Faculty Bibliography

Background and Objectives: Maltreatment from the caregiver induces vulnerability to later life psychopathology. Animal models of early life stress suggest this is due to disruption of neural development of long-distance circuits linking amygdala to prefrontal cortex. Methods: We used a rat model of early life maltreatment to examine amygdala connectivity using resting-state functional magnetic resonance imaging (R-fMRI). Rat pups were reared by a mother provided with insufficient bedding for nest building or by one with abundant bedding from postnatal days (PND) 8 to 12. In adolescence (at PND 45) and in early adulthood (at PND 60), R-fMRI sessions were conducted under light (*1%) isofluorane anesthesia. Behavioral tests were obtained in animals reared under identical conditions to model negative affectivity, including the Forced Swim Test, Sucrose Preference Test, and Social Behavior Test. Results: Behaviors reflecting negative affectivity were seen in both adolescent and adult animals. Amygdala functional connectivity (FC) with frontal, parietal, and basal ganglia, including thalamus, increased significantly with increased age. By contrast, local amygdala FC decreased significantly with age. Additionally, we detected significant interactions between abuse condition and age. Local amygdala FC decreased between PND 45 and 60 in control rats, but increased significantly in abused rats. The reverse pattern was observed for amygdala FC with medial frontal cortex and parietal cortex. Conclusions: Translation of an in vivo longitudinal imaging approach to a rodent model of early caregiver maltreatment revealed enduring evidence of differences in brain functional connectivity in adulthood that likely underlies negative affectivity and vulnerability to internalizing psychopathology in humans

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-art neuroimaging, and genetic samples must be generated and made openly available to the scientific community. The enhanced Nathan Kline Institute-Rockland Sample (NKI-RS) is a response to this need. NKI-RS is an ongoing, institutionally centered endeavor aimed at creating a large-scale (N > 1000), deeply phenotyped, community-ascertained, lifespan sample (ages 6-85 years old) with advanced neuroimaging and genetics. These data will be publically shared, openly, and prospectively (i.e., on a weekly basis). Herein, we describe the conceptual basis of the NKI-RS, including study design, sampling considerations, and steps to synchronize phenotypic and neuroimaging assessment. Additionally, we describe our process for sharing the data with the scientific community while protecting participant confidentiality, maintaining an adequate database, and certifying data integrity. The pilot phase of the NKI-RS, including challenges in recruiting, characterizing, imaging, and sharing data, is discussed while also explaining how this experience informed the final design of the enhanced NKI-RS. It is our hope that familiarity with the conceptual underpinnings of the enhanced NKI-RS will facilitate harmonization with future data collection efforts aimed at advancing psychiatric neuroscience and nosology.

Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship that has attracted much recent interest. Next, these profile functions are regressed on predictors of interest, whether categorical (e.g., acquisition site or diagnostic group) or continuous (e.g., age). This procedure can provide insight into the roles of multiple sources of variation, and detect large-scale patterns not easily available from conventional analyses. We illustrate the proposed methods with a resting state data set pooled across four imaging sites

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted 'U-shape'), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples

Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's 'functional connectome.' Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/

We investigated the relative involvement of cortical regions supporting attentional control in older and younger adults during performance on a modified version of the Stroop task. Participants were exposed to two different types of incongruent trials. One of these, an incongruent-ineligible condition, produces conflict at the non-response level, while the second, an incongruent-eligible condition, produces conflict at both non-response and response levels of information processing. Greater attentional control is needed to perform the incongruent-eligible condition compared to other conditions. We examined the cortical recruitment associated with this task in an event-related functional magnetic resonance imaging paradigm in 25 older and 25 younger adults. Our results indicated that while younger adults demonstrated an increase in the activation of cortical regions responsible for maintaining attentional control in response to increased levels of conflict, such sensitivity and flexibility of the cortical regions to increased attentional control demands was absent in older adults. These results suggest a limitation in older adults' capabilities for flexibly recruiting the attentional network in response to increasing attentional demands.

Regional manual volumetry is the gold standard of in vivo neuroanatomy, but is labor-intensive, can be imperfectly reliable, and allows for measuring limited number of regions. Voxel-based morphometry (VBM) has perfect repeatability and assesses local structure across the whole brain. However, its anatomic validity is unclear, and with its increasing popularity, a systematic comparison of VBM to manual volumetry is necessary. The few existing comparison studies are limited by small samples, qualitative comparisons, and limited selection and modest reliability of manual measures. Our goal was to overcome those limitations by quantitatively comparing optimized VBM findings with highly reliable multiple regional measures in a large sample (N=200) across a wide agespan (18-81). We report a complex pattern of similarities and differences. Peak values of VBM volume estimates (modulated density) produced stronger age differences and a different spatial distribution from manual measures. However, when we aggregated VBM-derived information across voxels contained in specific anatomically defined regions (masks), the patterns of age differences became more similar, although important discrepancies emerged. Notably, VBM revealed stronger age differences in the regions bordering CSF and white matter areas prone to leukoaraiosis, and VBM was more likely to report nonlinearities in age-volume relationships. In the white matter regions, manual measures showed stronger negative associations with age than the corresponding VBM-based masks. We conclude that VBM provides realistic estimates of age differences in the regional gray matter only when applied to anatomically defined regions, but overestimates effects when individual peaks are interpreted. It may be beneficial to use VBM as a first-pass strategy, followed by manual measurement of anatomically defined regions.

Models of selective attention predict that focused attention to spatially contiguous stimuli may result in enhanced activity in areas of cortex specialized for processing task-relevant and task-irrelevant information. We examined this hypothesis by localizing color-sensitive areas (CSA) and word and letter sensitive areas of cortex and then examining modulation of these regions during performance of a modified version of the Stroop task in which target and distractors are spatially coincident. We report that only the incongruent condition with the highest cognitive demand showed increased activity in CSA relative to other conditions, indicating an attentional enhancement in target processing areas. We also found an enhancement of activity in one region sensitive to word/letter processing during the most cognitively demanding incongruent condition indicating greater processing of the distractor dimension. Correlations with performance revealed that top-down modulation during the task was critical for effective filtering of irrelevant information in conflict conditions. These results support predictions made by models of selective attention and suggest an important mechanism of top-down attentional control in spatially contiguous stimuli.

Dedifferentiation, or decreased processing specificity, has been suggested to represent a ubiquitous characteristic of cognitive aging. In this study, we examined both age-related differences and intra-group differences in neural specificity in the ventral visual cortex for color, words, faces and places. Our results demonstrated that neural dedifferentiation was not ubiquitous across stimulus categories. Neural dedifferentiation was also relatively stable, across age, in a group of older adults. Older adults with more overall gray matter showed less neural dedifferentiation in the visual cortex. However, regional gray matter volume was not associated with neural dedifferentiation. We illustrate these effects using a discriminability metric, a signal detection theory measure, for neural dedifferentiation that takes into account both magnitude and variance of brain activation. The dedifferentiation measure provides a quantitative means to examine activation patterns and individual difference factors associated with neural dedifferentiation, and to test theories of behavioral dedifferentiation in cognitive aging literature.

Recent studies with multiple sclerosis (MS) participants have provided evidence for cortical reorganization. Greater recruitment of task-related areas and additional brain regions are thought to play an adaptive role in the performance of cognitive tasks. In this study, we compared cortical circuitry recruited by MS patients and controls during a selective attention task that requires both focusing attention on task-relevant information and ignoring or inhibiting task-irrelevant information. Despite comparable behavioral performance, MS patients demonstrated increased neural recruitment of task-related areas along with additional activation of the prefrontal cortices. However, this additional activation was associated with poor behavioral performance, thereby providing evidence against compensatory brain reorganization. Future studies specifically investigating the nature of additional activation seen in MS patients in a wider variety of cognitive tasks would provide insight into the specific cognitive decline in MS.