Deep brain stimulation (DBS) has gained wide use in movement disorders and remains an area of active research in psychiatric disorders. Recent clinical trial setbacks may reflect clinicians’ trial-and-error approach to selecting stimulation parameters . Newer studies focus on “closed-loop” approaches, where DBS settings are adjusted based on an objective, brain-based readout. Those studies divide roughly into “anatomical” approaches based on targeting stimulation to specific white matter (WM) bundles and “physiologic” approaches that focus on changing pathologic signatures in brain electrical activity. We argue that success in psychiatric applications may require a synthesis of both approaches: individualized anatomically guided electrode placement coupled with biomarker-responsive targeting of network dynamics.
The anatomical approach optimizes clinical response by tailoring electrode placement relative to individual brain anatomy. In subcallosal cingulate (SCC) DBS for depression, an open-label study prospectively targeted the intersection of four different tracts in peri-SCC WM using individualized probabilistic tractography. Out of 11, 9 patients responded, a substantial improvement over the same group’s prior results . The same approach is now being expanded beyond SCC WM to optimize DBS placement in the ventral striatum/ventral capsule and medial forebrain bundle .
In comparison, the physiology-based closed-loop DBS approach is making strides in neurological disorders. Clinical outcomes improve in Parkinson disease when DBS is targeted to suppress specific cortical electrical oscillations or is locked to the phase of those oscillations . A similar oscillatory feature was successfully used as a control signal in responsive DBS for Tourette syndrome . Closed-loop DBS-like stimulation has also enhanced human memory. Recordings from sites across the brain can predict periods of poor memory encoding, and lateral temporal stimulation at those timepoints rescues memory performance . If similar biomarkers can be identified for psychiatric symptoms, an analogous responsive stimulation approach should be possible in mental disorders. Preliminary evidence suggests that such biomarkers can be identified through a focus on cross-diagnostic domains of function, and that those markers can in turn be used for closed-loop control of psychiatrically relevant functions such as emotion regulation .
Psychiatric disorders likely involve dysfunction across multiscale neural networks [1, 7], and effective DBS appears to require modulation of multiple circuits . These results suggest the potential power of a multinode, network approach to sensing and stimulating in DBS. Delivering stimulation in response to features on multiple time scales (for instance, both amplitude and phase) may increase symptom relief while reducing side effects . In conditions with distributed pathology, recording from and stimulating multiple areas simultaneously may better control network interactions. The ability to sense multiple network nodes might allow a better assessment of stimulation’s effects on network connectivity/activity. Conversely, network activity might best be modulated by multisite stimulation. DBS and related technologies are believed to act by de-synchronizing brain networks, but this depends on stimulation efficiently propagating within those networks. In cases where single-site stimulation fails to adequately drive “downstream” nodes, a second stimulating site could enhance the network disruption. Fusing the anatomic and physiologic approaches into a dynamic, network-targeted approach to closed-loop DBS may be the next horizon for personalized treatment in severe psychiatric disorders.
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A.S.W. acknowledges support from the OneMind Institute, National Institutes of Health (contracts MH10972, MH111320, NS100548, and MH113103), MnDRIVE Brain Conditions initiative, and MnDRIVE Medical Discovery Team on Addictions. A.B.H. acknowledges support from the MnDRIVE Brain Conditions initiative.
The authors declare no competing interests.
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Herman, A.B., Widge, A.S. Dynamic network targeting for closed-loop deep brain stimulation. Neuropsychopharmacol 44, 219–220 (2019). https://doi.org/10.1038/s41386-018-0210-x
Personalized Medicine in Psychiatry (2019)