomics.

Candidate background

This project would suite candidates with a background in Neuroscience, Molecular Biology, Bioengineering, Computational Biology, or a related field.

Lab-specific question

Looking at the research undertaken in our lab, what would be your dream experiment to understand mechanisms of neural computation? What do you think would be the main challenge?

Funding Notes

Successful applicants will be awarded a non-taxable annual stipend of £27,715 plus payment of university tuition fees. Students of all nationalities are eligible to apply.

References

1. Tasic, B., Yao, Z., Graybuck, L.T., Smith, K.A., Nguyen, T.N., Bertagnolli, D., . . . Zeng, H. (2018) Shared and distinct transcriptomic cell types across neocortical areas. Nature 563: 72–78. PubMed abstract
2. Kim, M.H., Znamenskiy, P., Iacaruso, M.F. and Mrsic-Flogel, T.D. (2018) Segregated Subnetworks of Intracortical Projection Neurons in Primary Visual Cortex. Neuron 100: 1313–1321 e1316. PubMed abstract
3. Znamenskiy, P., Kim, M.H., Muir, D.R., Iacaruso, M.F., Hofer, S.B. and Mrsic-Flogel, T.D. (2024) Functional specificity of recurrent inhibition in visual cortex. Neuron 112: 991–1000 e1008. PubMed abstract
4. Becalick, A., Blot, A., Strom, M. and Znamenskiy, P. (2025) Preprint: Barcoded Rabies In Situ Connectomics for high-throughput reconstruction of neural circuits. Available at: bioRxiv https://www.biorxiv.org/content/10.1101/2025.07.16.665048v1.full.pdf
5. He, Y., Colas Nieto, A., Blot, A. and Znamenskiy, P. (2024) Preprint: A depth map of visual space in the primary visual cortex. Available at: bioRxiv https://www.biorxiv.org/content/10.1101/2024.09.27.615442v1.full.pdf