By applying an algorithm to functional magnetic resonance imaging, scientists have been able to see emotions at work in the human brain.
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The findings – recently published in the journalPLOS Biology – could enable better assessment of emotional states, which may help individuals who struggle to convey their feelings.
According to the research team – including Prof. Kevin LaBar of Duke University in Durham, NC – it is well established that movies, music, and other external stimuli can trigger emotions that are reflected in patterns of brain activity.
But what about past emotional experiences? Can the feelings induced by the memory of a birthday party or the recollection of the loss of a loved one be represented in brain activity?
This is what Prof. LaBar and colleagues set out to investigate in their new study.
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The researchers note that previous studies have shown that functional magnetic resonance imaging (fMRI) can differentiate between thoughts of specific objects, such as a face or a house.
In this study, the researchers applied an algorithm – incorporating various models of emotional experience – to the fMRI scans of 21 university students.
This allowed them to pinpoint seven brain activity patterns – or “maps” – that reflect certain emotional states, including contentment, amusement, surprise, fear, anger, sadness, and neutrality.
The students were asked to let their mind wander during fMRI; every 2 seconds, brain activity data were gathered, and every 30 seconds, subjects were asked about their current emotional state.
“We tested whether these seven brain maps of emotions occurred spontaneously while participants were resting in the fMRI scanner without any emotional stimuli being presented,” explains Prof. LaBar.
On comparing brain patterns that occurred 10 seconds prior to each subjects’ self-reported emotional state, the researchers found that they were able to accurately predict their feelings.
Bolstering the accuracy of their findings, Prof. LaBar notes that the brain data collected immediately after participants entered the fMRI scanner showed signs of anxiety. “That’s what you’d expect to see for most people when they first enter the machine,” he adds.
Brain maps predicted anxiety, depression
The team then applied their algorithm to the fMRI scans of a further 499 subjects who were part of the Duke Neurogenetics Study.
These participants were required to rest in the fMRI scanner for almost 9 minutes, and following their scans, the researchers gathered information on how depressed or anxious the subjects felt, as determined by scores on psychological questionnaires.
Using their “sadness” and “fear” brain maps, the researchers found they were able to predict the subjects’ depression and anxiety scores.
Additionally, the researchers found their algorithm was also able to pinpoint personality traits of anger, anxiety, and depression.
According to the team, this study provides proof of concept that emotional states can be identified from brain scans – a finding that could have significant clinical implications.
Commenting on the results, the authors say:
“Here we show that brain-based models of specific emotions can detect individual differences in mood and emotional traits and are consistent with self-reports of emotional experience during intermittent periods of wakeful rest.
[…] More practically, the results suggest that brain-based models of emotion may help assess emotional status in clinical settings, particularly in individuals incapable of providing self-report of their own emotional experience.”
In particular, Prof. LaBar believes their brain maps of emotion could benefit people with alexithymia – a psychological condition characterized by poor understanding, recognition, and expression of one’s own emotions, as well as the emotions of others.
The maps might also be useful in clinical trials, adds Prof. LaBar, as they could help test the efficacy of anti-anxiety medications and other therapies that regulate emotions.
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