A totally automated system for the detection and classification of neural spikes

@article{Yang1988ATA,
  title={A totally automated system for the detection and classification of neural spikes},
  author={Xiaosong Yang and S A Shamma},
  journal={IEEE Transactions on Biomedical Engineering},
  year={1988},
  volume={35},
  pages={806-816}
}
A system for neural spike detection and classification is presented which does not require a priori assumptions about spike shape or timing. The system is divided into two parts: a learning subsystem and a real-time detection and classification subsystem. The learning subsystem, comprising of feature learning phase and a template learning phase, extracts templates for each separate spike class. The real-time detection and classification subsystems identifies spikes in the noisy neural trace and… CONTINUE READING