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 Logan Grosenick A1 Michael Broxton A1 Christina K. Kim A1 Conor Liston A1 Ben Poole A1 Samuel Yang A1 Aaron Andalman A1 Edward Scharff A1 Noy Cohen A1 Ofer Yizhar A1 Charu Ramakrishnan A1 Surya Ganguli A1 Patrick Suppes A1 Marc Levoy A1 Karl Deisseroth 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.