Recognition of temporally changing action potentials in multiunit neural recordings Article

Mirfakhraei, K, Horch, K. (1997). Recognition of temporally changing action potentials in multiunit neural recordings . IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 44(2), 123-131. 10.1109/10.552242

cited authors

  • Mirfakhraei, K; Horch, K

authors

abstract

  • We present a method to iteratively train an artificial neural network (ANN) or other supervised pattern classifier in order to adaptively recognize and track temporally changing patterns. This method uses recently acquired data and the existing classifier to create new training sets, from which a new classifier is then trained. The procedure is repeated periodically using the most recently trained classifier. This scheme was evaluated by applying it to simulated situations that arise in chronic recordings of multiunit neural activity from peripheral nerves. The method was able to track the changes in these simulated chronic recordings and to provide better unit recognition rates than an unsupervised clustering method suited to this problem.

publication date

  • February 11, 1997

Digital Object Identifier (DOI)

start page

  • 123

end page

  • 131

volume

  • 44

issue

  • 2