RT Journal Article
SR Electronic
T1 Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.08.10.244723
DO 10.1101/2020.08.10.244723
A1 Joshua H. Siegle
A1 Peter Ledochowitsch
A1 Xiaoxuan Jia
A1 Daniel Millman
A1 Gabriel K. Ocker
A1 Shiella Caldejon
A1 Linzy Casal
A1 Andrew Cho
A1 Daniel J. Denman
A1 Séverine Durand
A1 Peter A. Groblewski
A1 Greggory Heller
A1 India Kato
A1 Sara Kivikas
A1 Jerome Lecoq
A1 Chelsea Nayan
A1 Kiet Ngo
A1 Philip R. Nicovich
A1 Kat R. North
A1 Tamina K. Ramirez
A1 Jackie Swapp
A1 Xana Waughman
A1 Ali Williford
A1 Shawn R. Olsen
A1 Christof Koch
A1 Michael A. Buice
A1 Saskia E. J. de Vries
YR 2020
UL http://biorxiv.org/content/early/2020/08/11/2020.08.10.244723.abstract
AB Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of neurons in the brain. While these two modalities have distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging or electrophysiology. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging. This work explores which data transformations are most useful for explaining these modality-specific discrepancies. We show that the higher selectivity in imaging can be partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could not reconcile differences in responsiveness without sub-selecting neurons based on event rate or level of signal contamination. This suggests that differences in responsiveness more likely reflect neuronal sampling bias or cluster-merging artifacts during spike sorting of electrophysiological recordings, rather than flaws in event detection from fluorescence time series. This work establishes the dominant impacts of the two modalities’ respective biases on a set of functional metrics that are fundamental for characterizing sensory-evoked responses.Competing Interest StatementThe authors have declared no competing interest.