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Updated: Oct 20, 2026

Investigating Drivers of Antireward in Addiction Behavior with Anatomically Specific Single-Cell Gene Expression Methods
Published on: August 4, 2022
Neural dysfunction underlying divergent thinking and its shared mechanisms with protracted withdrawal symptoms in
Yifan Wang1,2, Wenjuan Fu1,2, Wanyi Li1,2
1Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi'an, Shaanxi, China.
Background:
Drug use may induce transient bursts of inspiration but is also associated with increasing cognitive rigidity. How neurological damage induced by drug addiction affects higher-order thinking processes in humans remains elusive. This gap limits our understanding of broader cognitive impairment in addiction and prolonged maladaptation during withdrawal.
Methods:
The study investigated divergent thinking, a key component of flexible behavior, in heroin use disorder (HUD). Behavioral performance was assessed using the Realistic Presented Problem-Solving Task. Task-related neural signatures were recorded via functional near-infrared spectroscopy (fNIRS) in three groups of individuals: (1) HUD short withdrawal; (2) HUD long withdrawal; and (3) healthy controls (HC).
Results:
Both HUD groups exhibited poorer divergent thinking performance than the HC group. HUD participants showed hyperactivation in the prefrontal cortex (PFC) and temporoparietal junction (TPJ), accompanied by reduced functional connectivity within the PFC and between the PFC and TPJ. Network analysis further revealed reduced topological properties of PFC nodes and increased topological properties of TPJ nodes, indicating disrupted PFC-mediated top-down regulatory control. PFC subregional activation and functional connectivity with the bilateral TPJ served as shared neural features that predicted divergent thinking impairment and protracted withdrawal symptoms.
Conclusions:
These findings reveal a sustained compensatory pathological mechanism and an imbalance in neural resource allocation during complex cognition in HUD individuals. The identified signatures of cortical activity by fNIRS offer reliable biomarkers for the rapid detection of both higher-order cognitive deficits and withdrawal symptoms, and further offer precise cortical targets for their integrated intervention.
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