Viscoelasticity of reward and control systems in adolescent risk taking

McIlvain, Grace; Clements, Rebecca G; Spielberg, Jeffrey M.; Telzer, Eva H.; Johnson, Curtis L.

doi:10.1016/j.neuroimage.2020.116850

Cited by 14 publications

(16 citation statements)

References 67 publications

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“…This work represents the first detailed investigation of the mechanical properties of parcellations of the cerebral cortex, though initial MRE investigations into cortical structure-function relationships Schwarb et al, 2019), contributions to adolescent risk-taking behavior (McIlvain et al, 2020), and the mechanical integrity of the cortex in Alzheimer's disease (Hiscox, Johnson, McGarry, Marshall, et al, 2020) This MRE study is the first to report significant sex differences in viscoelasticity in a wide range of neuroanatomical structures which supplements the wealth of existing data that reports sex differences in neuroanatomy. Interestingly, we found that female brains are approximately 4% more viscous compared to males as indicated by significantly higher ξ in global WM, which contradicts an early study that reported female brains were 9% less viscous in large regions primarily comprising white matter (Sack, Streitberger, Krefting, Paul, & Braun, 2011).…”

Section: Discussionmentioning

confidence: 73%

“…This work represents the first detailed investigation of the mechanical properties of parcellations of the cerebral cortex, though initial MRE investigations into cortical structure–function relationships (Johnson et al, 2018; Schwarb et al, 2019), contributions to adolescent risk‐taking behavior (McIlvain et al, 2020), and the mechanical integrity of the cortex in Alzheimer's disease (Hiscox, Johnson, McGarry, Marshall, et al, 2020) have been reported. We show that separate regions of the cortex exhibit different viscoelastic properties and, remarkably in some cases, observe distinct viscoelastic properties which do not overlap in the range of values across participants.…”

Section: Discussionmentioning

confidence: 98%

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Standard‐space atlas of the viscoelastic properties of the human brain

Hiscox

McGarry

Schwarb

et al. 2020

Human Brain Mapping

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Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast-based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18-35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM-152. We find that average MRE brain templates contain emerging and

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Section: Discussionmentioning

confidence: 73%

“…This work represents the first detailed investigation of the mechanical properties of parcellations of the cerebral cortex, though initial MRE investigations into cortical structure–function relationships (Johnson et al, 2018; Schwarb et al, 2019), contributions to adolescent risk‐taking behavior (McIlvain et al, 2020), and the mechanical integrity of the cortex in Alzheimer's disease (Hiscox, Johnson, McGarry, Marshall, et al, 2020) have been reported. We show that separate regions of the cortex exhibit different viscoelastic properties and, remarkably in some cases, observe distinct viscoelastic properties which do not overlap in the range of values across participants.…”

Section: Discussionmentioning

confidence: 98%

Standard‐space atlas of the viscoelastic properties of the human brain

Hiscox

McGarry

Schwarb

et al. 2020

Human Brain Mapping

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“…Consistent evidence has also been observed in lab contexts, where experimental manipulations of the value-based system have been shown to interfere with cognitive control performance, especially in adolescents (21). By contrast, neuroscientific evidence for these theories has been far less consistent (25)(26)(27)(28)(29)(30). These inconsistencies have prompted some to advocate for updating simple system-based models with circuit-based (2) or whole-brain network accounts of adolescent neurodevelopment (31).…”

Section: Introductionmentioning

confidence: 94%

“…Another potential limitation of prior neurodevelopmental studies of risky decisionmaking is that most have focused on between-subject differences in risk taking behavior, rather than within-individual differences (22,23,(25)(26)(27)(28)36). However, most prior work has examined between-subject dynamics and the role of external factors in shaping behavior (e.g., peer or adult present during decision-making; affective versus neutral stimuli (37,38)).…”

Section: Introductionmentioning

confidence: 99%

Revisiting the Neural Architecture of Adolescent Decision-Making: Univariate and Multivariate Evidence for System-Based Models

Moreira¹,

Leal²,

Waizman³

et al. 2020

Preprint

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System-based theories are a popular approach to explaining the psychology of human decision making. Such theories posit that decision-making is governed by interactions between different psychological processes that arbitrate amongst each other for control over behavior. To date, system-based theories have received inconsistent support at the neural level, leading some to question their veracity. Here we examine the possibility that prior attempts to evaluate system-based theories have been limited by their reliance on predicting brain activity from behavior, and seek to advance evaluations of system-based models through modeling approaches that predict behavior from brain activity. Using within-subject decision-level modeling of fMRI data from a risk-taking task in a sample of over 2000 decisions across 51 adolescents—a population in which decision-making processes are particularly dynamic and consequential—we find support for system-based theories of decision-making. In particular, neural activity in lateral prefrontal cortex and a multivariate pattern of cognitive control both predicted a reduced likelihood of making a risky decision, whereas increased activity in the ventral striatum—a region typically associated with valuation processes—predicted a greater likelihood of engaging in risk-taking. These results comprise the first formalized within-subjects neuroimaging test of system-based theories, garnering support for the notion that competing systems drive decision behaviors.Significance StatementDecision making is central to adaptive behavior. While dominant psychological theories of decision-making behavior have found empirical support, their neuroscientific implementations have received inconsistent support. This may in part be due to statistical approaches employed by prior neuroimaging studies of system-based theories. Here we use brain modeling—an approach that predicts behavior from brain activity—of univariate and multivariate neural activity metrics to better understand how neural components of psychological systems guide decision behavior. We found broad support for system-based theories such that that neural systems involved in cognitive control predicted a reduced likelihood to make risky decisions, whereas value-based systems predicted greater risk-taking propensity.

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“…Light fitness exercise has also been shown to have a potential impact on hippocampal viscoelasticity and associated cerebral functions in multi-sclerosis patients [287]. These investigations laid the first stone for the characterisation of relationships between physical and cerebral functional behaviors, and brain viscoelasticity [288][289][290][291].…”

Section: Brainmentioning

confidence: 99%

Viscoelasticity Imaging of Biological Tissues and Single Cells Using Shear Wave Propagation

Flé

Bhatt

et al. 2021

Front. Phys.

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Changes in biomechanical properties of biological soft tissues are often associated with physiological dysfunctions. Since biological soft tissues are hydrated, viscoelasticity is likely suitable to represent its solid-like behavior using elasticity and fluid-like behavior using viscosity. Shear wave elastography is a non-invasive imaging technology invented for clinical applications that has shown promise to characterize various tissue viscoelasticity. It is based on measuring and analyzing velocities and attenuations of propagated shear waves. In this review, principles and technical developments of shear wave elastography for viscoelasticity characterization from organ to cellular levels are presented, and different imaging modalities used to track shear wave propagation are described. At a macroscopic scale, techniques for inducing shear waves using an external mechanical vibration, an acoustic radiation pressure or a Lorentz force are reviewed along with imaging approaches proposed to track shear wave propagation, namely ultrasound, magnetic resonance, optical, and photoacoustic means. Then, approaches for theoretical modeling and tracking of shear waves are detailed. Following it, some examples of applications to characterize the viscoelasticity of various organs are given. At a microscopic scale, a novel cellular shear wave elastography method using an external vibration and optical microscopy is illustrated. Finally, current limitations and future directions in shear wave elastography are presented.

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Viscoelasticity of reward and control systems in adolescent risk taking

Cited by 14 publications

References 67 publications

Standard‐space atlas of the viscoelastic properties of the human brain

Standard‐space atlas of the viscoelastic properties of the human brain

Revisiting the Neural Architecture of Adolescent Decision-Making: Univariate and Multivariate Evidence for System-Based Models

Viscoelasticity Imaging of Biological Tissues and Single Cells Using Shear Wave Propagation

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