Dataset Information

A multimodal neuroimaging classifier for alcohol dependence.

ABSTRACT: With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence.

SUBMITTER: Guggenmos M

PROVIDER: S-EPMC6962344 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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A multimodal neuroimaging classifier for alcohol dependence.

Guggenmos Matthias M Schmack Katharina K Veer Ilya M IM Lett Tristram T Sekutowicz Maria M Sebold Miriam M Garbusow Maria M Sommer Christian C Wittchen Hans-Ulrich HU Zimmermann Ulrich S US Smolka Michael N MN Walter Henrik H Heinz Andreas A Sterzer Philipp P

Scientific reports 20200115 1

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neu ...[more]

PMID: 31941972

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Project description:BackgroundPeople recovering from alcohol use disorder (AUD) show altered resting brain connectivity. The metabotropic glutamate 5 (mGlu5) receptor is an important regulator of synaptic plasticity potentially linked with synchronized brain activity and a target of interest in treating AUD. The goal of this work was to assess potential relationships of brain connectivity at rest with mGlu5 receptor availability in people with AUD at two time points early in abstinence.MethodsForty-eight image data sets were acquired with a multimodal neuroimaging battery that included resting-state functional magnetic resonance imaging (fMRI) and mGlu5 receptor positron emission tomography (PET) with the radiotracer [18 F]FPEB. Participants with AUD (n = 14) were scanned twice, at approximately 1 and 4 weeks after beginning supervised abstinence. [18 F]FPEB PET results were published previously. Primary comparisons of fMRI outcomes were performed between the AUD group and healthy controls (HCs; n = 23) and assessed changes over time within the AUD group. Relationships between resting-state connectivity measures and mGlu5 receptor availability were explored within groups.ResultsCompared to HCs, global functional connectivity of the orbitofrontal cortex was higher in the AUD group at 4 weeks of abstinence (p = 0.003), while network-level functional connectivity within the default mode network (DMN) was lower (p < 0.04). Exploratory multimodal analyses showed that mGlu5 receptor availability was correlated with global connectivity across all brain regions (HCs, r = 0.41; AUD group at 1 week of abstinence, r = 0.50 and at 4 weeks, r = 0.46; all p < 0.0001). Furthermore, a component of cortical and striatal mGlu5 availability was correlated with connectivity between the DMN and salience networks in HCs (r = 0.60, p = 0.003) but not in the AUD group (p > 0.3).ConclusionsThese preliminary findings of altered global and network connectivity during the first month of abstinence from drinking may reflect the loss of efficient network function, while exploratory relationships with mGlu5 receptor availability suggest a potential glutamatergic relationship with network coherence.

Project description:People affected by psychotic, depressive and developmental disorders are at a higher risk for alcohol and tobacco use. However, the further associations between alcohol/tobacco use and symptoms/cognition in these disorders remain unexplored. We identified multimodal brain networks involving alcohol use (n = 707) and tobacco use (n = 281) via supervised multimodal fusion and evaluated if these networks affected symptoms and cognition in people with psychotic (schizophrenia/schizoaffective disorder/bipolar, n = 178/134/143), depressive (major depressive disorder, n = 260) and developmental (autism spectrum disorder/attention deficit hyperactivity disorder, n = 421/346) disorders. Alcohol and tobacco use scores were used as references to guide functional and structural imaging fusion to identify alcohol/tobacco use associated multimodal patterns. Correlation analyses between the extracted brain features and symptoms or cognition were performed to evaluate the relationships between alcohol/tobacco use with symptoms/cognition in 6 psychiatric disorders. Results showed that (1) the default mode network (DMN) and salience network (SN) were associated with alcohol use, whereas the DMN and fronto-limbic network (FLN) were associated with tobacco use; (2) the DMN and fronto-basal ganglia (FBG) related to alcohol/tobacco use were correlated with symptom and cognition in psychosis; (3) the middle temporal cortex related to alcohol/tobacco use was associated with cognition in depression; (4) the DMN related to alcohol/tobacco use was related to symptom, whereas the SN and limbic system (LB) were related to cognition in developmental disorders. In summary, alcohol and tobacco use were associated with structural and functional abnormalities in DMN, SN and FLN and had significant associations with cognition and symptoms in psychotic, depressive and developmental disorders likely via different brain networks. Further understanding of these relationships may assist clinicians in the development of future approaches to improve symptoms and cognition among psychotic, depressive and developmental disorders.

Dataset Information

A multimodal neuroimaging classifier for alcohol dependence.

Publications

A multimodal neuroimaging classifier for alcohol dependence.

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