According to a new study, a simple brain scan could identify children at risk of suffering from depression later in life. If implemented, the early warning test could allow doctors to carry out treatment prior to the first instance of depression, making it less likely that the patient will suffer further bouts.
The study was conducted by an international team of researchers, and focused on a sample group of 27 children between the ages of 8 – 14 who were believed to be at a higher risk of suffering from depression owing to a family history with the disease. Brain scans carried out on this group were then compared to those of 16 children who had no family history of depression, in an attempt to isolate potential abnormalities.
Prior research in the field had isolated unusual brain activity in patients who suffered from the disease. The work highlighted increased activity between the subgenual anterior cingulate cortex (sgACC) and the amygdala. However, in this instance the researchers were unable to determine whether these abnormalities were the cause or the result of an instance of depression.
The new study made use of a process known as functional magnetic resonance imaging(fMRI) to monitor a patient's blood flow to certain regions of the brain. This allowed the researchers to measure localized brain activity, and in so doing isolate synchronization patterns highlighting which regions of the brain were communicating with each other while the patient was at rest.
For children believed to be at a heightened risk of depression, the scientists observed a number of distinct synchronization patterns. One of the key findings highlighted a strong connection between the sgACC and the default mode network.
The new study made use of a process known as functional magnetic resonance imaging(fMRI) to monitor a patient's blood flow to certain regions of the brain. This allowed the researchers to measure localized brain activity, and in so doing isolate synchronization patterns highlighting which regions of the brain were communicating with each other while the patient was at rest.
For children believed to be at a heightened risk of depression, the scientists observed a number of distinct synchronization patterns. One of the key findings highlighted a strong connection between the sgACC and the default mode network.
The unusual brain activity exhibited by the high-risk children bore many similarities to that of adults suffering from the disease, leading the researchers to conclude that the abnormalities are not the result of the disease, but may instead be contributing to its onset.
The next step for the team will be to continue monitoring the brain activity of the children in order to determine whether early treatment can prevent future episodes of depression.
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