Modeling positive Granger causality and negative phase lag between cortical areas.

Area of Science:

• Neuroscience
• Dynamical Systems Theory
• Computational Neuroscience

Background:

• Effective connectivity in the brain is often inferred using directional influence measures.
• A positive phase lag typically signifies a sender influencing a receiver, reflecting transmission time.
• However, experimental data shows sensorimotor cortex connectivity can exhibit both positive and negative time delays.

Purpose of the Study:

• To present a computational model of two coupled brain regions exhibiting directional influence.
• To investigate the phenomenon of Anticipated Synchronization in neural systems.
• To provide a theoretical basis for experimental observations of unusual time delays in brain connectivity.

Main Methods:

• Developed a computational model of two coupled dynamical systems with a master-slave configuration.
• Incorporated negative delayed self-feedback in the slave system to induce Anticipated Synchronization.
• Validated the model by reproducing experimental delay times and coherence spectra from primate sensorimotor cortex.

Main Results:

• The model successfully replicated the counterintuitive finding of negative time delays in directed brain connectivity.
• Demonstrated that Anticipated Synchronization, where the receiver leads the sender, can occur in coupled dynamical systems.
• The model's parameters and dynamics align with experimental observations in monkeys during cognitive tasks.

Conclusions:

• The study provides a theoretical framework for understanding Anticipated Synchronization in neural circuits.
• Suggests that primate cortex may utilize Anticipated Synchronization during normal neurocognitive function.
• Highlights the potential for this synchronization regime to explain complex brain dynamics and connectivity patterns.