THE ESSENTIAL
- Researchers have found that Parkinson’s patients process emotions differently than healthy people.
- They have difficulty recognizing fear, disgust and surprise.
- Analyzing brain responses to emotional stimuli using EEG and AI is proving to be an effective method for spotting people suffering from Parkinson’s.
In France, each year, there are nearly 26,000 new cases of Parkinson’s disease. It is also the second most common neurodegenerative pathology in the country, after Alzheimer’s.
Researchers from the University of Canberra and Kuwait College of Science and Technology have uncovered a new way to detect Parkinson’s disease. It involves analyzing responses to emotional situations such as fear, disgust and surprise.
Their discovery was the subject of an article published in the journal Intelligent Computing.
Parkinson’s disease: patients have difficulty distinguishing emotions
To better understand the impact of the disease characterized by progressive degeneration of dopamine neurons on the brain, researchers recorded the brain activity of 40 volunteers, half of whom suffered from Parkinson’s, while they watched videos and images using to an electroencephalogram (EEG). The content viewed was designed to provoke emotions: sadness, happiness, fear, disgust, anger and surprise.
The key characteristics of each emotion were identified on the EEG recordings. Data analysis – carried out with the help of artificial intelligence – shows that patients with Parkinson’s disease exhibit specific patterns of emotional perception. They perceived emotional arousal better than emotional valence. That is to say, they were “more attentive” of the intensity of the emotion as its pleasant or unpleasant character. Additionally, they had more difficulty distinguishing fear, disgust, and surprise than healthy people. They also confused opposite feelings like sadness and happiness.
Parkinson’s: analysis of brain waves in response to emotions could facilitate diagnosis
By studying analyzes of brain responses to emotions, the team was able to distinguish Parkinson’s patients from healthy people with an F-measure score of 0.97 (the best score being 1). This means that this diagnostic test, based solely on brain wave data, has an accuracy very close to 100%.
“The findings provide an objective way to diagnose this disabling movement disorder, instead of relying on clinical expertise and patient self-assessments, potentially improving treatment options and the overall well-being of those affected by Parkinson’s disease“, note the authors in the presentation of their study. They intend to continue their work to gather more data on this phenomenon and improve their diagnostic tool.
