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Active learning of cortical connectivity from two-photon imaging data.

Publication ,  Journal Article
Bertrán, MA; Martínez, NL; Wang, Y; Dunson, D; Sapiro, G; Ringach, D
Published in: PloS one
January 2018

Understanding how groups of neurons interact within a network is a fundamental question in system neuroscience. Instead of passively observing the ongoing activity of a network, we can typically perturb its activity, either by external sensory stimulation or directly via techniques such as two-photon optogenetics. A natural question is how to use such perturbations to identify the connectivity of the network efficiently. Here we introduce a method to infer sparse connectivity graphs from in-vivo, two-photon imaging of population activity in response to external stimuli. A novel aspect of the work is the introduction of a recommended distribution, incrementally learned from the data, to optimally refine the inferred network. Unlike existing system identification techniques, this "active learning" method automatically focuses its attention on key undiscovered areas of the network, instead of targeting global uncertainty indicators like parameter variance. We show how active learning leads to faster inference while, at the same time, provides confidence intervals for the network parameters. We present simulations on artificial small-world networks to validate the methods and apply the method to real data. Analysis of frequency of motifs recovered show that cortical networks are consistent with a small-world topology model.

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Published In

PloS one

DOI

EISSN

1932-6203

ISSN

1932-6203

Publication Date

January 2018

Volume

13

Issue

5

Start / End Page

e0196527

Related Subject Headings

  • Visual Cortex
  • Neurons
  • Nerve Net
  • Models, Neurological
  • Mice
  • Learning
  • General Science & Technology
  • Animals
  • Algorithms
 

Citation

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Bertrán, M. A., Martínez, N. L., Wang, Y., Dunson, D., Sapiro, G., & Ringach, D. (2018). Active learning of cortical connectivity from two-photon imaging data. PloS One, 13(5), e0196527. https://doi.org/10.1371/journal.pone.0196527
Bertrán, Martín A., Natalia L. Martínez, Ye Wang, David Dunson, Guillermo Sapiro, and Dario Ringach. “Active learning of cortical connectivity from two-photon imaging data.PloS One 13, no. 5 (January 2018): e0196527. https://doi.org/10.1371/journal.pone.0196527.
Bertrán MA, Martínez NL, Wang Y, Dunson D, Sapiro G, Ringach D. Active learning of cortical connectivity from two-photon imaging data. PloS one. 2018 Jan;13(5):e0196527.
Bertrán, Martín A., et al. “Active learning of cortical connectivity from two-photon imaging data.PloS One, vol. 13, no. 5, Jan. 2018, p. e0196527. Epmc, doi:10.1371/journal.pone.0196527.
Bertrán MA, Martínez NL, Wang Y, Dunson D, Sapiro G, Ringach D. Active learning of cortical connectivity from two-photon imaging data. PloS one. 2018 Jan;13(5):e0196527.

Published In

PloS one

DOI

EISSN

1932-6203

ISSN

1932-6203

Publication Date

January 2018

Volume

13

Issue

5

Start / End Page

e0196527

Related Subject Headings

  • Visual Cortex
  • Neurons
  • Nerve Net
  • Models, Neurological
  • Mice
  • Learning
  • General Science & Technology
  • Animals
  • Algorithms