Characterizing the brain’s dynamical response from scalp-level neural electrical signals: a review of methodology development

Guang Ouyang*, Changsong Zhou*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

11 Citations (Scopus)


The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain’s dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain’s working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.

Original languageEnglish
Pages (from-to)731-742
Number of pages12
JournalCognitive Neurodynamics
Issue number6
Early online date4 Sept 2020
Publication statusPublished - Dec 2020

Scopus Subject Areas

  • Cognitive Neuroscience

User-Defined Keywords

  • Brain response variability
  • Dynamical brain response
  • ERP decomposition
  • ERP latency jitter
  • Event-related potential


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