Altered static and dynamic functional network connectivity in individuals with subthreshold depression: a large-scale...

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Psychiatry

Background:

• Subthreshold depression (StD) represents a significant risk factor for major depressive disorder.
• Understanding the neural underpinnings of StD is crucial for early intervention.
• Dynamic functional network connectivity (dFNC) offers a more nuanced view of brain activity than static measures.

Purpose of the Study:

• To investigate alterations in static functional network connectivity (sFNC) and dFNC in individuals with StD compared to healthy controls (HCs).
• To examine the temporal properties and strength of brain network interactions in StD.
• To correlate functional connectivity changes with depression severity scores.

Main Methods:

• Utilized Group Independent Component Analysis (GICA) to identify key resting-state networks: executive control network (ECN), default mode network (DMN), sensorimotor network (SMN), and dorsal attentional network (DAN).
• Applied sliding window and k-means clustering analyses to characterize dFNC states and temporal dynamics.
• Compared sFNC and dFNC metrics between 42 StD individuals and 38 HCs, and used Spearman's correlation to assess relationships with the HAMD-17 score.

Main Results:

• StD individuals showed decreased sFNC strength in several network pairs (DMN-ECN, DMN-SMN, SMN-ECN, SMN-DAN).
• dFNC analysis revealed that StD subjects spent more time in a weakly connected state (state 4), associated with self-focused thought.
• The StD group exhibited reduced dFNC strength between DMN and DAN in state 2, and altered temporal properties correlated with HAMD-17 scores.

Conclusions:

• Subthreshold depression is characterized by disruptions in both static and dynamic functional brain network connectivity.
• Aberrant temporal dynamics, particularly prolonged periods of weak connectivity, are a key feature of StD.
• These findings provide insights into the neuropathological mechanisms underlying StD and highlight potential targets for intervention.