Closed-loop neuromodulation systems: next-generation treatments for psychiatric illness

Abstract

Despite deep brain stimulation's positive early results in psychiatric disorders, well-designed clinical trials have yielded inconsistent clinical outcomes. One path to more reliable benefit is closed-loop therapy: stimulation that is automatically adjusted by a device or algorithm in response to changes in the patient's electrical brain activity. These interventions may provide more precise and patient-specific treatments. This article first introduces the available closed-loop neuromodulation platforms, which have shown clinical efficacy in epilepsy and strong early results in movement disorders. It discusses the strengths and limitations of these devices in the context of psychiatric illness. It then describes emerging technologies to address these limitations, including pre-clinical developments such as wireless deep neurostimulation and genetically targeted neuromodulation. Finally, ongoing challenges and limitations for closed-loop psychiatric brain stimulation development, most notably the difficulty of identifying meaningful biomarkers for titration, are discussed. This is considered in the recently-released Research Domain Criteria (RDoC) framework, and how neuromodulation and RDoC are jointly very well suited to address the problem of treatment-resistant illness is described.

Keywords: Deep brain stimulation; bioengineering; biomarker; electrophysiology; neuromodulation; transdiagnostic.

Figure 1

Schematic of one possible closed-loop stimulator realization. The controller system senses (“decodes”) electrophysiological biomarkers from a brain region that is associated with disease symptoms. It delivers electrical stimulation to a deep brain structure based on the real-time algorithm.

Figure 2

The Activa PC+S electrode sensing configuration. (Left) The sensing electrodes are placed symmetrically about the stimulation electrode. The stimulation interference signals are then recorded as identical signal components (common mode signals) to the amplifier and can be rejected as a common mode disturbance. (Right) The neuromodulation stimulator case is implanted within the patient, enabling monopolar stimulation.

Figure 3

The NeuroPace RNS system. The system includes a neurostimulator, a depth leads for stimulation at or near the seizure foci and a cortical strip leads for EcoG recording (Sun, Morrell, & Wharen, 2008). Reprinted from Neurotherapeutics, Vol 5, Issue 1, Sun, Felice T, Morrell, Martha J, Wharen, Robert E. Responsive cortical stimulation for the treatment of epilepsy. Page 68–74, Copyright (2008), with permission from Springer.

Figure 4

The RNS detection methods. Red: Half-Wave method. The algorithm detects pre-defined segments of the signals partitioned at local and maximum values. The amplitude and duration of the half wave represent the amplitude and frequency of the signals. Blue: Line-Length method. The algorithm calculates the averaged amplitude difference between samples within a short term window. The value is compared with a long term window average and detection occurs when the short term value crosses a certain threshold pre-defined and based on the long term window average. Yellow: Area method. The algorithm calculates the averaged area underneath the curve of the signal within a short term window. Detection occurs when the short term window value crosses the threshold defined by the long term window averaged area.

Figure 5

TRANSFORM DBS proposed system. (A), schematic of cranially mounted device, including the central Hub signal processor and aggregator (A1) and the Satellite systems for signal digitization and stimulation routing (A2). (B), block diagram of system processing, illustrating partitioning of key components to different aspects of the end-to-end closed-loop therapy. (Figure courtesy of Draper Laboratory)

Figure 6

The neural dust system. Dust “motes” (small recording or stimulating units, about 100x smaller than existing electrodes) are implanted within the cortex. A sub-cranial transreceiver is implanted below the dura mater and powered by another external transreceiver through radio frequency (RF) power transfer. The sub-cranial transreceiver couples ultrasound energy into tissue to interrogate each sensing node and deliver stimulation through targeted activating nodes (Seo, Carmena, Rabaey, Maharbiz, & Alon, 2015). In other variants of this system concept, the implanted transreceiver is eliminated and the dust motes are activated/interrogated entirely from outside the skull, for a true minimally invasive system. Reprinted from Journal of Neuroscience Methods, Vol 244, Seo, Dongjin, Carmena, Jose M., Rabaey, Jan M. Maharbiz, Michel M. Alon, Elad. Model validation of untethered, ultrasonic neural dust motes for cortical recording. Page 114–122, Copyright (2015), with permission from Elsevier.