Frontiers in Computational Neuroscience (Jul 2023)

Empirical mode decomposition of local field potential data from optogenetic experiments

  • Sorinel A. Oprisan,
  • Xandre Clementsmith,
  • Tamas Tompa,
  • Tamas Tompa,
  • Antonieta Lavin

DOI
https://doi.org/10.3389/fncom.2023.1223879
Journal volume & issue
Vol. 17

Abstract

Read online

IntroductionThis study investigated the effects of cocaine administration and parvalbumin-type interneuron stimulation on local field potentials (LFPs) recorded in vivo from the medial prefrontal cortex (mPFC) of six mice using optogenetic tools.MethodsThe local network was subject to a brief 10 ms laser pulse, and the response was recorded for 2 s over 100 trials for each of the six subjects who showed stable coupling between the mPFC and the optrode. Due to the strong non-stationary and nonlinearity of the LFP, we used the adaptive, data-driven, Empirical Mode Decomposition (EMD) method to decompose the signal into orthogonal Intrinsic Mode Functions (IMFs).ResultsThrough trial and error, we found that seven is the optimum number of orthogonal IMFs that overlaps with known frequency bands of brain activity. We found that the Index of Orthogonality (IO) of IMF amplitudes was close to zero. The Index of Energy Conservation (IEC) for each decomposition was close to unity, as expected for orthogonal decompositions. We found that the power density distribution vs. frequency follows a power law with an average scaling exponent of ~1.4 over the entire range of IMF frequencies 2–2,000 Hz.DiscussionThe scaling exponent is slightly smaller for cocaine than the control, suggesting that neural activity avalanches under cocaine have longer life spans and sizes.

Keywords