Full-Band EEG Recordings Using Hybrid AC/DC-Divider Filters

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Conventional AC recordings compromise slow electrical brain signals.
• Full-band DC recordings face limitations in amplifier dynamic range and high-frequency signal loss.
• Existing inverse filtering methods for RRC filters offer only partial DC signal suppression and require further assessment for biological signals.

Purpose of the Study:

• To develop and validate a novel digital inverse filter for accurate full-band EEG signal reconstruction.
• To assess the signal reconstruction quality of RRC filters with inverse filtering for various biological signals.
• To establish RRC filters with inverse filtering as an optimal method for full-band EEG recordings.

Main Methods:

• Developed a novel digital inverse filter based on a mathematical model of RRC filter properties.
• Implemented procedures for evaluating inverse filter coefficients, optimized for individual recording channels.
• Tested the method on high-potassium-induced cortical spreading depolarizations (SDs), endothelin-induced ischemic negative ultraslow potentials (NUPs), and whole-cell membrane potential recordings.

Main Results:

• The novel digital inverse filter demonstrated high computational accuracy and versatility.
• Near 99% reconstruction quality was achieved for SDs, NUPs, and membrane potential recordings.
• The proposed method significantly outperformed existing inverse filtering procedures in reconstruction quality.

Conclusions:

• The developed RRC filters with inverse filtering provide a highly accurate and versatile solution for full-band EEG signal reconstruction.
• This approach overcomes limitations of conventional AC recordings and existing inverse filtering techniques.
• RRC filters with inverse filtering are optimal for diverse full-band EEG recording applications, enhancing the study of slow electrical brain signals.