Sihoon Moon

The paper uses network modularity to analyze time-varying functional connectivity in single-cell neural recordings, showing how context and network state influence module organization in C. elegans and whole-brain activity.

This study shows that aversive learning in C. elegans reorganizes neural dynamics globally, altering activity only during specific tasks while preserving essential functions.

This paper introduces a microfluidics-compatible open-top light-sheet microscope using model predictive control of a tunable lens to enable high-speed 3D imaging of C. elegans.

This paper develops and provides a set of optimized GCaMP reporters for C. elegans functional imaging, offering improved dynamic range, varied kinetics, and subcellular localization.

This paper introduces a deep learning framework for neuro-imaging denoising that improves speed, memory efficiency, and accuracy while requiring minimal training data.