As a storm of colds, flus, and fevers lays waste to Yale’s student body, there seem to be few who are spared – an elite class of superhuman, immune to the maladies of college life. I did not have the privilege to be one of these herculean souls. Before I knew it, I was sitting in Yale health, twiddling my thumbs, waiting for the nurse.
When she walked in, she checked my vitals, asked me what was wrong — normal nursing questions. But then she asked me, “On a scale of one to ten, how would you rate your pain?”
I sat there dumbfounded, unsure how to answer. How could I quantify my level of pain? What was a level three pain versus a level four versus a level seven? I could go on at length about the annoying sting in the back of my throat, the uncomfortable feeling when I swallowed, and the throbbing of my head, but I did not see how I could translate these feelings to a number.
When it comes to conveying how we feel, there are countless factors that influence how we communicate these emotions: our personality, our sensitivity, our level of comfort talking about our thoughts, our environment, and our level of arousal, to name a few. One person’s “great” might be another person’s “fine,” which might be another person’s “terrible.” One person’s level three pain might be another person’s level six. There is no common denominator of human emotion. This subjectivity makes it enormously difficult to extract how someone truly feels based solely on what he or she decides to reveal.
But fret no longer. A research team from Duke has been able to map emotions in the human brain using functional magnetic resonance imaging, or fMRI. The study’s findings, published in PLOS Biology in a paper entitled “Decoding Spontaneous Emotional States in the Human Brain,” are the result of a complicated algorithm that distinguishes seven universal human emotions – contentment, amusement, surprise, fear, anger, sadness, and neutrality. Twenty-one students were asked for their emotional status every thirty seconds. Due to the specificity in brain pattern of each of each of the seven emotions, the researchers were able to predict what the subjects were feeling ten seconds before the subjects reported their emotional statuses.
The group from Duke, seeing the potential in their algorithm, enlarged their study to 499 subjects. Using a similar method, the researchers looked specifically at the “sadness” and “fear” brain maps of the participants to assess the participants’ degree of depression and anxiety. Summarizing the paper’s findings, Philip A. Kragel states, “…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.”
Although researchers have been exploring pattern classification of the human brain for some time, this paper shows that existing fMRI technology can predict emotions without artificially stimulating the brain. Participants in the study were asked to merely sit in the fMRI scanner and let their minds wander. The fMRI is sensitive enough, and the algorithm is powerful enough, that the researchers could collect viable data from these resting and wandering brains.
The beauty of the algorithm lies in its objectivity. Clinicians need not rely on subjective self-reporting of emotions anymore. For patients with depression, anxiety, and alexithymia (a condition characterized by a lack of understanding and expression of emotion), these study’s findings are particularly useful. If someone thinks it, the machine will pick it up, regardless of whether the patient decides to reveal that emotion.
Essentially, this machine can not only read your mind, but it can also predict your verbal response before you even realize what you are thinking. The implications of this research are profound. Criminal investigators could use it as a redesigned lie-detector test. Teachers could use it to find a method of teaching that is most stimulating for their students. Next time I go to Yale Health, maybe I could even use it to establish whether this annoying tingle in my throat is a level three on the pain scale or a level four.
Will Burns is a freshman in Morse College. Contact him at firstname.lastname@example.org.
(Featured Image courtesy of the author).