An expanded GCaMP reporter toolkit for functional imaging in Caenorhabditis elegans.

In living organisms, changes in calcium flux are integral to many different cellular functions and are especially critical for the activity of neurons and myocytes. Genetically encoded calcium indicators (GECIs) have been popular tools for reporting changes in calcium levels in vivo. In particular, GCaMPs, derived from GFP, are the most widely used GECIs and have become an invaluable toolkit for neurophysiological studies.

Automated cell annotation in multi-cell images using an improved CRF_ID algorithm.

Cell identification is an important yet difficult process in data analysis of biological images. Previously, we developed an automated cell identification method called CRF_ID and demonstrated its high performance in whole-brain images (Chaudhary et al, 2021). However, because the method was optimized for whole-brain imaging, comparable performance could not be guaranteed for application in commonly used multi-cell images that display a subpopulation of cells.

An expanded GCaMP reporter toolkit for functional imaging in .

In living organisms, changes in calcium flux are integral to many different cellular functions and are especially critical for the activity of neurons and myocytes. Genetically encoded calcium indicators (GECIs) have been popular tools for reporting changes in calcium levels . In particular, GCaMP, derived from GFP, are the most widely used GECIs and have become an invaluable toolkit for neurophysiological studies.

Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning.

Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applied to denoise images, their applications to downstream analyses, such as recovering high-SNR calcium traces, have been limited. Further, these methods require temporally-sequential pre-registered data acquired at ultrafast rates.