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. 1991;86(2):440-6.
doi: 10.1007/BF00228970.

On a method to detect long-latency excitations and inhibitions of single hand muscle motoneurons in man

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On a method to detect long-latency excitations and inhibitions of single hand muscle motoneurons in man

F Awiszus et al. Exp Brain Res. 1991.

Abstract

The peri-stimulus-time histogram (PSTH) analysis of stimulus-related neuronal spike train data is usually regarded as a method to detect stimulus-induced excitations or inhibitions. However, for a fairly regularly discharging neuron such as the human alpha-motoneuron, long-latency modulations of a PSTH are difficult to interpret as PSTH modulations can also occur as a consequence of a modulated neuronal autocorrelation. The experiments reported here were made (i) to investigate the extent to which a PSTH of a human hand-muscle motoneuron may be contaminated by features of the autocorrelation and (ii) to develop methods that display the motoneuronal excitations and inhibitions without such contamination. Responses of 29 single motor units to electrical ulnar nerve stimulation below motor threshold were investigated in the first dorsal interosseous muscle of three healthy volunteers using an experimental protocol capable of demonstrating the presence of autocorrelative modulations in the neuronal response. It was found for all units that the PSTH as well as the cumulative sum (CUSUM) derived from these responses were severely affected by the presence of autocorrelative features. On the other hand, calculating the CUSUM in a slightly modified form yielded--for all units investigated--a neuronal output feature sensitive only to motoneuronal excitations and inhibitions induced by the afferent volley. The price that has to be paid to arrive at such a modified CUSUM (mCUSUM) was a high computational effort prohibiting the on-line availability of this output feature during the experiment. It was found, however, that an interspike interval superposition plot (IISP)--easily obtainable during the experiment--is also free of autocorrelative features.(ABSTRACT TRUNCATED AT 250 WORDS)

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