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 amygdalabased 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.The central role of the amygdala in processing emotions and mediating fear responses is well established (LeDoux, 2000). Tucked away in the medial temporal lobe and comparatively small in size, the human amygdala is not easily studied in vivo. Further, the amygdala is not a single structure, but a complex of structurally and functionally heterogeneous nuclei which have been examined extensively in rodents and non-human primates, but not in humans. In recent years, advances have also been made in the study of the amygdaloid complex in humans. For example, using cytoarchitectonic mapping methods similar to those used in animal studies, Amunts et al. (2005) delineated probabilistic maps of amygdala subregions. Neuroimaging studies haveCorresponding Author: Amy Krain Roy, Ph.D., NYU Child Study Center, 215 Lexington Avenue, 13 th Floor, New York, N.Y. 10016, Phone: (212) 263-2790, Fax: (212) 263-3691, amy.roy@nyumc.org. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Aut...

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.

Background Models of cocaine addiction emphasize the role of disrupted frontal circuitry supporting cognitive control processes. Yet, addiction-related alterations in functional interactions among brain regions, especially between the cerebral hemispheres, are rarely examined directly. Resting state fMRI approaches, which reveal patterns of coherent spontaneous fluctuations in the fMRI signal, offer a means to directly quantify functional interactions between the hemispheres. We examined interhemispheric resting state functional connectivity (RSFC) in cocaine dependence using a recently validated approach named “voxel-mirrored homotopic connectivity.” Methods We compared interhemispheric RSFC between 25 adults (aged 35.0±8.8) meeting DSM-IV criteria for cocaine dependence within the past 12 months, but currently abstaining (>2 weeks) from cocaine, and 24 healthy comparisons (35.1±7.5), group-matched on age, sex, education and employment status. Results We observed reduced prefrontal interhemispheric RSFC in cocaine dependent participants relative to controls. Further analyses demonstrated a striking cocaine-dependence-related reduction in interhemispheric RSFC among nodes of the dorsal attention network (DAN), comprising bilateral lateral frontal, medial premotor and posterior parietal areas. Further, within the cocaine-dependent group, RSFC within the DAN was associated with self-reported lapses of attention. Conclusions Our findings provide further evidence of an association between chronic exposure to cocaine and disruptions within large-scale brain circuitry supporting cognitive control. We did not detect group differences in DTI measures, suggesting that alterations in the brain’s functional architecture associated with cocaine exposure can be observed in the absence of detectable abnormalities in the white matter microstructure supporting that architecture.

Objective-Based on the increased recognition of the dimensional nature of autistic traits, we examined their neural correlates in neurotypical individuals using the Social Responsiveness Scale-Adult version (SRS-A). The SRS-A measures autistic traits that are continuously distributed in the general population. Here, we establish a novel approach to examining the neural basis of autistic traits, attempting to directly relate SRS-A scores to patterns of functional connectivity observed for the pregenual anterior cingulate cortex (pgACC), a region commonly implicated in social cognition.Methods-Resting state fMRI scans were collected in 25 neurotypical individuals (26.4 ± 5.6 y) who provided SRS-A completed by an informant who knew the participant in natural social settings. Whole brain corrected connectivity analyses were then conducted using the SRS-A as a covariate of interest.Results-We found a significant negative relationship between SRS-A and pgACC functional connectivity with the anterior portion of mid-insula (Z > 2.3; p < .05, corrected). Specifically, low levels of autistic traits were observed when a substantial portion of the anterior mid-insula showed positive connectivity with pgACC. In contrast, elevated levels of autistic traits were associated with negative connectivity between the pgACC and the anterior mid-insula.Conclusions-Resting state functional connectivity of the pgACC-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 the pgACC-anterior mid insula circuit is dimensionally related to the severity of autistic traits in clinical populations.

Intolerance of Uncertainty (IU) has contributed to our understanding of excessive worry and adult anxiety disorders, but there is a paucity of research on IU in child samples. This gap is due to the absence of a psychometrically sound measure of IU in youth. The present study adapted parallel child- and parent-report forms of the Intolerance of Uncertainty Scale (IUS) and examined the internal consistency, convergent validity, and classification properties of these forms in youth aged 7–17 (M = 11.6 years, SD = 2.6). Participating youth (N = 197; 100 females) either met diagnostic criteria for an anxiety disorder (N = 73) or were non-referred community participants (N = 124). The child-report form (i.e., IUS for Children, or IUSC), and to a lesser extent the parent-report form, demonstrated strong internal consistency and convergent validity, evidenced by significant associations with anxiety and worry (and reassurance-seeking in the case of the child-report form). Children diagnosed with anxiety disorders scored higher than non-referred community youth on both forms. ROC analysis demonstrated acceptable overall utility in distinguishing the two groups of youth. Findings provide preliminary support for use of the IUSC for continuous measurement of children’s ability to tolerate uncertainty.

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BackgroundResearch on the neural correlates of risk-related behaviors and personality traits has provided insight into mechanisms underlying both normal and pathological decision-making. Task-based neuroimaging studies implicate a distributed network of brain regions in risky decision-making. What remains to be understood are the interactions between these regions and their relation to individual differences in personality variables associated with real-world risk-taking.Methodology/Principal FindingsWe employed resting state functional magnetic resonance imaging (R-fMRI) and resting state functional connectivity (RSFC) methods to investigate differences in the brain's intrinsic functional architecture associated with beliefs about the consequences of risky behavior. We obtained an individual measure of expected benefit from engaging in risky behavior, indicating a risk seeking or risk-averse personality, for each of 21 participants from whom we also collected a series of R-fMRI scans. The expected benefit scores were entered in statistical models assessing the RSFC of brain regions consistently implicated in both the evaluation of risk and reward, and cognitive control (i.e., orbitofrontal cortex, nucleus accumbens, lateral prefrontal cortex, dorsal anterior cingulate). We specifically focused on significant brain-behavior relationships that were stable across R-fMRI scans collected one year apart. Two stable expected benefit-RSFC relationships were observed: decreased expected benefit (increased risk-aversion) was associated with 1) stronger positive functional connectivity between right inferior frontal gyrus (IFG) and right insula, and 2) weaker negative functional connectivity between left nucleus accumbens and right parieto-occipital cortex.Conclusions/SignificanceTask-based activation in the IFG and insula has been associated with risk-aversion, while activation in the nucleus accumbens and parietal cortex has been associated with both risk seeking and risk-averse tendencies. Our results suggest that individual differences in attitudes toward risk-taking are reflected in the brain's functional architecture and may have implications for engaging in real-world risky behaviors.

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