Neurotransmitter-informed connectivity maps and their application for outcome inference after stroke

Area of Science:

• Neuroscience
• Neurology
• Systems Neuroscience

Background:

• Neuropsychiatric disorders are increasingly viewed as network diseases.
• Neurotransmitter (NT) system alterations are key to disease development.
• Limited research connects whole-brain NT fingerprints to stroke outcomes.

Purpose of the Study:

• Integrate NT data with structural connectivity for stroke analysis.
• Understand NT system's contribution to stroke outcome variability.

Main Methods:

• Combined normative NT receptor/transporter data with structural connectomes.
• Generated NT-specific connectivity maps (serotonin, dopamine, GABA, glutamate, acetylcholine).
• Analyzed lesion data from 126 stroke patients using logistic regression, adjusting for covariates.

Main Results:

• Developed a novel method integrating PET tracer NT data with connectomes.
• NT-informed maps showed distinct spatial distributions.
• Damage to dopamine transporter (DAT) networks significantly predicted poorer stroke recovery.

Conclusions:

• Lesion-induced NT system disruptions offer greater insight into stroke outcome variability than structural damage alone.
• Disruptions in dopaminergic networks play a crucial role in stroke recovery.
• Findings support personalized medicine approaches in stroke care, including targeted pharmacologic interventions.