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Alzheimer's Disease vs Bipolar Disorder vs Healthy Control MRI Data and Processed Results

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This dataset contains structural and diffusion MRI data together with derived FA, TBSS, and VBM results for patients diagnosed with Alzheimer’s Disease (AD), Bipolar Disorder (BD), and healthy controls (HC).
It includes corresponding clinical and biomarker information organized in structured .csv files, supporting both neuroimaging and clinical correlation studies.

The dataset has been used in multiple peer-reviewed publications investigating white matter integrity, biomarker correlation, and multivariate diagnostic modeling of neurodegenerative and psychiatric disorders.

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Citation

Besga, A., Graña, M., & Chyzhyk, D. (2020).
Alzheimer’s Disease versus Bipolar Disorder versus Healthy Control MRI Data and Processed Results [Data set]. Zenodo.
https://doi.org/10.5281/zenodo.3935636

Source

https://doi.org/10.5281/zenodo.3935636
Contact: ariadna.besga@ehu.eus
Institutions: University of the Basque Country (UPV/EHU), University of Navarra, University of the Basque Country
Funding: European Commission — CybSPEED: Cyber-Physical Systems for PEdagogical Rehabilitation in Special Education (Grant No. 777720)

Dataset Information

Category Details
Subjects Patients diagnosed with Alzheimer’s Disease (EA), Bipolar Disorder (TB), and healthy controls (CRL)
Study Type Structural and diffusion MRI with derived FA, TBSS, and VBM analyses
File Format NIfTI (.nii/.nii.gz) for imaging, CSV for clinical data
Tools Used FSL (DTI, TBSS), SPM (VBM), MATLAB, Python, R
Diagnostic Codes crl = control, tb = bipolar disorder, ea = Alzheimer’s disease
Anonymization All subjects identified by numerical random keys
Registration Nonlinear alignment to MNI space using FSL
Publication Use Multiple neuroscience and diagnostic modeling studies

Clinical Data

The Clinical_data folder contains .csv files readable in Python, R, MATLAB, or any spreadsheet software.
Each file corresponds to a specific biomarker.

Key files include:

  • clinical_data_id_age_gender.csv: anonymized ID, diagnostic key, age, and gender.
  • clinical_data_corrected.csv: deprecated, can be ignored.

Diagnostic key:

  • crl = Healthy control
  • tb = Bipolar disorder
  • ea = Alzheimer’s disease

Publications Using This Dataset

  1. Graña et al. (2011) — Computer Aided Diagnosis system for Alzheimer’s Disease using DTI features, Neuroscience Letters, 502(3):225–229.
  2. Besga et al. (2012) — Discovering Alzheimer’s disease and bipolar disorder white matter effects using DTI, Neuroscience Letters, 520(1):71–76.
  3. Termenon et al. (2013) — Lattice ICA feature selection on DWI for Alzheimer’s classification, Neurocomputing, 114:132–141.
  4. Besga et al. (2015) — Discrimination between AD and late-onset BD using multivariate analysis, Frontiers in Aging Neuroscience, 7:231.
  5. Besga-Basterra et al. (2016) — Eigenanatomy on FA imaging differentiates AD and BD, Current Alzheimer Research, 13(5):557–565.
  6. Besga et al. (2017) — White matter tract integrity and inflammation in AD vs BD, Frontiers in Aging Neuroscience, 9:179.

Purpose

This dataset supports research in neurodegenerative and affective disorder differentiation, enabling:

  • Quantitative analysis of white matter microstructure (FA, TBSS).
  • Morphometric evaluation via SPM-based VBM.
  • Correlation between MRI-derived features and clinical biomarkers.
  • Machine learning model training for computer-aided diagnosis (CAD) of AD vs BD.

Keywords

MRI • Diffusion MRI • FA • TBSS • VBM • Alzheimer’s Disease • Bipolar Disorder • Healthy Control • FSL • SPM • Neurodegeneration • White Matter Integrity • Biomarkers

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