Power-law distribution of phase-locking intervals does not imply critical interaction

Area of Science:

• Neuroscience
• Complex Systems
• Statistical Physics

Background:

• Neural synchronization is fundamental to brain information processing.
• Characterizing synchronization patterns is key to understanding brain dynamics.
• Broadband criticality, indicated by power-law statistics, has been proposed as a brain state.

Purpose of the Study:

• To investigate the validity of using pairwise phase-locking intervals to detect criticality.
• To evaluate the effectiveness of global lability of synchronization as a measure of criticality.
• To differentiate between critical and noncritical neural interactions.

Main Methods:

• Analysis of a classical synchronization model.
• Pooling of pairwise phase-locking intervals from simulated systems.
• Assessment of power-law statistics using model selection approaches.
• Application of the global lability of synchronization measure.

Main Results:

• The pooling of pairwise phase-locking intervals from noncritical systems can spuriously appear as power-law distributed.
• Global lability of synchronization demonstrated a superior ability to distinguish critical from noncritical interactions.
• Model selection methods for power-law detection have limitations.

Conclusions:

• Pairwise phase-locking intervals alone may be insufficient to confirm broadband criticality in neural systems.
• Global lability of synchronization offers a more robust measure for identifying critical brain dynamics.
• Careful consideration of analytical methods is necessary when assessing neural criticality.