物质成瘾患者和行为成瘾患者在纹状体和前额叶激活的异同：基于双系统模型的元分析

doi:10.3724/SP.J.1041.2025.1333

摘要/Abstract

摘要：

尽管物质成瘾患者和行为成瘾患者在反思系统和冲动系统存在异常激活模式, 但尚不清楚两者异常激活模式是否存在相似和差异。针对这一问题, 本研究采用激活似然估计(activation likelihood estimation, ALE), 对物质成瘾患者和行为成瘾患者在抑制控制和奖赏相关任务下的神经激活数据进行定量分析。经过文献检索和筛选后, 本研究共纳入102项功能核磁共振技术(fMRI)研究。元分析结果发现：(1)在抑制控制任务中, 物质成瘾患者的背外侧前额叶皮层激活降低, 行为成瘾患者相应脑区激活增强。(2)在奖赏加工相关任务中, 两组患者的纹状体激活均增强。这些结果表明, 在冲动系统上, 物质成瘾患者和行为成瘾患者存在共同激活特征; 而在反思系统上, 物质成瘾患者功能受损, 行为成瘾患者则可能出现补偿性激活。总之, 本研究揭示了物质成瘾患者和行为成瘾患者在冲动系统和反思系统存在共同的异常激活特征; 同时, 两者也表现出各自独特的神经激活模式。

关键词: 元分析, 物质成瘾, 行为成瘾, 奖赏加工, 抑制控制

Abstract:

Based on the dual-system theory of addiction, substance addiction and behavioral addiction result from the interaction between the reflective system, represented by the prefrontal cortex, and the impulsive system, represented by the striatum. While most existing studies separately examined the functional changes in these systems for substance addiction and behavioral addiction, our understanding of their neural mechanisms across different cognitive tasks remains incomplete. Furthermore, the similarities and differences in the neural substrates underlying these two types of addiction have not been fully elucidated. To address these gaps, the present study employed a systematic meta-analytic approach to investigate the neural activation patterns in substance addiction and behavioral addiction during inhibitory control and reward processing tasks. Specifically, the study first conducted a meta-analysis to map the neural correlates of substance addiction and behavioral addiction in these tasks, followed by a contrast analysis to evaluate their similarities and differences in neural activation.

The present study used Activation Likelihood Estimation (ALE) to conduct a meta-analysis of neuroimaging data. It included 23 articles on inhibitory control tasks and 30 articles on reward processing tasks for substance addiction. For behavioral addiction, it included 12 articles on inhibitory control tasks and 37 articles on reward processing tasks. The meta-analysis was conducted in standard Montreal Neurological Institute (MNI) space, using GingerALE (3.0.2) to convert Talairach coordinates obtained in the studies to MNI space coordinates. For the inhibitory control tasks, a threshold of p < 0.001 (uncorrected) was used, with a minimum cluster size of 250mm³. For the reward tasks, the ‘true’ ALE scores were then tested against the ALE scores of the null distribution by adopting a cluster-level family wise error (cFWE)−corrected threshold of p < 0.05, while the cluster-forming voxel-wise threshold was set at p < 0.001 uncorrected. Finally, contrast analysis was conducted for substance addiction and behavioral addiction under the two different task conditions. The threshold for contrast analysis was set at p < 0.01 (uncorrected), with a minimum cluster size greater than 50mm³ (10, 000 permutations).

The findings revealed two principal patterns in neural activation: (1) In inhibitory control tasks, there was no overlap in commonly activated brain regions between substance addiction and behavioral addiction. Notably, the dorsolateral prefrontal cortex exhibited decreased activation in substance addiction, while showing increased activation in behavioral addiction. (2) In reward processing tasks, the striatum demonstrated consistently increased activation across both substance addiction and behavioral addiction.

In conclusion, the current meta-analysis provides novel insights into the neural mechanisms of substance addiction and behavioral addiction during inhibitory control and reward processing tasks. Both types of addiction are characterized by abnormal activation in the striatum, suggesting a shared impulsive system dysfunction. However, during inhibitory control, substance addiction was associated with reduced activation in the fronto-parietal control network, whereas behavioral addiction exhibited enhanced activation in this network. Additionally, behavioral addiction demonstrated both inhibitory control abnormalities and preserved inhibitory control capacity compared to substance addiction. The study reveals that both substance addiction and behavioral addiction have general abnormalities in the reflective and impulsive systems, but each type of addiction has its own unique neural activation patterns.

Key words: meta-analysis, substance addiction, behavioral addiction, reward processing, inhibitory control

中图分类号:

B845

何全兴, 李兆岚, 杨海波. (2025). 物质成瘾患者和行为成瘾患者在纹状体和前额叶激活的异同：基于双系统模型的元分析. 心理学报, 57(8), 1333-1348.

HE Quanxing, LI Zhaolan, YANG Haibo. (2025). Dual-system perspectives: A meta-analytic comparison of striatal and prefrontal cortex activation patterns in substance addiction versus behavioral addiction. Acta Psychologica Sinica, 57(8), 1333-1348.

图/表 8

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作者	成瘾组		成瘾组平均年龄(M ± SD)	对照组		对照组平均年龄(M ± SD)	成瘾物类型	任务
作者	男	女	成瘾组平均年龄(M ± SD)	男	女	对照组平均年龄(M ± SD)	成瘾物类型	任务
抑制控制
Ahmadi et al., (2013)	12	23	18.97 ± 0.45	31	25	18.80 ± 0.97	酒精	Go/no-go
Ceceli, King, et al., (2023)	31	9	40.90 ± 9.20	15	9	41.70 ± 11.30	海洛因	Stop signal task
Ceceli, Parvaz, et al., (2023)	24	4	44.07 ± 8.18	21	5	42.66 ± 7.05	可卡因	Stop signal task
Cyr et al., (2019)	17	11	19.30 ± 2	17	15	18.90 ± 2.70	大麻	Simon task
Czapla et al., (2017)	17	2	51.21 ± 7.36	17	4	41.95 ± 9.99	酒精	Go/no-go
Fu et al., (2008)	28		33.39 ± 5.98	15		29.59 ± 6.94	海洛因	Go/no-go
Gerhardt et al., (2021)	13	2	47 ± 12.30	9	6	41.90 ± 14.40	酒精	Simon-task & Go-/no-no & Stop-signal tsk
Hester et al., (2013)	13	2	38.20	13	2	42.70	可卡因	Go/no-go
Jan et al., (2014)	7	0	38.30 ± 5.60	7	3	32.30 ± 8.70	冰毒	Stroop
Kalhan et al., (2022)	10	10	24.30 ± 4.70	10	10	23.70 ± 4.30	尼古丁	Stop-Signal Task
Kober et al., (2014)	20		26.65 ± 9.81	20		29.20 ± 10.06	大麻	Stroop color-word interference task
Li et al., (2008)	15		37.70 ± 6.80	15		36.60 ± 6	可卡因	Stop signal task
Li et al., (2009)	18	6	38.70 ± 8.30	18	6	35.50 ± 5.90	酒精	Stop signal task
Ma et al., (2015)	12	1	37.40 ± 5.30	7	3	35.20 ± 7.30	可卡因	Easy no-go
Moeller et al., (2012)	28	5	44.20 ± 6.30	17	3	39.80 ± 5	可卡因	Stroop
Moeller et al., (2014)	28	5		18	2	39.60 ± 5.50	可卡因	Stroop
Morein-Zamir et al., (2013)	30	2	34.53 ± 7.81	26	15	31.68 ± 8.49	兴奋剂依赖	Stop-Signal Task
Müller-Oehring et al., (2019)	10	8	49.60 ± 11	17	4	50.30 ± 9.50	酒精	Addiction-Stroop color match-to- sample task
Nestor et al., (2011)	5	5	33.50 ± 9.30	11	7	36.40 ± 10.40	冰毒	Color-world Stroop
Schulte et al., (2012)	18		51 ± 6.60	17		50 ± 14.90	酒精	Stroop match-to-sample task
Stein et al., (2021)	10	3	45.62 ± 10.01	9	5	37.71 ±12.82	酒精	Go/no-go
Zerekidze et al., (2023)	14	4	32.40 ± 7.40	14	7	27.60 ± 3.50	冰毒	Stroop
富丽萍等人(2008)	30		33 ± 6	18		29 ± 7	海洛因	Go/no-go
奖赏加工
Blaine et al., (2020)	28	16	33 ± 11	23	20	32 ± 10	酒精	Cue-reactivity task
Conti et al., (2024)	14	9		11	8		尼古丁	Decision-making task
Dakhili et al., (2022)	53		32.12 ± 5.89	23		31.17 ± 5.69	冰毒	Cue-reactivity task
Dennis et al., (2020)	29	10	-	28	18	35 ± 11.80	酒精	Probabilistic delay discounting task
Filbey et al., (2013)	46	13	23.49 ± 6.37	5	22	30.32 ± 10.09	大麻	Monetary incentive delay task
Forbes et al., (2014)	15	9	27.20 ± 4.90	14	10	27.20 ± 3.70	酒精	Monetary reward task
Gilman & Hommer et al., (2008)	12		41.83 ± 8.39	12		38.08 ± 6.97	酒精	Visual stimulation task
Gilman et al., (2015)	12	6	30.50 ± 5.06	12	6	30.67 ± 7.10	酒精	Risk-taking task
Goudriaan et al., (2010)	10		-	17		34.70 ± 9.70	尼古丁	Cue-reactivity task
Grodin et al., (2016)	11	6	32.25 ± 6.94	9	8	27.72 ± 4.25	酒精	Monetary incentive delay task
Heinz et al., (2007)	6	6	39 ± 7	6	6	40 ± 8	酒精	Cue-reactivity task
Hong et al., (2017)	15		39.90 ± 4.90	15		39.20 ± 5.20	尼古丁	Cue-reactivity task
Huang et al., (2018)	28		31.68 ± 7.06	27		33.93 ± 7.21	冰毒	Cue-reactivity task
Huang et al., (2023)	25	7	40.25 ± 8.82	13	8	40.58 ± 10.84	海洛因	Cue-reactivity task
Jia et al., (2011)	12	8	38.60 ± 9.29	12	8	35.25 ± 10.19	可卡因	Monetary incentive delay task
Li et al., (2012)	24		32.80 ± 6.60	20		35 ± 7	海洛因	Cue-reactivity task
Luo et al., (2011)	20	15	34.10 ± 7.90	23	13	31.30 ± 7.10	尼古丁	Modified monetary incentive
May et al., (2024)	18	28	35.09 ± 8.42	32	58	33.51 ± 11.47	苯丙胺	Monetary incentive delay
Moeller et al., (2018)	28	9		18	8	43.10 ± 7.20	可卡因	Drug-choice task
Monterosso et al., (2007)	8	4	33.80 ± 8.10	12	5	29.70 ± 7.20	冰毒	Delay discounting task
Schulte et al., (2017)	18	8	49.90 ± 9.50	17	9	49.10 ± 11	酒精	Cue-reactivity task
Seo et al., (2016)	29	8	37.20 ± 7.90	23	14	34.30 ± 8.60	酒精	Cue-reactivity task
Sjoerds et al., (2014)	16	14	46.50 ± 8.50	11	4	46.80 ± 10	酒精	Cue-reactivity task
Tapert et al., (2003)	9	6	16.96 ± 0.78	9	6	16.35± 1.02	酒精	Alcoholic beverage pictures task
Wesley et al., (2014)	20	5	34.70 ± 20.90	13	12	39.90 ± 22.20	可卡因	Two cross-commodity temporal decision-making tasks
Wrase et al., (2007)	16		42.38 ± 7.52	16		39.94 ± 8.59	酒精	Cue-reactivity task
Yip et al., (2014)	20		26.65 ± 2.19	20		29.20 ± 2.25	大麻	Monetary incentive delay
Zhou et al., (2019)	18		22.94 ± 2.71	44		23.20 ± 4.32	大麻	Cue-reactivity task
Zühlsdorff et al., (2023)	19	1	34.30 ± 6.90	17	1	31.20 ± 4.70	可卡因	Probabilistic reversal learning
李强等(2013)	18		34.60 ± 6.80	20		35 ± 7	海洛因	线索渴求诱导

作者	成瘾组		成瘾组平均年龄(M ± SD)	对照组		对照组平均年龄(M ± SD)	成瘾物类型	任务
作者	男	女	成瘾组平均年龄(M ± SD)	男	女	对照组平均年龄(M ± SD)	成瘾物类型	任务
抑制控制
Ahmadi et al., (2013)	12	23	18.97 ± 0.45	31	25	18.80 ± 0.97	酒精	Go/no-go
Ceceli, King, et al., (2023)	31	9	40.90 ± 9.20	15	9	41.70 ± 11.30	海洛因	Stop signal task
Ceceli, Parvaz, et al., (2023)	24	4	44.07 ± 8.18	21	5	42.66 ± 7.05	可卡因	Stop signal task
Cyr et al., (2019)	17	11	19.30 ± 2	17	15	18.90 ± 2.70	大麻	Simon task
Czapla et al., (2017)	17	2	51.21 ± 7.36	17	4	41.95 ± 9.99	酒精	Go/no-go
Fu et al., (2008)	28		33.39 ± 5.98	15		29.59 ± 6.94	海洛因	Go/no-go
Gerhardt et al., (2021)	13	2	47 ± 12.30	9	6	41.90 ± 14.40	酒精	Simon-task & Go-/no-no & Stop-signal tsk
Hester et al., (2013)	13	2	38.20	13	2	42.70	可卡因	Go/no-go
Jan et al., (2014)	7	0	38.30 ± 5.60	7	3	32.30 ± 8.70	冰毒	Stroop
Kalhan et al., (2022)	10	10	24.30 ± 4.70	10	10	23.70 ± 4.30	尼古丁	Stop-Signal Task
Kober et al., (2014)	20		26.65 ± 9.81	20		29.20 ± 10.06	大麻	Stroop color-word interference task
Li et al., (2008)	15		37.70 ± 6.80	15		36.60 ± 6	可卡因	Stop signal task
Li et al., (2009)	18	6	38.70 ± 8.30	18	6	35.50 ± 5.90	酒精	Stop signal task
Ma et al., (2015)	12	1	37.40 ± 5.30	7	3	35.20 ± 7.30	可卡因	Easy no-go
Moeller et al., (2012)	28	5	44.20 ± 6.30	17	3	39.80 ± 5	可卡因	Stroop
Moeller et al., (2014)	28	5		18	2	39.60 ± 5.50	可卡因	Stroop
Morein-Zamir et al., (2013)	30	2	34.53 ± 7.81	26	15	31.68 ± 8.49	兴奋剂依赖	Stop-Signal Task
Müller-Oehring et al., (2019)	10	8	49.60 ± 11	17	4	50.30 ± 9.50	酒精	Addiction-Stroop color match-to- sample task
Nestor et al., (2011)	5	5	33.50 ± 9.30	11	7	36.40 ± 10.40	冰毒	Color-world Stroop
Schulte et al., (2012)	18		51 ± 6.60	17		50 ± 14.90	酒精	Stroop match-to-sample task
Stein et al., (2021)	10	3	45.62 ± 10.01	9	5	37.71 ±12.82	酒精	Go/no-go
Zerekidze et al., (2023)	14	4	32.40 ± 7.40	14	7	27.60 ± 3.50	冰毒	Stroop
富丽萍等人(2008)	30		33 ± 6	18		29 ± 7	海洛因	Go/no-go
奖赏加工
Blaine et al., (2020)	28	16	33 ± 11	23	20	32 ± 10	酒精	Cue-reactivity task
Conti et al., (2024)	14	9		11	8		尼古丁	Decision-making task
Dakhili et al., (2022)	53		32.12 ± 5.89	23		31.17 ± 5.69	冰毒	Cue-reactivity task
Dennis et al., (2020)	29	10	-	28	18	35 ± 11.80	酒精	Probabilistic delay discounting task
Filbey et al., (2013)	46	13	23.49 ± 6.37	5	22	30.32 ± 10.09	大麻	Monetary incentive delay task
Forbes et al., (2014)	15	9	27.20 ± 4.90	14	10	27.20 ± 3.70	酒精	Monetary reward task
Gilman & Hommer et al., (2008)	12		41.83 ± 8.39	12		38.08 ± 6.97	酒精	Visual stimulation task
Gilman et al., (2015)	12	6	30.50 ± 5.06	12	6	30.67 ± 7.10	酒精	Risk-taking task
Goudriaan et al., (2010)	10		-	17		34.70 ± 9.70	尼古丁	Cue-reactivity task
Grodin et al., (2016)	11	6	32.25 ± 6.94	9	8	27.72 ± 4.25	酒精	Monetary incentive delay task
Heinz et al., (2007)	6	6	39 ± 7	6	6	40 ± 8	酒精	Cue-reactivity task
Hong et al., (2017)	15		39.90 ± 4.90	15		39.20 ± 5.20	尼古丁	Cue-reactivity task
Huang et al., (2018)	28		31.68 ± 7.06	27		33.93 ± 7.21	冰毒	Cue-reactivity task
Huang et al., (2023)	25	7	40.25 ± 8.82	13	8	40.58 ± 10.84	海洛因	Cue-reactivity task
Jia et al., (2011)	12	8	38.60 ± 9.29	12	8	35.25 ± 10.19	可卡因	Monetary incentive delay task
Li et al., (2012)	24		32.80 ± 6.60	20		35 ± 7	海洛因	Cue-reactivity task
Luo et al., (2011)	20	15	34.10 ± 7.90	23	13	31.30 ± 7.10	尼古丁	Modified monetary incentive
May et al., (2024)	18	28	35.09 ± 8.42	32	58	33.51 ± 11.47	苯丙胺	Monetary incentive delay
Moeller et al., (2018)	28	9		18	8	43.10 ± 7.20	可卡因	Drug-choice task
Monterosso et al., (2007)	8	4	33.80 ± 8.10	12	5	29.70 ± 7.20	冰毒	Delay discounting task
Schulte et al., (2017)	18	8	49.90 ± 9.50	17	9	49.10 ± 11	酒精	Cue-reactivity task
Seo et al., (2016)	29	8	37.20 ± 7.90	23	14	34.30 ± 8.60	酒精	Cue-reactivity task
Sjoerds et al., (2014)	16	14	46.50 ± 8.50	11	4	46.80 ± 10	酒精	Cue-reactivity task
Tapert et al., (2003)	9	6	16.96 ± 0.78	9	6	16.35± 1.02	酒精	Alcoholic beverage pictures task
Wesley et al., (2014)	20	5	34.70 ± 20.90	13	12	39.90 ± 22.20	可卡因	Two cross-commodity temporal decision-making tasks
Wrase et al., (2007)	16		42.38 ± 7.52	16		39.94 ± 8.59	酒精	Cue-reactivity task
Yip et al., (2014)	20		26.65 ± 2.19	20		29.20 ± 2.25	大麻	Monetary incentive delay
Zhou et al., (2019)	18		22.94 ± 2.71	44		23.20 ± 4.32	大麻	Cue-reactivity task
Zühlsdorff et al., (2023)	19	1	34.30 ± 6.90	17	1	31.20 ± 4.70	可卡因	Probabilistic reversal learning
李强等(2013)	18		34.60 ± 6.80	20		35 ± 7	海洛因	线索渴求诱导

作者	成瘾组		成瘾组平均年龄(M ± SD)	对照组		对照组平均年龄(M ± SD)	成瘾物类型	任务
作者	男	女	成瘾组平均年龄(M ± SD)	男	女	对照组平均年龄(M ± SD)	成瘾物类型	任务
抑制控制
Ding et al., 2014)	14	3	16.41 ± 3.20	14	3	16.29 ± 2.95	IGD	Go/no-go
Dong et al., (2012)	12		23.60 ± 3.50	12		24.20 ± 3.10	IGD	Stroop
Dong et al., (2017)	18		21 ± 2.83	21		22 ± 2.45	IGD	Color-word interference Stroop task
Dong et al., (2013)	15		23.80 ± 3.70	15		24.10 ± 3.30	IGD	Stroop
Ko et al., (2014)	26		24.58 ± 3.23	23		24.35 ± 2.12	IGD	Go/no-go
Lee et al., (2015)	18		13.60 ± 0.90	18		13.40 ± 1	IGD	Stroop match-to-sample task
Liu et al., (2014)	11		23.45 ± 2.34	11		22.45 ± 1.70	IGD	Go/no-go
Luijten et al., (2015)	18		20.83 ± 3.05	16		21.38 ± 3.03	PG	Go/no-go & Stroop
Shen et al., (2023)	10	18	-	10	20	-	PMVG	Stroop
Wang, Yang, Zheng, Li, Wei et al., (2021)	15		22.60 ± 2.25	25		23 ± 2.50	IGD	Stop signal task
Zhang, Lin, et al., (2016)	19		22.20 ± 3.10	21		22.80 ± 2.40	IGD	Stroop
周于等人(2018)	8	2	15.60 ± 3.10	8	2	15.30 ± 2.90	IGD	Stroop
奖赏加工
Balodis et al., (2012)	10	4	35.80 ± 11.70	10	4	37.10 ± 11.30	PG	Monetary incentive delay task
Choi et al., (2012)	15		27.93 ± 3.59	15		26.60 ± 4.29	PG	Monetary incentive task
Crockford et al., (2005)	10		39.30 ± 7.60	10		39.20 ± 8.30	PG	Cue-reactivity task
Dong et al., (2011)	14		23.40 ± 3.30	13		24.10 ± 3.20	网络成瘾	Guessing task
Dong et al., (2017)	18		21 ± 2.83	21		22 ± 2.45	IGD	Guessing task
Dong, Hu, & Lin (2013)	16		21.40 ± 3.10	15		22.10 ± 3.60	网络成瘾	Reality-simulated guessing task
Dong, Hu, Lin, et al., (2013)	16		21.40 ± 3.10	15		22.10 ± 3.60	网络成瘾	Continuous win/ losses
Gelskov et al., (2016)	14		29.43 ± 6.05	15		29.87 ± 6.06	PG	Gambling task
Goudriaan et al., (2010)	17		35.30 ± 9.40	17		34.70 ± 9.70	PG	Cue-reactivity task
Kim et al., (2014)	15		13.87 ± 0.83	15		13.87 ± 0.83	网络成瘾	Right-left discrimination test
Kim et al., (2017)	18		22.20 ± 2	20		21.20 ± 2.20	IGD	The feedback type
Ko et al., (2009)	10		22	10		22.70	IGD	Cue-reactivity task
Ko et al., (2013)	15		24.67 ± 3.11	15		24.47 ± 2.83	IGD	Cue-reactivity task
Lei et al., (2022)	45		20.82 ± 1.37	42		21.29 ± 1.52	IGD	Reward-related prediction-error task
Limbrick-Oldfield et al., (2017)	19		31	19		28	PG	Cue-reactivity task
Lin et al., (2015)	19		22.20 ± 3.08	21		22.80 ± 2.35	IGD	Probability discounting task
Liu et al., (2016)	11	8	21.40 ± 1	11	8	20.80 ± 1.10	IGD	Internet game video task
Liu, Yip, et al., (2017)	39		22.64 ± 2.12	23		23.09 ± 2.13	IGD	Cue-reactivity task
Liu, Xue, et al., (2017)	41		21.93 ± 1.88	27		22.74 ± 2.35	IGD	The cups task
Lorenz et al., (2013)	8		25 ± 7.40	9		24.80 ± 6.90	PMVG	Dot probe paradigm
Miedl et al., (2012)	15	1	35 ± 2	15	1	38 ± 2	PG	Delay discounting Probabilistic discounting
Miedl et al., (2015)	15		36.70 ± 5.80	15		36.80 ± 5.60	PG	Monetary-choice task
Power et al., (2012)	13		42.40 ± 10.80	13		41 ± 11	PG	Iowa gambling task
Schmidt et al., (2021)	25		27.90 ± 9.30	28		26.80 ± 5.80	PG	Monetary incentive delay task
Seok et al., (2015)	15		22.20 ± 3.07	15		22.47 ± 2.53	网络成瘾	Financial decision-making task
Sescousse et al., (2013)	18		34.10 ± 11.60	20		31 ± 7.30	PG	Incentive delay task
Sun et al., (2012)	10		20.40 ± 1.51	10		20.30 ± 0.68	IGD	Cue-reactivity task
Wang, Hu, et al., (2017)	18		22.10 ± 3.20	21		23.10 ± 2	IGD	Delay discounting task
Wang, Wu, et al., (2017)	27	3	21.07 ± 1.34	26	4	21.45 ± 1.32	IGD	Cue-reactivity task
Wang, Yang, Zheng, Li, Qi, et al., (2021)	27		22.52 ± 2.33	26		23.23 ± 2.37	IGD	Timeline of the roulette task
Zhang, Yao, et al., (2016)	40		21.95 ± 1.84	19		22.89 ± 2.23	IGD	Cue-reactivity video task
Zhang et al., (2023)	24	6	21.13 ± 2.33	33	19	21.44 ± 2.07	IGD	Playing an online game
Zhang, Hu, et al., (2020)	29	25		36	21		IGD	Card-guessing task
Zheng et al., (2023)	33	26		41	23		IGD	Delay discounting task
Zhou et al., (2021)	10	11	21.29 ± 1.52	15	8	21.61 ± 1.95	IGD	Cue-reactivity task
Zühlsdorff et al., (2023)	16	2	33.60 ± 8	17	1	31.20 ± 4.70	PG	Probabilistic reversal learning
丁伟娜等人(2013)	14	3	16.41 ± 3.20	14	3	16.29 ± 2.95	IGD	概率性猜牌任务

作者	成瘾组		成瘾组平均年龄(M ± SD)	对照组		对照组平均年龄(M ± SD)	成瘾物类型	任务
作者	男	女	成瘾组平均年龄(M ± SD)	男	女	对照组平均年龄(M ± SD)	成瘾物类型	任务
抑制控制
Ding et al., 2014)	14	3	16.41 ± 3.20	14	3	16.29 ± 2.95	IGD	Go/no-go
Dong et al., (2012)	12		23.60 ± 3.50	12		24.20 ± 3.10	IGD	Stroop
Dong et al., (2017)	18		21 ± 2.83	21		22 ± 2.45	IGD	Color-word interference Stroop task
Dong et al., (2013)	15		23.80 ± 3.70	15		24.10 ± 3.30	IGD	Stroop
Ko et al., (2014)	26		24.58 ± 3.23	23		24.35 ± 2.12	IGD	Go/no-go
Lee et al., (2015)	18		13.60 ± 0.90	18		13.40 ± 1	IGD	Stroop match-to-sample task
Liu et al., (2014)	11		23.45 ± 2.34	11		22.45 ± 1.70	IGD	Go/no-go
Luijten et al., (2015)	18		20.83 ± 3.05	16		21.38 ± 3.03	PG	Go/no-go & Stroop
Shen et al., (2023)	10	18	-	10	20	-	PMVG	Stroop
Wang, Yang, Zheng, Li, Wei et al., (2021)	15		22.60 ± 2.25	25		23 ± 2.50	IGD	Stop signal task
Zhang, Lin, et al., (2016)	19		22.20 ± 3.10	21		22.80 ± 2.40	IGD	Stroop
周于等人(2018)	8	2	15.60 ± 3.10	8	2	15.30 ± 2.90	IGD	Stroop
奖赏加工
Balodis et al., (2012)	10	4	35.80 ± 11.70	10	4	37.10 ± 11.30	PG	Monetary incentive delay task
Choi et al., (2012)	15		27.93 ± 3.59	15		26.60 ± 4.29	PG	Monetary incentive task
Crockford et al., (2005)	10		39.30 ± 7.60	10		39.20 ± 8.30	PG	Cue-reactivity task
Dong et al., (2011)	14		23.40 ± 3.30	13		24.10 ± 3.20	网络成瘾	Guessing task
Dong et al., (2017)	18		21 ± 2.83	21		22 ± 2.45	IGD	Guessing task
Dong, Hu, & Lin (2013)	16		21.40 ± 3.10	15		22.10 ± 3.60	网络成瘾	Reality-simulated guessing task
Dong, Hu, Lin, et al., (2013)	16		21.40 ± 3.10	15		22.10 ± 3.60	网络成瘾	Continuous win/ losses
Gelskov et al., (2016)	14		29.43 ± 6.05	15		29.87 ± 6.06	PG	Gambling task
Goudriaan et al., (2010)	17		35.30 ± 9.40	17		34.70 ± 9.70	PG	Cue-reactivity task
Kim et al., (2014)	15		13.87 ± 0.83	15		13.87 ± 0.83	网络成瘾	Right-left discrimination test
Kim et al., (2017)	18		22.20 ± 2	20		21.20 ± 2.20	IGD	The feedback type
Ko et al., (2009)	10		22	10		22.70	IGD	Cue-reactivity task
Ko et al., (2013)	15		24.67 ± 3.11	15		24.47 ± 2.83	IGD	Cue-reactivity task
Lei et al., (2022)	45		20.82 ± 1.37	42		21.29 ± 1.52	IGD	Reward-related prediction-error task
Limbrick-Oldfield et al., (2017)	19		31	19		28	PG	Cue-reactivity task
Lin et al., (2015)	19		22.20 ± 3.08	21		22.80 ± 2.35	IGD	Probability discounting task
Liu et al., (2016)	11	8	21.40 ± 1	11	8	20.80 ± 1.10	IGD	Internet game video task
Liu, Yip, et al., (2017)	39		22.64 ± 2.12	23		23.09 ± 2.13	IGD	Cue-reactivity task
Liu, Xue, et al., (2017)	41		21.93 ± 1.88	27		22.74 ± 2.35	IGD	The cups task
Lorenz et al., (2013)	8		25 ± 7.40	9		24.80 ± 6.90	PMVG	Dot probe paradigm
Miedl et al., (2012)	15	1	35 ± 2	15	1	38 ± 2	PG	Delay discounting Probabilistic discounting
Miedl et al., (2015)	15		36.70 ± 5.80	15		36.80 ± 5.60	PG	Monetary-choice task
Power et al., (2012)	13		42.40 ± 10.80	13		41 ± 11	PG	Iowa gambling task
Schmidt et al., (2021)	25		27.90 ± 9.30	28		26.80 ± 5.80	PG	Monetary incentive delay task
Seok et al., (2015)	15		22.20 ± 3.07	15		22.47 ± 2.53	网络成瘾	Financial decision-making task
Sescousse et al., (2013)	18		34.10 ± 11.60	20		31 ± 7.30	PG	Incentive delay task
Sun et al., (2012)	10		20.40 ± 1.51	10		20.30 ± 0.68	IGD	Cue-reactivity task
Wang, Hu, et al., (2017)	18		22.10 ± 3.20	21		23.10 ± 2	IGD	Delay discounting task
Wang, Wu, et al., (2017)	27	3	21.07 ± 1.34	26	4	21.45 ± 1.32	IGD	Cue-reactivity task
Wang, Yang, Zheng, Li, Qi, et al., (2021)	27		22.52 ± 2.33	26		23.23 ± 2.37	IGD	Timeline of the roulette task
Zhang, Yao, et al., (2016)	40		21.95 ± 1.84	19		22.89 ± 2.23	IGD	Cue-reactivity video task
Zhang et al., (2023)	24	6	21.13 ± 2.33	33	19	21.44 ± 2.07	IGD	Playing an online game
Zhang, Hu, et al., (2020)	29	25		36	21		IGD	Card-guessing task
Zheng et al., (2023)	33	26		41	23		IGD	Delay discounting task
Zhou et al., (2021)	10	11	21.29 ± 1.52	15	8	21.61 ± 1.95	IGD	Cue-reactivity task
Zühlsdorff et al., (2023)	16	2	33.60 ± 8	17	1	31.20 ± 4.70	PG	Probabilistic reversal learning
丁伟娜等人(2013)	14	3	16.41 ± 3.20	14	3	16.29 ± 2.95	IGD	概率性猜牌任务

cluster	体积/mm³	ALE值/×10^-3	Z值	X	Y	Z	BA区	脑区	Cluster贡献研究数量	FSN
物质抑制增强(k = 13)
1	400	10.36	3.72	4	50	−2	32	右前扣带回	2	4 < FSN <27
2	368	13.40	4.31	−12	−40	−16		左前叶	2	4 < FSN < 27
物质抑制降低(k = 20)
1	472	15.26	4.20	60	10	22	9	右额下回	2	> 20
2	472	18.17	4.70	−54	14	38	8	左额中回	3	6 < FSN < 40
3	464	14.72	4.09	32	−14	56	6	右中央前回	3	6 < FSN < 40
4	392	14.53	4.06	54	4	−26	21	右颞中回	2	6 < FSN < 20
5	352	15.30	4.21	−44	8	−28	38	左颞上回	2	6 < FSN < 20
6	352	16.84	4.49	−12	−12	−8		丘脑底核	2	6 < FSN < 20
7	352	14.06	3.96	44	0	48	6	右中央前回额中回	2	> 20
8	304	12.68	3.68	18	34	24	32	右扣带回	2	< 6
		12.67	3.68	18	32	28	9	右额中回	2	< 6
9	256	14.66	4.08	−60	−28	26	40	左顶下小叶	2	< 6
10	256	12.40	3.63	−32	−60	44	39	左角回	2	< 6
		11.68	3.50	−30	−62	48	19	左楔前叶	2	< 6
行为抑制增强(k = 9)
1	568	13.47	4.76	30	32	28	9	右额中回	2	> 31
2	336	9.48	4.00	−16	−12	54	6	左额中回	2	3 < FSN < 31