The brain at rest includes levels of empathy

The brain at rest includes levels of empathy
Doctor examining MRI scan results of a patient on the computer monitor in the hospital.

Empathy allows us to connect on both an emotional and physical level with others. Now, work may have found the origin of that visceral feeling in the resting state of the brain.

New research shows the brain can help predict who is an empathetic person even in his resting state.
New research shows the brain can help predict who is an empathetic person even in his resting state.

Scientists have long been concerned about the cognitive underpinnings of empathy.

Scientists have always tried to dig deep into the brain, looking for the origins of this profound human feeling, from mirror neurons that help us “channel” the feelings of other people, to using brain scans to identify different kinds of empathy.

Now, they posed another interesting question: Is it possible for the brain to demonstrate how empathetic a person is, even in his or her resting condition?

According to the results of new research which appears in the journal Frontiers in Integrative Neuroscience, the answer seems to be yes.

The senior author of the new research is Marco Iacoboni, who is a professor of psychiatry and biobehavioral sciences at the David Geffen School of Medicine at the University of California Los Angeles (UCLA).

He describes the study’s inspiration, saying, “Assessing empathy is often the toughest in communities that need it the most.”

“Empathy is a pillar of mental health and wellbeing. Through our compassion for others it promotes social and cooperative behaviour. It also helps us infer and predict other people’s inner feelings, behaviors, and behavior.

Examining empathy in the brain

Prof. Iacoboni and colleagues asked 58 male and female participants aged 18 to 35 to take part in a functional MRI (fMRI) experiment in which the scientists measured and mapped brain activity by measuring subtle changes in the blood flow.

The researchers asked participants during the experiment to look at a white fixation cross on a black screen and “just let[ their] mind wander.”

Researchers captured functional images of the brain in its resting state. We have used BOLD imaging techniques primarily to analyze the brain.

The researchers asked the participants to fill in the Interpersonal Reactivity Index (IRI), a standard questionnaire that tests the “cognitive” and “emotional” dimensions of empathy, following the fMRI experiment.

The IRI consists of “24 statements that the participants rate from 0 (Does not describe me very well) to 5 (Describes me very well) on a five-point scale.”

Examples of IRI statements include: “I often have soft, caring feelings towards people less fortunate than me;” “Often, when they have issues, I don’t feel very sorry for other people;” “When I see someone being taken advantage of, I feel kind of defensive towards them;” “I often seek to better understand my friends by seeing how things look through their viewpoint.”

Findings may lead to new therapies

Using machine learning algorithms the researchers set out to investigate whether the empathetic proneness of a individual was predicted by subtle trends in fMRI results.

“We find that even if not directly engaged in a task involving empathy, brain activity within those networks can demonstrate the empathic nature of people,” reports Prof. Iacoboni.

“The benefit of the research is that the MRIs have helped us predict the results of the questionnaire of each participant,” he continues, adding that the study can support those with autism spectrum disorder and other conditions that some experts believe indicate little to no empathy.

“People with these conditions are thought to lack empathy,” Prof. Iacoboni explains.

“But if we can demonstrate that their brains have the capability for empathy, we can work to improve it through training and the use of other therapies.”

– Prof. Marco Iacoboni

“When applied to brain data, the predictive power of machine learning algorithms like this one can also help us predict how well a patient will react to a given therapy, helping us tailor optimal therapeutic strategies from the get-go,” the scientist adds.

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