A joint study from Yale and the Icahn School of Medicine at Mount Sinai utilized computer learning algorithms to better understand how post-traumatic stress disorder affects the brain.
Using an MRI, researchers measured how combat veterans reacted to electrical shocks and displays of angry faces. They found that not only do soldiers with severe PTSD symptoms overreact when they experience things they do not expect, but they also have a harder time “unlearning” these exaggerated behaviors compared to soldiers who do not have PTSD. By using computer analysis, the findings provide tangible data that could be used to treat mental disorders such as depression, anxiety or even PTSD itself. The study was published in Nature Neuroscience on Jan. 21.
“We know generally that people after combat exposure have various degrees of PTSD symptoms and are different in how they respond to stimuli in their environment when they are associated with something negative,” said co-author and Icahn School of Medicine associate professor of neuroscience and psychiatry Daniela Schiller. “Here, it gave us very, very specific computation on what exactly is different, or what is the most predictive aspect of it.”
To acquire the data, researchers first presented two different angry faces to 54 combat veterans in an MRI machine. When one face was shown, the veteran would get a shock to his or her right ankle. Then, to see how their brains reacted to surprise, researchers shocked them when they saw the other angry face.
According to Schiller, since overreaction to negative surprises — in this case, an uncomfortable shock — is a key component of severe PTSD, understanding how the brain works when exposed to unpleasant surprises can help predict who is more prone to developing PTSD.
“By further looking at this data and trying to see if they relate to a set of symptoms, we might be able to better understand these processes and relate this to other disorders,” she said.
In addition to these findings, researchers also found a relationship between the size of the amygdala — the part of the brain associated with experiencing emotions — and the severity of PTSD symptoms. According to the study, soldiers with smaller amygdala volume were more likely to have higher PTSD severity than those who did not.
Schiller said that the study was inspired by a desire to look at conventional ideas about PTSD using a different approach.
“PTSD is really a disorder of memory. It’s about something you remember and how that memory’s affecting you,” she said. “We were just targeting it from a different direction, which was how well do they learn in this situation. Still, there’s something fundamentally different in how they track and compute and how their brain is responding.”
According to co-author and Yale psychiatry professor Ilan Harpaz-Rotem, the scientific breakthroughs in this study have large implications for treating the disorder. He said that by using the data, his team of researchers can begin to understand what is hindering soldiers’ ability to control their fear responses. Since treatment of PTSD is mostly symptomatic, meaning that it controls the symptoms instead of the underlying cause, further research can contribute to curing the disorder.
“If we can really pinpoint those things that contribute to this deficit in learning, then we can improve treatment outcomes,” he said.
However, according to Schiller, more research is necessary to see if the same neurocomputational properties found in the study among combat veterans with PTSD are prevalent among victims of traumatic natural disasters or domestic abuse situations. Since angry faces are common threats among veterans deployed to war zones but may be completely absent in traumatic experiences caused by car crashes or tsunamis, for example, the same research procedure may not be applicable.
“The field of PTSD is one diagnosis but it could be potentially broken down to multiple, depending on the type of trauma,” she said.
PTSD was officially recognized as a diagnosable health condition in the 1980 version of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders.
Matt Kristoffersen | matthew.kristoffersen@yale.edu