STOCHASTIC VERSUS DETERMINISTIC VARIABILITY IN SIMPLE NEURONAL CIRCUITS .1. MONOSYNAPTIC SPINAL-CORD REFLEXES

Long time series of monosynaptic la-afferent to alpha-motoneuron reflexes were recorded in the L7 or S1 ventral roots in the cat. Time series were collected before and after spinalization at T13 during constant amplitude stimulations of group la muscle afferents in the triceps surae muscle nerves. Using autocorrelation to analyze the linear correlation in the time series demonstrated oscillations in the decerebrate state (4/4) that were eliminated after spinalization (5/5). Three tests for determinism were applied to these series: 1) local flow, 2) local dispersion, and 3) nonlinear prediction. These algorithms were validated with time series generated from known deterministic equations. For each experimental and theoretical time series used, matched ti me-series of stochastic surrogate data were gene rated to serve as mathematical and statistical controls. Two of the ti me series collected in the decerebrate state (2/4) demonstrated evidence for deterministic structure. This structure could not be accounted for by the autocorrelation in the data, and was abolished following spinalization. None of the time series collected in the spinalized state (0/5) demonstrated evidence of determinism. Although monosynaptic reflex variability is generally stochastic in the spinalized state, this simple driven system may display deterministic behavior in the decerebrate state.