학술논문

Adaptively Clock-Boosted Auto-Ranging Neural-Interface for Emerging Neuromodulation Applications
Document Type
Periodical
Source
IEEE Transactions on Biomedical Circuits and Systems IEEE Trans. Biomed. Circuits Syst. Biomedical Circuits and Systems, IEEE Transactions on. 16(6):1138-1152 Dec, 2022
Subject
Bioengineering
Components, Circuits, Devices and Systems
Electrodes
Neuromodulation
Recording
Satellite broadcasting
Interference
Epilepsy
Transient analysis
Analog-to-digital converter
brain implant
brain-machine interface
brain-computer interface
chopping
closed-loop
DC-coupled
delta modulator
input impedance
opamp-less
radix-2 auto-ranging
spectrum equalization
temporally interfering stimulation
neural-ADC
non-invasive neuromodulation
stimulation artifact
Language
ISSN
1932-4545
1940-9990
Abstract
Responsive deep brain stimulation (DBS) requires recruiting deep brain structures without affecting the superficial neuronal population. Neurosurgeons widely use implanted electrodes, which are highly localized but invasive, to stimulate the deep brain. Temporally interfering stimulation (TIS) excites the deep brain non-invasively. This neuromodulation technique utilizes two high-frequency sinusoidal electric fields that do not recruit superficial neural structures but have a small frequency differential. The small differential causes a low-frequency interference envelope that stimulates deep regions and is steerable by changing the intensity of the electric fields without physically moving the electrodes. Using TIS as a non-invasive DBS method generates high-frequency stimulation artifacts at recording sites, which may saturate a conventional recording front-end. This paper presents a low-power bidirectional 64-channel CMOS neural-ADC that is immune to artifacts such as those in the TIS techniques or conventional biphasic stimulation. The presented DC-coupled chopped analog front-end leverages delta-spectrum shaping to remove electrode DC offset voltage and maintain the input impedance higher than 250 MΩ, which is sufficient for interfacing with non-invasive scalp electrodes. The AFE operates on the input signal difference to detect large and rapid stimulation artifacts. It incorporates both exponential tracking and boosted-rate sampling to recover within 100 μ s. Upon recovery, the neural-ADC range and speed are reduced to achieve noise and power efficiency factors of 2.98 and 10.6, respectively. In vivo recordings from anesthetized mice demonstrate the unique capabilities of the presented architecture in resolving local field potentials from the surface and epidural electrodes.