New lab member

We are pleased to welcome to Chiara to the lab!

Chiara joins us on our Wellcome funded project on the retinal basis of vision in fish. She will be studying the cone-type dependence of various visual behaviours and their underlying circuits.

New paper about cone-integration on bioRxiv

Bartel P, Yoshimatsu T, Janiak FK, Baden T§. Spectral inference reveals principal cone-integration rules of the zebrafish inner retina. bioRxiv doi: 10.1101/2021.08.10.455697. direct link pdf.

The central goal of this study was to try and infer the total effective cone-integration logic of bipolar cells in larval zebrafish by way of linking highly resolved spectral tuning functions across these two populations of neurons.

We previously showed that the four zebrafish cones exhibit distinct but highly stereoypical tunings at the level of their output (Yoshimatsu et al. bioRxiv 2020). Accordingly, we used the same recording conditions to also obtain spectral tuning functions of the downstream neurons, the retinal bipolar cells (right).

We find that this works very well, allowing us to explain ~95% of the variance in bipolar cell responses based on linear cone-combinations. Based on this, we chart an overview of the total cone-integration logic in larval zebrafish, and relate these insights to spectral processing in mammalians.

 

Paper on ribbon-tuning now out at eLife

With EM, 2p-imaging and computational modelling we show that on the synaptic level of single neuron types in the retina there exist highly specialized mechanisms which are advantageous for the encoding of different visual features. 

Already in EM we see different geometries of the ribbon depending on the location of the UV-cones.

We confirm these differences by “dual-color” 2-photon imaging of pre-synaptic calcium and glutamate release of the synapse.

We use these recordings to build a computational model of the ribbon synapse, which reproduces region-specific response properties. An interactive model tool can be found on #github and you can run it on #googlecolab here: http://www.tinyurl.com/h3avl1ga

By using simulation-based inference we get full posterior estimations of the parameter distributions and can compare these between different retinal regions.

Finally, the computational model allows us to extrapolate to new stimuli and predict response behaviours of different synapse configurations. Hereby we identify principles which are advantageous for the encoding of different visual features, which may be more relevant in different locations of the visual field.

This work builds on previous findings, where we showed fovea-like photoreceptor specializations in UV Cones in zebrafish, which drives prey-capture behavior: https://www.cell.com/neuron/pdf/S0896-6273(20)30313-5.pdf

Congratulations Dr. Mingyi!

We are most delighted that Mingyi Zhou has just passed her PhD viva!

For her thesis, Mingyi investigated spectral processing in zebrafish retinal ganglion cells.

Thank you to Rob Hindges and Corne Kros for serving as examiners, and Leon Lagnado for chairing!

Mingyi’s papers

Zhou M*, Bear J*, Roberts PA, Janiak FK, Semmelhack J, Yoshimatsu T, Baden T§. Zebrafish Retinal Ganglion Cells Asymmetrically Encode Spectral and Temporal Information Across Visual Space. Current Biology 30, 2927-2942. (bioRxiv version). direct link. pdf.

Janiak FK§, Bartel P, Bale M, Yoshimatsu T, Komulainen EH, Zhou M, Staras K, Prieto Godino LL, Euler T, Maravall M, Baden T§. Divergent excitation two photon microscopy for 3D random access mesoscale imaging at single cell resolution. bioRxiv doi: https:/doi.org/10.1101/821405. direct link. pdf.

 

New lab members

We are pleased to welcome to Eira and Carola to the lab.

Eira is part of the new Leverhulme DTC on biomimetic AI at Sussex. She will be doing her PhD on individual differences in zebrafish vision. Her project is co-supervised by Jenny Bosten from Sussex Psychology.

Carola is a new MarieCurie Fellow, with additional support from the Leverhulme Trust. She will work on “Colour vision in the dark“, using the frog visual system as a model.