UCLA researchers quantify participants’ levels of empathy in new study
(Cat Nordstrom/Daily Bruin)
Feb. 27, 2020 11:41 p.m.
UCLA researchers were able to assess the ability to feel empathy in a person not doing anything.
The study found that machine learning could use brain patterns to determine levels of empathy, said Leonardo Christov-Moore, lead author of the study and a former neuroscience doctoral student at UCLA. Machine learning is a subdivision of artificial intelligence based on the idea that computer systems can find patterns in large quantities of data. The study was published in Frontiers in Integrative Neuroscience on Feb. 14.
Researchers scanned participants’ brains using an MRI machine while the participants allowed their minds to wander, said Christov-Moore, currently a postdoctoral fellow at USC’s Brain and Creativity Institute. The researchers were able to produce scans of participants’ brains while the participants were not primed in an empathetic state.
Participants later answered a questionnaire that measured different aspects of empathy. Researchers used machine learning to predict people’s scores on the questionnaire based on the interaction between bottom-up and top-down systems in their brain scans, Christov-Moore said.
Many theories suggest empathy is based on either a bottom-up or a top-down system, he said.
In a theorized bottom-up system, empathy occurs when somebody sees another person in pain and feels that pain vicariously. A top-down system of empathy is more complex and involves looking through someone else’s perspective, Christov-Moore said.
“The picture that is starting to emerge is that empathy consists of both those processes,” Christov-Moore said. “It has automatic processes that lets you quickly feel what other people are feeling, and these sort of high-level processes that are more complex that help you understand.”
Researchers then trained the machine-learning model to predict questionnaire responses based on participant brain patterns, said Nicco Reggente, a co-author of the study who received his neuroscience doctoral degree at UCLA.
“From the complex patterns of interaction, we were able to predict people’s empathy from the connectivity between (the bottom-up and top-down) systems,” Christov-Moore said.
The approach was multivariate, meaning they analyzed the connection between multiple regions of the brain, Reggente said.
Empathy is a complicated process that relies on many parts of the brain working well together, which is why many patients with certain psychiatric or neurological disorders lack the ability to empathize, Christov-Moore said.
Unlike other tests, the patient doesn’t have to do anything to be diagnosed.
“What tests like this might allow us to do is to bypass all these questionnaires and measures that use self-reporting, and just look directly at the person’s brain when they’re sitting down in the scanner doing nothing,” Christov-Moore said.
The results of this study can also be used for finding medications to improve the connectivity between brain areas to further improve empathy, said senior author Marco Iacoboni, a professor of psychiatry and biobehavioral sciences at the David Geffen School of Medicine at UCLA.
“Empathy is such an important cornerstone for what’s called social cognition – your ability to navigate the social environment, to interact with people to establish relationships …” he said. “You can give medicine that is really effective in treating symptoms in some mental health patients, like hallucinations, but you still won’t be able to change their daily functioning if you don’t help them with social cognition and empathy.”
The study also could allow for further understanding of other behavioral measures beyond empathy, said Reggente, who is currently a project officer at The Tiny Blue Dot Foundation, an organization studying consciousness.
“What we’ve done here, this general concept and design, is something that should be done for not just empathy but many other behavioral measures,” Reggente said.
In the future, researchers may be able to produce behavior individuals want, Reggente said.
“If we want to become more empathic, we need to first understand the nature of empathy on the neural level,” he said.