NeuroResource Simultaneous Denoising , D econvolution , and Demixing of Calcium Imaging Data Highlights
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Timothy A. Machado | J. Merel | L. Paninski | R. Yuste | Daniel Soudry | D. Pfau | R. Bruno | D. Peterka | Yu Mu | M. Ahrens | Yuanjun Gao | T. Jessell | E. Pnevmatikakis | Clay Lacefield | Weijian Yang | T. Reardon | David Pfau
[1] L. Paninski,et al. Simultaneous Multi-plane Imaging of Neural Circuits , 2016, Neuron.
[2] Timothy A. Machado,et al. Primacy of Flexor Locomotor Pattern Revealed by Ancestral Reversion of Motor Neuron Identity , 2015, Cell.
[3] Matthias Bethge,et al. Supervised learning sets benchmark for robust spike rate inference from calcium imaging signals , 2015, bioRxiv.
[4] Fred A. Hamprecht,et al. Sparse Space-Time Deconvolution for Calcium Image Analysis , 2014, NIPS.
[5] Takashi Kawashima,et al. Mapping brain activity at scale with cluster computing , 2014, Nature Methods.
[6] Attila Losonczy,et al. SIMA: Python software for analysis of dynamic fluorescence imaging data , 2014, Front. Neuroinform..
[7] Toru Aonishi,et al. Detecting cells using non-negative matrix factorization on calcium imaging data , 2014, Neural Networks.
[8] René Vidal,et al. Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing , 2014, ICML.
[9] E. Boyden,et al. Simultaneous whole-animal 3D-imaging of neuronal activity using light-field microscopy , 2014, Nature Methods.
[10] Liam Paninski,et al. Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions , 2013, NIPS.
[11] Adam M. Packer,et al. Extracting regions of interest from biological images with convolutional sparse block coding , 2013, NIPS.
[12] Fred A. Hamprecht,et al. Learning Multi-level Sparse Representations , 2013, NIPS.
[13] Liam Paninski,et al. Bayesian spike inference from calcium imaging data , 2013, 2013 Asilomar Conference on Signals, Systems and Computers.
[14] D. Fitzpatrick,et al. Three-dimensional mapping of microcircuit correlation structure , 2013, Front. Neural Circuits.
[15] Stefan R. Pulver,et al. Ultra-sensitive fluorescent proteins for imaging neuronal activity , 2013, Nature.
[16] Pier Luigi Dragotti,et al. A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging , 2013, Journal of neural engineering.
[17] Philipp J. Keller,et al. Whole-brain functional imaging at cellular resolution using light-sheet microscopy , 2013, Nature Methods.
[18] Spencer L. Smith,et al. Parallel processing of visual space by neighboring neurons in mouse visual cortex , 2010, Nature Neuroscience.
[19] Rafael Yuste,et al. Fast nonnegative deconvolution for spike train inference from population calcium imaging. , 2009, Journal of neurophysiology.
[20] Benjamin F. Grewe,et al. High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision , 2010, Nature Methods.
[21] Mark J. Schnitzer,et al. Automated Analysis of Cellular Signals from Large-Scale Calcium Imaging Data , 2009, Neuron.
[22] Nathalie L Rochefort,et al. Sparsification of neuronal activity in the visual cortex at eye-opening , 2009, Proceedings of the National Academy of Sciences.
[23] Brendon O. Watson,et al. Spike inference from calcium imaging using sequential Monte Carlo methods. , 2009, Biophysical journal.
[24] Brendon O. Watson,et al. SLM Microscopy: Scanless Two-Photon Imaging and Photostimulation with Spatial Light Modulators , 2008, Frontiers in neural circuits.
[25] Keith J. Kelleher,et al. Three-dimensional random access multiphoton microscopy for functional imaging of neuronal activity , 2008, Nature Neuroscience.
[26] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .