The theme of my research is to understand both the biological causes and psychological consequences of differences on the major dimensions of personality, temperament and cognitive variation that have been observed consistently in multivariate statistical analyses of psychological data. Some 30 years ago I chose to study brain electrical activity, manifest in the electroencephalogram (EEG), as the phenomenon most likely to provide information about the biological causes of these systematic psychological differences; and ultimately to reveal the biological causes of the ‘functional’ psychiatric disorders. However, at that time, the existing methods of EEG measurement and analysis had failed to reveal meaningful relationships with measures of psychological variation. Most investigators and reviewers attributed this to the poor quality of the theories motivating such research; and for those less well acquainted with the psychometric literature there have always been doubts concerning the validity of ‘soft science’ questionnaire measures of personality.

At the time, I had my own very serious doubts about the quality of psychological measures. However, after thoroughly reviewing the relevant literature I concluded that the failure to find meaningful relationships was more likely to be a consequence of the use of inadequate methods of EEG measurement and analysis. Many different EEG measures had been employed. These were entirely superficial and of unknown significance since there was no theory that could specify how individual differences in the functional character of neural systems would be expected to cause EEG differences. There was also no theory to suggest how such differences could result in psychological differences. In the absence of such theories there was no basis for making decisions about what should be measured, and no basis for the conduct of meaningful research.

Therefore, my first task was to acquire an understanding of the physical dynamics of EEG activity and to relate this to the functional characteristics of neural systems. The outcome of this research was the formulation of a theory that explains EEG activity, and all oscillatory electrical activity of the central nervous system, in terms of the interaction of excitatory and inhibitory neurons within closed loops or circuits. Extensive testing of this EEG theory was first described in a paper published in 1983. The same paper provides a detailed account of the methodology that is required for a systematic and meaningful analysis of EEG activity.

With the new methods of EEG measurement and analysis described in my 1983 paper it was subsequently possible to demonstrate relationships between EEG differences and psychological differences; and these relationships could be explained in terms of differences in the functional properties of large neural systems. This led to the development of the only theory in the field of psychology that provides an integrated and comprehensive account of the biological bases of personality and intelligence differences. The first comprehensive description of this theory, and of the earlier empirical research on which it is based, was provided in my 1996 book Brain, Mind, and Behaviour: A New Perspective on Human Nature.

Subsequent publications, listed elsewhere on this website, describe further testing and refinement of the theory; and in this case using new methods for the analysis of EEG responses evoked by conventional stimulation procedures (averaged evoked potentials or AEPs). This work demonstrates that it is possible to distinguish alpha, theta and delta wave components in ordinary AEPs that can be attributed to the major brain-stem and thalamocortical arousal systems. There is reason to believe that these components correspond to the alpha, delta and theta activity of the spontaneous EEG and it has been possible to demonstrate that they relate to each other, and to differences in temperament and personality, in the precise manner predicted by theory.

A revised edition of my 1996 book has just been published. It describes how one can measure normal individual differences in EEG parameters that indicate the relative influence of thalamocortical and brain-stem processes, and of GABA and glutamatergic acid, the major neurotransmitters of the thalamocortical system and of the CNS. This book also specifies the combinations of EEG parameters that are associated with optimal psychological profiles. On the basis of this information it should soon be possible to provide an objective basis for the diagnosis of different psychiatric disorders and for the monitoring of the therapeutic effects of drugs used to treat these disorders.

It is fitting to conclude this account with reference to the comments of a very experienced EEG researcher who carried out a careful and critical appraisal of my ideas and findings. More specifically, I would like to refer to a book published in 2003 by the late Dr. John Shaw. Dr. Shaw was personally engaged in EEG research for over 50 years - and from the earliest days of its clinical application. He set up and managed one of the first EEG Departments in the U.K. and subsequently worked as a full-time EEG researcher for the U.K. Medical Research Council.

In his book, entitled The Brain’s Alpha Rhythms and the Mind, there is a very comprehensive review of classical and modern studies of the EEG alpha rhythm, with commentaries on the associated neuroscience and neurophysiology. Despite his obvious preference for the physical and neurophysiological aspects of EEG research, Dr. Shaw devoted a large part of one chapter to my work. His general conclusion is best indicated by quoting a paragraph from his ‘Acknowledgements’. He wrote as follows: “I am also grateful to David Robinson, Professor of Psychology, Kuwait University, for his critical comments on selected chapters, in particular Chapter 9 in which his work is described. Whilst David’s work has not always received the recognition it deserves, I believe his novel approach . . . linking the neurophysiology of the EEG with the psychology of behaviour . . . will yet prove to be a landmark in the development of EEG research.


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