Shin, UisubDing, CongSomappa, LaxmeeshaWoods, VirginiaWidge, Alik s.Shoaran, Mahsa2024-06-072024-06-072024-06-07202210.1109/CICC53496.2022.9772806https://infoscience.epfl.ch/handle/20.500.14299/208465Measuring 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.text::conference output::conference paper not in proceedings