Pulse-based signal compression for implanted neural recording systems
Today's implanted neural systems are bound by tight constraints on power and communication bandwidth. Most conventional ADC-based approaches fall into two categories. Either they transmit all of the information at the Nyquist rate but are ultimately limited to only a handful of channels due to communication bandwidth constraints. Or they perform spike detection on the front-end which allows a scale up to 100 or more channels but prevents the use of spike sorting on the backend. Spike sorting is an important step that provides a labeling to multiple neurons on each channel and further improves the accuracy of spike detection. In this paper we describe the pulse-based approach used in the FWIRE (Florida wireless implantable recording electrodes) project. A hardware spiking neuron on each channel is configured either to transmit pulses for full reconstruction on the back-end, or to transmit dramatically fewer pulses but still allow for spike sorting on the back-end. Spike sorting results show that the pulse-based spike sorting accuracy is competitive with conventional methods used in daily practice.