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What We Learn About Empathy through Brains


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Empathy is a quality which allows a person to relate to and feel someone else's emotions as if they were their own.  It differs from sympathy, which is the ability to relate and understand someone else's emotions, while not taking on their feelings in such a personalized way.  Empathy is needed to understand the complex human social structure and is a quality that can be underdeveloped in people with mental illness.  This is a clear indication of how the brain's chemistry and unique internal environment can shape personality, but how do you measure empathy by examining the brain?  A new study has discovered it is possible to explore the depth of a person's empathy by studying brain scans, but it's with a twist: the brains have to be resting.

In the past, empathy could only be measured by a psychological assessment or questionnaires, but it can be  difficult to elicit accurate information from those people that have autism or mental illnesses.  The recent study led by UCLA School of Medicine focused on 58 participants, male and female, aged 18 to 35 years old.  The participants' brains were studied during functional MRI (fMRI) scans because fMRI maps activity and small changes in the brains' blood flow.  The study asked the participants to focus their eyes on a cross on a black screen but could let their minds think of whatever came up.

The second part of the study involved questionnaires that could index and measure empathy on a scale that ranged from responses like “not well” to “very well.”  The researchers of the study were attempting to determine if they could have anticipated how empathetic the participants were based on what they could derive from the brain scans.  The scientists made their hypotheses based on what the scans revealed in the areas of the brain networks which they know are involved in empathy based on earlier studies.

The scientists chose to use AI (artificial intelligence) to seek out the subtle differences in the brain scan that their traditional data analysis techniques could leave behind.  The AI used was machine learning.  This combination of techniques were able to accurately predict how empathetic the participants were, so the scientific community is very excited about being able to apply these techniques to people who may not be able to fill out questionnaires, are non-verbal, or have difficulties expressing and identifying emotion.

It's important for people with these conditions to be thought of as possible of expressing empathy because the symptoms of their conditions can mask these emotional abilities.  Without that knowledge, the divide between people who have a condition and those who do not will grow wider.  With more research, the stigma of mental and emotional illness will hopefully grow into scientific facts and acceptance.


Leonardo Christov-Moore, Nicco Reggente, Pamela K. Douglas, Jamie D. Feusner, Marco Iacoboni. Predicting Empathy From Resting State Brain Connectivity: A Multivariate Approach. Frontiers in Integrative Neuroscience, 2020; 14 DOI: 10.3389/fnint.2020.00003


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