Individualized phenotyping of functional amyotrophic lateral sclerosis pathology in sensorimotor cortex

Area of Science:

• Neuroscience
• Medical Imaging

Background:

• Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease causing motor neuron loss, muscle weakness, and typically leading to death within 3 years.
• Individualized phenotyping of functional ALS pathology remains a challenge despite known disease subtypes.

Purpose of the Study:

• To investigate the utility of 7 Tesla functional MRI (fMRI) for individualized phenotyping of ALS.
• To determine if functional connectivity or local activation changes better model ALS onset and severity.
• To identify disease signatures within the primary motor cortex and relate them to clinical subtypes.

Main Methods:

• Acquired 7 Tesla fMRI data from ALS patients and controls during motor tasks involving affected and non-affected body parts.
• Applied Shared Response Modelling for group classification and Partial Least Squares regression for correlating latent variables with clinical data.
• Analyzed functional connectivity and local activation changes, and mapped model weights to brain regions.

Main Results:

• Functional connectivity changes, not local activation, were more effective in modeling ALS onset and severity.
• The strongest functional disease information in the primary motor cortex was not located in the behaviorally first-affected area.
• Highest model weights for King stage classification were observed in the foot and tongue/face regions.

Conclusions:

• Task-based functional connectivity measures using 7 Tesla fMRI are crucial for classifying ALS patients, complementing structural imaging.
• 7 Tesla fMRI can identify a unique disease signature for individual ALS patients.
• Findings suggest a potential dissociation between behavioral presentation and underlying functional pathology in ALS.