Ephys directly reports spiking of neurons with high signal-to-noise ratio, temporal fidelity, and dynamic range, but typically offers access only to a sparse subset of relatively active neurons. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Įlectrophysiological recordings (‘ephys’) and calcium imaging offer distinct tradeoffs for interrogating activity in neural populations. funded by the visitor program at Janelia Research Campus. K.D, K.S and S.D are funded by the Simons foundation collaboration on the global brain SCGB 542969SPI Z.W is funded by SCGB 542943SPI S.D is funded by NIH NS104781. įunding: T.W.C is supported by a career development grant (NHRI-ex-105-10509NC) from the Taiwan National Health Research Institute. We also provide repos for benchmarks of S2F and F2S models at (DOI: 10.5281/zenodo.3960635) and comparison metrics at (DOI: 10.5281/zenodo.3979786) and website interface at. The API will come with a user-friendly interface in which one can reproduce all results in our paper and extensive results on. All codes for model benchmarks and comparison metrics are recompiled and packed with data through im-phys-API ( ), which can be available at. manually both of them can be downloaded at. and (2) imaging data in 6f-TG mice in anterior lateral motor cortex (delayed discrimination task) that were recorded by K.D. The new raw data in precompiled data include (1) simultaneously ephys-imaging data in TG mice in primary visual cortex (passive viewing task) that were recorded by B.J.L. Precompiled data used in the paper can be download at. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All data are available at both figshare and. Received: ApAccepted: JPublished: September 15, 2020Ĭopyright: © 2020 Wei et al. Gutkin, École Normale Supérieure, College de France, CNRS, FRANCE Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to predict and understand differences between them.Ĭitation: Wei Z, Lin B-J, Chen T-W, Daie K, Svoboda K, Druckmann S (2020) A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology. We developed a model transforming spike trains to synthetic-imaging data which recapitulated many of the differences in analyses. We report multiple discrepancies between analyses performed on the two types of data at the single neuron and population level. We compared neuronal spikes and fluorescence recorded in matched neural populations in behaving mice performing the same task. Electrophysiological recordings report neural activity directly with high temporal precision but have limitations of their own such as being less likely to accurately pickup neurons with low activity. But it does not record activity directly, reporting it rather through a transformation from intracellular calcium. Imaging can sample neural activity of hundreds of neurons in a local area and can be targeted to specific cell-types. Broadly speaking, two different approaches are commonly used, each with its own advantages and disadvantages. To be able to address such questions one must first record the activity of neurons. Many studies in neuroscience revolve around understanding the patterns of activity of neurons and their relation to behavior. Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to understand differences between these data. The model recapitulated the differences in analyses. Using these recordings we developed a model transforming spike trains to synthetic-imaging data. To model the relation between spiking and fluorescence we simultaneously recorded spikes and fluorescence from individual neurons. These were only partially resolved by spike inference algorithms applied to fluorescence. We report multiple discrepancies between analyses performed on the two types of data, including changes in single-neuron selectivity and population decoding. We compared neuronal spikes and fluorescence in matched neural populations in behaving mice. The transform between neural activity and calcium-related fluorescence involves nonlinearities and low-pass filtering, but the effects of the transformation on analyses of neural populations are not well understood. Calcium imaging with fluorescent protein sensors is widely used to record activity in neuronal populations.
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