José Zariffa

This paper introduces a printed self-folding cuff electrode with integrated rigid electrical components for chronic peripheral nerve interfacing, demonstrating reliable nerve recordings in locusts and rats.

This study shows that precise hippocampal stimulation timed to saccadic ERPs enhances memory, while random or early stimulation impairs it, challenging rodent theta rhythm assumptions.

This paper demonstrates closed-loop control of functional electrical stimulation using a CNN to classify nerve cuff recordings and trigger stimulation based on detected hindpaw states.

The paper develops resource-efficient neural network architectures for classifying nerve cuff recordings, achieving significant reductions in weights, memory, and FLOPs while maintaining comparable accuracy.

This paper develops an algorithm to automatically reconstruct peripheral nerve models from histological images, achieving moderate accuracy compared to manual ground truths.

The paper classifies naturally evoked compound action potentials using spatiotemporal signatures from multi-contact nerve cuff recordings in rats, achieving moderate accuracy and correlation with original firing rates.