A baseline drift detrending technique for fast scan cyclic voltammetry.

Area of Science:

• Neuroscience
• Analytical Chemistry
• Biomedical Engineering

Background:

• Fast scan cyclic voltammetry (FSCV) is crucial for measuring brain neurotransmitters.
• Unstable background currents limit traditional FSCV data analysis to short durations.
• Existing methods struggle with background drift, hindering long-term monitoring.

Purpose of the Study:

• To introduce a zero-phase high pass filter (HPF) for improved FSCV data analysis.
• To address limitations caused by unstable background currents in FSCV.
• To enable robust analysis of FSCV data over extended periods.

Main Methods:

• Applied a zero-phase high pass filter (HPF) with low cutoff frequencies (0.001-0.01 Hz) to temporal FSCV datasets.
• Utilized HPF at each voltage point to remove background drift, preserving temporal kinetics.
• Compared HPF performance against principal component analysis (PCA) for drift reduction.

Main Results:

• HPF effectively removed background drift in FSCV data while preserving dopamine response kinetics.
• HPF significantly outperformed PCA in drift reduction on 24-hour Tris buffer data (p < 0.0001).
• Dopamine peaks were clearly visible in 5-hour in vivo FSCV data using HPF without background subtraction.

Conclusions:

• Zero-phase HPF offers a simple, robust method for analyzing FSCV data with unstable backgrounds.
• This technique enhances the ability to study neurotransmitter dynamics over longer timescales.
• HPF provides a valuable tool for neuroscience research utilizing FSCV.