Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies

Abstract

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer's disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.

Keywords: DBS (deep brain stimulation); adaptive DBS; neuroethics; neuroimaging; novel hardware; optogenetics.

FIGURE 1

Implant plan. StereoEEG electrodes (red) are placed in a variety of brain regions thought to be part of the depression network (dorsolateral prefrontal cortex, dlPFC; ventrolateral PFC, vlPFC; dorsomedial PFC, dmPFC; medial and lateral orbitofrontal cortex, mOFC, lOFC; dorsal anterior cingulate cortex, dACC; medial temporal lobe, MTL). DBS leads (blue) are placed in the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). Placement is individualized using tractography derived from diffusion MRI.

FIGURE 2

Personalization in Targeting. Closed-loop DBS model for depression, patient selection, and personalized clinical mapping integrating clinical responses, functional and structural connectivity mapping.

FIGURE 3

Individualized tractography-guided, template-matching lead implantation procedure for SCC DBS for TRD. (A) 4-bundle tractography target template (Riva-Posse et al., 2014). (B) Overlap of whole-brain deterministic tractography in patient-specific stereotactic frame space using the “StimVision” toolbox (Noecker et al., 2018). (C) Initial placement of electrode within SCC and visualization of WM pathways passing through the VTA. (D) Personalized optimal electrode location with the arc and ring angle determination by a neurosurgeon. Estimated VTA with standard stimulation settings (i.e., 3.5V, 130Hz, 90ms) is visualized with local field potential recording from adjacent contacts (sandwiching recording to minimize stimulation artifact). Composite images courtesy of Ki Sueng Choi, Icahn School of Medicine at Mount Sinai.

FIGURE 4

Using connectomics to guide surgery and DBS programming. (Top) DBS tract filtering. Four DBS electrodes implanted to the anteromedial subthalamic nucleus and anterior limb of the internal capsule in a patient with obsessive compulsive disorder. Active contacts are marked in red. A tract associated with optimal clinical improvement across 50 patients (limbic hyperdirect pathway within the anterior limb of the internal capsule) is shown in red, one associated with poor improvement (posterior limb of the anterior commissure) in blue. (Bottom left) Clinical DBS setting. (Bottom middle) Upon further confirmation of results, based on the existing electrode and the connectomic information, the stimulation settings could be optimized. (Bottom right) In novel patients, both surgical targeting and DBS programming could potentially be optimized. Data from Li et al. (2020), background slices show the BigBrain dataset (Amunts et al., 2013) after precise co-registration.

FIGURE 5

Image-based analyses of multicenter data from the International Tourette Syndrome (TS) Deep Brain Stimulation (DBS) Registry and Database. (A) Active contact locations for N = 70 patients implanted in the centromedial (CM) thalamus (red); anteromedial globus pallidus internus (GPi) (yellow); posteroventral GPi (green); nucleus accumbens/anterior limb of internal capsule (NA/ALIC) (turquoise); CM thalamus and GPi (blue); or CM thalamus and NA/ALIC (purple). From Johnson et al. (2019). (B,C) Stimulation-dependent structural connectivity associated with improvement in tics in patients implanted with DBS in the (B) GPi or (C) CM thalamus. From Johnson et al. (2020).

FIGURE 6

UCSF protocol for data streaming from Summit RC + S. Quadripolar leads were placed bilaterally into the subthalamic nuclei and over the motor cortex. Leads were connected to the ipsilateral Summit RC + S neural interfaces. Each RC + S device wirelessly communicates with a pocket-sized relay device, usually worn on the patient. The relay devices transmit by Bluetooth to a single small Windows-based tablet at a distance of up to 12 m, allowing sensing of local field potentials from up to four bipolar electrode pairs for up to 30 h per device, before recharge is needed. Data from a wristwatch-style actigraphy monitor (Parkinson’s Kinetograph, Global Kinetics) are synchronized off-line with neural recordings to facilitate brain-behavior correlations.

FIGURE 7

Digital Platform for Neurological and Psychiatric Disease. Integration of brain implants, smart phones, wearable sensors, and computing environments that provide data analytics synchronized with biomarker or user triggered interactions that can enable new therapy paradigms.

FIGURE 8

The methodological framework to entangle network proxies for prediction of the outcome of the DBS patients from volume of tissue activated (VTA) modeling to identifying the correct modalities to identify the network changes and use it for individual prediction using matching learning algorithms.

FIGURE 9

Remote real-time deep brain recording and DBS tele-programming. (A) The G106RS system, a sensing-enabled DBS with Bluetooth connection, can monitor deep brain rhythms remotely. Specifically, it was capable of transmitting up to eight channels of local field potentials (LFPs) with 1,000 Hz sampling rate, one channel of electrocardiogram (ECG) and 3-D accelerometer signals; (B) DBS patient equipped with G106RS device with Bluetooth connection and wireless charging. A tele-programming DBS system can remotely adjust parameters via Bluetooth technology by the provider. The LFP, ECG and 3-D accelerometer signals can be transmitted remotely from the G106RS device to a data receiver accessed by the provider.

FIGURE 10

Multi-objective particle swarm optimization algorithm for determining DBS parameter sets that more selectively active one or more axonal pathways adjacent to a DBS lead. (A) Multiple particles explore electrode configurations and stimulation amplitudes, and are guided by panel (B), an inertial, cognitive, and social component amongst the N particles. (C–E) Particles are mapped onto a multi-objective space that describes the goal of activating one or more pathways over other pathways within the brain. Through an iterative process, non-dominated particles are tracked to create a Pareto front with particles corresponding to optimized electrode configurations. Reproduced with permission from Pena et al. (2018).