Differentiating phase shift and delay in narrow band coherent signals

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Distinguishing between fixed activation patterns (phase shifts) and conduction time (time delays) in rhythmic biological signals is physiologically important but methodologically challenging.
• Oscillatory interactions in biological systems, such as tremor, involve complex temporal dynamics that require precise analysis.

Purpose of the Study:

• To develop and validate a method for differentiating phase shifts from time delays in rhythmic physiological signals.
• To investigate the mechanisms underlying tremor-related oscillatory interactions in Parkinsonian patients.

Main Methods:

• The maximizing coherence method was employed to estimate time delays.
• Phase spectra were calculated for simulated data (AR2 process and its delayed copy), surface electromyograms (EMGs) from antagonistic forearm muscles, and electroencephalogram (EEG) and EMG data from Parkinsonian tremor patients.

Main Results:

• The maximizing coherence method accurately estimated delays in simulated data, showing minimal bias from phase shifts.
• Reciprocal muscle activation patterns in forearm muscles were identified as pure phase shifts, lacking significant time delays.
• Analysis of Parkinsonian tremor data revealed distinct phase relationships between cortical activity and EMG, indicating different mechanisms for oscillatory interactions.

Conclusions:

• Phase shifts and time delays represent distinct mechanisms in tremor-related oscillatory interactions.
• The maximizing coherence method is effective in differentiating between phase shifts and time delays, offering valuable insights into biological signal dynamics.