Statistical modelling of artificial neural network for sorting temporally synchronous spikes

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

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

2 Scopus citations


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 publicationNeural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
EditorsTingwen Huang, Qingshan Liu, Weng Kin Lai, Sabri Arik
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319265544
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)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other22nd International Conference on Neural Information Processing, ICONIP 2015

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Statistical modelling of artificial neural network for sorting temporally synchronous spikes'. Together they form a unique fingerprint.

Cite this