Neurodegenerative disorders such as Parkinson’s and Alzheimer’s disease affect millions of people in the United States every year. New research could soon improve early detection of these illnesses, as scientists may have discovered a way to predict neurological disorders – at least in painters.
Parkinson’s disease is also common. According to the National Institutes of Health (NIH), approximately
Neurological disorders falling under the umbrella term “dementia” occur when nerve cells die or can no longer function properly, often resulting in memory loss and impaired reasoning. Patients currently receive a dementia diagnosis when their cognitive impairment becomes so severe that it interferes with their daily activities.
New research published in the journal Neuropsychology may have found a way to identify neurodegenerative disease in patients before they have been formally diagnosed.
Researchers led by psychologist Dr. Alex Forsythe – from the School of Psychology of the University of Liverpool, United Kingdom – analyzed 2,092 paintings by seven famous painters. The team collaborated with Dr. Tamsin Williams, of Tees, Esk, and Wear Valleys NHS Trust, and Dr. Ronan G. Reilly, from Maynooth University in Ireland.
Of the seven artists examined, two (Salvador Dali and Norval Morrisseau) had experienced Parkinson’s disease, while another two (James Brooks and Willem De Kooning) had Alzheimer’s disease.
Three of the artists – Marc Chagall, Pablo Picasso, and Claude Monet – had undergone a normal aging process, with no recorded neurodegenerative diseases.
The artists’ paint strokes were analyzed by applying non-traditional mathematics to the patterns known as “fractals.”
Fractals are infinitely complex patterns that repeat themselves with mathematical precision at different scales. Fractals can be natural or created. Natural fractals include branching patterns – which can be found in trees, rivers, blood vessels, lightning bolts, or mountains – and spiral patterns – such as seashells, galaxies, or variant forms of cauliflower.
Fractal analysis has previously been used to establish the authenticity of major works of art. A prior analysis of 23 paintings by Jackson Pollock has revealed a 100 percent success rate in terms of the artworks’ fractal content, as opposed to a 100 percent failure rate in paintings of unknown origin.
This shows that artists use unique fractal behaviors when they paint, and that computers can accurately detect the patterns characteristic of famous painters.
In the present study by Dr. Forsythe and her team, even though researchers examined different painters working within different genres, the fractal patterns in their paint strokes remained comparable.
Researchers examined the changes in the artists’ unique fractals over time, in an attempt to see if they were due to normal aging or cognitive deterioration typical of neurodegenerative disease.
“Art has long been embraced by psychologists as an effective method of improving the quality of life for those persons living with cognitive disorders. We have built on this tradition by unpicking artists’ ‘handwriting’ through the analysis of their individual connection with the brush and paint.”
Dr. Alex Forsythe
The analysis revealed evident patterns of change in the fractal dimensions of the different painters. These changes showed a clear demarcation between artists who had experienced neurological deterioration and those who aged normally.
Dr. Forsythe and team hope that their study will open up new avenues for future research into neurodegenerative disease.
“This process offers the potential for the detection of emerging neurological problems. We hope that our innovation may open up new research directions that will help to diagnose neurological disease in the early stages,” says the lead study author.