Latency Reduction during Telemetry Transmission in Brain-Machine Interfaces

Advanced array processing techniques are becoming an indispensable requirement for integrating the rapid developments in wireless high-density electronic interfaces to the central nervous system with computational neuroscience. This work aims at describing a systems approach for latency reduction in telemetry-linked brain machine interfaces to enable real-time transmission of high volumes of neural data. We show that the tradeoff between transmission bit rate and processing complexity requires a smart processing mechanism to strip the redundancy and extract the useful information early in the data stream. The results presented demonstrate that space-time processing offers tremendous savings in communication costs compared to on-chip spike detection followed by off-chip classification. They also demonstrate that the performance asymptotically approaches that of on-chip spike detection and sorting. Detailed performance evaluation is described