Shan Yu

Toward a Neural Foundation Model: A Probabilistic Spike Representation Model to Mitigate Neural Variability

The Probabilistic Neural Representation Transformer (PNRT) is proposed, a framework that models variable spike activities into a consistent latent probabilistic distribution and implements an activity-based neuronal reordering method that decouples the model from physical electrode positions to mitigate misalignment.