title: Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles.
abstract: BACKGROUND
  The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data.
  
  
  METHODS
  We propose a complete pipeline for the cluster analysis of ERP data. To increase the signal-to-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA) to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA).
  
  
  RESULTS
  After validating the pipeline on simulated data, we tested it on data from two experiments - a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership.
  
  
  CONCLUSIONS
  Our analysis operates on denoised single-trials, the number of clusters are determined in a principled manner and the results are presented through an intuitive visualisation.
  
  
  CONCLUSIONS
  Given the cluster structure in some experimental conditions, we suggest application of cluster analysis as a preliminary step before ensemble averaging.
authors.affiliation: Centre for Integrative Neuroscience & Neurodynamics, University of Reading, Whiteknights Campus, Reading RG6 6AH, United Kingdom. Electronic address: nitinwilliams@gmail.com.
authors.forename: N J
authors.initials: NJ
authors.lastname: Williams
authors.affiliation: Centre for Integrative Neuroscience & Neurodynamics, University of Reading, Whiteknights Campus, Reading RG6 6AH, United Kingdom.
authors.forename: S J
authors.initials: SJ
authors.lastname: Nasuto
authors.affiliation: Centre for Integrative Neuroscience & Neurodynamics, University of Reading, Whiteknights Campus, Reading RG6 6AH, United Kingdom.
authors.forename: J D
authors.initials: JD
authors.lastname: Saddy
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D062207:Brain-Computer Interfaces; D016000:Cluster Analysis; D003198:Computer Simulation; D066264:Datasets as Topic; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials; D006801:Humans; D007802:Language; D007807:Language Tests; D008959:Models, Neurological; D009483:Neuropsychological Tests; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D014796:Visual Perception / Q000502:physiology
keywords: ERP cluster analysis; Empirical Mode Decomposition; Genetic Algorithms; Stability Index; k-means clustering