BU/VA Study Identifies Neural Mechanisms that Underlie Suicidal Thoughts, Behaviors
Implicit Association Tests (IATs) are computerized tests that can be used to assess the subconscious association between different concepts. A form of the IAT, the Suicide Implicit Association Test (S-IAT), can measure people’s associations between the “self” and concepts relating to death/dying/suicide. While S-IAT is one of the few tests that uniquely predicts future suicide risk, there has been limited research investigating brain activation related to the S-IAT.
For the first time in a Veteran population, researchers have identified several brain regions that were sensitive to self-death associations. These brain regions are a part of brain networks that are involved in identifying important stimuli in our environment and processing information as it relates to our “self”. The results from this study mark an important step towards characterizing neural mechanisms that contribute to suicidality.
Audreyana Jagger-Rickels, PhD“Currently, there is no consensus on what neural mechanisms contribute to suicide risk, so observing brain activation related to the S-IAT could lead to a breakthrough in our understanding the underlying neural mechanisms of suicide risk,” explains corresponding author Audreyana Jagger-Rickels, PhD, assistant professor of psychiatry.
Forty-two post-9/11 Veterans at low risk for suicide completed S-IAT concurrently with functional magnetic resonance imaging (fMRI) – a neuroimaging technique that measures brain activity by detecting changes in blood flow. The S-IAT included a total of 20 target words; five words from each of these four word categories: Death, Life, Me, Not Me.
For each trial, one of the 20 target words was presented in the center of the screen. Simultaneously, on the top left and top right of the screen were two choices for categorizing the target word. The participant categorized the target word in the center of the screen into one of the two categories at the top of the screen. In certain trials, participants categorized “death” and “me” words to the same side of the screen. These trials measured implicit self-death associations. To identify brain activation related to self-death associations, the researchers then contrasted a participant making a self-death association compared to the brain activation when someone was not making a self-death association.
“The brain circuit that we identified could be a novel treatment target for suicidality. For instance, changing the activity of this brain circuit with techniques like neuro-feedback, brain stimulation, or pharmacotherapies could reduce suicide risk by targeting the brain circuit that underlies this suicide-specific cognition (self-death implicit association),” adds Jagger-Rickels who also is principal investigator in the National Center for PTSD at the VA Boston Healthcare System.
According to the researchers, one of the challenges in identifying brain circuits related to suicide is that we are often indirectly relating some brain pattern to a patient’s history or reported symptoms related to suicide. While this type of analysis is informative, it does not tell us how the brain activates to initiate or sustain suicidal thoughts and behaviors. As a result, identifying brain circuits related to suicide risk has been limited as we can identify brain regions associated with suicide risk but not how they are contributing to suicide risk. “Using measures like the S-IAT, which measures a suicide-specific cognition, will not only help us identify brain mechanisms that underlie suicidality but also how they contribute to suicidality. In turn, this may also aid in the development of novel treatments targeting the brain mechanisms underlying suicidal thoughts and behaviors.”
These findings appear online in journal Suicide and Life-Threatening Behavior.