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An Unbiased Approach of Sampling TEM Sections in Neuroscience
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Sparse sampling: theory, methods and an application in neuroscience.

Jon Oñativia1, Pier Luigi Dragotti

  • 1Communications and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, UK, jon.onativia@imperial.ac.uk.

Biological Cybernetics
|December 3, 2014
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Summary
This summary is machine-generated.

This study introduces a new sampling theory for signals with finite rate of innovation (FRI), extending beyond bandlimited signals. It presents tools for neuroscience applications, like inferring neural spiking activity from calcium imaging data.

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Area of Science:

  • Signal Processing
  • Neuroscience
  • Information Theory

Background:

  • Classical sampling theory, based on the Shannon-Whittaker-Kotelnikov theorem, is limited to bandlimited signals.
  • A new framework, signals with finite rate of innovation (FRI), broadens sampling theory beyond frequency content to innovation parameters.
  • Bandlimited signals are a subset of the more general FRI signals definition.

Purpose of the Study:

  • To provide an overview of the finite rate of innovation (FRI) sampling framework.
  • To present tools for applying FRI theory in neuroscience research.
  • To demonstrate the inference of individual neuron spiking activity from two-photon calcium imaging data.

Main Methods:

  • Overview of the finite rate of innovation (FRI) sampling theory.
  • Development of tools for applying FRI in neuroscience.
  • Application to reconstruct neural spiking activity from calcium imaging data, reducing the problem to a stream of decaying exponentials.

Main Results:

  • The study outlines the theoretical framework of FRI sampling.
  • Tools are presented for practical application in neuroscience.
  • Successful reduction of inferring neural activity to reconstructing decaying exponentials from imaging data.

Conclusions:

  • The finite rate of innovation (FRI) framework offers a more general approach to signal sampling and reconstruction.
  • The presented tools facilitate the application of FRI theory in neuroscience.
  • This approach enables effective monitoring and inference of neural spiking activity from calcium imaging.