Precision-mapping Functional Connectivity in Parkinson Disease: Feasibility & Reliability (P7-3.005)

Area of Science:

• Neuroscience
• Medical Imaging
• Systems Biology

Background:

• Standard resting-state functional connectivity (RSFC) methods use limited data (≤ 10 min) and group averages.
• Precision-mapping RSFC utilizes extensive data (> 40 min) to create individualized network maps.
• This technique reveals significant individual differences in brain network size, strength, and location.

Purpose of the Study:

• To assess the feasibility and reliability of precision-mapping resting-state functional connectivity (RSFC) in Parkinson disease.
• To establish if individualized RSFC maps can be consistently generated across multiple sessions.
• To determine the minimum data required for reliable RSFC mapping in this population.

Main Methods:

• Participants with Parkinson disease underwent multiple fMRI sessions (3-5) over seven months.
• Stringent motion censoring was applied to ensure high-quality, low-motion fMRI data (> 40 min per participant).
• RSFC map stability was assessed by comparing maps across sessions, and reliability was measured using split-half analyses.

Main Results:

• Precision-mapping RSFC demonstrated high feasibility in Parkinson disease patients, with ample high-quality data obtained (average frame retention 75%).
• Individual RSFC maps showed strong stability across sessions (r > 0.7).
• High reliability was confirmed, with split-half analyses yielding strong correlations (r > 0.8) using >40 min of data.

Conclusions:

• Precision-mapping techniques are feasible and reliable for generating individual-level RSFC networks in Parkinson disease.
• This approach enables the study of how individual brain network variability correlates with clinical symptoms and disease progression.
• Future research can leverage this technique to understand the relationship between brain network alterations and Parkinson disease manifestations.