Low-latency VLSI architecture for neural cross-frequency coupling analysis.

Abstract

Growing evidence suggests that cross-frequency coupling (CFC) is a key mechanism in neuronal computation, communication, and learning in the brain. Abnormal CFC has been implicated in pathological brain states such as epilepsy and Parkinson's disease. A reduction in excessive coupling has been shown in effective neuromodulation treatments, suggesting that CFC may be a useful feedback measure in closed-loop neural stimulation devices. However, processing latency limits the responsiveness of such systems. A VLSI architecture is presented which implements three selectable measures of CFC to enable the application specific trade-off between low-latency and high-accuracy processing. The architecture is demonstrated using in-vitro human neocortical slice recordings, with a latency of 48ms.