Tantárgy adatlapja
Description of the subject:
1.Fiber photometry methodology introduction
2.Fluorophores used in fiber photometry
3.Fiber photometry analysis overview
4.Demodulating fiber photometry signals 1: theory
5.Demodulating fiber photometry signals 2: practical examples
6.Detrending fiber photometry signals 1: theory
7.Detrending fiber photometry signals 2: practical examples
8.Normalizing fiber photometry signals 1: theory
9.Normalizing fiber photometry signals 2: practical examples
10.Fiber photometry confounding sources of variability
11.Fiber photometry data quality control
12.Fiber photometry peri-event analysis
Selected literature:
[1]T. Akam and M. E. Walton, “pyPhotometry: Open source Python based hardware and software for fiber photometry data acquisition,” Sci. Rep., vol. 9, no. 1, p. 3521, 2019, doi: 10.1038/s41598-019-39724-y.
[2]E. H. Simpson et al., “Lights, fiber, action! A primer on in vivo fiber photometry,” Neuron, vol. 112, no. 5, pp. 718–739, Mar. 2024, doi: 10.1016/J.NEURON.2023.11.016.
[3]T. W. Chen et al., “Ultrasensitive fluorescent proteins for imaging neuronal activity,” Nat. 2013 4997458, vol. 499, no. 7458, pp. 295–300, Jul. 2013, doi: 10.1038/nature12354.
[4]Y. Zhang et al., “Cholinergic suppression of hippocampal sharp-wave ripples impairs working memory,” Proc. Natl. Acad. Sci. U. S. A., vol. 118, no. 15, p. e2016432118, Apr. 2021, doi: 10.1073/PNAS.2016432118/SUPPL_FILE/PNAS.2016432118.SAPP.PDF.
[5]A. A. Legaria et al., “Fiber photometry in striatum reflects primarily nonsomatic changes in calcium,” Nat. Neurosci. 2022 259, vol. 25, no. 9, pp. 1124–1128, Aug. 2022, doi: 10.1038/s41593-022-01152-z.
Required professional competences:
data processing, fiber photometry, MATLAB programming skills, algorithm development
