Theresa Wiesner

Astro-BEATS detects and segments miniature synaptic calcium transients in fluorescence imaging using astronomical transient detection techniques, outperforming threshold-based methods and enabling efficient training of deep learning models.

The paper presents a presynapse-on-glass model to study presynaptic actin architecture, showing actin enrichment correlates with synaptic cycling activity and identifies actin nanostructures.

The paper shows spectrin condensates facilitate the formation of the periodic axonal structure by acting as local assembly hubs that later develop into a stable lattice.

The paper identifies non-synaptic exocytosis along axon shafts and shows how the submembrane actin-spectrin skeleton regulates this process.

This paper introduces a PU learning-based method for detecting and segmenting miniature synaptic calcium transients, showing improved performance over traditional methods in cultured rat neurons.

This paper introduces TA-GAN, a deep learning model that enhances image resolution in optical nanoscopy by incorporating auxiliary tasks, improving accuracy and enabling online imaging assistance.

The paper uses deep learning to analyze F-actin structures in hippocampal neurons, showing activity-dependent remodeling in dendrites but not axons.