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Chen P, Wang J, Tang G, Chen G, Xiao S, Guo Z, Qi Z, Wang J, Wang Y. Large-scale network abnormality in behavioral addiction. J Affect Disord 2024; 354:743-751. [PMID: 38521138 DOI: 10.1016/j.jad.2024.03.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 03/01/2024] [Accepted: 03/09/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Researchers have endeavored to ascertain the network dysfunction associated with behavioral addiction (BA) through the utilization of resting-state functional connectivity (rsFC). Nevertheless, the identification of aberrant patterns within large-scale networks pertaining to BA has proven to be challenging. METHODS Whole-brain seed-based rsFC studies comparing subjects with BA and healthy controls (HC) were collected from multiple databases. Multilevel kernel density analysis was employed to ascertain brain networks in which BA was linked to hyper-connectivity or hypo-connectivity with each prior network. RESULTS Fifty-six seed-based rsFC publications (1755 individuals with BA and 1828 HC) were included in the meta-analysis. The present study indicate that individuals with BAs exhibit (1) hypo-connectivity within the fronto-parietal network (FN) and hypo- and hyper-connectivity within the ventral attention network (VAN); (2) hypo-connectivity between the FN and regions of the VAN, hypo-connectivity between the VAN and regions of the FN and default mode network (DMN), hyper-connectivity between the DMN and regions of the FN; (3) hypo-connectivity between the reward system and regions of the sensorimotor network (SS), DMN and VAN; (4) hypo-connectivity between the FN and regions of the SS, hyper-connectivity between the VAN and regions of the SS. CONCLUSIONS These findings provide impetus for a conceptual framework positing a model of BA characterized by disconnected functional coordination among large-scale networks.
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Affiliation(s)
- Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Junjing Wang
- Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou 510006, China
| | - Guixian Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Shu Xiao
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zixuan Guo
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Jurong Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou 510630, China.
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Kraynak TE, Marsland AL, Wager TD, Gianaros PJ. Functional neuroanatomy of peripheral inflammatory physiology: A meta-analysis of human neuroimaging studies. Neurosci Biobehav Rev 2018; 94:76-92. [PMID: 30067939 DOI: 10.1016/j.neubiorev.2018.07.013] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 07/18/2018] [Accepted: 07/22/2018] [Indexed: 01/18/2023]
Abstract
Communication between the brain and peripheral mediators of systemic inflammation is implicated in numerous psychological, behavioral, and physiological processes. Functional neuroimaging studies have identified brain regions that associate with peripheral inflammation in humans, yet there are open questions about the consistency, specificity, and network characteristics of these findings. The present systematic review provides a meta-analysis to address these questions. Multilevel kernel density analysis of 24 studies (37 statistical maps; 264 coordinates; 457 participants) revealed consistent effects in the amygdala, hippocampus, hypothalamus, striatum, insula, midbrain, and brainstem, as well as prefrontal and temporal cortices. Effects in some regions were specific to particular study designs and tasks. Spatial pattern analysis revealed significant overlap of reported effects with limbic, default mode, ventral attention, and corticostriatal networks, and co-activation analyses revealed functional ensembles encompassing the prefrontal cortex, insula, and midbrain/brainstem. Together, these results characterize brain regions and networks associated with peripheral inflammation in humans, and they provide a functional neuroanatomical reference point for future neuroimaging studies on brain-body interactions.
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Affiliation(s)
- Thomas E Kraynak
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 15260, USA; Center for the Neural Basis of Cognition, Pittsburgh, PA, 15260, USA.
| | - Anna L Marsland
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 15260, USA
| | - Tor D Wager
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, 80309, USA; Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Peter J Gianaros
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, 15260, USA; Center for the Neural Basis of Cognition, Pittsburgh, PA, 15260, USA
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Zhang R, Geng X, Lee TMC. Large-scale functional neural network correlates of response inhibition: an fMRI meta-analysis. Brain Struct Funct 2017; 222:3973-3990. [PMID: 28551777 PMCID: PMC5686258 DOI: 10.1007/s00429-017-1443-x] [Citation(s) in RCA: 202] [Impact Index Per Article: 28.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Accepted: 05/09/2017] [Indexed: 12/22/2022]
Abstract
An influential hypothesis from the last decade proposed that regions within the right inferior frontal cortex of the human brain were dedicated to supporting response inhibition. There is growing evidence, however, to support an alternative model, which proposes that neural areas associated with specific inhibitory control tasks co-exist as common network mechanisms, supporting diverse cognitive processes. This meta-analysis of 225 studies comprising 323 experiments examined the common and distinct neural correlates of cognitive processes for response inhibition, namely interference resolution, action withholding, and action cancellation. Activation coordinates for each subcategory were extracted using multilevel kernel density analysis (MKDA). The extracted activity patterns were then mapped onto the brain functional network atlas to derive the common (i.e., process-general) and distinct (i.e., domain-oriented) neural network correlates of these processes. Independent of the task types, activation of the right hemispheric regions (inferior frontal gyrus, insula, median cingulate, and paracingulate gyri) and superior parietal gyrus was common across the cognitive processes studied. Mapping the activation patterns to a brain functional network atlas revealed that the fronto-parietal and ventral attention networks were the core neural systems that were commonly engaged in different processes of response inhibition. Subtraction analyses elucidated the distinct neural substrates of interference resolution, action withholding, and action cancellation, revealing stronger activation in the ventral attention network for interference resolution than action inhibition. On the other hand, action withholding/cancellation primarily engaged the fronto-striatal circuit. Overall, our results suggest that response inhibition is a multidimensional cognitive process involving multiple neural regions and networks for coordinating optimal performance. This finding has significant implications for the understanding and assessment of response inhibition.
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Affiliation(s)
- Ruibin Zhang
- Laboratory of Neuropsychology, The University of Hong Kong, Rm 656, Jockey Club Tower, Pokfulam Road, Hong Kong, Hong Kong.,Laboratory of Cognitive Affective Neuroscience, The University of Hong Kong, Hong Kong, Hong Kong
| | - Xiujuan Geng
- Laboratory of Neuropsychology, The University of Hong Kong, Rm 656, Jockey Club Tower, Pokfulam Road, Hong Kong, Hong Kong.,Laboratory of Cognitive Affective Neuroscience, The University of Hong Kong, Hong Kong, Hong Kong.,The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong
| | - Tatia M C Lee
- Laboratory of Neuropsychology, The University of Hong Kong, Rm 656, Jockey Club Tower, Pokfulam Road, Hong Kong, Hong Kong. .,Laboratory of Cognitive Affective Neuroscience, The University of Hong Kong, Hong Kong, Hong Kong. .,The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, Hong Kong. .,Institute of Clinical Neuropsychology, The University of Hong Kong, Hong Kong, Hong Kong.
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