Simulation of Astrocytic Calcium Dynamics in Lattice Light Sheet Microscopy Images

Abstract

Astrocytes regulate neuronal information processing through a variety of spatio-temporal calcium signals. Recent advances in calcium imaging have started to shine light on astrocytic activity, but the complexity and size of the recorded data strongly call for more advanced computational analysis tools. Their development is currently hindered by the lack of reliable, labeled annotations that are essential for the evaluation of algorithms and the training of learning-based methods. To solve this labeling problem, we have designed a generator of 2D/3D lattice light sheet microscopy (LLSM) sequences which realistically depict the calcium dynamics of astrocytes. By closely modeling calcium kinetics in real astrocytic ramifications, the generated datasets open the door for the deployment of convolutional neural networks in LLSM.

Reinforcing Interdisciplinary Collaborations To Unravel The Astrocyte "Calcium Code"

“…Models have for example been used to finely tune the spatial distribution of calcium channels (molecules that, when open, result in a calcium influx into the cytosol, forming a calcium signal) within the cell and explore its impact on astrocyte activity [68,69]. Moreover, models can be used to generate realistic datasets that can be used to train tools developed to characterize the system's behavior (see section Analysis of astrocyte calcium signals) [54]. Lastly, computational models are useful to go beyond correlational observations and to propose mechanistic principles that explain experimentally-observed data.…”

Biomolecule trafficking and network tomography-based simulations

“…In biomedical imaging, simulations are required for validating physical models, understanding recorded data, evaluating the performance of image analysis algorithms [5], or training complex models from large-scale synthetic datasets as recently investigated with supervised Deep Learning methods [21,22]. Nevertheless, the proposed simulation methods used to build benchmarking data sets are limited yet since they are not able to represent the whole complexity of interacting biomolecules as observed in real image sequences.…”

“…However, unlike physics-based modeling, the data-driven approach can capture the features of complex multiscale systems as a whole. The data-driven and physics-based approaches can also be gently combined to model the main components of the image sequence, as recently investigated in [22] to mimic calcium dynamics in astrocytes observed in lattice light sheet microscopy.…”

A generative model to simulate spatiotemporal dynamics of biomolecules in cells

“…Among them, particle-based stochastic models form the main class of tracking models (2)(3)(4)(5) and they are often at the basis of single molecule localization microscopy (SMLM) simulators. (6)(7)(8)(9)(10) Popular softwares providing particle-based stochastic simulations include Virtual Cell, (11) MCell, (12) and Smoldyn, (13) but they are mainly dedicated to reaction-diffusion dynamics for specific biophysics applications. In particular, as mentioned in the review paper, (14) they are "also known as Brownian motion simulators" and as such they hardly represent the diversity of particle motions observed in some applications.…”