A 16-Channel 60μW Neural Synchrony Processor for Multi-Mode Phase-Locked Neurostimulation

Uisub Shin, Cong Ding, Laxmeesha Somappa, Virginia Woods, Alik S. Widge, Mahsa Shoaran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Measuring neural oscillatory synchrony facilitates our understanding of complex brain networks and the underlying pathological states. Altering the cross-regional synchrony-as a measure of brain network connectivity-via phase-locked deep brain stimulation (DBS) could provide a new therapeutic solution for various neurological [1] and psychiatric disorders [2]. This feature is missing in current neuromodulation devices and requires an accurate, energy-efficient computation of oscillatory phase and cross-regional synchrony on chip. The conventional iterative vector processing approach via CORDIC [3] can accurately extract the instantaneous phase and phase locking value (PLV) at the cost of high power consumption (400μW). As a result, it cannot be applied to large-scale (>100-CH) neuronal networks. Moreover, the latency in the pipelined CORDIC processor may hinder timely phase-locked stimulation in the absence of an excessively high clock speed. Alternatively, the PLV extractors in [4], [5] utilized simple approximation algorithms such as 1-bit quantization and local minima detection. These methods, albeit efficient, compromise PLV accuracy and cannot extract the instantaneous phase of neuronal signals. To provide an efficient, flexible, and accurate phase-locked DBS platform, this paper integrates a 16-channel low-noise AFE, an energy-efficient multi-mode phase synchrony processor, and a 4-channel neurostimulator that is locked to specific neuronal oscillatory phases (i.e., fixed or random phase, PLV or PAC). An amplitude-locked control can be further enabled through envelope and multi-band spectral energy extraction for common use cases such as epilepsy.

Original languageEnglish (US)
Title of host publication2022 IEEE Custom Integrated Circuits Conference, CICC 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665407564
StatePublished - 2022
Event43rd Annual IEEE Custom Integrated Circuits Conference, CICC 2022 - Newport Beach, United States
Duration: Apr 24 2022Apr 27 2022

Publication series

NameProceedings of the Custom Integrated Circuits Conference
ISSN (Print)0886-5930


Conference43rd Annual IEEE Custom Integrated Circuits Conference, CICC 2022
Country/TerritoryUnited States
CityNewport Beach

Bibliographical note

Funding Information:
This work was supported by the National Institute of Mental Health Grant R01-MH-123634

Publisher Copyright:
© 2022 IEEE.


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