Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the field of veterinary medicine using X-rays as a key adjunct test. EEG signals were analyzed using Principal Component Analysis (PCA) and Logistic Regression Analysis.

Principal component analysis revealed three patterns that accounted for 85% of the total variance in EEG activity recorded while veterinarians read a clinical history, examined an X-ray image pertinent to a medical case, and selected between alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and executive control of the task. The other pattern is proposed to be related to the reasoning process that occurs during diagnostic decision-making.

PCA analysis was successful in revealing the distinct patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3) and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in revealing the brain activity associated with successful clinical reasoning and, together with regression analysis, showed that clinical practice reorganizes the neural circuits that support clinical reasoning.