Approaches to predictably control neural oscillations are needed to understand their causal role in brain function in healthy and diseased states and to advance the development of neuromodulation therapies. In this article, we present a neural control and optimization framework to actively suppress or amplify neural oscillations observed in local field potentials in real-time by using electrical stimulation. The rationale behind this control approach is that neural oscillatory activity evoked by electrical pulses can suppress or amplify spontaneous oscillations via destructive or constructive interference when stimulation pulses are continuously delivered at precise phases of these oscillations in a closed-loop scheme. We tested this technique in two nonhuman primates that exhibited a robust increase in low-frequency (8-30 Hz) oscillatory power in the subthalamic nucleus following administration of the neurotoxin MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine). The control approach was capable of actively and robustly suppressing or amplifying low-frequency oscillations in real-time in the studied subjects.
Significance StatementWe developed and tested an approach to systematically and predictably control neural oscillations recorded from local field potentials in-vivo by using electrical stimulation. This neural modulation technique is capable of actively suppressing or amplifying neural oscillations with the resolution and time specificity needed to characterize the functional role of oscillatory dynamics in brain circuits. We resolve the experimentally-intractable problem of finding optimal stimulation parameters to suppress or amplify neural oscillations by using subject-specific neurophysiological data and data-driven computer simulations. Together these neural control and optimization approaches allow one to characterize in controlled experiments the role of circuit-level neural oscillations in brain function and study electrical stimulation therapies that predictably modulate brain oscillations.
Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 8-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinson's disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical stimulation with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequency-specific (16-22 Hz) neural activity in a PD patient. Amplification of targeted oscillations led to an increase in the variance of motor tracking delays, supporting the hypothesis that pallidal beta oscillations are linked to motor performance. Our results highlight the utility of eiDBS to characterize the pathophysiology of PD and other brain conditions in the human and develop personalized neuromodulation therapies.
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