Debregeas, G. | bioRxiv Science

bioRxiv2018

Whole-brain calcium imaging during physiological vestibular stimulation in larval zebrafish

During in vivo functional imaging, animals are head-fixed and thus deprived from vestibular inputs, which severely hampers the design of naturalistic virtual environments. To overcome this limitation, we developed a miniaturized ultra-stable light-sheet microscope that can be dynamically rotated during imaging along with a head-restrained zebrafish larva. We demonstrate that this system enables whole-brain functional imaging at single-cell resolution under controlled vestibular stimulation. We recorded for the first time the dynamic whole-brain response of a vertebrate to physiological vestibular stimulation. This development largely expands the potential of virtual-reality systems to explore complex multisensory-motor integration in 3D.

neuroscience↗

bioRxiv2017

Blind sparse deconvolution for inferring spike trains from fluorescence recordings

The parallel developments of genetically-encoded calcium indicators and fast fluorescence imaging techniques makes it possible to simultaneously record neural activity of extended neuronal populations in vivo, opening a new arena for systems neuroscience. To fully harness the potential of functional imaging, one needs to infer the sequence of action potentials from fluorescence time traces. Here we build on recently proposed computational approaches to develop a blind sparse deconvolution algorithm (BSD), which we motivate by a theoretical analysis. We demonstrate that this method outperforms existing sparse deconvolution algorithms in terms of robustness, speed and/or accuracy on both synthetic and real fluorescence data. Furthermore, we provide solutions for the practical problems of thresholding and determination of the rise and decay time constants. We provide theoretical bounds on the performance of the algorithm in terms of precision-recall and temporal accuracy. Finally, we extend the computational framework to support temporal superresolution whose performance is established on real data.

neuroscience↗