The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms.

Reliable single unit neuron recordings from chronically implanted microelectrode arrays (MEAs) are essential tools in the field of neural engineering. However, following implantation, MEAs undergo a foreign body response that functionally isolates them from the brain and reduces the useful longevity of the array. We tested a novel electrodeposited platinum-iridium coating (EPIC) on penetrating recording MEAs to determine if it improved recording performance. We chronically implanted the arrays in rats and used electrophysiological and histological measurements to compare quantitatively the single unit recording performance of coated vs. uncoated electrodes over a 12-week period. The coated electrodes had substantially lower impedance at 1 kHz and reduced noise, increased signal-to-noise ratio, and increased number of discernible units per electrode as compared to uncoated electrodes. Post-mortem immunohistochemistry showed no significant differences in the immune response between coated and uncoated electrodes. Overall, the EPIC arrays provided superior recording performance than uncoated arrays, likely due to lower electrode impedance and reduced noise.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective therapy for the motor symptoms of Parkinson's disease (PD). However, the neural elements mediating symptom relief are unclear. A previous study concluded that direct optogenetic activation of STN neurons was neither necessary nor sufficient for relief of parkinsonian symptoms. However, the kinetics of the channelrhodopsin-2 (ChR2) used for cell-specific activation are too slow to follow the high rates required for effective DBS, and thus the contribution of activation of STN neurons to the therapeutic effects of DBS remains unclear. We quantified the behavioral and neuronal effects of optogenetic STN DBS in female rats following unilateral 6-hydroxydopamine (6-OHDA) lesion using an ultrafast opsin (Chronos). Optogenetic STN DBS at 130 pulses per second (pps) reduced pathologic circling and ameliorated deficits in forelimb stepping similarly to electrical DBS, while optogenetic STN DBS with ChR2 did not produce behavioral effects. As with electrical DBS, optogenetic STN DBS exhibited a strong dependence on stimulation rate; high rates produced symptom relief while low rates were ineffective. High-rate optogenetic DBS generated both increases and decreases in firing rates of single neurons in STN, globus pallidus externa (GPe), and substantia nigra pars reticular (SNr), and disrupted b band oscillatory activity in STN and SNr. High-rate optogenetic STN DBS can indeed ameliorate parkinsonian motor symptoms through reduction of abnormal oscillatory activity in the STN-associated neural circuit, and these results highlight that the kinetic properties of opsins have a strong influence on the effects of optogenetic stimulation.

Peripheral nerve stimulation (PNS) is an effective tool for the treatment of chronic pain, although its efficacy and utilization have previously been significantly limited by technology. In recent years, purpose-built percutaneous PNS devices have been developed to overcome the limitations of conventional permanently implanted neurostimulation devices. Recent clinical evidence suggests clinically significant and sustained reductions in pain can persist well beyond the PNS treatment period, outcomes that have not previously been observed with conventional permanently implanted neurostimulation devices. This narrative review summarizes mechanistic processes that contribute to chronic pain, and the potential mechanisms by which selective large diameter afferent fiber activation may reverse these changes to induce a prolonged reduction in pain. The interplay of these mechanisms, supported by data in chronic pain states that have been effectively treated with percutaneous PNS, will also be discussed in support of a new theory of pain management in neuromodulation: Peripherally Induced Reconditioning of the Central Nervous System (CNS).

Objective Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main Results The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.