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Stochastic description of complex and simple spike firing in cerebellar Purkinje cells
Author(s) -
Shin SoonLim,
Rotter Stefan,
Aertsen Ad,
De Schutter Erik
Publication year - 2007
Publication title -
european journal of neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.346
H-Index - 206
eISSN - 1460-9568
pISSN - 0953-816X
DOI - 10.1111/j.1460-9568.2007.05308.x
Subject(s) - spike (software development) , simple (philosophy) , interval (graph theory) , train , biological system , poisson distribution , spike train , renewal theory , neuroscience , stochastic process , poisson process , process (computing) , statistical physics , computer science , physics , mathematics , biology , combinatorics , statistics , philosophy , software engineering , cartography , epistemology , geography , operating system
Cerebellar Purkinje cells generate two distinct types of spikes, complex and simple spikes, both of which have conventionally been considered to be highly irregular, suggestive of certain types of stochastic processes as underlying mechanisms. Interestingly, however, the interspike interval structures of complex spikes have not been carefully studied so far. We showed in a previous study that simple spike trains are actually composed of regular patterns and single interspike intervals, a mixture that could not be explained by a simple rate‐modulated Poisson process. In the present study, we systematically investigated the interspike interval structures of separated complex and simple spike trains recorded in anaesthetized rats, and derived an appropriate stochastic model. We found that: (i) complex spike trains do not exhibit any serial correlations, so they can effectively be generated by a renewal process, (ii) the distribution of intervals between complex spikes exhibits two narrow bands, possibly caused by two oscillatory bands (0.5–1 and 4–8 Hz) in the input to Purkinje cells and (iii) the regularity of regular patterns and single interspike intervals in simple spike trains can be represented by gamma processes of orders, which themselves are drawn from gamma distributions, suggesting that multiple sources modulate the regularity of simple spike trains.