Dynamic network dysfunction in cocaine dependence: Graph theoretical metrics and stop signal reaction time

Area of Science:

• Neuroscience
• Graph Theory
• Functional Connectivity Analysis

Background:

• Graph theoretical metrics are increasingly used to characterize neural network functional connectivity.
• Understanding how network connectivity is altered in neuropsychiatric disorders like cocaine addiction is crucial.

Purpose of the Study:

• To describe dynamic network connectivities in cocaine-dependent (CD) individuals compared to healthy controls (HC).
• To investigate temporal flexibility and spatiotemporal diversity of brain networks during a response inhibition task.

Main Methods:

• Functional magnetic resonance imaging (fMRI) was used on 78 CD and 85 HC participants during a stop-signal task (SST).
• Graph theoretical analysis was applied to assess temporal flexibility and spatiotemporal diversity across 14 whole-brain networks.
• Stop-signal reaction time (SSRT) was measured to assess response inhibition.

Main Results:

• CD participants showed prolonged SSRT compared to HC, indicating deficits in response inhibition.
• CD individuals exhibited decreased temporal flexibility and increased spatiotemporal diversity in most neural networks compared to HC.
• Default mode network graph metrics negatively correlated with SSRT in CD participants.

Conclusions:

• Cocaine addiction is associated with diminished temporal flexibility and compensatory increased spatiotemporal diversity in brain networks.
• These connectivity alterations are linked to impaired executive functions, specifically response inhibition.
• Graph theoretical metrics offer novel insights into neural network dysfunction in addiction that may be missed by conventional measures.