Faculty Bibliography

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.

Diffusion tensor imaging (DTI) has widely been used to investigate the microstructural damage of white matter tracts that occur in individuals with traumatic brain injury (TBI). In the current review, we discuss the white matter regions which are commonly affected in adults with TBI. We also describe the current literature that has utilized DTI to investigate the relationship between microstructural integrity with neuropsychological performance and clinical outcome measures. Finally, a model is presented of the potential utilization of DTI as a biomarker of efficacy in neurorehabilitation for individuals with TBI.

Schizophrenia has been increasingly conceptualized as a disorder of brain connectivity, in large part due to findings emerging from white matter and functional connectivity (FC) studies. This work has focused primarily on within-hemispheric connectivity, however some evidence has suggested abnormalities in callosal structure and interhemispheric interaction. Here we examined functional connectivity between homotopic points in the brain using a technique called voxel-mirrored homotopic connectivity (VMHC). We performed VMHC analyses on resting state fMRI data from 23 healthy controls and 25 patients with schizophrenia or schizoaffective disorder. We found highly significant reductions in VMHC in patients for a number of regions, particularly the occipital lobe, the thalamus, and the cerebellum. No regions of increased VMHC were detected in patients. VMHC in the postcentral gyrus extending into the precentral gyrus was correlated with PANSS Total scores. These results show substantial impairment of interhemispheric coordination in schizophrenia.

BACKGROUND: Abnormalities have been identified in the Cognitive Control Network (CCN) and the Default Mode Network (DMN) during episodes of late-life depression. This study examined whether functional connectivity at rest (FC) within these networks characterizes late-life depression and predicts antidepressant response. METHODS: 26 non-demented, non-MCI older adults were studied. Of these, 16 had major depression and 10 had no psychopathology. Depressed patients were treated with escitalopram (target dose 20mg) for 12weeks after a 2-week placebo phase. Resting state time series was determined prior to treatment. FC within the CCN was determined by placing seeds in the dACC and the DLPFC bilaterally. FC within the DMN was assessed from a seed placed in the posterior cingulate. RESULTS: Low resting FC within the CCN and high resting FC within the DMN distinguished depressed from normal elderly subjects. Beyond this "double dissociation", low resting FC within the CCN predicted low remission rate and persistence of depressive symptoms and signs, apathy, and dysexecutive behavior after treatment with escitalopram. In contrast, resting FC within the DMN was correlated with pessimism but did not predict treatment response. CONCLUSIONS: If confirmed, these findings may serve as a signature of the brain's functional topography characterizing late-life depression and sustaining its symptoms. By identifying the network abnormalities underlying biologically meaningful characteristics (apathy, dysexecutive behavior, pessimism) and sustaining late-life depression, these findings can provide a novel target on which new somatic and psychosocial treatments can be tested.

PURPOSE OF REVIEW: Aggression in schizophrenia is associated with poor treatment outcomes, hospital admissions, and stigmatization of patients. As such it represents an important public health issue. This article reviews recent neuroimaging studies of aggression in schizophrenia, focusing on PET/single photon emission computed tomography and MRI methods. RECENT FINDINGS: The neuroimaging literature on aggression in schizophrenia is in a period of development. This is attributable in part to the heterogeneous nature and basis of that aggression. Radiological methods have consistently shown reduced activity in frontal and temporal regions. MRI brain volumetric studies have been less consistent, with some studies finding increased volumes of inferior frontal structures, and others finding reduced volumes in aggressive individuals with schizophrenia. Functional MRI studies have also had inconsistent results, with most finding reduced activity in inferior frontal and temporal regions, but some also finding increased activity in other regions. Some studies have made a distinction between types of aggression in schizophrenia in the context of antisocial traits, and this appears to be useful in understanding the neuroimaging literature. SUMMARY: Frontal and temporal abnormalities appear to be a consistent feature of aggression in schizophrenia, but their precise nature likely differs because of the heterogeneous nature of that behavior

This study examined self-reported impulsivity and aggression and performance on the stop-signal task in patients with schizophrenia or schizoaffective disorder and healthy volunteers. Compared to controls, patients had higher scores on interview and questionnaire measures of impulsivity and aggression and showed increased stop-signal reaction time and greater response variability. These findings are consistent with a specific impairment in response inhibition in schizophrenia

Functional connectivity between the piriform cortex and limbic and neocortical areas was assessed using functional magnetic resonance imaging (fMRI) of urethane anesthetized rats that spontaneously cycled between slow-wave and fast-wave states. Slow-wave and fast-wave states were determined indirectly through monitoring of respiration rate, which was confirmed to co-vary with state as determined by electrophysiological recordings. Previous electrophysiological data have suggested that the piriform cortex shifts between responsiveness to afferent odor input during fast-wave states and enhanced functional connectivity with limbic areas during slow-wave state. The present results demonstrate that fMRI-based resting state functional connectivity between the piriform cortex and both limbic and neocortical areas is enhanced during slow-wave state compared to fast-wave state using respiration as an indirect measure of state in urethane anesthetized rats. This state-dependent shift in functional connectivity may be important for sleep-dependent odor memory consolidation

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