Cycle-frequency content EEG analysis improves the assessment of respiratory-related cortical activity.

Abstract

Objective. Time-frequency (T-F) analysis of electroencephalographic (EEG) is a common technique to characterise spectral changes in neural activity. This study explores the limitations of utilizing conventional spectral techniques in examining cyclic event-related cortical activities due to challenges, including high inter-trial variability.Approach. Introducing the cycle-frequency (C-F) analysis, we aim to enhance the evaluation of cycle-locked respiratory events. For synthetic EEG that mimicked cycle-locked pre-motor activity, C-F had more accurate frequency and time localization compared to conventional T-F analysis, even for a significantly reduced number of trials and a variability of breathing rhythm.Main results. Preliminary validations using real EEG data during both unloaded breathing and loaded breathing (that evokes pre-motor activity) suggest potential benefits of using the C-F method, particularly in normalizing time units to cyclic activity phases and refining baseline placement and duration.Significance. The proposed approach could provide new insights for the study of rhythmic neural activities, complementing T-F analysis.