Mouhamad Hammami1, Fernando Maestu2, Maria Eugenia López3, Susan Bowyer4
1Physics, Oakland University, 2Experimental Psychology, Universidad Complutense de Madrid, 3Universidad Complutense de Madrid, 4Henry Ford Hospital
Objective:
Use MEG to detect imaging bio markers for mild cognitive impairment
Background:
Alzheimer’s Disease (AD) is a type of dementia that effects 50 million people worldwide. This is a progressive disease that affects memory loss and cognitive dysfunction. Magnetoencephalography (MEG) is a noninvasive functional brain imaging technique that measures the magnetic brain waves arising from neuronal activity during rest or during a cognitive task. MEG may help detect AD in its early stages, when confusion first starts to happen.
Design/Methods:
Resting state MEG data from 20 patients with mild cognitive impairment were compared to 20 control subjects. MEG data were filtered into 4 different frequency bands: theta 4-7Hz, alpha 8-13HZ, beta 14-30Hz, and gamma 30-85 Hz. Network brain activity for each frequency band was mapped for the strength of connectivity across 27 regions in each hemisphere, resulting in 1431 pairings in the brain. Only the most statistically significant connections between the control group and the patient group where further analyzed, these were based on a p-value of less than 0.05.
Results:
Patients with MCI had more hyperexcited/coherent activity in the default mode network compared to controls. The two most statistically significant pathways differences in the beta band frequency were found in the frontal to occipital and frontal to temporal connections.
Conclusions:
MEG was able to detect clear differences in active networks during rest in patients with MCI compared to controls. This will have future applications to improve or tailor treatments during the early diagnosis of dementia. Our next step will be to determine the identification of AD network differences from MCI.