Application of EEG source localization algorithms to the monitoring of active pathways in peripheral nerves

Improved techniques for identifying active pathways in peripheral nerves using extraneural measurements would have numerous applications in the fields of neuroprostheses, neural system engineering, and diagnostics. In this study, we propose to approach this issue as an inverse problem of bioelectric source localization, using measurements from a multi-contact nerve cuff electrode. This problem is a modified version of the electroencephalogram / magneto-encephalogram (EEG/MEG) source localization problem. We therefore evaluate the performance of two well-known EEG/MEG source localization algorithms, namely sLORETA and sFOCUSS, when they are applied to the peripheral nerve problem. sLORETA is found to be a potentially viable approach, albeit with limited resolution, while sFOCUSS is found to produce too many spurious pathways in the presence of noise.