RT Journal Article
SR Electronic
T1 Identification of cellular-activity dynamics across large tissue volumes in the mammalian brain
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 132688
DO 10.1101/132688
A1 Grosenick, Logan
A1 Broxton, Michael
A1 Kim, Christina K.
A1 Liston, Conor
A1 Poole, Ben
A1 Yang, Samuel
A1 Andalman, Aaron
A1 Scharff, Edward
A1 Cohen, Noy
A1 Yizhar, Ofer
A1 Ramakrishnan, Charu
A1 Ganguli, Surya
A1 Suppes, Patrick
A1 Levoy, Marc
A1 Deisseroth, Karl
YR 2017
UL http://biorxiv.org/content/early/2017/05/01/132688.abstract
AB Tracking the coordinated activity of cellular events through volumes of intact tissue is a major challenge in biology that has inspired significant technological innovation. Yet scanless measurement of the high-speed activity of individual neurons across three dimensions in scattering mammalian tissue remains an open problem. Here we develop and validate a computational imaging approach (SWIFT) that integrates high-dimensional, structured statistics with light field microscopy to allow the synchronous acquisition of single-neuron resolution activity throughout intact tissue volumes as fast as a camera can capture images (currently up to 100 Hz at full camera resolution), attaining rates needed to keep pace with emerging fast calcium and voltage sensors. We demonstrate that this large field-of-view, single-snapshot volume acquisition method—which requires only a simple and inexpensive modification to a standard fluorescence microscope—enables scanless capture of coordinated activity patterns throughout mammalian neural volumes. Further, the volumetric nature of SWIFT also allows fast in vivo imaging, motion correction, and cell identification throughout curved subcortical structures like the dorsal hippocampus, where cellular-resolution dynamics spanning hippocampal subfields can be simultaneously observed during a virtual context learning task in a behaving animal. SWIFT’s ability to rapidly and easily record from volumes of many cells across layers opens the door to widespread identification of dynamical motifs and timing dependencies among coordinated cell assemblies during adaptive, modulated, or maladaptive physiological processes in neural systems.