Faculty Bibliography

OBJECTIVE:Compelling evidence indicates that disruption in functional connectivity (FC) in brain networks underlies many psychiatric and developmental disorders. Current theory posits that biological (i.e., cortisol) and environmental (i.e., stress) experiences in early life are strong determinants in the development of functional brain systems and formative in the genesis of such disorders. The objective of this study was to examine the extent to which individual differences in cortisol concentrations during FC magnetic resonance imaging (MRI) would map onto variability in hippocampal to default mode network (DMN) connectivity in typically developing youth. METHOD/METHODS:Salivary cortisol and FC MRI data were collected concurrently in 33 scan-naive 7- to 15-year-old participants. Twenty-nine of these participants previously completed the Trier Social Stress Test. Hippocampal to DMN FC and endogenous cortisol variability during MRI were examined. A possible association between MRI cortisol and cortisol response to the Trier Social Stress Test during the preceding visit or a participant's ratings of anxiety during MRI was tested. RESULTS:There were significant positive relations between MRI cortisol levels and measurements in the following 3 areas: hippocampal to DMN FC during the resting state, cortisol levels during the Trier Social Stress Test, and fear/anxiety ratings during MRI. Fear/anxiety ratings during MRI also related to self-reported anxiety on standardized measurements. CONCLUSIONS:This study shows for the first time that FC of the hippocampus is altered with changing cortisol responsivity in youth. Altered FC during the resting state may represent altered alertness or monitoring resulting from variation in glucocorticoid function in youth, which carries implications for the effect of stress on response monitoring and decision making.

Effective navigation of the social world relies on the correct interpretation of facial emotions. This may be particularly important in formative years. Critically, literature examining the emergence of face processing in youth (children and adolescents) has focused on the neural and behavioral correlates of processing adult faces, which are relationally different from youth participants, and whose facial expressions may convey different meaning than faces of their peers. During a functional magnetic resonance imaging (fMRI) scan, we compared concurrent neural and behavioral responses as youth (N=25) viewed validated, emotionally varied (i.e., anger, fear, happy, and neutral) adult and child face stimuli. We observed that participants made fewer errors when matching adult, compared to child, face stimuli, and that while similar brain regions were involved in processing both adult and child faces, activation in the face processing neural network was greater for adult than child faces. This was true across emotions, and also when comparing neutral adult versus neutral child faces. Additionally, a valence by stimuli-type effect was observed within the amygdala. That is, within adult face stimuli, negative and neutral face stimuli elicited the largest effects, whereas within child face stimuli, happy face stimuli elicited the largest amygdala effects. Thus, heightened engagement of the amygdala was observed for happy child and angry adult faces, which may reflect age-specific salience of select emotions in early life. This study provides evidence that the relational age of the perceived face influences neural processing in youth.

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain-behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective--population neuroscience--that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.

Resting-state MRI (rs-fMRI) is a powerful procedure for studying whole-brain neural connectivity. In this study we provide the first empirical evidence of the longitudinal reliability of rs-fMRI in children. We compared rest-retest measurements across spatial, temporal and frequency domains for each of six cognitive and sensorimotor intrinsic connectivity networks (ICNs) both within and between scan sessions. Using Kendall'sW, concordance of spatial maps ranged from .60 to .86 across networks, for various derived measures. The Pearson correlation coefficient for temporal coherence between networks across all Time 1-Time 2 (T1/T2) z-converted measures was .66 (p<.001). There were no differences between T1/T2 measurements in low-frequency power of the ICNs. For the visual network, within-session T1 correlated with the T2 low-frequency power, across participants. These measures from resting-state data in children were consistent across multiple domains (spatial, temporal, and frequency). Resting-state connectivity is therefore a reliable method for assessing large-scale brain networks in children.

The functional significance of the brain's white matter was not fully appreciated until new imaging methods were developed to visualize fiber pathways and connections in the living brain. Rapid advances in diffusion tensor imaging (DTI) have led to substantial insights into human brain development and disease processes and have thrust white matter into the focus of researchers and clinicians alike. The full clinical potential of this relatively new technique remains to be determined, but early indicators suggest that DTI will be a significant new technology in mapping mechanisms of human health and disease. Here we review brain changes that have been studied with DTI over the human lifespan and findings in a variety of neuropsychiatric disorders. We also suggest future areas where DTI is likely to have significant impact.

BACKGROUND:Major depressive disorder (MDD) has been associated reliably with ruminative responding; this kind of responding is composed of both maladaptive and adaptive components. Levels of activity in the default-mode network (DMN) relative to the task-positive network (TPN), as well as activity in structures that influence DMN and TPN functioning, may represent important neural substrates of maladaptive and adaptive rumination in MDD. METHODS:We used a unique metric to estimate DMN dominance over TPN from blood oxygenation level-dependent data collected during eyes-closed rest in 17 currently depressed and 17 never-disordered adults. We calculated correlations between this metric of DMN dominance over TPN and the depressive, brooding, and reflective subscales of the Ruminative Responses Scale, correcting for associations between these measures both with one another and with severity of depression. Finally, we estimated and compared across groups right fronto-insular cortex (RFIC) response during initiations of ascent in DMN and in TPN activity. RESULTS:In the MDD participants, increasing levels of DMN dominance were associated with higher levels of maladaptive, depressive rumination and lower levels of adaptive, reflective rumination. Moreover, our RFIC state-change analysis showed increased RFIC activation in the MDD participants at the onset of increases in TPN activity; conversely, healthy control participants exhibited increased RFIC response at the onset of increases in DMN activity. CONCLUSIONS:These findings support a formulation in which the DMN undergirds representation of negative, self-referential information in depression, and the RFIC, when prompted by increased levels of DMN activity, initiates an adaptive engagement of the TPN.

BACKGROUND:Responses to stress vary greatly in young adolescents, and little is known about neural correlates of the stress response in youth. The purpose of this study was to examine whether variability in cortisol responsivity following a social stress test in young adolescents is associated with altered neural functional connectivity (FC) of the salience network (SN) measured during resting-state functional magnetic resonance imaging (rs-fMRI). METHODS:Forty-nine typically developing young adolescents participated in a social stress test during which they contributed salivary cortisol samples. Following this, they underwent rs-fMRI scanning. We examined the association of FC of the SN [composed of anterior cingulate cortex and bilateral anterior insula regions] with cortisol responsivity. RESULTS:Greater cortisol responsivity was significantly positively correlated with higher FC between subgenual anterior cingulate cortex (Cg25) and the SN, controlling for participant age. There were no regions of the brain that showed an inverse relation. CONCLUSIONS:Brain systems that have been implicated in autonomic arousal and that influence subjective feeling states show altered FC associated with stress responsivity in early life.

Vector autoregression (VAR) and structural equation modeling (SEM) are two popular brain-network modeling tools. VAR, which is a data-driven approach, assumes that connected regions exert time-lagged influences on one another. In contrast, the hypothesis-driven SEM is used to validate an existing connectivity model where connected regions have contemporaneous interactions among them. We present the two models in detail and discuss their applicability to FMRI data, and their interpretational limits. We also propose a unified approach that models both lagged and contemporaneous effects. The unifying model, structural vector autoregression (SVAR), may improve statistical and explanatory power, and avoid some prevalent pitfalls that can occur when VAR and SEM are utilized separately.

Research on resting-state functional connectivity reveals intrinsically connected networks in the brain that are largely consistent across the general population. However, there are individual differences in these networks that have not been elucidated. Here, we measured the influence of naturally occurring mood on functional connectivity. In particular, we examined the association between self-reported levels of anxiety and connectivity in the default mode network (DMN). Healthy youth (n=43; ages 10-18) and adult participants (n=24, ages 19-59) completed a 6-min resting-state functional magnetic resonance imaging scan, then immediately completed questionnaires assessing their mood and thoughts during the scan. Regression analyses conducted separately for the youth and adult samples revealed brain regions in which increases in connectivity differentially corresponded to higher anxiety in each group. In one area, the left insular cortex, both groups showed similar increased connectivity to the DMN (youth: -30, 26, 14; adults: -33, 12, 14) with increased anxiety. State anxiety assessed during scanning was not correlated with trait anxiety, so our results likely reflect state levels of anxiety. To our knowledge, this is the first study to relate naturally occurring mood to resting state connectivity.

Magnetic resonance imaging (MRI) has been used to image the in utero fetus for the past 3 decades. Although not as commonplace as other patient-oriented MRI, it is a growing field and demonstrating a role in the clinical care of the fetus. Indeed, the body of literature involving fetal MRI exceeds 3000 published articles. Indeed, there is interest in accessing even the healthy fetus with MRI to further understand the development of humans during the fetal stage. On the horizon is fetal imaging using 3.0-T clinical systems. Although a clear path is not necessarily determined, experiments, theoretical calculations, advances in pulse sequence design, new hardware, and experience from imaging at 1.5 T help define the path.