57 — Resting-state connectivity predicts patient-specific effects of deep brain stimulation for Parkinson's disease

Chen et al (10.1101/203406)

Read on 17 October 2017
#fMRI  #parkinsons  #deep-brain-stimulation  #neuroscience  #connectome 

This paper explores target-audiences for deep-brain stimulation (DBS), a therapy often recommended to individuals suffering from Parkinson’s. DBS stimulation in Parkinson’s patients often leads to amelioration of symptoms (though it does not addressunderlying etiology).

While DBS is widely used and appears to reduce symptoms dramatically, its cellular mechanisms are still largely unknown. (When I first heard of DBS, I was astounded to discover that stimulation targets are often chosen at random, within certain nuclei. Though we’ve progressed since then, this practice remains — pretty distressingly — mostly the same.)

The authors of this paper use a resting-state functional brain connectome (rfMRI) from 43 volunteer PD patients (alongside 46 healthy controls) to determine if certain brain areas, identified using this fMRI connectomics and imaging technique, were particularly well-suited for DBS.

Basal ganglia / globus pallidus areas were, unsurprisingly, the most widely activated target during therapy (86.1% of the PD patients). Of the control patient brains, no particular region stood out so clearly, suggesting that the prediction of brain region is a function of PD connectivity or brain structure and not a function of sampling bias.

These results seem to suggest that individual patients differ susceptability to both PD and DBS therapies; this approach also appears to present a viable strategy for determining the ideal DBS target.

Despite this, for 51.2% of the PD patients the “ideal target zone” was not in GP or STN regions, and for some patients basal ganglia nuclei showed very low ranking for DBS candidacy. This might indicate there is more nuance to the subtypes or susceptibilities of PD than previously thought; or this methodology produces more noise than is controlled for statistically.