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Conference: Bucharest University Faculty of Physics 2022 Meeting

Section: Biophysics; Medical Physics

Title:

Orthogonal decomposition of transient response in optogenetic data

Authors:

Sorinel A. OPRISAN (1), Xandre CLEMENTSMITH (2), Tamas TOMPA (3,4), Antonieta LAVIN (3)

Affiliation:

(1) Department of Physics and Astronomy, College of Charleston, Charleston SC, USA

(2) Department of Psychology, College of Charleston, Charleston, USA

(3) Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA

(4) Faculty of Healthcare, Department of Preventive Medicine, University of Miskolc, Miskolc, Hungary

E-mail

oprisans@cofc.edu

Keywords:

keywords: optogenetics, prefrontal cortex, empirical mode decomposition, cocaine

Abstract:

Gamma oscillations in the brain's prefrontal area show strong coherence during associative learning [1], and their duration is proportional to the decision time in behavioral tests. Gamma rhythm involves the reciprocal interaction between parvalbumin fast-spiking interneurons (Pv-FSI) and principal cells to ensure fine-tuned excitation-inhibition balance in the brain [2]. We used optogenetic tools to investigate the response of the local network in the medial prefrontal cortex (mPFC) of mice [3]. The Pv-FSI [4] were infected with the viral vector Channelrhodopsin-2 (ChR2) [5], a transmembrane protein that rapidly forms a nonselective cation channel leading to membrane depolarization when activated by blue light [6]. Briefly, 10 ms laser pulses were delivered with an optrode that allowed the recording of the local field potential (LFP) response for 2 seconds [7]. Each procedure was repeated 100 times, and only data from stable couplings were reported for control and systemic cocaine administration [8,9]. Given the transient nature of the response, we used the empirical mode decomposition (EMD) for data analysis [10]. The orthogonal decomposition of the original LFP into intrinsic mode functions (IMFs) allows clear identification of the frequency bands and the corresponding energy distributions. The orthogonality indices show a certain amount of leakage among the IMFs, most likely due to noise contaminating all frequency bands. The IMFs show distinct relaxation coefficients for cocaine versus control that allow rapid data screening.

References:

[1] W.H. Miltner, C. Braun, M. Arnold, H. Witte, and E. Taub. Coherence of gamma-band eeg activity as a basis for associative learning. Nature, 397:434{436, 1999.

[2] Roger D. Traub, John G .R. Jefferys, and Miles A. Whittington. Simulation of gamma rhythms in networks of interneurons and pyramidal cells. Journal of Computational Neuroscience, 4(2):141{150, 1997.

[3] Jonathan E Dilgen, Tamas Tompa, Shalini Saggu, Thomas D Naselaris, and Antonieta Lavin. Optogenetically evoked gamma oscillations are disturbed by cocaine administration. Frontiers in Cellular Neuroscience, 7(213), 2013.

[4] L. Nahar, B.M. Delacroix, H.W. Nam, The Role of Parvalbumin Interneurons in Neurotransmitter Balance and Neurological Disease. Front Psychiatry. 2021;12:679960.

[5] Ji Guangchen, Neugebauer Volker, Modulation of medial prefrontal cortical activity using in vivo recordings and optogenetics, Molecular Brain 2012, 5:36.

[6] Thomas Knopfel, Edward S. Boyden (Eds), Optogenetics: Tools for Controlling and Monitoring Neuronal Activity, Progress in Brain Research, vol. 196, Elsevier, 2012.

[7] S.A. Oprisan, Lynn PE, Tompa T, and Lavin A, Low-dimensional attractor for neural activity from local field potentials in optogenetic mice. Frontiers in Computational Neuroscience. 2015, 9:125.

[8] Oprisan SA, Imperatore J, Helms J, Tompa T, and Lavin A, Cocaine-induced changes in low-dimensional attractors of local field potentials in optogenetic mice, Frontiers in Computational Neuroscience. 2018, 12:1.

[9] Oprisan SA, Clementsmith X, Tompa T, Lavin A (2019) Dopamine receptor antagonists effects on low-dimensional attractors of local field potentials in optogenetic mice. PLoS ONE 14(10): e0223469.

[10] Norden E. Huang, Zheng Shen, Steven R. Long, Manli C. Wu, Hsing H. Shih, Quanan Zheng, Nai-Chyuan Yen, Chi Chao Tung and Henry H. Liu, The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 1998, 454: 903-995.

Acknowledgement:

SAO acknowledges partial support for this project from the College of Charleston R&D grant and miniREAP grant from the South Carolina Space Grant Consortium. This project was also supported by grants from the National Center for Research Resources (5 P20 RR016461) and the National Institute of General Medical Sciences (8 P20 GM103499) from the National Institutes of Health. This work is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.