Statistical modelling of artificial neural network for sorting temporally synchronous spikes

Rakesh Veerabhadrappa, Asim Bhatti, Chee Peng Lim, Thanh Thi Nguyen, Susannah J Tye, Paul Monaghan, Saeid Nahavandi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Artificial neural network (ANN) models are able to predict future events based on current data. The usefulness of an ANN lies in the capacity of the model to learn and adjust the weights following previous errors during training. In this study, we carefully analyse the existing methods in neuronal spike sorting algorithms. The current methods use clustering as a basis to establish the ground truths, which requires tedious procedures pertaining to feature selection and evaluation of the selected features. Even so, the accuracy of clusters is still questionable. Here, we develop an ANN model to specially address the present drawbacks and major challenges in neuronal spike sorting. New enhancements are introduced into the conventional backpropagation ANN for determining the network weights, input nodes, target node, and error calculation. Coiflet modelling of noise is employed to enhance the spike shape features and overshadow noise. The ANN is used in conjunction with a special spiking event detection technique to prioritize the targets. The proposed enhancements are able to bolster the training concept, and on the whole, contributing to sorting neuronal spikes with close approximations.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages261-272
Number of pages12
Volume9491
ISBN (Print)9783319265544
DOIs
StatePublished - 2015
Event22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey
Duration: Nov 9 2015Nov 12 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9491
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other22nd International Conference on Neural Information Processing, ICONIP 2015
CountryTurkey
CityIstanbul
Period11/9/1511/12/15

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Veerabhadrappa, R., Bhatti, A., Lim, C. P., Nguyen, T. T., Tye, S. J., Monaghan, P., & Nahavandi, S. (2015). Statistical modelling of artificial neural network for sorting temporally synchronous spikes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9491, pp. 261-272). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9491). Springer Verlag. https://doi.org/10.1007/978-3-319-26555-1_30