Charting the road forward in psychiatric neurosurgery: proceedings of the 2016 American Society for Stereotactic and Functional Neurosurgery workshop on neuromodulation for psychiatric disorders.

OBJECTIVE: Refractory psychiatric disease is a major cause of morbidity and mortality worldwide, and there is a great need for new treatments. In the last decade, investigators piloted novel deep brain stimulation (DBS)-based therapies for depression and obsessive-compulsive disorder (OCD). Results from recent pivotal trials of these therapies, however, did not demonstrate the degree of efficacy expected from previous smaller trials. To discuss next steps, neurosurgeons, neurologists, psychiatrists and representatives from industry convened a workshop sponsored by the American Society for Stereotactic and Functional Neurosurgery in Chicago, Illinois, in June of 2016. DESIGN: Here we summarise the proceedings of the workshop. Participants discussed a number of issues of importance to the community. First, we discussed how to interpret results from the recent pivotal trials of DBS for OCD and depression. We then reviewed what can be learnt from lesions and closed-loop neurostimulation. Subsequently, representatives from the National Institutes of Health, the Food and Drug Administration and industry discussed their views on neuromodulation for psychiatric disorders. In particular, these third parties discussed their criteria for moving forward with new trials. Finally, we discussed the best way of confirming safety and efficacy of these therapies, including registries and clinical trial design. We close by discussing next steps in the journey to new neuromodulatory therapies for these devastating illnesses. CONCLUSION: Interest and motivation remain strong for deep brain stimulation for psychiatric disease. Progress will require coordinated efforts by all stakeholders.

Pulse duration settings in subthalamic stimulation for Parkinson's disease.

BACKGROUND: Stimulation parameters in deep brain stimulation (DBS) of the subthalamic nucleus for Parkinson's disease (PD) are rarely tested in double-blind conditions. Evidence-based recommendations on optimal stimulator settings are needed. Results from the CUSTOM-DBS study are reported, comparing 2 pulse durations. METHODS: A total of 15 patients were programmed using a pulse width of 30 µs (test) or 60 µs (control). Efficacy and side-effect thresholds and unified PD rating scale (UPDRS) III were measured in meds-off (primary outcome). The therapeutic window was the difference between patients' efficacy and side effect thresholds. RESULTS: The therapeutic window was significantly larger at 30 µs than 60 µs (P = ·0009) and the efficacy (UPDRS III score) was noninferior (P = .00008). INTERPRETATION: Subthalamic neurostimulation at 30 µs versus 60 µs pulse width is equally effective on PD motor signs, is more energy efficient, and has less likelihood of stimulation-related side effects. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Automated optimization of deep brain stimulation parameters for modulating neuroimaging-based targets.

Objective.Therapeutic efficacy of deep brain stimulation (DBS) in both established and emerging indications, is highly dependent on accurate lead placement and optimized clinical programming. The latter relies on clinicians' experience to search among available sets of stimulation parameters and can be limited by the time constraints of clinical practice. Recent innovations in device technology have expanded the number of possible electrode configurations and parameter sets available to clinicians, amplifying the challenge of time constraints. We hypothesize that patient specific neuroimaging data can effectively assist the clinical programming using automated algorithms.Approach.This paper introduces the DBS Illumina 3D algorithm as a tool which uses patient-specific imaging to find stimulation settings that optimizes activating a target area while minimizing the stimulation of areas outside the target that could result in unknown or undesired side effects. This approach utilizes preoperative neuroimaging data paired with the postoperative reconstruction of the lead trajectory to search the available stimulation space and identify optimized stimulation parameters. We describe the application of this algorithm in three patients with treatment-resistant depression who underwent bilateral implantation of DBS in subcallosal cingulate cortex and ventral capsule/ventral striatum using tractography optimized targeting with an imaging defined target previously described.Main results.Compared to the stimulation settings selected by the clinicians (informed by anatomy), stimulation settings produced by the algorithm that achieved similar or greater target coverage, produced a significantly smaller stimulation area that spilled outside the target (P= 0.002).Significance. The DBS Illumina 3D algorithm is seamlessly integrated with the clinician programmer software and effectively and rapidly assists clinicians with the analysis of image based anatomy, and provides a starting point to search the highly complex stimulation parameter space and arrive at the stimulation settings that optimize activating a target area.

New Frontiers for Deep Brain Stimulation: Directionality, Sensing Technologies, Remote Programming, Robotic Stereotactic Assistance, Asleep Procedures, and Connectomics.

Over the last few years, while expanding its clinical indications from movement disorders to epilepsy and psychiatry, the field of deep brain stimulation (DBS) has seen significant innovations. Hardware developments have introduced directional leads to stimulate specific brain targets and sensing electrodes to determine optimal settings via feedback from local field potentials. In addition, variable-frequency stimulation and asynchronous high-frequency pulse trains have introduced new programming paradigms to efficiently desynchronize pathological neural circuitry and regulate dysfunctional brain networks not responsive to conventional settings. Overall, these innovations have provided clinicians with more anatomically accurate programming and closed-looped feedback to identify optimal strategies for neuromodulation. Simultaneously, software developments have simplified programming algorithms, introduced platforms for DBS remote management via telemedicine, and tools for estimating the volume of tissue activated within and outside the DBS targets. Finally, the surgical accuracy has improved thanks to intraoperative magnetic resonance or computerized tomography guidance, network-based imaging for DBS planning and targeting, and robotic-assisted surgery for ultra-accurate, millimetric lead placement. These technological and imaging advances have collectively optimized DBS outcomes and allowed "asleep" DBS procedures. Still, the short- and long-term outcomes of different implantable devices, surgical techniques, and asleep vs. awake procedures remain to be clarified. This expert review summarizes and critically discusses these recent innovations and their potential impact on the DBS field.

Current Directions in Deep Brain Stimulation for Parkinson's Disease-Directing Current to Maximize Clinical Benefit.

Several single-center studies and one large multicenter clinical trial demonstrated that directional deep brain stimulation (DBS) could optimize the volume of tissue activated (VTA) based on the individual placement of the lead in relation to the target. The ability to generate axially asymmetric fields of stimulation translates into a broader therapeutic window (TW) compared to conventional DBS. However, changing the shape and surface of stimulating electrodes (directional segmented vs. conventional ring-shaped) also demands a revision of the programming strategies employed for DBS programming. Model-based approaches have been used to predict the shape of the VTA, which can be visualized on standardized neuroimaging atlases or individual magnetic resonance imaging. While potentially useful for optimizing clinical care, these systems remain limited by factors such as patient-specific anatomical variability, postsurgical lead migrations, and inability to account for individual contact impedances and orientation of the systems of fibers surrounding the electrode. Alternative programming tools based on the functional assessment of stimulation-induced clinical benefits and side effects allow one to collect and analyze data from each electrode of the DBS system and provide an action plan of ranked alternatives for therapeutic settings based on the selection of optimal directional contacts. Overall, an increasing amount of data supports the use of directional DBS. It is conceivable that the use of directionality may reduce the need for complex programming paradigms such as bipolar configurations, frequency or pulse width modulation, or interleaving. At a minimum, stimulation through directional electrodes can be considered as another tool to improve the benefit/side effect ratio. At a maximum, directionality may become the preferred way to program because of its larger TW and lower energy consumption.

Nanobiolistic delivery of indicators to the living mouse retina.

The development of a technique to load functional indicators into living neurons is an ongoing challenge in retinal neurophysiology. In a number of live-cell preparations, fluorescence-based indicators have been of particular importance for investigating ionic concentrations, protein localization, and other physiological parameters. In the present study, we demonstrate a novel technique that uses a modified gene gun to propel silver nanoparticles coated with indicators into live retinal neurons, and we highlight the advantages of using this technique to deliver these functional indicators.

Classification of retinal ganglion cells: a statistical approach.

Numerous studies have shown that retinal ganglion cells exhibit an array of responses to visual stimuli. This has led to the idea that these cells can be sorted into distinct physiological classes, such as linear versus nonlinear or on versus off. Although many classification schemes are widely accepted, few studies have provided statistical support to favor one scheme over another. Here we test whether some of the most widely used classification schemes can be statistically verified, using the mouse retina as the model system. We used a cluster analysis approach and focused on 4 standard response parameters: 1) response latency, 2) response duration, 3) relative amplitude of the on and off responses, and 4) degree of nonlinearity in the stimulus-to-response transformation. For each parameter, we plotted its distribution and tested quantitatively, using a bootstrap method, whether it divided into distinct clusters. Our analysis showed that mouse ganglion cells clustered into several groups based on response latency, duration, and relative amplitude of the on and off responses, but did not cluster into more than one group based on degree of nonlinearity-the latter formed a single, large, continuous group. Thus while some well-known schemes for classifying ganglion cells could be statistically verified, others could not. Knowledge of which schemes can be confirmed is important for building models of how retinal output is processed and how retinal circuits are built. Finally, this cluster analysis approach is general and can be used to test other classification proposals as well, both physiological and anatomical.