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Neuroimage. 2018 Apr 1;169:352-362. doi: 10.1016/j.neuroimage.2017.12.070. Epub 2017 Dec 22.

Macroscale variation in resting-state neuronal activity and connectivity assessed by simultaneous calcium imaging, hemodynamic imaging and electrophysiology.

Author information

1
Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; Department of Radiology, Mayo Clinic, Rochester, MN, United States. Electronic address: murphy.matthew@mayo.edu.
2
Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; NYU Langone Eye Center, Department of Ophthalmology, NYU School of Medicine, NYU Langone Medical Center, New York University, New York, NY, United States; Department of Radiology, NYU School of Medicine, NYU Langone Medical Center, New York University, New York, NY, United States.
3
Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
4
Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States. Electronic address: alv15@pitt.edu.

Abstract

Functional imaging of spontaneous activity continues to play an important role in the field of connectomics. The most common imaging signal used for these experiments is the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal, but how this signal relates to spontaneous neuronal activity remains incompletely understood. Genetically encoded calcium indicators represent a promising tool to study this problem, as they can provide brain-wide measurements of neuronal activity compared to point measurements afforded by electrophysiological recordings. However, the relationship between the calcium signal and neurophysiological parameters at the mesoscopic scale requires further systematic characterization. Therefore, we collected simultaneous resting-state measurements of electrophysiology, along with calcium and hemodynamic imaging, in lightly anesthetized mice to investigate two aims. First, we examined the relationship between each imaging signal and the simultaneously recorded electrophysiological signal in a single brain region, finding that both signals are better correlated with multi-unit activity compared to local field potentials, with the calcium signal possessing greater signal-to-noise ratio and regional specificity. Second, we used the resting-state imaging data to model the relationship between the calcium and hemodynamic signals across the brain. We found that this relationship varied across brain regions in a way that is consistent across animals, with delays increasing by600 ms towards posterior cortical regions. Furthermore, while overall functional connectivity (FC) measured by the hemodynamic signal is significantly correlated with FC measured by calcium, the two estimates were found to be significantly different. We hypothesize that these differences arise at least in part from the observed regional variation in the hemodynamic response. In total, this work highlights some of the caveats needed in interpreting hemodynamic-based measurements of FC, as well as the need for improved modeling methods to reduce this potential source of bias.

KEYWORDS:

BOLD; Calcium; Electrophysiology; Functional connectivity; GCaMP; Hemodynamic response function (HRF); Impulse response function (IRF); Resting-state; fMRI

PMID:
29277650
PMCID:
PMC5856618
[Available on 2019-04-01]
DOI:
10.1016/j.neuroimage.2017.12.070
[Indexed for MEDLINE]

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