Do we measure what we think we are measuring?
EPFL
Abstract
Tests used in the empirical sciences are often (implicitly) assumed to be representative of a target mechanism in the sense that similar tests should lead to similar results. In this talk, using resting-state electroencephalogram (EEG) as an example, I will argue that this assumption does not necessarily hold true. Typically EEG studies are conducted selecting one analysis method thought to be representative of the research question asked. Using multiple methods, we extracted a variety of features from a single resting-state EEG dataset and conducted correlational and case-control analyses. We found that many EEG features revealed a significant effect in the case-control analyses. Similarly, EEG features correlated significantly with cognitive tasks. However, when we compared these features pairwise, we did not find strong correlations. A number of explanations to these results will be discussed.
Topics
Related Job Opportunities
Postdoctoral Scientist - Sarvestani Lab
The Sarvestani Lab at Cornell University is recruiting a postdoctoral scientist in systems neuroscience to study how visual and motor systems across the brain and body support perception and…
PhD Studentship: Mitochondrial Metabolism and Novel Therapeutic Strategies for Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) (Fixed Term)
Supervisors: Professor Andrew Murray, Department of Physiology, Development and Neuroscience, University of Cambridge Dr Ross Lindsay, Novo Nordisk Funding: Fully funded PhD studentship (Home/UK…
Research Associate (Fixed Term)
We seek a highly motivated Postdoctoral Research Associate to join the laboratory of Professor Kathy Niakan. We are based in the Loke Centre for Trophoblast Research (LCTR), in the Department of…