Combining frequency and time domain approaches to systems with multiple spike train input and output

Brillinger, D.R., Rosenberg, J. and Lindsay, K. (2009) Combining frequency and time domain approaches to systems with multiple spike train input and output. Biological Cybernetics, 100(6), pp. 459-474. (doi: 10.1007/s00422-008-0289-y)

[img] Text



A frequency domain approach and a time domain approach have been combined in an investigation of the behaviour of the primary and secondary endings of an isolated muscle spindle in response to the activity of two static fusimotor axons when the parent muscle is held at a fixed length and when it is subjected to random length changes. The frequency domain analysis has an associated error process which provides a measure of how well the input processes can be used to predict the output processes and is also used to specify how the interactions between the recorded processes contribute to this error. Without assuming stationarity of the input, the time domain approach uses a sequence of probability models of increasing complexity in which the number of input processes to the model is progressively increased. This feature of the time domain approach was used to identify a preferred direction of interaction between the processes underlying the generation of the activity of the primary and secondary endings. In the presence of fusimotor activity and dynamic length changes imposed on the muscle, it was shown that the activity of the primary and secondary endings carried different information about the effects of the inputs imposed on the muscle spindle. The results presented in this work emphasise that the analysis of the behaviour of complex systems benefits from a combination of frequency and time domain methods.

Item Type:Articles (Other)
Glasgow Author(s) Enlighten ID:Lindsay, Professor Kenneth and Rosenberg, Prof Jay
Authors: Brillinger, D.R., Rosenberg, J., and Lindsay, K.
Subjects:Q Science > QP Physiology
College/School:College of Medical Veterinary and Life Sciences
College of Science and Engineering > School of Mathematics and Statistics > Mathematics
Journal Name:Biological Cybernetics
Journal Abbr.:Biol Cybern
ISSN (Online):1432-0770
Copyright Holders:Copyright © 2009 The Authors
First Published:First published in Biological Cybernetics 100(6):459-474
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher.

University Staff: Request a correction | Enlighten Editors: Update this record