Yijie Zhao1,2,3, Samantha N Sallie4, Hailun Cui4, Ningning Zeng5, Jiang Du5, Tifei Yuan5, Dianyou Li3, Dirk De Ridder6, Chencheng Zhang3. 1. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China. 2. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China. 3. Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. 4. Department of Psychiatry, University of Cambridge, Level E4, Addenbrooke's Hospital, Cambridge, UK. 5. Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China. 6. Department of Surgical Sciences, Section of Neurosurgery, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Abstract
OBJECTIVES: Substance use disorder (SUD) is characterized by compulsive use of addictive substances with considerable impact on both the medical system and society as a whole. The craving of substances leads to relapse in the majority of patients within one year of traditional treatments. In recent decades, neuromodulation approaches have emerged as potential novel treatments of SUD, but the ideal neural target remains contentious. MATERIALS AND METHODS: In this review, we discuss new insights on the anterior cingulate cortex (ACC) as a neuromodulation target for SUD. RESULTS AND CONCLUSION: First, we illustrate that the ACC serves as a central "hub" in addiction-related neural networks of cognitive functions, including, but not limited to, decision-making, cognitive inhibition, emotion, and motivation. Then, we summarize the literature targeting the ACC to treat SUDs via available neuromodulation approaches. Finally, we propose potential directions to improve the effect of stimulating the ACC in SUD treatment. We emphasize that the ACC can be divided into at least four sub-regions, which have distinctive functions and connections. Studies focusing on these sub-regions may help to develop more precise and effective ACC stimulation according to patients' symptom profiles and cognitive deficits.
OBJECTIVES: Substance use disorder (SUD) is characterized by compulsive use of addictive substances with considerable impact on both the medical system and society as a whole. The craving of substances leads to relapse in the majority of patients within one year of traditional treatments. In recent decades, neuromodulation approaches have emerged as potential novel treatments of SUD, but the ideal neural target remains contentious. MATERIALS AND METHODS: In this review, we discuss new insights on the anterior cingulate cortex (ACC) as a neuromodulation target for SUD. RESULTS AND CONCLUSION: First, we illustrate that the ACC serves as a central "hub" in addiction-related neural networks of cognitive functions, including, but not limited to, decision-making, cognitive inhibition, emotion, and motivation. Then, we summarize the literature targeting the ACC to treat SUDs via available neuromodulation approaches. Finally, we propose potential directions to improve the effect of stimulating the ACC in SUD treatment. We emphasize that the ACC can be divided into at least four sub-regions, which have distinctive functions and connections. Studies focusing on these sub-regions may help to develop more precise and effective ACC stimulation according to patients' symptom profiles and cognitive deficits.
Authors: Johannes Petzold; Andy C Dean; Jean-Baptiste Pochon; Dara G Ghahremani; Richard De La Garza; Edythe D London Journal: Addict Biol Date: 2022-09 Impact factor: 4.093
Authors: Maria Paraskevopoulou; Daan van Rooij; Aart H Schene; Albert Batalla; Roselyne J Chauvin; Jan K Buitelaar; Arnt F A Schellekens Journal: Addict Biol Date: 2022-03 Impact factor: 4.093
Authors: Rajat Kumar; Lilianne R Mujica-Parodi; Michael Wenke; Anar Amgalan; Andrew Lithen; Sindhuja T Govindarajan; Rany Makaryus; Helene Benveniste; Helmut H Strey Journal: Pharmaceutics Date: 2021-12-03 Impact factor: 6.321