Brain Connectivity Analysis in Anesthetized and Awake States: an ECoG Study in Monkeys.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Changes in brain network topology are linked to alterations in consciousness.
• The prefrontal-parietal network's functional connectivity differs between awake and anesthetized states.

Purpose of the Study:

• To investigate brain network topology differences between awake and anesthetized states using electrocorticography.
• To assess the efficacy of functional connectivity features in distinguishing between these states.

Main Methods:

• Acquired electrocorticography data from two monkeys in awake and anesthetized states.
• Constructed functional connectivity matrices using the phase lag index across multiple frequency bands.
• Analyzed network topology using graph-theoretic properties.

Main Results:

• Significant differences in brain network topology were observed between awake and anesthetized states.
• Anesthesia led to increased overall and Delta prefrontal-frontal connectivity, and decreased Alpha, Beta1, and Beta2 prefrontal-frontal connectivity.
• Functional connectivity features achieved 93.68% classification accuracy in distinguishing states.

Conclusions:

• Functional connectivity patterns effectively differentiate between awake and anesthetized states.
• These findings provide a basis for developing new methods for monitoring anesthesia depth.
• The study highlights the utility of graph-theoretic analysis in understanding brain states.