TY - JOUR T1 - Real-time suppression and amplification of neural oscillations using electrical stimulation and phase feedback JF - bioRxiv DO - 10.1101/2020.02.09.940643 SP - 2020.02.09.940643 AU - David Escobar Sanabria AU - Luke A. Johnson AU - Ying Yu AU - Zachary Busby AU - Shane Nebeck AU - Jianyu Zhang AU - Noam Harel AU - Matthew D. Johnson AU - Gregory F. Molnar AU - Jerrold L. Vitek Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/03/25/2020.02.09.940643.abstract N2 - 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 Statement We 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. ER -