Faculty Bibliography

Recent years have witnessed an upsurge in the usage of resting-state functional magnetic resonance imaging (fMRI) to examine functional connectivity (fcMRI), both in normal and pathological populations. Despite this increasing popularity, concerns about the psychologically unconstrained nature of the 'resting-state' remain. Across studies, the patterns of functional connectivity detected are remarkably consistent. However, the test-retest reliability for measures of resting state fcMRI measures has not been determined. Here, we quantify the test-retest reliability, using resting scans from 26 participants at 3 different time points. Specifically, we assessed intersession (>5 months apart), intrasession (<1 h apart), and multiscan (across all 3 scans) reliability and consistency for both region-of-interest and voxel-wise analyses. For both approaches, we observed modest to high reliability across connections, dependent upon 3 predictive factors: 1) correlation significance (significantly nonzero > nonsignificant), 2) correlation valence (positive > negative), and 3) network membership (default mode > task positive network). Short- and long-term measures of the consistency of global connectivity patterns were highly robust. Finally, hierarchical clustering solutions were highly reproducible, both across participants and sessions. Our findings provide a solid foundation for continued examination of resting state fcMRI in typical and atypical populations

OBJECTIVES: To highlight recent advances in the conceptualization of attention-deficit hyperactivity disorder (ADHD) emerging from neuroimaging and endophenotypic approaches. METHODS: We selectively reviewed recent published literature on the phenomena of resting-state functional connectivity, intrasubject variability, and diffusion tensor imaging pertaining to ADHD. RESULTS: Recent advances based on the novel approach of resting-state functional connectivity appear to be highly promising and likely to link to studies of intrasubject variability. CONCLUSIONS: Endophenotypic fractionation may offer a means of addressing the complex heterogeneity of ADHD on the path to testable models of pathophysiology. Such models focusing on intrasubject variability, intrinsic brain activity, and reward-related processing are progressing rapidly

Major depressive disorder (MDD) begins frequently in adolescence and is associated with severe outcomes, but the developmental neurobiology of MDD is not well understood. Research in adults has implicated fronto-limbic neural networks in the pathophysiology of MDD, particularly in relation to the subgenual anterior cingulate cortex (ACC). Developmental changes in brain networks during adolescence highlight the need to examine MDD-related circuitry in teens separately from adults. Using resting state functional magnetic resonance imaging (fMRI), this study examined functional connectivity in adolescents with MDD (n=12) and healthy adolescents (n=14). Seed-based connectivity analysis revealed that adolescents with MDD have decreased functional connectivity in a subgenual ACC-based neural network that includes the supragenual ACC (BA 32), the right medial frontal cortex (BA 10), the left inferior (BA 47) and superior frontal cortex (BA 22), superior temporal gyrus (BA 22), and the insular cortex (BA 13). These preliminary data suggest that MDD in adolescence is associated with abnormal connectivity within neural circuits that mediate emotion processing. Future research in larger, un-medicated samples will be necessary to confirm this finding. We conclude that hypothesis-driven, seed-based analyses of resting state fMRI data hold promise for advancing our current understanding of abnormal development of neural circuitry in adolescents with MDD

OBJECTIVE: The Social Responsiveness Scale-Adult Version (SRS-A) measures autistic traits that are continuously distributed in the general population. Based on increased recognition of the dimensional nature of autistic traits, the authors examined the neural correlates of these traits in neurotypical individuals using the SRS-A and established a novel approach to assessing the neural basis of autistic characteristics, attempting to directly relate SRS-A scores to patterns of functional connectivity observed in the pregenual anterior cingulate cortex, a region commonly implicated in social cognition. METHOD: Resting state functional magnetic resonance imaging scans were collected for 25 neurotypical adults. All participants provided SRS-A ratings completed by an informant who had observed them in natural social settings. Whole brain-corrected connectivity analyses were then conducted using SRS-A scores as a covariate of interest. RESULTS: Across participants, a significant negative relationship between SRS-A scores and the functional connectivity of the pregenual anterior cingulate cortex with the anterior portion of the mid-insula was found. Specifically, low levels of autistic traits were observed when a substantial portion of the anterior mid-insula showed positive connectivity with the pregenual anterior cingulate cortex. In contrast, elevated levels of autistic traits were associated with negative connectivity between these two regions. CONCLUSIONS: Resting state functional connectivity of the pregenual anterior cingulate cortex-insula social network was related to autistic traits in neurotypical adults. Application of this approach in samples with autism spectrum disorders is needed to confirm whether this circuit is dimensionally related to the severity of autistic traits in clinical populations

Functional connectivity (FC) analyses of resting-state fMRI data allow for the mapping of large-scale functional networks, and provide a novel means of examining the impact of dopaminergic challenge. Here, using a double-blind, placebo-controlled design, we examined the effect of L-dopa, a dopamine precursor, on striatal resting-state FC in 19 healthy young adults. We examined the FC of 6 striatal regions of interest (ROIs) previously shown to elicit networks known to be associated with motivational, cognitive and motor subdivisions of the caudate and putamen (Di Martino et al., 2008). In addition to replicating the previously demonstrated patterns of striatal FC, we observed robust effects of L-dopa. Specifically, L-dopa increased FC in motor pathways connecting the putamen ROIs with the cerebellum and brainstem. Although L-dopa also increased FC between the inferior ventral striatum and ventrolateral prefrontal cortex, it disrupted ventral striatal and dorsal caudate FC with the default mode network. These alterations in FC are consistent with studies that have demonstrated dopaminergic modulation of cognitive and motor striatal networks in healthy participants. Recent studies have demonstrated altered resting state FC in several conditions believed to be characterized by abnormal dopaminergic neurotransmission. Our findings suggest that the application of similar experimental pharmacological manipulations in such populations may further our understanding of the role of dopaminergic neurotransmission in those conditions

The neural nicotinic acetylcholine receptor alpha4 subunit (CHRNA4), at 20q13.2-q13.3, is an important candidate gene for conferring susceptibility to attention deficit/hyperactivity disorder (ADHD). Several studies have already looked for association/linkage between ADHD and CHRNA4 in different populations. We used the Pedigree Disequilibrium Test to search for evidence of association between ADHD and six SNP marker loci in families from the isolated Paisa population. We found that the T allele of SNP rs6090384 exhibits a deficit of transmission in unaffected individuals (OR = 5.43, IC 1.54-19.13) (global P value = 0.014). We also found significant association and linkage to extended haplotypes rs2273502-rs6090384 (combination of variants C-T, respectively) (P = 0.02) and rs6090384-rs6090387 (P = 0.04) (combination of variants T-G, respectively). SNP rs6090384, variant T, has also been reported to be associated with inattention in a previous study. This makes ours the ninth study to examine the association of CHRNA4 with ADHD and the seventh one to find evidence for association in a population with a different ethnicity.

The amygdala is composed of structurally and functionally distinct nuclei that contribute to the processing of emotion through interactions with other subcortical and cortical structures. While these circuits have been studied extensively in animals, human neuroimaging investigations of amygdala-based networks have typically considered the amygdala as a single structure, which likely masks contributions of individual amygdala subdivisions. The present study uses resting state functional magnetic resonance imaging (fMRI) to test whether distinct functional connectivity patterns, like those observed in animal studies, can be detected across three amygdala subdivisions: laterobasal, centromedial, and superficial. In a sample of 65 healthy adults, voxelwise regression analyses demonstrated positively-predicted ventral and negatively-predicted dorsal networks associated with the total amygdala, consistent with previous animal and human studies. Investigation of individual amygdala subdivisions revealed distinct differences in connectivity patterns within the amygdala and throughout the brain. Spontaneous activity in the laterobasal subdivision predicted activity in temporal and frontal regions, while activity in the centromedial nuclei predicted activity primarily in striatum. Activity in the superficial subdivision positively predicted activity throughout the limbic lobe. These findings suggest that resting state fMRI can be used to investigate human amygdala networks at a greater level of detail than previously appreciated, allowing for the further advancement of translational models.

Human cerebral development is remarkably protracted. Although microstructural processes of neuronal maturation remain accessible only to morphometric post-mortem studies, neuroimaging tools permit the examination of macrostructural aspects of brain development. The analysis of resting-state functional connectivity (FC) offers novel possibilities for the investigation of cerebral development. Using seed-based FC methods, we examined the development of 5 functionally distinct cingulate-based intrinsic connectivity networks (ICNs) in children (n = 14, 10.6 +/- 1.5 years), adolescents (n = 12, 15.4 +/- 1.2) and young adults (n=14, 22.4 +/- 1.2). Children demonstrated a more diffuse pattern of correlation with voxels proximal to the seed region of interest (ROI) ('local FC'), whereas adults exhibited more focal patterns of FC, as well as a greater number of significantly correlated voxels at long distances from the seed ROI. Adolescents exhibited intermediate patterns of FC. Consistent with evidence for different maturational time courses, ICNs associated with social and emotional functions exhibited the greatest developmental effects. Our findings demonstrate the utility of FC for the study of developing functional organization. Moreover, given that ICNs are thought to have an anatomical basis in neuronal connectivity, measures of FC may provide a quantitative index of brain maturation in healthy subjects and those with neurodevelopmental disorders

The default mode network (DMN), based in ventromedial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC), exhibits higher metabolic activity at rest than during performance of externally oriented cognitive tasks. Recent studies have suggested that competitive relationships between the DMN and various task-positive networks involved in task performance are intrinsically represented in the brain in the form of strong negative correlations (anticorrelations) between spontaneous fluctuations in these networks. Most neuroimaging studies characterize the DMN as a homogenous network, thus few have examined the differential contributions of DMN components to such competitive relationships. Here, we examined functional differentiation within the DMN, with an emphasis on understanding competitive relationships between this and other networks. We used a seed correlation approach on resting-state data to assess differences in functional connectivity between these two regions and their anticorrelated networks. While the positively correlated networks for the vmPFC and PCC seeds largely overlapped, the anticorrelated networks for each showed striking differences. Activity in vmPFC negatively predicted activity in parietal visual spatial and temporal attention networks, whereas activity in PCC negatively predicted activity in prefrontal-based motor control circuits. Granger causality analyses suggest that vmPFC and PCC exert greater influence on their anticorrelated networks than the other way around, suggesting that these two default mode nodes may directly modulate activity in task-positive networks. Thus, the two major nodes comprising the DMN are differentiated with respect to the specific brain systems with which they interact, suggesting greater heterogeneity within this network than is commonly appreciated.