Abstract
The Contingent Negative Variation (CNV) is one of many types of electrical response signals which appear in the electroencephalogram (EEG) of man subsequent to one or more stimuli. Generally these responses are small in comparison to the normal background EEG and had always been thought to consist of a response component which was added to the background EEG. Professor B. McA. Sayers of Imperial College suggested that the auditory response might actually be due to a temporary ordering of the phases of the components of the background EEG. A model, allowing for additive and ordering effects, is proposed here. This model was tested on both auditory and CNV responses using statistical tests not previously used in evoked potential studies. The tests showed that while the additive model satisfactorily described the auditory responses, it did not explain the CNV responses so well. However, both sets of responses showed a certain amount of phase ordering and this was consistent with the model which showed that a repetitive additional component would always incorporate the phase ordering effect. In the absence of detectable additivity pure phase re-ordering might alternatively occur as proposed by Sayers. The CNV's of a patient group were also studied and certain tests are proposed as a possible method of diagnosis. The reliability of these tests was not conclusively proved as much larger control and patient groups would be required to do this. An important part of this work involved the introduction of a quantitative method for assessing the effectiveness of methods of removing eye movement artefact from the EEG. This allowed the development of a more extensive correction method which was tested against two other techniques and found to be superior. This correction method will provide the basis for further research and the development of a corrector to be made commercially.
Document Type
Thesis
Publication Date
1982
Recommended Citation
Nichols, M. (1982) An Investigation of the Contingent Negative Variation Using Signal Processing Methods. Thesis. University of Plymouth. Retrieved from https://pearl.plymouth.ac.uk/secam-theses/70