Automated neuron tracking inside moving and deforming animals using deep learning and targeted augmentation
Mahsa Barzegar Keshteli, Vladislav Susoy, Core Francisco Park, Kseniia Korchagina, Ariane Delrocq, Aravinthan D. T. Samuel, Sahand Jamal Rahi · COSYNE 2023
Advances in functional brain imaging now allow sustained rapid 3D visualization of large numbers of neurons inside behaving animals. To decode circuit activity, imaged neurons must be individually segmented and tracked. This is particularly challenging when the brain itself moves and deforms inside a flexible body. The field has lacked general methods for solving this problem effectively. To address this need, we developed a method based on a convolutional neural network (CNN) with specific enhancements which we apply to freely moving C. elegans. For a traditional CNN to track neurons across i
Sat, Mar 11, 2023