Brain networking analysis in migraine with and without aura

Area of Science:

• Neuroscience
• Computational Neuroscience
• Medical Imaging

Background:

• Migraine with aura (MA) and without aura (MO) represent distinct neurological conditions.
• Understanding the underlying brain network differences is crucial for diagnosis and treatment.
• Previous studies have explored brain activity in migraine, but effective connectivity remains less understood.

Purpose of the Study:

• To investigate effective connectivity using nonlinear Granger Causality (GC) and brain networking analysis.
• To compare EEG-based findings with Blood Oxygen Level Dependent (BOLD) signal changes.
• To differentiate brain network dynamics in MA and MO patients during resting state and visual stimulation.

Main Methods:

• Utilized 65-channel EEG recordings in 19 MA/MO patients and 11 controls.
• Applied nonlinear Granger Causality (GC) and brain networking analysis to EEG data.
• Correlated EEG findings with BOLD signal changes in a subgroup of MA/MO patients under identical visual stimulation (0.5 and 2.0 cpd checkerboard gratings).

Main Results:

• Resting-state analysis revealed distinct patterns of reduced (MO) versus increased (MA) GC.
• During visual stimulation, both groups showed increased information transfer to fronto-central regions.
• MA patients exhibited a segregated posterior network cluster and increased visual cortex BOLD signal, particularly at 2.0 cpd.

Conclusions:

• The findings suggest altered information processing in migraine patients.
• Increased information exchange in parietal-occipital regions of MA patients indicates heightened visual cortex excitability.
• This heightened excitability is a potential key factor in the manifestation of typical aura symptoms.