Abstract
Background
Substance use disorder is conceptualized as a neuropsychiatric disease with multifaceted
phenotypic manifestations including disrupted interactions between brain networks.
While the current understanding of brain network interactions is mostly based on static
functional connectivity, accumulating evidence suggests that temporal dynamics of
these network interactions may better reflect brain function and disease-related dysfunction.
We thus investigated brain dynamics in cocaine use disorder and assessed their relationship
with cocaine dependence severity.
Methods
Using a time frame analytical approach on resting-state functional magnetic resonance
imaging data of 54 cocaine users and 54 age- and sex-matched healthy control participants,
we identified temporally recurring brain network configuration patterns, termed brain
states. With Menon’s triple network model as a guide, we characterized these state
dynamics by quantifying their occurrence rate and transition probability. Group differences
in the state dynamics and their association with cocaine dependence were assessed.
Results
Three recurrent brain states with spatial patterns resembling the default mode, salience,
and executive control networks were identified. Compared with healthy control subjects,
cocaine users showed a higher default mode state occurrence rate and higher probability
of transitioning from the salience state to the default mode state, with the former
being attributed to the latter. A composite state transition probability negatively
correlated with cocaine dependence severity.
Conclusions
Our results provide novel evidence supporting the triple network model. While confirming
hyperactivity of default mode network in cocaine users, our findings indicate the
failure of salience network in toggling between default mode and executive control
networks in cocaine use disorder.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Biological Psychiatry: Cognitive Neuroscience and NeuroimagingAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Key Substance Use and Mental Health Indicators in the United States: Results from the 2020 National Survey on Drug Use and Health. Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration..(Available at:)https://www.samhsa.gov/data/sites/default/files/reports/rpt35319/2020NSDUHFFR1PDFW102121.pdfDate: 2021Date accessed: November 10, 2021
- Neurocircuitry of addiction.Neuropsychopharmacol Rev. 2010; 35: 217-238
- Impulsivity, compulsivity, and top-down cognitive control.Neuron. 2011; 69: 680-694
- Neurobiology of addiction: A neurocircuitry analysis.Lancet Psychiatry. 2016; 3: 760-773
- Heroin addicts have higher discount rates for delayed rewards than non-drug-using controls.J Exp Psychol Gen. 1999; 128: 78-87
- Heroin and cocaine abusers have higher discount rates for delayed rewards than alcoholics or non-drug-using controls.Addiction. 2004; 99: 461-471
- Addiction: Decreased reward sensitivity and increased expectation sensitivity conspire to overwhelm the brain's control circuit.Bioessays. 2010; 32: 748-755
- Impaired response inhibition function in abstinent heroin dependents: An fMRI study.Neurosci Lett. 2008; 438: 322-326
- Dysfunction of the prefrontal cortex in addiction: Neuroimaging findings and clinical implications.Nat Rev Neurosci. 2011; 12: 652-669
- Addiction: A disease of learning and memory.Am J Psychiatry. 2005; 162: 1414-1422
- A role for brain stress systems in addiction.Neuron. 2008; 59: 11-34
- Addiction: Beyond dopamine reward circuitry.Proc Natl Acad Sci U S A. 2011; 108: 15037-15042
- Resting-state functional connectivity reflects structural connectivity in the default mode network.Cereb Cortex. 2009; 19: 72-78
- Spontaneous low-frequency BOLD signal fluctuations: An fMRI investigation of the resting-state default mode of brain function hypothesis.Hum Brain Mapp. 2005; 26: 15-29
- From The Cover: The human brain is intrinsically organized into dynamic, anticorrelated functional networks.Proc Natl Acad Sci U S A. 2005; 102: 9673-9678
- Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.Nat Rev Neurosci. 2007; 8: 700-711
- Dissociable intrinsic connectivity networks for salience processing and executive control.J Neurosci. 2007; 27: 2349-2356
- A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks.Proc Natl Acad Sci U S A. 2008; 105: 12569-12574
- Large-scale brain networks and psychopathology: A unifying triple network model.Trends Cogn Sci. 2011; 15: 483-506
- Resting state functional connectivity in addiction: Lessons learned and a road ahead.Neuroimage. 2012; 62: 2281-2295
- Neuroimaging impaired response inhibition and salience attribution in human drug addiction: A systematic review.Neuron. 2018; 98: 886-903
- Common dysfunction of large-scale neurocognitive networks across psychiatric disorders.Biol Psychiatry. 2019; 85: 379-388
- The brain's default network.Ann N Y Acad Sci. 2008; 1124: 1-38
- Saliency, switching, attention and control: A network model of insula function.Brain Struct Funct. 2010; 214: 655-667
- Interactions between the salience and default-mode networks are disrupted in cocaine addiction.J Neurosci. 2015; 35: 8081-8090
- Executive control network connectivity strength protects against relapse to cocaine use.Addict Biol. 2017; 22: 1790-1801
- Triple network resting state connectivity predicts distress tolerance and is associated with cocaine use.J Clin Med. 2019; 8: 2135
- Large-scale brain network coupling predicts acute nicotine abstinence effects on craving and cognitive function.JAMA Psychiatry. 2014; 71: 523-530
- Dynamic functional connectivity: Promise, issues, and interpretations.Neuroimage. 2013; 80: 360-378
- Tracking whole-brain connectivity dynamics in the resting state.Cereb Cortex. 2014; 24: 663-676
- The Dynamics of functional brain networks: Integrated network states during cognitive task performance.Neuron. 2016; 92: 544-554
- Large-scale brain networks in cognition: Emerging methods and principles.Trends Cogn Sci. 2010; 14: 277-290
- Brain state expression and transitions are related to complex executive cognition in normative neurodevelopment.Neuroimage. 2018; 166: 293-306
- Temporal dynamics of functional brain states underlie cognitive performance.Cereb Cortex. 2021; 31: 2125-2138
- Impaired functional connectivity within and between frontostriatal circuits and its association with compulsive drug use and trait impulsivity in cocaine addiction.JAMA Psychiatry. 2015; 72: 584-592
- Laboratory validation study of drug evaluation and classification program: Ethanol, cocaine, and marijuana.J Anal Toxicol. 1996; 20: 468-483
- A generalized Louvain method for community detection implemented in MATLAB..(Available at:)http://netwiki.amath.unc.edu/GenLouvainDate accessed: April 17, 2018
- Decomposition of spontaneous brain activity into distinct fMRI co-activation patterns.Front Syst Neurosci. 2013; 7: 101
- Investigations into resting-state connectivity using independent component analysis.Philos Trans R Soc Lond B Biol Sci. 2005; 360: 1001-1013
- Knee Point. MATLAB Central File Exchange.(Available at:)https://www.mathworks.com/matlabcentral/fileexchange/35094-knee-pointDate accessed: August 16, 2022
- Altered coupling of default-mode, executive-control and salience networks in Internet gaming disorder.Eur Psychiatry. 2017; 45: 114-120
- The role of default network deactivation in cognition and disease.Trends Cogn Sci. 2012; 16: 584-592
- The neural bases of momentary lapses in attention.Nat Neurosci. 2006; 9: 971-978
- Default-mode and task-positive network activity in major depressive disorder: Implications for adaptive and maladaptive rumination.Biol Psychiatry. 2011; 70: 327-333
- Salience and default mode network dysregulation in chronic cocaine users predict treatment outcome.Brain. 2017; 140: 1513-1524
- Brain default-mode network dysfunction in addiction.Neuroimage. 2019; 200: 313-331
- Neuropsychological consequences of alcohol and drug abuse on different components of executive functions.J Psychopharmacol. 2010; 24: 1317-1332
- Molecular basis of long-term plasticity underlying addiction.Nat Rev Neurosci. 2001; 2: 119-128
Article info
Publication history
Published online: September 02, 2022
Accepted:
August 22,
2022
Received in revised form:
July 28,
2022
Received:
April 23,
2022
Publication stage
In Press Journal Pre-ProofFootnotes
TZ and HG contributed equally to this work.
Identification
Copyright
Published by Elsevier Inc on behalf of Society of Biological Psychiatry.