Using modern methods, researchers have been able to identify key changes in the brain that may indicate the risk of developing a depressive disorder in childhood.
This was reported by News Medical.
A recent study sheds light on depression by analyzing the structural and functional changes in the brain associated with the disease. Researchers have discovered specific changes that may contribute to depression, which will help treat people with depression.
Until recently, neuroimaging studies provided only limited data on the causes of mood swings. However, in recent years new areas of science have been actively developing, such as precision functional mapping, which aims to study subtle changes in brain networks using high-precision data.
In a new study published in the journal Nature, researchers examined how depression changes the structure of functional brain networks and how these changes affect mood over time. The study included six patients with severe depression and 37 healthy volunteers. The patients with depression underwent a series of multi-echo fMRI sessions, while the healthy participants underwent fewer sessions. Data from Stanford University and Weill Cornell Medical Center were used, along with large MRI data sets from 812 controls and 299 people with treatment-resistant depression.
Machine learning methods have identified significant differences in the size of functional brain networks between patients with depression and healthy individuals. In particular, depressed patients show an increase in the size of the frontostriatal attention network, which is associated with reward processing (a set of nervous system structures involved in regulating and controlling behavior through positive reactions to actions) and the integration of autonomic signals. This network interacts with other brain networks, which may promote greater synaptic plasticity.
Interestingly, the size of this network remains unchanged even after antidepressant treatment, suggesting its role as a stable marker of depression. The results also show that an increase in the frontostriatal network is observed in children before the onset of depressive symptoms in adolescence, which may indicate its potential importance in predicting the risk of developing depression.
Furthermore, the study identified mood-dependent changes in striatal connections to the attention network that are associated with fluctuations in anxiety and anhedonia, which may help predict the future development of these symptoms.
These results open new horizons for understanding the neural mechanisms of depression and may contribute to the development of more precise methods for diagnosing and treating this disorder.
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