@article {65321, title = {Rapid mesoscale volumetric imaging of neural activity with synaptic resolution.}, journal = {Nature Methods}, volume = {17}, year = {2020}, month = {2020 Mar 02}, pages = {291-4}, abstract = {

Imaging neurons and neural circuits over large volumes at high speed and subcellular resolution is a difficult task. Incorporating a Bessel focus module into a two-photon fluorescence mesoscope, we achieved rapid volumetric imaging of neural activity over the mesoscale with synaptic resolution. We applied the technology to calcium imaging of entire dendritic spans of neurons as well as neural ensembles within multiple cortical regions over two hemispheres of the awake mouse brain.

}, issn = {1548-7105}, doi = {10.1038/s41592-020-0760-9}, author = {Lu, Rongwen and Liang, Yajie and Meng, Guanghan and Zhou, Pengcheng and Svoboda, Karel and Paninski, Liam and Ji, Na} } @article {67280, title = {CaImAn an open source tool for scalable calcium imaging data analysis}, journal = {eLife}, volume = {8}, year = {2019}, month = {01/2019}, abstract = {

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. We present CaImAn, an open-source library for calcium imaging data analysis. CaImAn\ provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good scalability on computers ranging from laptops to high-performance computing clusters. CaImAn\ is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn\ we collected and combined a corpus of manual annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn\ achieves near-human performance in detecting locations of active neurons

}, doi = {10.7554/eLife.38173}, url = {https://elifesciences.org/articles/38173}, author = {Giovannucci, Andrea and Friedrich, Johannes and Gunn, Pat and Kalfon, J{\'e}r{\'e}mie and Brown, Brandon L and Koay, Sue Ann and Taxidis, Jiannis and Najafi, Farzaneh and Gauthier, Jeffrey L and Zhou, Pengcheng and Khakh, Baljit S and Tank, David W and Chklovskii, Dmitri B and Pnevmatikakis, Eftychios A} } @article {67289, title = {CalmAn: An open source tool for scalable Calcium Imaging data Analysis}, journal = {bioRxiv}, year = {2018}, month = {06/2018}, abstract = {

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over the course of months. Here we present CaImAn, an open-source library for calcium imaging data analysis. CaImAn provides automatic and scalable methods to address problems common to pre-processing, including motion correction, neural activity identification, and registration across different sessions of data collection. It does this while requiring minimal user intervention, with good performance on computers ranging from laptops to high-performance computing clusters. CaImAn is suitable for two-photon and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the performance of CaImAn we collected a corpus of ground truth annotations from multiple labelers on nine mouse two-photon datasets. We demonstrate that CaImAn achieves near-human performance in detecting locations of active neurons.

}, doi = {10.1101/339564}, url = {https://www.biorxiv.org/content/early/2018/06/05/339564}, author = {Giovannucci, Andrea and Friedrich, Johannes and Gunn, Pat and Kalfon, J{\'e}r{\'e}mie and Koay, Sue Ann and Taxidis, Jiannis and Najafi, Farzaneh and Gauthier, Jeffrey L. and Zhou, Pengcheng and Tank, David W. and Chklovskii, Dmitri and Pnevmatikakis, Eftychios A.} }