Latent state-trait structure of cerebral blood flow in a resting state

Cerebellum Anatomy Predicts Individual Risk-taking Behavior and Risk Tolerance

Human risk tolerance is highly idiosyncratic and individuals often show distinctive preferences when faced with similar risky situations. However, the neural underpinnings of individual differences in risk-taking remain unclear. Here we combined structural and perfusion MRI and examined the associations between brain anatomy and individual risk-taking behavior/risk tolerance in a sample of 115 healthy participants during the Balloon Analogue Risk Task, a well-established sequential risky decision paradigm. Both whole brain and region-of-interest analyses showed that the left cerebellum gray matter volume (GMV) has a strong association with individual risk-taking behavior and risk tolerance, outperforming the previously reported associations with the amygdala and right posterior parietal cortex (PPC) GMV. Left cerebellum GMV also accounted for risk tolerance and risk-taking behavior changes with aging. However, regional cerebral blood flow (CBF) provided no additional predictive power. These findings suggest a novel cerebellar anatomical contribution to individual differences in risk tolerance. Further studies are necessary to elucidate the underestimated important role of cerebellum in risk-taking.

Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain

Neuromelanin-sensitive MRI (NM-MRI) purports to detect the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). Interindividual variability in dopamine function may result in varying levels of NM accumulation in the SN; however, the ability of NM-MRI to measure dopamine function in nonneurodegenerative conditions has not been established. Here, we validated that NM-MRI signal intensity in postmortem midbrain specimens correlated with regional NM concentration even in the absence of neurodegeneration, a prerequisite for its use as a proxy for dopamine function. We then validated a voxelwise NM-MRI approach with sufficient anatomical sensitivity to resolve SN subregions. Using this approach and a multimodal dataset of molecular PET and fMRI data, we further showed the NM-MRI signal was related to both dopamine release in the dorsal striatum and resting blood flow within the SN. These results suggest that NM-MRI signal in the SN is a proxy for function of dopamine neurons in the nigrostriatal pathway. As a proof of concept for its clinical utility, we show that the NM-MRI signal correlated to severity of psychosis in schizophrenia and individuals at risk for schizophrenia, consistent with the well-established dysfunction of the nigrostriatal pathway in psychosis. Our results indicate that noninvasive NM-MRI is a promising tool that could have diverse research and clinical applications to investigate in vivo the role of dopamine in neuropsychiatric illness.

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI

Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition.

A latent state-trait analysis of interoceptive accuracy

Interoceptive accuracy (IAc), that is, the ability to accurately perceive one's own bodily signals, is widely assumed to be a trait, although experimental manipulations such as stress may affect IAc. We used structural equation modeling to estimate the reliability of IAc, and the proportions of individual differences in IAc, explained by a trait and occasion-specific effects of situation and person-situation interactions. We assessed IAc in 59 healthy participants (40 women, M_Age  = 23.4 years) on three consecutive measurement occasions, approximately 1 week apart, in a rest and poststress condition, using a heartbeat counting and a heartbeat discrimination task. The results showed fair temporal stability (intraclass correlation coefficients ≥ 0.38) and good reliability (Mdn = .63; range .49-.83) for both methods. While around 40% of the variance of a single IAc measurement could be explained by a trait, approximately 27% was accounted for by occasion-specific effects of situation and person-situation interaction. These results suggest that IAc measures are relatively consistent and that situations and person-situation interactions impact IAc as measured at a certain point in time. An aggregation across at least two measurements is recommended when using IAc as a trait variable.

Post-conventional moral reasoning is associated with increased ventral striatal activity at rest and during task

People vary considerably in moral reasoning. According to Kohlberg’s theory, individuals who reach the highest level of post-conventional moral reasoning judge moral issues based on deeper principles and shared ideals rather than self-interest or adherence to laws and rules. Recent research has suggested the involvement of the brain’s frontostriatal reward system in moral judgments and prosocial behaviors. However, it remains unknown whether moral reasoning level is associated with differences in reward system function. Here, we combined arterial spin labeling perfusion and blood oxygen level-dependent functional magnetic resonance imaging and measured frontostriatal reward system activity both at rest and during a sequential risky decision making task in a sample of 64 participants at different levels of moral reasoning. Compared to individuals at the pre-conventional and conventional level of moral reasoning, post-conventional individuals showed increased resting cerebral blood flow in the ventral striatum and ventromedial prefrontal cortex. Cerebral blood flow in these brain regions correlated with the degree of post-conventional thinking across groups. Post-conventional individuals also showed greater task-induced activation in the ventral striatum during risky decision making. These findings suggest that high-level post-conventional moral reasoning is associated with increased activity in the brain’s frontostriatal system, regardless of task-dependent or task-independent states.

Distinguishing state variability from trait change in longitudinal data: the role of measurement (non)invariance in latent state-trait analyses

Researchers analyzing longitudinal data often want to find out whether the process they study is characterized by (1) short-term state variability, (2) long-term trait change, or (3) a combination of state variability and trait change. Classical latent state-trait (LST) models are designed to measure reversible state variability around a fixed set-point or trait, whereas latent growth curve (LGC) models focus on long-lasting and often irreversible trait changes. In the present article, we contrast LST and LGC models from the perspective of measurement invariance testing. We show that establishing a pure state-variability process requires (1) the inclusion of a mean structure and (2) establishing strong factorial invariance in LST analyses. Analytical derivations and simulations demonstrate that LST models with noninvariant parameters can mask the fact that a trait-change or hybrid process has generated the data. Furthermore, the inappropriate application of LST models to trait change or hybrid data can lead to bias in the estimates of consistency and occasion specificity, which are typically of key interest in LST analyses. Four tips for the proper application of LST models are provided.

Tune it down to live it up? Rapid, nongenomic effects of cortisol on the human brain

The stress hormone cortisol acts on the brain, supporting adaptation and time-adjusted coping processes. Whereas previous research has focused on slow emerging, genomic effects of cortisol, we addressed the rapid, nongenomic cortisol effects on in vivo neuronal activity in humans. Three independent placebo-controlled studies in healthy men were conducted. We observed changes in CNS activity within 15 min after intravenous administration of a physiological dose of 4 mg of cortisol (hydrocortisone). Two of the studies demonstrated a rapid bilateral thalamic perfusion decrement using continuous arterial spin labeling. The third study revealed rapid, cortisol-induced changes in global signal strength and map dissimilarity of the electroencephalogram. Our data demonstrate that a physiological concentration of cortisol profoundly affects the functioning and perfusion of the human brain in vivo via a rapid, nongenomic mechanism. The changes in neuronal functioning suggest that cortisol acts on the thalamic relay of background as well as on task-specific sensory information, allowing focus and facilitation of adaptation to challenges.

A comparison of four approaches to account for method effects in latent state-trait analyses

Latent state-trait (LST) analysis is frequently applied in psychological research to determine the degree to which observed scores reflect stable person-specific effects, effects of situations and/or person-situation interactions, and random measurement error. Most LST applications use multiple repeatedly measured observed variables as indicators of latent trait and latent state residual factors. In practice, such indicators often show shared indicator-specific (or method) variance over time. In this article, the authors compare 4 approaches to account for such method effects in LST models and discuss the strengths and weaknesses of each approach based on theoretical considerations, simulations, and applications to actual data sets. The simulation study revealed that the LST model with indicator-specific traits (Eid, 1996) and the LST model with M - 1 correlated method factors (Eid, Schneider, & Schwenkmezger, 1999) performed well, whereas the model with M orthogonal method factors used in the early work of Steyer, Ferring, and Schmitt (1992) and the correlated uniqueness approach (Kenny, 1976) showed limitations under conditions of either low or high method-specificity. Recommendations for the choice of an appropriate model are provided.

Applications of arterial spin labeled MRI in the brain

Perfusion provides oxygen and nutrients to tissues and is closely tied to tissue function while disorders of perfusion are major sources of medical morbidity and mortality. It has been almost two decades since the use of arterial spin labeling (ASL) for noninvasive perfusion imaging was first reported. While initial ASL magnetic resonance imaging (MRI) studies focused primarily on technological development and validation, a number of robust ASL implementations have emerged, and ASL MRI is now also available commercially on several platforms. As a result, basic science and clinical applications of ASL MRI have begun to proliferate. Although ASL MRI can be carried out in any organ, most studies to date have focused on the brain. This review covers selected research and clinical applications of ASL MRI in the brain to illustrate its potential in both neuroscience research and clinical care.

Serotonin transporter genotype modulates the association between depressive symptoms and amygdala activity among psychiatrically healthy adults

Recent attempts to understand the biological bases of depression vulnerability have revealed that both the short allele of the serotonin transporter-linked polymorphic region (5-HTTLPR) and activity in the amygdala are associated with depression. Other studies have reported amygdala hyperactivity associated with the 5-HTTLPR short allele, linking the genetic and neuroimaging lines of research and suggesting a mechanism whereby the short allele confers depression risk. However, fewer investigations have examined the associations among depression, 5-HTTLPR variability, and amygdala activation in a single study. The current study thus investigated whether 5-HTTLPR genotype modulates the association between depressive symptoms and amygdala activity among psychiatrically healthy adults. Regional cerebral blood flow was measured with perfusion fMRI during a task-free scan. We hypothesized differential associations between depressive symptoms and amygdala activity among individuals homozygous for the short allele and individuals homozygous for the long allele. Both whole brain analyses and region-of-interest analyses confirmed this prediction, revealing a significant negative association among the long allele group and a trend of positive association among the short allele group. These results complement existing reports of short allele related amygdala hyperactivity and suggest an additional neurobiological mechanism whereby the 5-HTTLPR is associated with psychiatric outcomes.

Resting cerebral blood flow, attention, and aging

Aging is accompanied by a decline of fluid cognitive functions, e.g., a slowing of information processing, working memory, and division of attention. This is at least partly due to structural and functional changes in the aging brain. Although a decrement of resting cerebral blood flow (CBF) has been positively associated with cognitive functions in patients with brain diseases, studies with healthy participants have revealed inconsistent results. Therefore, we investigated the relation between resting cerebral blood flow and cognitive functions (tonic and phasic alertness, selective and divided attention) in two samples of healthy young and older participants. We found higher resting CBF and better cognitive performances in the young than in the older sample. In addition, resting CBF was inversely correlated with selective attention in the young and with tonic alertness in the elderly participants. This finding is discussed with regard to the neural efficiency hypothesis of human intelligence.