A hardware system for real-time decoding of in vivo calcium imaging data

Miniscope Recording Calcium Signals at Hippocampus of Mice Navigating an Odor Plume

Mice are able to navigate an odor plume with a complex spatiotemporal structure in the dark to find the source of odorants. We developed a protocol to monitor behavior and record Ca 2+ transients in dorsal CA1 stratum pyramidale neurons at the hippocampus (dCA1) in mice navigating an odor plume in a 50 cm x 50 cm x 25 cm odor arena. Ca 2+ transients were imaged by an epifluorescence miniscope focused through a GRIN lens on dCA1 neurons expressing the calcium sensor GCaMP6f in Thy1-GCaMP6f mice. We describe the behavioral protocol to train the mice to perform this odor plume navigation task in an automated odor arena. We provide the step-by-step procedure for the surgery for GRIN lens implantation and baseplate placement for imaging GCaMP6f in CA1. We provide information on real time tracking of the mouse position to automate the start of the trials and delivery of a sugar water reward. In addition, we provide information on the use of an Intan board to synchronize metadata describing the automation of the odor navigation task and frame times for the miniscope and a FLIR camera tracking mouse position. Moreover, we delineate the pipeline used to process GCaMP6f fluorescence movies by motion correction using NorMCorre followed by identification of regions of interest (ROIs) with EXTRACT. Finally, we describe use of artificial neural network (ANN) machine learning to decode spatial paths from CA1 neural ensemble activity to predict mouse navigation of the odor plume.

SUMMARY

This protocol describes how to investigate the brain-behavior relationship in hippocampal CA1 in mice navigating an odor plume. We provide a step-by-step protocol including the surgery to access imaging of the hippocampus, behavioral training, miniscope GCaMP6f recording and processing of the brain and behavioral data to decode the mouse position from ROI neural activity.

Advances in cellular resolution microscopy for brain imaging in rats

Rats are used in neuroscience research because of their physiological similarities with humans and accessibility as model organisms, trainability, and behavioral repertoire. In particular, rats perform a wide range of sophisticated social, cognitive, motor, and learning behaviors within the contexts of both naturalistic and laboratory environments. Further progress in neuroscience can be facilitated by using advanced imaging methods to measure the complex neural and physiological processes during behavior in rats. However, compared with the mouse, the rat nervous system offers a set of challenges, such as larger brain size, decreased neuron density, and difficulty with head restraint. Here, we review recent advances in in vivo imaging techniques in rats with a special focus on open-source solutions for calcium imaging. Finally, we provide suggestions for both users and developers of in vivo imaging systems for rats.

FPGA-Based In-Vivo Calcium Image Decoding for Closed-Loop Feedback Applications

Miniaturized calcium imaging is an emerging neural recording technique that has been widely used for monitoring neural activity on a large scale at a specific brain region of rats or mice. Most existing calcium-image analysis pipelines operate offline. This results in long processing latency, making it difficult to realize closed-loop feedback stimulation for brain research. In recent work, we have proposed an FPGA-based real-time calcium image processing pipeline for closed-loop feedback applications. It can perform real-time calcium image motion correction, enhancement, fast trace extraction, and real-time decoding from extracted traces. Here, we extend this work by proposing a variety of neural network based methods for real-time decoding and evaluate the tradeoff among these decoding methods and accelerator designs. We introduce the implementation of the neural network based decoders on the FPGA, and show their speedup against the implementation on the ARM processor. Our FPGA implementation enables the real-time calcium image decoding with sub-ms processing latency for closed-loop feedback applications.