Brain activity can reveal empathy

Empathy is the ability to understand and share the feelings of other people. Is it possible to detect a person's empathy through brain activity?

Image Credit: Alexxndr / Shutterstock
Image Credit: Alexxndr / Shutterstock

A team of researchers has found that it's possible to assess a person's ability to feel empathy when the brain is at rest, rather than while it's busy in performing specific tasks.

In the past, empathy can be assessed just by letting the person answer a questionnaire or through psychological evaluations. In the study, published in the journal Frontiers in Integrative Neuroscience, the team wanted a new method to assess empathy, especially for people who can't answer questionnaires, like those who have mental health disorders or autism.

"Assessing empathy is often the hardest in the populations that need it most. Empathy is a cornerstone of mental health and well-being. It promotes social and cooperative behavior through our concern for others. It also helps us to infer and predict the internal feelings, behavior, and intentions of others," Dr. Marco Iacoboni, professor of psychiatry and biobehavioral sciences at the David Geffen School of Medicine at UCLA, said.

Resting brain activity

The team recruited 58 diverse adults, between the ages of 18 and 35, 30 of whom are females, and 28 are males.

They studied the brain's activity to determine when is the best time to assess empathy. The researchers collected resting brain activity through functional magnetic resonance imaging (fMRI), which is a new technique to gauge and map brain activity by looking at blood flow changes. The team advised the participants to look at a black screen or a fixation to keep their eyes still while letting their minds wander.

Using machine learning, the team demonstrated that patterns of resting-state fMRI connectivity of resonance and control networks predict trait empathic concern, which was also predicted by connectivity patterns in the somatomotor network.

The team answered questionnaires devised to measure empathy and rated the questions on a five-point scale, from the lowest of "not well" to "very well." From there, the researchers measured for the participants' empathic disposition, which involves the willingness to understand the situation of others, through the analysis of their brain scans.

Study findings

After the series of tests, the team made the predictions by looking into the resting activity in certain brain networks, which were linked to empathy. They used machine learning to detect patterns in data that more conventional analyses might not pick up.

"We found that even when not engaged directly in a task that involves empathy, brain activity within these networks can reveal people's empathic disposition. The beauty of the study is that the MRIs helped us predict the results of each participant's questionnaire," Iacoboni explained.

The new findings of the study can help in the assessment of empathy for those who can't verbalize their feelings, such as people with autism or schizophrenia. They may have a hard time answering questionnaires, and some of them may have difficulty expressing their emotions.

Past studies have shown that people with schizophrenia and autism lack empath, but if scientists can study their brains and how they react to certain situations, health care professionals can work to improve diagnostics and tests and develop new therapies.

Machine learning has helped many scientists because of its predictive power, which can be applied to brain data. It can help scientists predict how the patient will respond to a situation and intervention, providing a means to provide individualized or tailored care for the patients.

Journal reference:

Christov-Moore Leonardo, Reggente Nicco, Douglas Pamela K., Feusner Jamie D., Iacoboni Marco, Predicting Empathy From Resting State Brain Connectivity: A Multivariate Approach, Frontiers in Integrative Neuroscience, DOI:10.3389/fnint.2020.00003

Angela Betsaida B. Laguipo

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Angela Betsaida B. Laguipo

Angela is a nurse by profession and a writer by heart. She graduated with honors (Cum Laude) for her Bachelor of Nursing degree at the University of Baguio, Philippines. She is currently completing her Master's Degree where she specialized in Maternal and Child Nursing and worked as a clinical instructor and educator in the School of Nursing at the University of Baguio.

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