Submitted to the Annals of Applied Statistics SCALPEL : EXTRACTING NEURONS FROM CALCIUM IMAGING DATA By
暂无分享,去创建一个
[1] Shanna L Resendez,et al. E � cient and accurate extraction of 1 in vivo calcium signals from 2 microendoscopic video data , 2018 .
[2] Liam Paninski,et al. Fast online deconvolution of calcium imaging data , 2016, PLoS Comput. Biol..
[3] Helen Shen. Brain-data gold mine could reveal how neurons compute , 2016, Nature.
[4] H. Sebastian Seung,et al. Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks , 2016, NIPS.
[5] David Pfau,et al. Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data , 2016, Neuron.
[6] L. Paninski,et al. Fast Constrained Non-negative Matrix Factorization for Whole-Brain Calcium Imaging Data , 2016 .
[7] Fred A. Hamprecht,et al. Sparse Space-Time Deconvolution for Calcium Image Analysis , 2014, NIPS.
[8] Matthijs J. Warrens,et al. Similarity, Dissimilarity, and Distance, Measures of , 2014 .
[9] Toru Aonishi,et al. Detecting cells using non-negative matrix factorization on calcium imaging data , 2014, Neural Networks.
[10] René Vidal,et al. Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing , 2014, ICML.
[11] E. Boyden,et al. Simultaneous whole-animal 3D-imaging of neuronal activity using light-field microscopy , 2014, Nature Methods.
[12] Adam M. Packer,et al. Extracting regions of interest from biological images with convolutional sparse block coding , 2013, NIPS.
[13] Fred A. Hamprecht,et al. Learning Multi-level Sparse Representations , 2013, NIPS.
[14] Stefan R. Pulver,et al. Ultra-sensitive fluorescent proteins for imaging neuronal activity , 2013, Nature.
[15] Philipp J. Keller,et al. Whole-brain functional imaging at cellular resolution using light-sheet microscopy , 2013, Nature Methods.
[16] Susanne Reichinnek,et al. Automated identification of neuronal activity from calcium imaging by sparse dictionary learning , 2013, 2013 IEEE 10th International Symposium on Biomedical Imaging.
[17] Noah Simon,et al. A Sparse-Group Lasso , 2013 .
[18] J. Simon Wiegert,et al. Multiple dynamic representations in the motor cortex during sensorimotor learning , 2012, Nature.
[19] Christine Grienberger,et al. Imaging Calcium in Neurons , 2012, Neuron.
[20] L. Looger,et al. Genetically encoded neural activity indicators , 2012, Current Opinion in Neurobiology.
[21] Robert Tibshirani,et al. Hierarchical Clustering With Prototypes via Minimax Linkage , 2011, Journal of the American Statistical Association.
[22] Joshua T. Vogelstein,et al. A Bayesian approach for inferring neuronal connectivity from calcium fluorescent imaging data , 2011, 1107.4228.
[23] P. J. Sjöström,et al. Functional specificity of local synaptic connections in neocortical networks , 2011, Nature.
[24] Spencer L. Smith,et al. Parallel processing of visual space by neighboring neurons in mouse visual cortex , 2010, Nature Neuroscience.
[25] Rafael Yuste,et al. Fast nonnegative deconvolution for spike train inference from population calcium imaging. , 2009, Journal of neurophysiology.
[26] Benjamin F. Grewe,et al. High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision , 2010, Nature Methods.
[27] Nicholas M. Mellen,et al. Semi-automated region of interest generation for the analysis of optically recorded neuronal activity , 2009, NeuroImage.
[28] Mark J. Schnitzer,et al. Automated Analysis of Cellular Signals from Large-Scale Calcium Imaging Data , 2009, Neuron.
[29] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[30] Hongbo Jia,et al. Calcium imaging in the living brain: prospects for molecular medicine. , 2008, Trends in molecular medicine.
[31] Samuel S-H Wang,et al. Identification and clustering of event patterns from in vivo multiphoton optical recordings of neuronal ensembles. , 2008, Journal of neurophysiology.
[32] D. Tank,et al. Imaging Large-Scale Neural Activity with Cellular Resolution in Awake, Mobile Mice , 2007, Neuron.
[33] Liam Paninski,et al. Statistical models for neural encoding, decoding, and optimal stimulus design. , 2007, Progress in brain research.
[34] K. Svoboda,et al. Principles of Two-Photon Excitation Microscopy and Its Applications to Neuroscience , 2006, Neuron.
[35] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .
[36] W. Denk,et al. Deep tissue two-photon microscopy , 2005, Nature Methods.
[37] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[38] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[39] Milan Sonka,et al. Image Processing, Analysis and Machine Vision , 1993, Springer US.