Larissa Heinrich

The paper investigates how neuronal populations encode visual scenes invariant to perspective changes, finding equivariant structures in higher-order visual areas.

This paper creates high-resolution brain and ventral nerve cord templates for Drosophila using advanced imaging and registration techniques, showing improved accuracy and efficiency compared to existing templates.

The paper presents an automatic method to identify synaptic partners in a whole-brain Drosophila EM dataset using convolutional neural networks, achieving high accuracy in predicting synaptic connections.