SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration

Wang, Lei; Alpert, Kathryn I.; Calhoun, Vince D.; Cobia, Derin; Keator, David B.; King, Margaret D.; Kogan, Alexander; Landis, Drew; Tallis, Marcelo; Turner, Matthew D.; Potkin, Steven G.; Turner, Jessica A.; Ambite, José Luis

doi:10.1016/j.neuroimage.2015.06.065

Cited by 94 publications

(64 citation statements)

References 52 publications

(68 reference statements)

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“…Brain imaging data from 6 independent studies were obtained through either the SchizConnect and OpenfMRI data sharing platforms (http://schizconnect.org; https://openfmri.org) or local scanning (Çetin et al, 2014;Gollub et al, 2013;Kogan et al, 2016;Orban et al, 2016;Poldrack et al, 2016;Wang et al, 2016). The 6 datasets differed in terms of both scanning site and cognitive context during fMRI data acquisition (resting-state, emotional memory, Sternberg item recognition paradigm, N-back, task-switching and oddball tasks).…”

Section: Datasetsmentioning

confidence: 99%

Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity

Orban

Christian

Desbois

et al. 2017

Preprint

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Our objective was to assess the generalizability, across sites and cognitive contexts, of schizophrenia classification based on functional brain connectivity. We tested different training-test scenarios combining fMRI data from 191 schizophrenia patients and 191 matched healthy controls obtained at 6 scanning sites and under different task conditions. Diagnosis classification accuracy generalized well to a novel site and cognitive context provided data from multiple sites were used for classifier training. By contrast, lower classification accuracy was achieved when data from a single distinct site was used for training. These findings indicate that it is beneficial to use multisite data to train fMRI-based classifiers intended for large-scale use in the clinical realm.

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Section: Datasetsmentioning

confidence: 99%

Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity

Orban

Christian

Desbois

et al. 2017

Preprint

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“…In addition, there is a plan to also make FBIRN’s schizophrenia-control data sets available via the SchizConnect resource (www.schizconnect.org) 40 . SchizConnect has been designed to federate schizophrenia data and provides an integrated domain model with other data resources.…”

Section: Methodsmentioning

confidence: 99%

The Function Biomedical Informatics Research Network Data Repository

et al. 2016

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The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical datasets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 dataset consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 Tesla scanners. The FBIRN Phase 2 and Phase 3 datasets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN’s multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

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“…MRI data from 78 patients with schizophrenia strict diagnosis (DSM IV) SCZ (64 males, 14 females) and 91 healthy controls (CON) (65 males, 26 females) were downloaded from the open COBRE database ({http://fcon_1000.projects.nitrc.org/indi/retro/cobre.html) (Ambite et al 2015;Wang et al 2016). Age ranged from 18 to 65 years in both groups.…”

Section: Participantsmentioning

confidence: 99%

Disrupted modular organization of primary sensory brain areas in schizophrenics

Bordier

Nicolini

Bifone

2017

Preprint

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Abnormal brain resting-state functional connectivity has been consistently observed in patients affected by Schizophrenia (SCZ) using functional MRI and other neuroimaging methods. Graph theoretical methods provide a framework to investigate these defective functional interactions and their effects on the modular organization of brain connectivity networks. A few studies have shown abnormal distribution of connectivity within and between functional modules, an indication of imbalanced functional segregation ad integration in SCZ patients. However, no major alterations in the modular structure of functional connectivity networks in patients have been reported, and unambiguous identification of the neural substrates involved remains elusive. Recently, it has been demonstrated that current modularity analysis methods suffer from a fundamental and severe resolution limit, as they fail to detect features that are smaller than a scale determined by the size of the entire connectivity network. This resolution limit is likely to have hampered the ability to resolve differences between patients and controls in previous cross-sectional studies. Here, we apply a novel, resolution limit-free approach to study the modular organization of resting state functional connectivity networks in a large cohort of SCZ patients, and in matched healthy controls. Leveraging these important methodological advances, we find new evidence of substantial fragmentation and reorganization involving primary sensory, auditory and visual areas in SCZ patients. Conversely, frontal and prefrontal areas, typically associated with higher cognitive functions, appear to be largely unaffected, with changes selectively involving language and speech processing areas. Our findings provide support to the hypothesis that cognitive dysfunction in SCZ may arise from deficits occurring already at early stages of sensory processing.

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SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration

Cited by 94 publications

References 52 publications

Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity

Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity

The Function Biomedical Informatics Research Network Data Repository

Disrupted modular organization of primary sensory brain areas in schizophrenics

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