waveCSD: A method for estimating transmembrane currents originated from propagating neuronal activity in the...

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biophysics

Background:

• Estimating current source densities (CSDs) from local field potentials (LFPs) is crucial for understanding neocortical activity.
• Existing CSD methods often assume tangential uniformity, limiting their application to propagating neuronal activity like alpha waves or cortical spreading depression.
• Accurate CSD estimation is vital for deciphering complex neural dynamics.

Purpose of the Study:

• To develop a novel mathematical method, waveCSD, for analyzing LFPs associated with planar waves of neocortical neuronal activity.
• To address the limitations of existing CSD methods when dealing with propagating neural signals.
• To provide a robust tool for characterizing transmembrane currents during wave propagation.

Main Methods:

• Developed the waveCSD algorithm, a novel mathematical approach for CSD analysis.
• Applied waveCSD to local field potential (LFP) data from propagating neocortical neuronal activity.
• Validated the method using simulations and in vivo experimental recordings from rat neocortex.

Main Results:

• The waveCSD algorithm demonstrates robustness against noise and uncertainties in propagation velocity.
• Achieved high accuracy across various electrode resolutions, outperforming iCSD and kCSD methods.
• Successfully characterized transmembrane currents during cortical spreading depressions in rat neocortex.

Conclusions:

• The waveCSD method offers a significant advancement in estimating transmembrane currents from LFPs during wave propagation.
• Provides a robust and accurate tool for analyzing dynamic neural activity patterns.
• Enables new experimental paradigms for studying wave-like phenomena in the neocortex.