Naumann, E. A. | bioRxiv Science

bioRxiv2021

Gigapixel behavioral and neural activity imaging with a novel multi-camera array microscope

The dynamics of living organisms are organized across many spatial scales. However, current cost-effective imaging systems can measure only a subset of these scales at once. We have created a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from cellular structures to large-group behavioral dynamics. By collecting data from up to 96 cameras, we computationally generate gigapixel-scale images and movies with a field of view over hundreds of square centimeters at 5um sensitivity. This allows us to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold. The MCAM architecture allows stereoscopic tracking of the z-position of organisms using the overlapping field of view from adjacent cameras. Further, we demonstrate the ability to acquire dual color fluorescence video of multiple freely moving zebrafish, recording neural activity via ratiometric calcium imaging. Overall, the MCAM provides a powerful platform for investigating cellular and behavioral processes across a wide range of spatial scales by removing the bottlenecks imposed by single-camera image acquisition systems.

bioengineering↗

bioRxiv2021

improv: A flexible software platform for adaptive neuroscience experiments

Current neuroscience research is often limited to testing predetermined hypotheses and post hoc analysis of already collected data. Adaptive experimental designs, in which modeling drives ongoing data collection and selects experimental manipulations, offer a promising alternative. Still, tight integration between models and data collection requires coordinating diverse hardware configurations and complex computations under real-time constraints. Here, we introduce improv, a software platform that allows users to fully integrate custom modeling, analysis, and visualization with data collection and experimental control. We demonstrate both in silico and in vivo how improv enables more efficient experimental designs for discovery and validation across various model organisms and data types. Improv can orchestrate custom real-time behavioral analyses, rapid functional typing of neural responses from large populations via calcium microscopy, and optimal visual stimulus selection. We incorporate real-time machine learning methods for dimension reduction and predictive modeling of latent neural and behavioral features. Finally, we demonstrate how improv can perform model-driven interactive imaging and simultaneous optogenetic photostimulation of visually responsive neurons in the larval zebrafish brain expressing GCaMP6s and the red-shifted opsin rsChRmine. Together, these results demonstrate the power of improv to integrate modeling with data collection and experimental control to achieve next-generation adaptive experiments.

neuroscience↗