Advanced time‐series analysis of MEG data as a method to explore olfactory function in healthy controls and Parkinson's disease patients

Objectives:

To determine whether time‐series analysis of magnetoencephalography (MEG) data is a suitable method to study brain activity related to olfactory information processing, and to detect differences in odor‐induced brain activity between patients with Parkinson's disease (PD) and controls.

Methods:

Whole head 151‐channel MEG recordings were obtained in 21 controls and 20 patients with PD during a 10‐min olfactory stimulus paradigm, consisting of 10 alternating rest‐stimulus cycles (30 s each), using phenylethyl alcohol administered by means of a Burghart olfactometer. Relative spectral power and synchronization likelihood (SL; an unbiased measure of functional connectivity) were calculated for delta, theta, alpha1, alpha2, beta, and gamma frequency bands.

Results:

In controls, olfactory stimulation produced an increase in theta power and a decrease in beta power. In patients with PD, there was a decrease in alpha1 power. No significant interaction between group and condition was found for spectral power. SL analysis revealed a significantly different response to olfactory stimulation in patients with PD compared to controls. In controls, the odor stimulus induced a decrease in local beta band SL. The response in patients with PD involved a decrease in intrahemispheric alpha2 band SL.

Conclusion:

This is the first study to show that time‐series analysis of MEG data, including spectral power and SL, can be used to detect odor‐induced changes in brain activity. In addition, differences in odor‐induced brain activity were found between patients with PD and controls using analysis of SL, but not of spectral power. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.