Deep brain stimulation (DBS) is a remarkably effective clinical tool, used primarily for movement/ndisorders. DBS relies on precise targeting of specific brain regions to rebalance the oscillatory behaviour/nof whole-brain neural networks. Traditionally, DBS targeting has been based upon animal/nmodels (such asMPTPfor Parkinson’s disease) but has also been the result of serendipity during/nhuman lesional neurosurgery. There are, however, no good animal models of psychiatric disorders/nsuch as depression and schizophrenia, and progress in this area has been slow. In this paper, we use/nadvanced tractography combined with whole-brain anatomical parcellation to provide a rational/nfoundation for identifying the connectivity ‘fingerprint’ of existing, successful DBS targets. This/nknowledge can then be used pre-surgically and even potentially for the discovery of novel targets. First,/nusing data from our recent case series of cingulate DBS for patients with treatment-resistant chronic/npain, we demonstrate how to identify the structural ‘fingerprints’ of existing successful and unsuccessful/nDBS targets in terms of their connectivity to other brain regions, as defined by the whole-brain/nanatomical parcellation. Second, we use a number of different strategies to identify the successful fingerprints/nof structural connectivity across four patients with successful outcomes compared with/ntwo patients with unsuccessful outcomes. This fingerprinting method can potentially be used presurgically/nto account for a patient’s individual connectivity and identify the best DBS target. Ultimately,/nour novel fingerprinting method could be combined with advanced whole-brain computational/nmodelling of the spontaneous dynamics arising from the structural changes in disease, to/nprovide new insights and potentially new targets for hitherto impenetrable neuropsychiatric/ndisorders.

We thank Ms Eloise Starkfor her valuable comments. MLK was supported by the ERC ConsolidatorGrant:/nCAREGIVING (n. 615539) and the TrygFonden Charitable Foundation. GD was supported by the ERC Advanced/nGrant: DYSTRUCTURE (n. 295129), by the Spanish Research Project SAF2010-16085 and the FP7-ICT BrainScales.