Multimodal ultra-high-field MRI, clinical, cognitive, and genetic profiles across the ALS–FTD spectrum

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Authors: Thomas B. Shaw, Aiman Al Najjar, Markus Barth, Steffen Bollmann, Steffen Bollmann, Pierrick Bourgeat, Jeryn Chang, Harriet Dempsey‐Jones, Amir H. Fazlollahi, Jurgen Fripp, Natalie Garden, Christine C. Guo
+15 more Robert D. Henderson, Elaine Kuan, Jinglei Lv, Pamela McCombe, Aswin Narayanan, Shyuan Thieu Ngo, Vinh Nguyen, Kieran O’Brien, Gail Robinson, Simon Robinson, Olivier Salvado, Ashley Stewart, Frederik J. Steyn, Saskia Bollmann, Saskia Bollmann
Cited by: 1
References: 76

Abstract

This dataset was acquired and curated to explore the spectrum of Motor Neuron Disease (MND) and Fronto-Temporal Dementia (FTD) with Ultra-High Field Magnetic Resonance Imaging (7 Tesla) and compare these to non-neurodegenerative disease controls (known colloquially as "The 7 T hEalthy Ageing study [7TEA]"). Twenty people living with neurodegenerative disease and 14 non-neurodegenerative controls underwent a comprehensive multimodal MRI protocol including structural, diffusion, quantitative MRI, resting state, and task fMRI, alongside cognitive testing and genetic screening. This dataset combines detailed imaging phenotypes with extensive clinical characterisations. It facilitates investigations into the spectrum of MND and FTD, has provided a basis for developing novel quantitative biomarkers, and supports the exploration of interactions between imaging features and clinical progression. The availability of this dataset supports various research avenues, from detailed hippocampal subfield analyses, network connectivity assessments, and multimodal genetic, cognitive, and imaging studies. The dataset is published on OpenNeuro (dataset ds007036) and is curated in the Brain Imaging Data Structure (BIDS) standard.

Fields of Study & Subjects

Amyotrophic Lateral Sclerosis Research Functional Brain Connectivity Studies Genetic Neurodegenerative Diseases

Publication details

Journal / source
Scientific Data
Publisher
Springer Science and Business Media LLC
Volume
13
Issue
1
Publication date
19 May 2026
Language
EN