Drug Cues Induce Abnormal Changes in Brain Activation: An ALE Meta-Analysis
摘要
Based on a voxel-based activation likelihood estimation (ALE) meta-analysis, this study aims to systematically compare differences in brain region activation between individuals with drug use disorders (DUDs) and healthy controls (HCs) under a visual drug cue task. The aim is to reveal the changes in the core neural circuits of drug addiction, providing a practical reference for targeted treatment to restore brain function in DUDs and reduce their drug cravings.
Recent FindingsThe analysis included 18 studies, comprising 429 individuals with DUDs and 395 HCs. Relative to controls, the experimental group exhibited hyperactivation in the basal ganglia (caudate nucleus, putamen) and limbic system (amygdala, hypothalamus), reflecting overdrive of reward and motivation circuits. This provides a neural basis for the intense cravings and automatic drug-seeking behavior elicited by drug-related cues. Conversely, hypoactivation in the prefrontal cortex (particularly Brodmann area 9), alongside heightened activation in the anterior cingulate cortex, indicating increased conflict monitoring, suggests impaired cognitive control circuitry in individuals with DUDs. This impairment underlies diminished impulse inhibition and compromised rational decision-making. Additionally, activation in brain regions associated with episodic memory and self-referential processing, such as the parahippocampal gyrus and precuneus, indicates that memory and self-related systems have been co-opted. As a result, drug cues abnormally and efficiently evoke drug-related memories and self-associations, thereby increasing relapse risk.
SummaryDUDs exhibit systemic functional abnormalities in the basal ganglia–limbic system–prefrontal cortex circuit during drug cue processing, characterized by overactivation of reward- and emotion-related brain regions and reduced prefrontal cortical control. This provides neural evidence for the loss of control and cue salience mechanisms underlying addiction, supporting the three-stage addiction model. These regions may therefore serve as potential biomarkers for assessing addiction severity and predicting relapse.