Evidence map›Paper›PMID 28291787›Full record

ArticlePLoS computational biology2017

Fast online deconvolution of calcium imaging data.

Johannes Friedrich, Pengcheng Zhou, Liam Paninski

Abstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 331 papers.

0numbers the graph read from it
0cells of the map it votes in
331citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

331 citing papers in PubMed.

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  8. Distinct types of dendritic CaScience advances · 2026
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  13. Parvalbumin interneurons contribute to spontaneous hemodynamic fluctuations.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
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  20. Precise calcium-to-spike inference using biophysical generative models.bioRxiv : the preprint server for biology · 2026
    Article

271 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Johannes FriedrichDepartment of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.ORCID 0000-0002-1321-5866
Pengcheng ZhouDepartment of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.
Liam PaninskiDepartment of Statistics, Grossman Center for the Statistics of Mind, and Center for Theoretical Neuroscience, Columbia University, New York, New York, United States of America.

Funding

Diversity supplement to Analysis of Nonstationary Point Process DataR01MH064537 · NIMH · CARNEGIE-MELLON UNIVERSITY · PI KASS, ROBERT E · 2001 to 2024
$7.2M
Interdiscplinary Training in Computational NeuroscienceR90DA023426 · NIDA · CARNEGIE-MELLON UNIVERSITY · PI KASS, ROBERT E, RUBIN, JONATHAN E. · 2006 to 2020
$4.5M
Next-Generation Calcium Imaging Analysis MethodsR01EB022913 · NIBIB · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI PANINSKI, LIAM M · 2016 to 2018
$1.1M
Optimal calcium imaging with shaped excitationR21EY027592 · NEI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PANINSKI, LIAM M, PETERKA, DARCY S · 2016 to 2018
$563k
NEI NIH HHS R21 EY027592NIBIB NIH HHS R01 EB022913NIDA NIH HHS R90 DA023426NIMH NIH HHS R01 MH064537
6 · The paper itself

Abstract

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 fluorescence calcium imaging data is a nontrivial problem. We present a fast online active set method to solve this sparse non-negative deconvolution problem. Importantly, the algorithm 3progresses through each time series sequentially from beginning to end, thus enabling real-time online estimation of neural activity during the imaging session. Our algorithm is a generalization of the pool adjacent violators algorithm (PAVA) for isotonic regression and inherits its linear-time computational complexity. We gain remarkable increases in processing speed: more than one order of magnitude compared to currently employed state of the art convex solvers relying on interior point methods. Unlike these approaches, our method can exploit warm starts; therefore optimizing model hyperparameters only requires a handful of passes through the data. A minor modification can further improve the quality of activity inference by imposing a constraint on the minimum spike size. The algorithm enables real-time simultaneous deconvolution of O(105) traces of whole-brain larval zebrafish imaging data on a laptop.

Indexed as

AnimalsCalciumCalcium SignalingData Interpretation, StatisticalHumansImage Interpretation, Computer-AssistedMicroscopy, FluorescenceMolecular ImagingNeuronsReproducibility of ResultsSensitivity and SpecificityVoltage-Sensitive Dye ImagingCalcium

Identifiers

PMID28291787
PMCPMC5370160

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.