Common Neural Patterns of Substance Use Disorder: A Seed-based Resting-State Functional Connectivity
Poster No:
1877
Submission Type:
Abstract Submission
Authors:
Feifei Zhang1, Xiaonan Zhang2, Yaming Cao3, Hui Zhang1
Institutions:
1First Hospital of Shanxi Medical University, Tai Yuan, shanxi, 2First Hospital of Shanxi Medical University, Tai yuan, shanxi, 3Zhongbei University, Tai yuan, shanxi
First Author:
Co-Author(s):
Introduction:
Substance use disorder (SUD) shares common clinical features, including impulsive and compulsive behaviors (Koob, 2008) which are linked to dysfunctions in the reward circuit (Liu, 2016). Resting-state functional magnetic resonance imaging (rs-fMRI) studies have shown inconsistent results due to variability in substances and stages of addiction. Identifying common neurobiological patterns in SUD could enhance understanding and treatment strategies.
Methods:
A comprehensive meta-analysis was conducted on 53 whole-brain rs-fMRI studies involving SUD patients. The Seed-based d Mapping toolkit was used to analyze connectivity patterns of key brain regions in the reward circuit: anterior cingulate cortex (ACC), prefrontal cortex (PFC), striatum, thalamus, and amygdala. We also explored correlations between resting-state functional connectivity (rsFC) patterns and impulsivity scores.
Results:
The meta-analysis included 1700 SUD patients and 1792 healthy controls (HCs). Compared with HCs, SUD patients exhibited significant dysfunctions in the cortical-striatal-thalamic-cortical circuit. The ACC showed increased connectivity with the inferior frontal gyrus (IFG), lentiform nucleus, and putamen. The PFC demonstrated hyperconnectivity with the superior frontal gyrus (SFG) and striatum, and hypoconnectivity with the IFG. The striatum exhibited hyperconnectivity with the SFG and hypoconnectivity with the median cingulate gyrus (MCG). Thalamic connectivity with the SFG, dorsal ACC, and caudate nucleus was decreased. The amygdala showed hypoconnectivity with the SFG and ACC. Connectivity alterations were also observed between several seed regions and the parahippocampal gyrus. Notably, the total score of BIS-11 in SUD patients was significantly negatively correlated with decreased rsFC between the striatum and MCG. After family-wise error (FWE) correction, cortical-striatal-cortical circuit dysfunctions persisted.
Conclusions:
our study identifies disruptions in two critical reward circuits: the cortical-striatal-thalamic-cortical (CSTC) circuit and the cortical-striatal-HIP/PHG-amygdala-cortical (CSHAC) circuit. The CSTC circuit is crucial for mediating reward-related behaviors, emotional regulation, and addiction mechanisms (Haber, 2010). Furthermore, the CSTC circuit is associated with impaired decision-making, which is a hallmark feature of addiction (Redish, 2004). The CSHAC circuit, which integrates sensory information from the amygdala and episodic memory information from the hippocampus, projects back to the frontal cortex via the striatum. This loop's involvement in emotional regulation and memory formation suggests its crucial role in reward-based learning and addiction (Everitt, 2005). While the CSTC loop has been extensively studied, the CSHAC loop's role in addiction and reward processing has been relatively underexplored. The identification of these disrupted reward circuits aligns with existing theories on the neural mechanisms underlying SUD. Volkow (Volkow, 2016) proposes that addiction involves alterations in brain circuits related to reward, motivation, memory, and inhibitory control. The CSTC and CSHAC loops' disruptions observed in our study support this model, highlighting the critical neural pathways involved in SUD.
Our findings revealed specific network abnormalities in SUD patients, highlighting disrupted connectivity within the brain's reward circuit. These abnormalities were associated with impulsivity and may provide a theoretical basis for effective interventions to restore normal connectivity patterns.
Our findings revealed specific network abnormalities in SUD patients, highlighting disrupted connectivity within the brain's reward circuit. These abnormalities were associated with impulsivity and may provide a theoretical basis for effective interventions to restore normal connectivity patterns.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Emotion, Motivation and Social Neuroscience:
Emotion and Motivation Other
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making 2
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
Novel Imaging Acquisition Methods:
BOLD fMRI 1
Keywords:
Addictions
FUNCTIONAL MRI
Meta- Analysis
MRI
Psychiatric Disorders
1|2Indicates the priority used for review
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2.Liu, T., Li, J., Zhao, Z., Zhong, Y., Zhang, Z., Xu, Q., Yang, G., Lu, G., Pan, S., Chen, F., 2016. Betel quid dependence is associated with functional connectivity changes of the anterior cingulate cortex: a resting-state fMRI study. Journal of translational medicine 14, 33.
3.Haber, S.N., Knutson, B., 2010. The reward circuit: linking primate anatomy and human imaging. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 35, 4-26.
4.Redish, A.D., 2004. Addiction as a computational process gone awry. Science (New York, N.Y.) 306, 1944-1947.
5.Everitt, B.J., Robbins, T.W., 2005. Neural systems of reinforcement for drug addiction: from actions to habits to compulsion. Nature neuroscience 8, 1481-1489.
6.Volkow, N.D., Koob, G.F., McLellan, A.T., 2016. Neurobiologic Advances from the Brain Disease Model of Addiction. The New England journal of medicine 374, 363-371.