Real-time functional magnetic resonance imaging neurofeedback for treatment of Parkinson's disease

Abstract

Self-regulation of brain activity in humans based on real-time feedback of functional magnetic resonance imaging (fMRI) signal is emerging as a potentially powerful, new technique. Here, we assessed whether patients with Parkinson's disease (PD) are able to alter local brain activity to improve motor function. Five patients learned to increase activity in the supplementary motor complex over two fMRI sessions using motor imagery. They attained as much activation in this target brain region as during a localizer procedure with overt movements. Concomitantly, they showed an improvement in motor speed (finger tapping) and clinical ratings of motor symptoms (37% improvement of the motor scale of the Unified Parkinson's Disease Rating Scale). Activation during neurofeedback was also observed in other cortical motor areas and the basal ganglia, including the subthalamic nucleus and globus pallidus, which are connected to the supplementary motor area (SMA) and crucial nodes in the pathophysiology of PD. A PD control group of five patients, matched for clinical severity and medication, underwent the same procedure but did not receive feedback about their SMA activity. This group attained no control of SMA activation and showed no motor improvement. These findings demonstrate that self-modulation of cortico-subcortical motor circuits can be achieved by PD patients through neurofeedback and may result in clinical benefits that are not attainable by motor imagery alone.

Figure 1.

Experimental procedure. During fMRI scanning, participants saw a yellow or green screen with a central thermometer. During the localizer runs, patients were required to rest when a yellow background appeared (for 20 s) and squeeze their left hand when the background turned green (for 20 s). The thermometer display remained blue throughout the run. A run consisted of 10 cycles. The two neurofeedback runs were similar to the localizer run except here the patients had to increase brain activity when the background turned green without overt movement. As brain activity in the target area increased, the blue bars on the thermometer filled up with red, and as activity decreased, the red bars empty back to blue.

Figure 2.

The region-of-interest analysis shows the success of the neurofeedback procedure for the experimental group. A, Example of target area for the neurofeedback run for one patient (x = −6). B–D, The mean time course during the localizer run (B), neurofeedback run 1 (C), and neurofeedback run 2 (D). The pink bars in B–D indicate activity in the target area during periods of upregulation, and the gray bars indicate rest periods. The patient was able to increase activity during upregulation and decrease activity during the rest periods for both neurofeedback runs. x-axis, Time (1TR = 2 s); y-axis, fMRI signal strength. E, Mean β values for the localizer runs and neurofeedback/imagery runs during both the scan sessions for all patients in the experimental and control group shown as scatter plots depicting the values for each individual person. The plots indicate that all patients in the experimental group were able to activate the target area during the neurofeedback (NF) session; this was not the case for all CG patients. Note: One patient in the EG did not show significant localizer (LOC) activation in scan 2, but this area was used to define the ROI for the neurofeedback runs based on the anatomical criteria, and then successfully upregulated.

Figure 3.

EMG recordings ruled out the effect of overt movements. EMG data (for one patient) from two channels during the localizer and neurofeedback runs over a similar time period. The upper pair of traces shows the expected increased innervation of hand muscles during the movement periods. No such activity was observed during the corresponding (upregulation) periods of the neurofeedback run (bottom pair of traces). The right column shows that the frequency signature of the EMG was similar during neurofeedback (NF) to that recorded during rest and very different from that recorded during overt movements.

Figure 4.

A, Whole-brain analysis revealed the modulation of cortico-subcortical circuits through neurofeedback. Whole-brain analysis for the neurofeedback runs shows activation in the SMA, PCG, GP (y = ±3/z = 7), and a contiguous cluster covering STN and cerebellum (CB). For detailed coordinates, see Table 3. B, Plot showing β values of brain areas (whole-brain analysis for EG) for the neurofeedback (NF) and localizer (LOC) runs. All areas were found to be more active during the localizer runs compared with the neurofeedback runs. C, Contrast map of the two groups during the NF runs. A and C show coronal and axial views in radiological convention. For detailed coordinates, see Table 4 (y = 0; z = −4).

Figure 5.

The functional improvement was apparent from the increase in finger-tapping frequency. Mean number of finger taps is shown for all sessions, with error bars showing the SD. Patients in the experimental group were able to increase the number of finger taps from session 1 to session 3 (the final assessment) (p < 0.05).