Using Network Control Theory to analyze Brain Dynamics in Individuals with Cocaine Use Disorder
Poster No:
418
Submission Type:
Abstract Submission
Authors:
Hussain Bukhari1, S. Parker Singleton2, Keith Jamison1, Aliza Brzezinski3, Eduardo Garza-Villarreal4, Conor Liston1, Amy Kuceyeski5
Institutions:
1Weill Cornell Medicine, New York, NY, 2University of Pennsylvania, Philadelphia, PA, 3University of McGill, Montreal, Quebec, 4Universidad Nacional Autónoma de México campus Juriquilla, Juriquilla, Querétaro, 5Cornell, Ithaca, NY
First Author:
Co-Author(s):
Eduardo Garza-Villarreal, M.D., Ph.D.
Universidad Nacional Autónoma de México campus Juriquilla
Juriquilla, Querétaro
Universidad Nacional Autónoma de México campus Juriquilla
Juriquilla, Querétaro
Introduction:
Individuals with cocaine use disorder (CUD) engage in drug use despite continuous negative impacts on social relationships, loss of economic opportunity and alienation from society (Volkow et al., 2010). Prolonged cocaine use alters dopaminergic circuits, bringing about a shift that leads to maladaptive behaviors categorized by a lack of inhibitory control (Spronk et al., 2013). This weakened inhibition may underlie the compulsive drug seeking behavior that is typical of individuals with CUD (Ricard et al., 2024). We use network control theory, a technique capable of modeling and analyzing the brain's functional activation dynamics, to analyze differences in dynamics of CUD compared to healthy controls.
Methods:
We use the SUDMEX CONN dataset, consisting of multi-modal MRI, CUD metrics, and demographics of 132 individuals (18-50 years old), with N=61 (11 female) non-user controls and N=71 individuals with chronic CUD (9 females) (Angeles-Valdez et al., 2022). Structural connectivity matrices were extracted for the Tian 116 atlas (116 regions) (Tian et al., 2020). We concatenated resting state fMRI time series (all subjects, both conditions) and applied K means clustering used to identify common brain activation patterns i.e. functional brain states (Singleton et al., 2024). We used representative structural connectomes for people with CUD and non-user healthy controls with network control theory to identify the minimum control energy necessary to transition between brain states. We used ANCOVAs to compare average transition energies (TEs) at a global-, network- and region-level across groups, while controlling for covariates for age, sex, mean framewise displacement, tobacco use, and interactions of group with age, sex and tobacco use. P-values were corrected for multiple comparisons using the Benjamini-Hochberg correction.
Results:
People with CUD had higher fractional occupancy and appearance rate for a lower order state defined by high amplitude activity in somatomotor network (Fig. 1). Global TEs were significantly reduced in individuals with CUD compared to non-user healthy controls. This global decrease was driven by higher order network TE, specifically control (CON) and dorsal attention (DAN) networks. In these two networks, transition energies for cocaine users did not exhibit the same decrease typical of healthy non-users across age. (Fig. 2).
Conclusions:
Prolonged cocaine use leads to an aberrantly dynamic system, and differential energetic barriers for people with CUD in comparison to non-user controls. This work suggests that cocaine addiction impacts the landscape of brain dynamics by shifting toward bottom-order states. Specifically, people with CUD have higher occupancy of lower order states and decreases in the energy demand for higher order states, which could be reflective of decreased inhibitory control.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Lifespan Development:
Aging
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Task-Independent and Resting-State Analysis
Keywords:
Addictions
Other - Network Control Theory
1|2Indicates the priority used for review
Abstract Information
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
Ricard, J. A., Labache, L., Segal, A., Dhamala, E., Cocuzza, C. V., Jones, G., Yip, S. W., Chopra, S., & Holmes, A. J. (2024). A shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D2/3 receptor densities. Communications Biology, 7(1), 1178. https://doi.org/10.1038/s42003-024-06836-9
Singleton, S. P., Velidi, P., Schilling, L., Luppi, A. I., Jamison, K., Parkes, L., & Kuceyeski, A. (2024). Altered Structural Connectivity and Functional Brain Dynamics in Individuals With Heavy Alcohol Use Elucidated via Network Control Theory. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. https://doi.org/10.1016/j.bpsc.2024.05.006
Spronk, D. B., van Wel, J. H. P., Ramaekers, J. G., & Verkes, R. J. (2013). Characterizing the cognitive effects of cocaine: A comprehensive review. In Neuroscience and Biobehavioral Reviews (Vol. 37, Issue 8). https://doi.org/10.1016/j.neubiorev.2013.07.003
Tian, Y., Margulies, D. S., Breakspear, M., & Zalesky, A. (2020). Topographic organization of the human subcortex unveiled with functional connectivity gradients. Nature Neuroscience, 23(11), 1421–1432. https://doi.org/10.1038/s41593-020-00711-6
Volkow, N. D., Wang, G. J., Fowler, J. S., Tomasi, D., Telang, F., & Baler, R. (2010). Addiction: Decreased reward sensitivity and increased expectation sensitivity conspire to overwhelm the brain’s control circuit. In BioEssays (Vol. 32, Issue 9). https://doi.org/10.1002/bies.201000042