Scientists develop new method to improve fiber optic measurement of changes in brain activity

UNC School of Medicine researchers, led by Ian Shih, PhD, associate professor of neurology and biomedical research imaging center, have developed an improved fiber-based optical method for measuring activity changes in the brain.

UNC School of Medicine researchers, led by Ian Shih, PhD, associate professor of neurology and biomedical research imaging center, have developed an improved fiber-based optical method for measuring activity changes in the brain.

Fiber photometry, an increasingly popular neurotechnology, uses fiber optics to deliver certain wavelengths of light to excite fluorescent proteins sensitive to that wavelength and record dependent light emission of the activity. Through this process, scientists can directly measure the activity of a specific population of cells or neurochemicals at a specific location in the brain.

However, not all light passes through – a significant amount is absorbed by hemoglobin (Hb) in blood vessels distributed throughout the brain, and there was previously no reliable method to quantify this influence in the photometry of fibers. In a research paper featured on Cell Reports Methods, co-authors Weiting Zhang, MD, PhD, and Tzu-Hao Harry Chao, PhD, describe a new method to quantify this hemoglobin uptake in fiber photometry and show how use their method to get a more accurate measure of changes in brain activity.

“Given the rapidly increasing use of fiber photometry in neuroscience and the significant absorption of light by hemoglobin, we realized it was important to correct for relevant artifacts in photometry measurements. Our specific approach is to take a reading of photons through the wavelengths of an activity-independent fluorescent protein and use known hemoglobin absorption coefficients to calculate hemoglobin dynamics. then restore the underlying dynamics of the fluorescent signal from the targeted cells, without artifact,” said Zhang, who is the first author and works in a research unit of the Department of Neurology and the Center for Imaging Research. biomedical.

“We have now implemented a few approaches to correct for hemoglobin uptake artifacts – one of which does not require additional activity-independent fluorescent protein expression and can easily be used to measure multiple sensors at that time. The beauty of our platform is that it is easily scalable for multiple regions and adaptable to study transfer functions between neuronal activity, neurotransmitter release, as well as vascular dynamics,” said Chao, co-lead author and scientist at the Center for Animal MRI.

To best disseminate their methods and help scientists elsewhere replicate this technology, Zhang and Chao also published a protocol document with step-by-step instructions and their analytical codes in the journal STAR Protocols.

“We would like to share our technique with our colleagues on campus. Please contact us via [email protected] if you are interested in using multi-channel spectral fiber photometry for your research,” Zhang said.

Zhang et al. (2022) highlight the importance of recognizing and correcting for hemoglobin artifacts in fiber photometry data, beyond what the field currently does… This is particularly important to consider when performing fiber photometry recordings during pharmacological interventions live, which can lead to significant changes in cerebral blood volume. In these settings, using their computational models with a spectrometer can eliminate unwanted hemoglobin uptake artifacts, leading to more accurate neural registration data with fiber photometry,” said Run Zhang and Christina Kim. from the University of California, Davis in their preview article covering this study on cell reporting methods.

The authors built the multi-channel spectral fiber photometry system using the 2018-19 Medical School Research Infrastructure Equipment Grant awarded to the Department of Neurology. Other authors of this work include Yue Yang, Tzu-Wen Wang, Sung-Ho Lee, Esteban Oyarzabal, Randy Nonneman, Nicolas Pegard, and Hongtu Zhu of UNC-Chapel Hill; and Jingheng Zhou and Guohong Cui of NIEHS.

This research was supported primarily by NIH Brain Initiative awards (R01MH111429 and RF1MH117053) to the Shih lab. Shih is also a member of the UNC Bowles Center for Alcohol Studies, UNC Intellectual and Developmental Disabilities Research Center, UNC McAllister Heart Institute, and UNC-NCSU Joint Department of Biomedical Engineering.

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