Quantifying periodic activity in central pattern generators: the crayfish swimmeret.
Experimental recordings from neurons are generally difficult to quantify. Spike patterns and membrane potential cycles are often compared qualitatively and are hence limited by human resolution and judgement. This paper describes a statistical method for quantifying individual spike patterns and membrane potential fluctuations in oscillating systems, allowing quantification of successive 'individual' bursts. The neuronal activities of the network can therefore be subject to more extensive analyses and comparisons. Principal-component analysis was used to extract the principal components from a sequence of bursts recorded in vitro from the crayfish (Pacifasticus leniusculus) swimmeret. The principal component coefficients were correlated with intuitive biological concepts such as burst displacement, number of spikes in a burst, and burst width. The bursting of both interneurones and motor neurones were found to be modulated by some unidentified oscillator that displaced the bursts in time. The amplitude of the time displacements was significant, i.e., of the order of the bursting period (1.5 s), and the period of the oscillation was approximately 200 bursts. The strength of the method is that this feature was detected without any prior suspicion of its existence.
Olsen
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Department of Electronics and Electrical Engineering, University of Glasgow, Scotland, UK.
Murray-Smith
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D000200:Action Potentials; D000818:Animals; D003400:Astacoidea / Q000502:physiology; D002490:Central Nervous System / Q000502:physiology*; D004594:Electrophysiology; D017952:Ganglia, Invertebrate / Q000166:cytology / Q000502:physiology; D007395:Interneurons / Q000502:physiology; D009046:Motor Neurons / Q000502:physiology; D010507:Periodicity; D013223:Statistics as Topic