Classification of action potentials in multi-unit intrafascicular recordings using neural network pattern recognition techniques Conference

cited authors

  • Mirfakhraei, K; Horch, KW

fiu authors

abstract

  • Neural network pattern recognition techniques were applied to classify action potentials in multi-unit neural recordings made from chronically and acutely implanted intrafascicular electrodes in cats. The success of unit potential classification with the neural network was compared to that with a previously described template system. The neural network reliably separated 89 of the 194 recorded units, while the template system only separated 31 of the units. The network was able to reliably separate 6 or 7 units per recording, on average. The results demoustrate the potential superiority of neural networks over template matching approaches to classification of neural activity in multi-unit recordings.

publication date

  • January 1, 1992

Digital Object Identifier (DOI)

start page

  • 1328

end page

  • 1329

volume

  • 4