Neurological disorders present a worldwide multi-factorial burden. They affect as many as one billion people globally - and that number is predicted to increase in the next decades. The wide-range effects of this problem are both pervasive and staggering. As such, we are ethically compelled to carefully consider and address this crisis. Unfortunately, the biological basis of dysfunction for these disorders is largely unknown; furthermore, the diagnosis for psychiatric disorders remains subjective.

The development of new neurotechnologies can offer both therapeutic relief and the opportunity to better understand the underlying pathomechanisms of dysfunction. Deep brain stimulation (DBS) is a relatively new therapy which has enjoyed successful application and approval for several neurological disorders.  It is suggested that DBS substantially reduces refractory symptoms in these disorders via the modulation of dysregulated networks. This theory is supported by the reports of correlation between improved symptomatology and the observed changes in synchronization of oscillatory rhythms. Although these data consequently suggest an important role for oscillatory rhythms, the scope of these rhythms in the pathological network and the mechanism(s) which exact their modification in the improved disease state has not been elucidated. Such information would bear directly on the important issues, including that of target selection and the quest for biomarkers. Therefore, DBS serves as a powerful tool to better understand the neurodynamics of systems level dysfunction subserving neuropsychiatric disorders.

While DBS can provide therapeutic benefit in otherwise treatment-refractory cases, it is not without risk and must be a carefully considered option. Several ethical issues must be deliberated, including risk v. benefit, age, post-surgical follow-up, and patient profile.

This presentation will address both the opportunities that DBS offers as well as the ethical challenges that are inherent in the determination of candidacy for and application of DBS. Gilles de la Tourette syndrome will be the model used to express such variables.