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Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles.

N J Williams1, S J Nasuto1, J D Saddy1

  • 1Centre for Integrative Neuroscience & Neurodynamics, University of Reading, Whiteknights Campus, Reading RG6 6AH, United Kingdom.

Journal of Neuroscience Methods
|February 21, 2015
PubMed
Summary

This study introduces a novel pipeline for analyzing event-related potential (ERP) data, revealing significant cluster structures. Applying this cluster analysis before ensemble averaging is recommended for more accurate ERP research.

Keywords:
ERP cluster analysisEmpirical Mode DecompositionGenetic AlgorithmsStability Indexk-means clustering

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Data Analysis

Background:

  • Ensemble averaging of event-related potential (ERP) data assumes identical trials, a premise often invalid.
  • A need exists for preliminary data analysis to identify cluster structures in ERP datasets.

Purpose of the Study:

  • To develop and validate a comprehensive pipeline for cluster analysis of ERP data.
  • To address the limitations of ensemble averaging by identifying underlying data structures.

Main Methods:

  • A pipeline utilizing Empirical Mode Decomposition (EMD) for denoising single-trial ERPs.
  • A bootstrap-based Stability Index (SI) to determine the optimal number of clusters.
  • A Genetic Algorithm (GA) for initial centroid selection, followed by k-means clustering.
  • Principal Component Analysis (PCA) for visualizing clustering results.

Main Results:

  • The pipeline was validated on simulated data and applied to real experimental ERP data.
  • Evidence of 6 distinct clusters was found in a language processing study condition.
  • Subject influenced cluster membership, as indicated by a two-way chi-square test.

Conclusions:

  • The proposed analysis method operates on denoised single-trials with principled cluster number determination.
  • Results are presented via an intuitive visualization scheme.
  • Cluster analysis is suggested as a preliminary step prior to ensemble averaging in ERP studies.