Bach, DR;
Friston, KJ;
Dolan, RJ;
(2013)
An improved algorithm for model-based analysis of evoked skin conductance responses.
Biological Psychology
, 94
(3)
pp. 490-497.
10.1016/j.biopsycho.2013.09.010.
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Abstract
Model-based analysis of psychophysiological signals is more robust to noise - compared to standard approaches - and may furnish better predictors of psychological state, given a physiological signal. We have previously established the improved predictive validity of model-based analysis of evoked skin conductance responses to brief stimuli, relative to standard approaches. Here, we consider some technical aspects of the underlying generative model and demonstrate further improvements. Most importantly, harvesting between-subject variability in response shape can improve predictive validity, but only under constraints on plausible response forms. A further improvement is achieved by conditioning the physiological signal with high pass filtering. A general conclusion is that precise modelling of physiological time series does not markedly increase predictive validity; instead, it appears that a more constrained model and optimised data features provide better results, probably through a suppression of physiological fluctuation that is not caused by the experiment.
| Type: | Article |
|---|---|
| Title: | An improved algorithm for model-based analysis of evoked skin conductance responses. |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.biopsycho.2013.09.010 |
| Publisher version: | http://dx.doi.org/10.1016/j.biopsycho.2013.09.010 |
| Language: | English |
| Additional information: | © 2013 The Authors. Published by Elsevier B.V. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited. |
| Keywords: | Electrodermal activity (EDA), Galvanic skin response (GSR), General linear convolution model (GLM), Generative model, Model inversion, Skin conductance responses (SCR) |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1423204 |
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