Matthew M Gerhold, Ph.D.


I conducted my doctoral research in the Faculty of Health Sciences at the University of Cape Town, working within the Division of Biomedical Engineering, Department of Human Biology. My undergraduate research training was in the Department of Psychology, University of Cape Town, where I spent 4 years as a teaching assistant. The degree of Doctor of Neuroscience was conferred in Cape Town, December 2017. A large portion of my doctoral research has been published and/or is currently under peer-review. Fundamentally, I devote myself to the proper application of the scientific method in order to address a research question/problem. This involves not only deep knowledge of current methods and protocols, but also a strong ethical stance in daily research practices.

My neuroscience specialisation is within the area of non-invasive electrophysiological measurements related to thought and emotion in alcohol-related disorders and in normal daily life. My skill-set encompasses expert domain knowledge of biological data-acquisition, biomedical signal-processing, biostatistics, and identification of bioelectrical changes related to the human mind and human behaviour. In addition, I have extensive experience in cognitive and behavioural sciences, working with perceptual and decision-making tasks. I am also have extensive hand-on experience with a range of eye-tracking data-acquisition set-ups.

To date, my work (extending over 14 years of research) has encompassed a range of neuroscientific applications. These have included cross-cultural studies of electrophysiological correlates of melodic perception, advertising and marketing applications, and clinical research into alcohol-related disorders. All of this work has been conducted with a hand-ons approach from data-acquisition through to report delivery, presentation and in applicable instance publication in peer-reviewed journals.

Current interests involve scientific ethics in daily research practice and principles of effective scientific leadership related to commercial neuroscientific application—this area, I feel is tragically underdeveloped and needs serious development. Methodologically, I am interested source-level connectivity measurements derived from the electroencephalogram. Specifically, this involves questions related to spatial filters and resultant connectivity maps, the use of graph theory to identify connectivity patterns, and the application of multivariate parametric approaches to model EEG signals. In terms of advancing scientific understanding, application of EEG/machine-learning approaches to measure effectiveness of audio-visual content delivery (with partial application to marketing and advertising). Musical processing and perception in the human mind. Decision-making paradigms and analysis of such data in the context of consumer neuroscience – the relation to decision-making processes and the dynamics of the electrocortical field.

Subscribe to