Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type
D O'Connor,
F Mandino,
X Shen,
C Horien,
X Ge,
P Herman,
F Hyder,
M Crair,
X Papademetris,
EMR Lake,
RT Constable
Affiliations
D O'Connor
Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Corresponding author at: Biomedical Engineering, Yale University, 300 Cedar Street, New Haven, Connecticut 06520, United States.
F Mandino
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
X Shen
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
C Horien
Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
X Ge
Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, USA
P Herman
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
F Hyder
Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
M Crair
Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA; Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, USA; Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA
X Papademetris
Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
EMR Lake
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
RT Constable
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA; Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
To improve ‘bench-to-bedside’ translation, it is integral that knowledge flows bidirectionally—from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data—an emerging mode applicable in animal models—as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.
