Nino F. Läubli

NeuroSuite provides a non-invasive platform for long-term electrophysiological monitoring of brain organoids, revealing neural network development and activity changes.

This study shows α-synuclein modulates spontaneous dopamine release via calcium and phosphorylation-dependent mechanisms, independent of full-fusion recycling.

The paper shows that Aβ and mutant Tau reduce neuronal activity in young C. elegans before amyloid aggregation, with muscle-expressed Aβ affecting neurons via retrograde signaling.

The paper develops a hybrid machine learning framework to identify TDP-43 aggregation inhibitors, discovering two compounds effective in reducing aggregation in cell and model organism assays.

FLIMngo, a deep learning model, enables fast and accurate fluorescence lifetime predictions from low-photon FLIM data, improving throughput and reducing phototoxicity for in vivo applications.

FLIMPA is an open-source software for FLIM phasor analysis that integrates data from multiple trials and provides tools for quantifying microtubule depolymerisation.

The paper introduces PseudoSort, a machine learning algorithm for spike sorting, and applies it to MEA data from hippocampal neurons exposed to monomeric Tau, revealing its impact on neuronal activity.