Information-Theoretic Approach and Fundamental Limits of Resolving Two Closely Timed Neuronal Spikes in Mouse Brain Calcium Imaging.

Published

Journal Article

OBJECTIVE:Although optical imaging of neurons using fluorescent genetically encoded calcium sensors has enabled large-scale in vivo experiments, the sensors' slow dynamics often blur closely timed action potentials into indistinguishable transients. While several previous approaches have been proposed to estimate the timing of individual spikes, they have overlooked the important and practical problem of estimating interspike interval (ISI) for overlapping transients. METHODS:We use statistical detection theory to find the minimum detectable ISI under different levels of signal-to-noise ratio (SNR), model complexity, and recording speed. We also derive the Cramer-Rao lower bounds (CRBs) for the problem of ISI estimation. We use Monte-Carlo simulations with biologically derived parameters to numerically obtain the minimum detectable ISI and evaluate the performance of our estimators. Furthermore, we apply our detector to distinguish overlapping transients from experimentally obtained calcium imaging data. RESULTS:Experiments based on simulated and real data across different SNR levels and recording speeds show that our algorithms can accurately distinguish two fluorescence signals with ISI on the order of tens of milliseconds, shorter than the waveform's rise time. Our study shows that the statistically optimal ISI estimators closely approached the CRBs. CONCLUSION:Our work suggests that full analysis using recording speed, sensor kinetics, SNR, and the sensor's stochastically distributed response to action potentials can accurately resolve ISIs much smaller than the fluorescence waveform's rise time in modern calcium imaging experiments. SIGNIFICANCE:Such analysis aids not only in future spike detection methods, but also in future experimental design when choosing sensors of neuronal activity.

Full Text

Duke Authors

Cited Authors

  • Soltanian-Zadeh, S; Gong, Y; Farsiu, S

Published Date

  • November 2018

Published In

Volume / Issue

  • 65 / 11

Start / End Page

  • 2428 - 2439

PubMed ID

  • 29993383

Pubmed Central ID

  • 29993383

Electronic International Standard Serial Number (EISSN)

  • 1558-2531

International Standard Serial Number (ISSN)

  • 0018-9294

Digital Object Identifier (DOI)

  • 10.1109/tbme.2018.2812078

Language

  • eng