Лей Ма

This paper introduces CLG, a structural-functional calibration method for volumetric calcium imaging that corrects neuron identity errors, reducing duplicate counts and improving network analysis accuracy.

This paper introduces EM-DINO and OmniEM, a foundation model and architecture for EM image analysis, improving restoration and segmentation across diverse datasets.

MetaWorm integrates brain, body, and environment simulations to model C. elegans behavior, revealing how neural structure influences activity and movement.

This paper introduces a GPU-based framework that accelerates neuron simulations and applies it to neuroscience and AI tasks, showing significant speed improvements over traditional methods.

This paper introduces DeepDAM, a framework that improves neural connectivity inference by aligning synthetic and in vivo data domains, achieving high accuracy in rodent and other systems.

The paper introduces U-RISC, a high-resolution EM dataset for cell membrane segmentation, and evaluates deep learning methods, finding a gap between current performance and human-level accuracy.