This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

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Background-White matter microstructural disruptions have been observed in patients with schizophrenia. However, whether changes exist prior to disease onset or in high-risk individuals is unclear. Here we investigated white matter integrity, as assessed by diffusion tensor imaging (DTI), in individuals at ultra high risk for psychosis (UHR), relative to healthy controls (HC), and the relationship between baseline DTI measures and functional outcome over time.

Neurofibromatosis type I (NF1) is one of the most common singlegene causes of learning disabilities. Here, we use behavioral working memory probes and electrophysiological studies in a mouse model of NF1 (Nf1 heterozygous null mutants; Nf1 +/− ) to demonstrate that (i) Neurofibromin regulates prefrontal and striatal inhibitory networks, specifically activity-dependent GABA release and (ii) is required for working memory performance, with inhibitiondependent working memory deficits seen in Nf1 +/− mice. We find that increased inhibition in medial prefrontal cortex (mPFC) is sufficient to alter persistent activity in a biophysical model of an mPFC microcircuit, suggesting a possible mechanism for Nf1 +/− working memory deficits. Accordingly, working memory assays applied during functional MRI (fMRI) studies in human subjects with NF1 reveal hypoactivation of corticostriatal networks, which is associated with impaired working memory performance. Collectively, these integrative mouse and human studies reveal molecular and cellular mechanisms contributing to working memory deficits in NF1.GABA | Ras | prefrontal cortex | learning disability | neurofibromatosis type I N eurofibromatosis type 1 (NF1) is a valuable model for understanding mechanisms of learning disabilities (1). NF1 is a common genetic disorder (incidence 1:3,000) that results from mutations in a single gene (Nf1) that encodes the neurofibromin protein (2, 3). Specific deficits in the domains of visuospatial and executive functions are among the most common cognitive deficits associated with this syndrome (1,4,5). Previous mechanistic studies in a mouse model of NF1 (Nf1 heterozygous null mutants or Nf1 +/− ) demonstrated that neurofibromin modulates Rasdependent GABA release in the hippocampus, which in turn modulates long-term potentiation (LTP) and hippocampaldependent learning (6, 7). However, the mechanisms underlying frontal executive dysfunction in NF1, including prominent working memory deficits (5), are unknown. Therefore, to investigate mechanisms underlying working memory deficits associated with the NF1 mutation we carried out parallel experiments in mice and humans.Working memory is a cognitive construct involving the ability to hold and update information transiently in mind in the service of higher-order cognitive activities. Executive functions, including working memory, are thought to depend on common corticostriatal networks (8-11). Therefore, our experiments focused on frontal corticostriatal circuitry, with an emphasis on the dorsolateral prefrontal cortex (DLPFC) in humans, thought to be critical for working memory (12), and its functionally analogous structure in rodents, the medial prefrontal cortex (mPFC) (13,14).Here, we report Ras-dependent increases in GABA release in the mPFC and striatum of the Nf1 +/− mouse model. Increased GABAergic inhibition is likely to be responsible for the working memory deficits that we found in the Nf1 +/− mice because these deficits could be reversed with a drug that decreased inhibition. Further,...

Physiological disturbances in the dorsolateral prefrontal cortex contribute differentially to patients' difficulties with maintaining spatial information across a brief delay, as well as with manipulating the maintained representation. These differences persisted when comparing conditions in which the 2 groups were equivalent in behavioral accuracy.

Objective Clinical response to antipsychotic drug treatment is highly variable, yet prognostic biomarkers are lacking. The authors recently demonstrated that successful antipsychotic drug treatment alters resting-state functional connectivity of the striatum. The goal of the present study was to test whether intrinsic striatal connectivity patterns provide prognostic information and can serve as a potential biomarker of treatment response to antipsychotic drugs. Method The authors used resting-state functional MRI (fMRI) to develop a prognostic index in a discovery cohort of 41 first-episode schizophrenia patients, then tested this index in an independent cohort of 40 newly hospitalized chronic patients with acute psychosis. In the discovery cohort, patients underwent resting-state fMRI scanning at the initiation of randomized controlled treatment with a second-generation antipsychotic. Whole-brain functional connectivity maps were generated for each subject from striatal seed regions. A stringent measure of clinical response was calculated that required sustained improvement over two consecutive study visits. Clinical response was entered into a survival analysis, and Cox regression was applied to the functional connectivity data. A striatal connectivity index was created, comprising functional connections of the striatum that predicted treatment response. This striatal connectivity index was tested on a generalizability cohort of patients with psychotic disorders who were hospitalized for an acute psychotic episode. Results A total of 91 regions functionally connected with the striatum provided significant prognostic information. Connectivity in these regions was used to create a baseline striatal connectivity index that predicted response to antipsychotic treatment with high sensitivity and specificity in both the discovery and generalizability cohorts. Conclusions These results provide evidence that individual differences in striatal functional connectivity predict response to antipsychotic drug treatment in acutely psychotic patients. With further development, this has the potential to serve as a prognostic biomarker with clinical utility and to reduce the overall burden associated with psychotic illnesses.

Diffusion tensor imaging (DTI) is used extensively in neuroscience to noninvasively estimate white matter (WM) microarchitecture. However, the diffusion signal is inherently ambiguous because it infers WM structure from the orientation of water diffusion and cannot identify the biological sources of diffusion changes. To compare inferred WM estimates to directly labeled axonal elements, we performed a novel within-subjects combination of high-resolution ex vivo DTI with two-photon laser microscopy of intact mouse brains rendered optically transparent by Clear Lipid-exchanged, Anatomically Rigid, Imaging/immunostaining compatible, Tissue hYdrogel (CLARITY). We found that myelin basic protein (MBP) immunofluorescence significantly correlated with fractional anisotropy (FA), especially in WM regions with coherent fiber orientations and low fiber dispersion. Our results provide evidence that FA is particularly sensitive to myelination in WM regions with these characteristics. Furthermore, we found that radial diffusivity (RD) was only sensitive to myelination in a subset of WM tracts, suggesting that the association of RD with myelin should be used cautiously. This combined DTI-CLARITY approach illustrates, for the first time, a framework for using brain-wide immuno-labeling of WM targets to elucidate the relationship between the diffusion signal and its biological underpinnings. This study also demonstrates the feasibility of a within-subject combination of noninvasive neuroimaging and tissue clearing techniques that has broader implications for neuroscience research.