647 citations · 1.7k across the 29 of their papers we have counts for
9 papers · 1 filter
Chronic, cortex-wide imaging of specific cell populations during behavior
Joao Couto, Simon Musall, Xiaonan R Sun +8
Measurements of neuronal activity across brain areas are important for understanding the neural correlates of cognitive and motor processes like attention, decision-making, and act…
A zero-inflated gamma model for deconvolved calcium imaging traces
Xue-Xin Wei, Ding Zhou, Andres Grosmark +6
Calcium imaging is a critical tool for measuring the activity of large neural populations. Much effort has been devoted to developing "pre-processing" tools for calcium video data,…
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
E. Kelly Buchanan, Ian Kinsella, Ding Zhou +17
Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large…
Automated scalable segmentation of neurons from multispectral images
Uygar Sümbül, Douglas Roussien, Fei Chen +5
Reconstruction of neuroanatomy is a fundamental problem in neuroscience. Stochastic expression of colors in individual cells is a promising tool, although its use in the nervous sy…
Fast Online Deconvolution of Calcium Imaging Data
Johannes Friedrich, Pengcheng Zhou, Liam Paninski
Fluorescent calcium indicators are a popular means for observing the spiking activity of large neuronal populations, but extracting the activity of each neuron from raw fluorescenc…
Linear dynamical neural population models through nonlinear embeddings
Yuanjun Gao, Evan Archer, Liam Paninski +1
A body of recent work in modeling neural activity focuses on recovering low-dimensional latent features that capture the statistical structure of large-scale neural populations. Mo…
A structured matrix factorization framework for large scale calcium imaging data analysis
Eftychios A. Pnevmatikakis, Yuanjun Gao, Daniel Soudry +6
We present a structured matrix factorization approach to analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of t…
Bayesian spike inference from calcium imaging data
Eftychios A. Pnevmatikakis, Josh Merel, Ari Pakman +1
We present efficient Bayesian methods for extracting neuronal spiking information from calcium imaging data. The goal of our methods is to sample from the posterior distribution of…
A shotgun sampling solution for the common input problem in neural connectivity inference
Daniel Soudry, Suraj Keshri, Patrick Stinson +3
Inferring connectivity in neuronal networks remains a key challenge in statistical neuroscience. The `common input' problem presents the major roadblock: it is difficult to reliabl…