A framework for the analysis of neuronal networks

A. M. Amjad, P. Breeze, B. A. Conway, D. M. Halliday, J. R. Rosenberg

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


The object of this work is to consider the application of some methods of spike train analysis that are not widely known, and are concerned with the description of the interactions between spike trains and the determination of causal connections between them. The notation and terminology follow conventions established in the statistical literature. The examples given are based on in-continuity recordings of the spontaneous activity of single Ia afferents from the soleus muscle and single motor units from the same muscle. Cumulant densities are shown to be simple extensions of the traditional cross-correlation methods, and are useful in characterizing the pattern of activity in one spike train that influences that in another, and to reveal interactions between spike trains that would not be apparent from the correlation histogram alone. Parameters based on the Fourier transforms of the spike trains are shown to be useful in determining timing relations between them, and in inferring patterns of connectivity not possible by correlation methods alone.

Original languageEnglish
Pages (from-to)243-255
Number of pages13
JournalProgress in Brain Research
Issue numberC
Publication statusPublished - 1 Jan 1989


  • coherence
  • correlation
  • fourier analysis
  • Ia afferent
  • motor unit
  • neuronal network
  • partial coherence
  • partial spectrum
  • point process
  • spike train


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