FRM 2025 Symposium

Advances and applications in Voltage Imaging

When

Wednesday, 18 June

09:45-11:00

Where

University of Oslo,
campus Blindern

SLH, Sophus Lies auditorium

Chairs:

Matthijs Dorst, University of Oslo, Norway

Janos Fuzik, Karolinska Institutet, Sweden

Speakers:

Christiane Grimm, Vision Institute, France

Weijian Zong, NTNU Norwegian University of Science and Technology, Norway

Madhuvanthi Kannan, University of Minnesota, USA

Abstract

The ability to infer neural activity through optical methods has gained widespread adoption over the last decade, primarily in the form of calcium imaging. Voltage imaging provides a more faithful record of membrane potentials, but has historically proven technically challenging to implement. In recent years, new voltage sensors and new imaging modalities have been developed that finally bring voltage imaging within practical reach. Thus, in recent years, Voltage Imaging has matured from a niche application that requires great technical expertise and limited applicability, to a practical tool that can now be implemented by a broad range of labs. Advances in both sensors and microscopy techniques have recently opened up Voltage Imaging to a much wider range of applications. The objectives for this symposium are therefore as follows:

1. To demonstrate practical applications of voltage imaging, and highlight the unique capabilities offered by this technique.

2. To provide insight into newly developed microscopy systems which further broaden its usability.

Our speakers include Dr. Christiane Grimm, who is working on development on holographic voltage imaging techniques, Dr. Weijian Zong whose work enables recording voltage signals in freely moving animals, and Dr. Madhuvanthi Kannan who will present her work on multipopulation voltage imaging to investigate the dynamic interplay between cortical neuron-types in visual function and attention. These speakers and their work offer a unique glimpse into the exciting future of all-optical electrophysiology.

Keywords

AI; computational neuroscience; neural circuits