L
Liam Paninski
Researcher at Columbia University
Publications - 279
Citations - 21265
Liam Paninski is an academic researcher from Columbia University. The author has contributed to research in topics: Spike train & Population. The author has an hindex of 59, co-authored 266 publications receiving 17868 citations. Previous affiliations of Liam Paninski include University College London & Brown University.
Papers
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Journal ArticleDOI
Spatio-temporal correlations and visual signalling in a complete neuronal population
Jonathan W. Pillow,Jonathon Shlens,Liam Paninski,Alexander Sher,Alan Litke,E. J. Chichilnisky,Eero P. Simoncelli +6 more
TL;DR: The functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells is analysed using a model of multi-neuron spike responses, and a model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlation activity in populations of neurons.
Journal ArticleDOI
Estimation of entropy and mutual information
TL;DR: In this article, the authors use an exact local expansion of the entropy function to prove almost sure consistency and central limit theorems for three of the most commonly used discretized information estimators.
Journal ArticleDOI
Instant neural control of a movement signal.
Mijail D. Serruya,Nicholas G. Hatsopoulos,Nicholas G. Hatsopoulos,Liam Paninski,Liam Paninski,Matthew R. Fellows,John P. Donoghue +6 more
TL;DR: In this paper, the activity from a few motor cortex neurons can be decoded into a signal that a monkey is able to use immediately to move a computer cursor to any new position in its workspace.
Book
Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition
TL;DR: This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience.
Journal ArticleDOI
Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data
Eftychios A. Pnevmatikakis,Daniel Soudry,Yuanjun Gao,Timothy A. Machado,Josh Merel,David Pfau,Thomas Reardon,Thomas Reardon,Yu Mu,Clay Lacefield,Weijian Yang,Misha B. Ahrens,Randy M. Bruno,Thomas M. Jessell,Thomas M. Jessell,Darcy S. Peterka,Rafael Yuste,Liam Paninski +17 more
TL;DR: This work presents a modular approach for analyzing calcium imaging recordings of large neuronal ensembles that relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neurons in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time.