Multiplication of Compound Signals in Neural Array Signal Processing Improves Signal Quality and Detectability of Action Potentials.

Electrode arrays along peripheral nerves can record sensory, motor and autonomic signals propagating in afferent and efferent direction at different conduction velocities. To extract this temporal information in a delay-and-sum approach, velocity-selective recording (VSR) utilizes summation to amplify time-aligned action potentials and average out noise. This improved contrast subsequently improves the automated detection and classification of action potentials-an essential prerequisite to interface with the peripheral nervous system. In this study, we replaced the summation with multiplication and investigated resulting signal changes. We focused on two derived methods: Lock-IN-Dispersion-Analysis (LINDA) multiplies all recorded signals; Delay-Combinatory-Multiply-And-Sum (DCMAS) multiplies all combinations of an adjustable number of signals and sums the products. Processing simulated neural array recordings, we compared the effects of LINDA and DCMAS on contrast-to-noise ratio (CNR), signal-to-noise-and distortion ratio (SINAD) and AP detectability after thresholding. Compared to VSR, both methods increased CNR, SINAD, and AP detectability but also introduced noise intermodulation distortion which limited SINAD gains. Additionally, LINDA formed a logical AND-gate between signals, suppressing interfering signal peaks. Overall, by increasing CNR, signal multiplication may improve decoding of array recordings, despite increased signal distortion. It may thereby advance neural interfaces for fundamental research, diagnostics or applications in bioelectronic medicine and neuroprostheses.