New preprint from the lab

Very proud of our new preprint in which we model the impact of retinal and non-retinal inputs on dLGN activity. We find that a subpopulation of poorly visually responsive neurons profits most from accounting of non-retinal inputs in our model. In addition, our model uncovered that CT feedback is most effective in the absence of a patterned visual stimulus, Finally, stimulus information can be better decoded during suppression of CT feedback. We discuss how these findings can be embedded into current views on the role of CT feedback in stimulus processing.

Welcome to Nancy Mulaiese!

We are very happy to welcome Nancy Mulaiese as a new doctoral researcher to the team. Nancy is joining through the IMPRS-BI program and will work on an exciting project regarding the impact of cortico-thalamic feedback on information processing in visual cortex. We will perform detailed circuit manipulations and recordings from dLGN and V1. We will also collaborate with Tatjana Tchumatchenko on extending V1 network models with the thalamo-cortico-thalamic loop.

New publication from the lab by previous doctoral researcher Simon Renner

Very proud of this new publication from the lab, driven forward on the LMU side by previous doctoral researcher Simon Renner. Within the SPP2041 Computational Connectomics and in a tight experiment-theory collaboration with Tatjana Tchumatchenko‘s lab, we worked on inferring connectivity of V1 and the thalamic inputs exploiting the stabilized supralinear network.

Kraynyukova, N.*, Renner, S.*, Born, G., Bauer, Y., Spacek, M.A., Tushev, G., Busse, L.**, Tchumatchenko, T.** (2022). In vivo extracellular recordings of thalamic and cortical visual responses reveal V1 connectivity rules. Proc. Natl. Acad. Sci. U.S.A. 119, e2207032119. [*shared first authors, **shared last authors]

Welcome to Verena Peterreins!

A warm welcome to Verena Peterreins who returns to the lab after a successful MSc thesis in Human Biology as a GSN doctoral researcher! Verena will use the next few months to dive deep into our project on “Natural stimuli for mice”. Welcome to the team!

New bioRxiv preprint

Very proud to share a new bioRxiv preprint, where we explore how efficient coding can improve predictions of neural responses to noise stimuli. This work resulted from a fantastic collaboration with Thomas Euler’s lab, as part of the SFB1233 on Robust Vision.

Qiu, Y., Klindt, D.A., Szatko, K.P., Gonschorek, D., Hoefling, L., Schubert, T., Busse, L., Bethge, M., and Euler, T. (2022). Efficient coding of natural scenes improves neural system identification. BioRxiv, https://doi.org/10.1101/2022.01.10.475663

Welcome to Anna Kryshtal

A warm welcome to GSN student Anna Kryshtal who will spend the next few weeks in our group. In her lab rotation, she will contribute to our project on estimating connectivity from extracellular activity.

Welcome to two new doctoral researchers

We welcome Ann H Kotkat and Lukas Meyerolbersleben who joined our lab and the GSN for their doctoral studies. Both Ann and Lukas have done their MSc thesis with us – looking forward very much to continuing working together!