ArticleSchizophrenia research2012
Automated classification of fMRI during cognitive control identifies more severely disorganized subjects with schizophrenia.
Article in Schizophrenia research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 5 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 5 syntheses or guidelines pooled it, 45 citations in OpenAlex.
- Artificial intelligence approaches for schizophrenia prediction and its biomarkers using medical imaging data.Frontiers in psychiatry · 2026Pooled it
- Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis.Psychiatry and clinical neurosciences · 2024Pooled it
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- Peripheral Blood-Based Gene Expression Studies in Schizophrenia: A Systematic Review.Frontiers in genetics · 2021Pooled it
- Towards a brain-based predictome of mental illness.Human brain mapping · 2020Pooled it
- Multimodal Mental Health Digital Biomarker Analysis From Remote Interviews Using Facial, Vocal, Linguistic, and Cardiovascular Patterns.IEEE journal of biomedical and health informatics · 2024Article
- Similarity in evoked responses does not imply similarity in macroscopic network states.Network neuroscience (Cambridge, Mass.) · 2024Article
- Altered Associations Between Task Performance and Dorsolateral Prefrontal Cortex Activation During Cognitive Control in Schizophrenia.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2023Article
- Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.BMC medicine · 2023Article
- Mechanisms underlying dorsolateral prefrontal cortex contributions to cognitive dysfunction in schizophrenia.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Review
- Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification.International journal of environmental research and public health · 2021Review
- Global disruption in excitation-inhibition balance can cause localized network dysfunction and Schizophrenia-like context-integration deficits.PLoS computational biology · 2021Article
- Correcting for Superficial Bias in 7T Gradient Echo fMRI.Frontiers in neuroscience · 2021Article
- Association of Age at Onset and Longitudinal Course of Prefrontal Function in Youth With Schizophrenia.JAMA psychiatry · 2018Article
- Longitudinal stability of cognitive control in early psychosis: Nondegenerative deficits across diagnoses.Journal of abnormal psychology · 2018Article
- Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.NeuroImage · 2017Review
- [Neuroimaging in psychiatry: multivariate analysis techniques for diagnosis and prognosis].Der Nervenarzt · 2014Review
- Multivariate classification of blood oxygen level-dependent FMRI data with diagnostic intention: a clinical perspective.AJNR. American journal of neuroradiology · 2014Review
- Towards the identification of imaging biomarkers in schizophrenia, using multivariate pattern classification at a single-subject level.NeuroImage. Clinical · 2013Review
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
The establishment of a neurobiologically based nosological system is one of the ultimate goals of modern biological psychiatry research. Developments in neuroimaging and statistical/machine learning have provided useful basic tools for these efforts. Recent studies have demonstrated the utility of fMRI as input data for the classification of schizophrenia, but none, to date, has used fMRI of cognitive control for this purpose. In this study, we evaluated the accuracy of an unbiased classification method on fMRI data from a large cohort of subjects with first episode schizophrenia and a cohort of age matched healthy control subjects while they completed the AX version of the Continuous Performance Task (AX-CPT). We compared these results to classifications based on AX-CPT behavioral data. Classification accuracy for DSM-IV defined schizophrenia using fMRI data was modest and comparable to classifications conducted with behavioral data. Interestingly fMRI classifications did however identify a distinct subgroup of patients with greater behavioral disorganization, whereas behavioral data classifications did not. These results suggest that fMRI-based classification could be a useful tool in defining a neurobiologically distinct subgroup within the clinically defined syndrome of schizophrenia, reflecting alterations in discrete neural circuits. Independent validation of classification-based phenotypes using other biological data such as genetics would provide a strong test of this hypothesis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.