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  and psychiatric disorders . 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  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 ,  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 language||English (US)|
|Title of host publication||2022 IEEE Custom Integrated Circuits Conference, CICC 2022 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - 2022|
|Event||43rd Annual IEEE Custom Integrated Circuits Conference, CICC 2022 - Newport Beach, United States|
Duration: Apr 24 2022 → Apr 27 2022
|Name||Proceedings of the Custom Integrated Circuits Conference|
|Conference||43rd Annual IEEE Custom Integrated Circuits Conference, CICC 2022|
|Period||4/24/22 → 4/27/22|
Bibliographical noteFunding Information:
This work was supported by the National Institute of Mental Health Grant R01-MH-123634
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