MULTIVIsion

Multiphoton Voltage Imaging

Overall aim: Understanding the brain through novel tools and methods to perturb, record and interpret brain activity based on advances in physical sciences and engineering.   

Specific aim: Development and application of genetically encoded voltage indicators (GEVIs) for mulitiphoton Voltage Imaging. The project aims to evolve, characterize and apply a rhodopsin scaffold with superior properties for multiphoton voltage imaging (in terms of sensitivity, photon budget and speed compared to current multiphoton GEVIs), and apply this construct in a motor learning assay while imaging cells in the olivocerebellar loop, to investigate whether there is information about the learning process in the detailed electrical dynamics of the cells under investigation.

Understanding the brain is one of the great scientific challenges of our time. This pursuit fundamentally depends on advances in physical sciences and engineering to provide novel tools and methods to perturb, record and interpret brain activity. Information in the brain is encoded in changes in the voltage across the membrane of brain cells. Voltage imaging with genetically encoded voltage indicators (GEVIs) is a revolutionary method that allows faithful recording of the fast electrical dynamics of many genetically targeted cells in parallel. This provides an unprecedented means to record how patterns of change in this membrane voltage, called action potentials, manifest in subcellular compartments, cells, and networks across the brain, which is the only way to arrive at a fundamental understanding of brain functions like learning and memory, and of neurogenerative diseases. For this promise to be fulfilled, we need voltage imaging deep in the living brain of awake and behaving organisms. To achieve this, I will evolve a GEVI optimized for multiphoton (2P and 3P) imaging, by screening mutant libraries of GEVIs directly for brightness and photostability under 2P and 3P-excitation, voltage sensitivity, and membrane trafficking in neurons. I will optimize the photocycle dynamics of GEVIs with temporally structured light, using a NOPA with tunable repetition rate, pockels cell and multiple optical delay lines, to create optimal multiphoton excitation protocols. Crucially, this optimization will not depend on spectral phase and is therefore compatible with high speed multiphoton imaging, aberration correction, and deep tissue imaging. The developed constructs will be applied in a cerebellar imaging assay in a mouse model, while performing an eye blink task. The objective is to achieve faster and more faithful imaging of cerebellar dynamics influenced by learning than currently possible.

Time frame: 09.12.2022 – 31.03.2023

Funding: ERC (EU Funding)