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S060-2

Neural Plasticity and Neural Network Abnormal in Patients with Depression

Tianmei Si

Peking University Institute of Mental Health, China

Background/Objective: Worldwide, depression is a seriously disabling public health problem of
very high prevalence. But to date, the diagnosis, treatment selection and efficacy evaluation of
depression has largely been based on self-reported symptoms of patients and subjective judgment of
clinicians, which is an important cause for the misdiagnosis and inappropriate treatment of
depression. The fMRI technology shows a great potential in the development of neuroscience-based
diagnosis and treatment strategy for depression. Here, we give a brief review on the fMRI studies
investigating the biomarkers of depression from Chinese patient’s population.

Method: The fMRI studies investigating the resting-state and task-based functional abnormalities in
neural circuitry subserving cognitive and emotional processes, diffusion tensor imaging (DTI)
studies investigating the white matter connectivity impairments, and structural MRI studies
investigating the abnormalities in gray matter volumes were included.

Result: The fMRI studies showed the functional and structural abnormalities in neural systems that
include those supporting emotion processing, reward seeking, and emotion regulation. The
connectomics studies showed disrupted topological organization of large-scale functional and
structural brain networks in depression, involving global topology, modular structure and network
hubs. These neural disruptions showed important correlates with genetic and environmental factors.
The antidepressant (mainly selective serotonin reuptake inhibitors [SSRIs]) could selectively
modulate the activity or connectivity associated with the medial prefrontal-limbic loop. The
resting-state activity in the angular gyrus and default mode network showed a high sensitivity and
specificity for the diagnosis or antidepressant efficacy prediction of depression.

Conclusion: Overall, the studies have identified a number of putative biomarkers for diagnosing and
treating depression. These fMRI-based imaging studies present new opportunities to reconceptualize
the classification system, and also, identify the biological targets for personalized medication of
depression.

Reference: Jafri MJ, Pearlson GD, Stevens M, Calhoun VD (2008): A method for functional
network connectivity among spatially independent resting-state components in schizophrenia.
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