The conception of the ABCD study: From substance use to a broad NIH collaboration

Volkow, Nora D.; Koob, George F.; Croyle, Robert T.; Bianchi, Diana W.; Gordon, Joshua A.; Koroshetz, Walter J.; Pérez‐Stable, Eliseo J.; Riley, William T.; Bloch, Michele; Conway, Kevin P.; Deeds, Bethany Griffin; Dowling, Gayathri J.; Grant, Steven; Howlett, Katia Delrahim; Matochik, John A.; Morgan, Glen D.; Murray, Margaret; Noronha, Antonio; Spong, Catherine Y.; Wargo, Eric; Warren, K. S.; Weiss, Susan R.B.

doi:10.1016/j.dcn.2017.10.002

Cited by 713 publications

(562 citation statements)

References 9 publications

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“…Thus, genetic and predisposing environmental factors may be associated with neurobehavioral changes in CB users, perhaps including SC-FC coupling. The recently initiated NIH Adolescent and Brain Cognitive Development Study, which will follow 10,000 healthy children into adulthood in conjunction with periodic brain imaging, may allow a better understanding of the contributions of genetic factors, environmental factors and CB use on brain network organization and dynamics (Volkow, et al, 2017). …”

Section: Discussionmentioning

confidence: 99%

Aberrant structural–functional coupling in adult cannabis users

Kim

Martin

Shin³

et al. 2018

Human Brain Mapping

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Cellular studies indicate that endocannabinoid type-1 retrograde signaling plays a major role in synaptic plasticity. Disruption of these processes by delta-9-tetrahydrocannabinol (THC) could produce alterations either in structural and functional brain connectivity or in their association in cannabis (CB) users. Graph theoretic structural and functional networks were generated with diffusion tensor imaging and resting-state functional imaging in 37 current CB users and 31 healthy non-users. The primary outcome measures were coupling between structural and functional connectivity, global network characteristics, association between the coupling and network properties, and measures of rich-club organization. Structural-functional (SC-FC) coupling was globally preserved showing a positive association in current CB users. However, the users had disrupted associations between SC-FC coupling and network topological characteristics, most perturbed for shorter connections implying region-specific disruption by CB use. Rich-club analysis revealed impaired SC-FC coupling in the hippocampus and caudate of users. This study provides evidence of the abnormal SC-FC association in CB users. The effect was predominant in shorter connections of the brain network, suggesting that the impact of CB use or predispositional factors may be most apparent in local interconnections. Notably, the hippocampus and caudate specifically showed aberrant structural and functional coupling. These structures have high CB1 receptor density and may also be associated with changes in learning and habit formation that occur with chronic cannabis use.

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Section: Discussionmentioning

confidence: 99%

Aberrant structural–functional coupling in adult cannabis users

Kim

Martin

Shin³

et al. 2018

Human Brain Mapping

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“…A second, larger study, the Adolescent Brain Cognitive Development (ABCD), is following over 11,000 9‐ to 10‐year‐olds for 10 years in 19 sites around the United States. Enrollment of the study began in 2016, and as of early 2018, over 11,000 participants have been enrolled, with baseline data available to researchers for 4500 participants …”

Section: The Effects Of Alcohol On Brain Developmentmentioning

confidence: 99%

The neurobiology of addiction

Uhl

Koob

Cable³

2019

Annals of the New York Academy of Sciences

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143

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Substance and alcohol use disorders impose large health and economic burdens on individuals, families, communities, and society. Neither prevention nor treatment efforts are effective in all individuals. Results are often modest. Advances in neuroscience and addiction research have helped to describe the neurobiological changes that occur when a person transitions from recreational substance use to a substance use disorder or addiction. Understanding both the drivers and consequences of substance use in vulnerable populations, including those whose brains are still maturing, has revealed behavioral and biological characteristics that can increase risks of addiction. These findings are particularly timely, as law‐ and policymakers are tasked to reverse the ongoing opioid epidemic, as more states legalize marijuana, as new products including electronic cigarettes and newly designed abused substances enter the legal and illegal markets, and as “deaths of despair” from alcohol and drug misuse continue.

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“…To better understand effects such as age differentiation and dedifferentiation, future studies will need to model age-related changes within the same individual. The complexity and expense of collecting such longitudinal data has long precluded such investigations, but new cohorts such as the ABCD sample (Volkow et al, 2018) will allow us to model longitudinal changes in the future. Secondly, since the tasks modelled here were not identical between cohorts, detailed interpretations of similarities and differences between the CALM and NKI-Rockland samples should be treated with caution.…”

Section: Limitations Of the Present Studymentioning

confidence: 99%

Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

Simpson-Kent

Fuhrmann

Bathelt

et al. 2019

Preprint

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Despite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N=551 (N=165 imaging), age range: 5-18 years, NKI-Rockland: N=337 (N=65 imaging), age range: 6-18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf)abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7-8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence.

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The conception of the ABCD study: From substance use to a broad NIH collaboration

Cited by 713 publications

References 9 publications

Aberrant structural–functional coupling in adult cannabis users

Aberrant structural–functional coupling in adult cannabis users

The neurobiology of addiction

Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

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