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.