Resting-state networks and their relationship with MoCA performance in PD patients

Area of Science:

• Neuroscience
• Neurology
• Cognitive Science

Background:

• Mild cognitive impairment (MCI) is a frequent non-motor symptom in Parkinson's Disease (PD).
• Resting-state network (RSN) alterations linked to MCI onset in PD are not well understood.
• Understanding these changes is crucial for diagnosing and managing cognitive decline in PD.

Purpose of the Study:

• To investigate RSN alterations in individuals with PD.
• To determine the association between RSN changes and cognitive performance in PD.
• To differentiate neurobiological patterns of cognitive impairment in PD.

Main Methods:

• Functional magnetic resonance imaging (fMRI) was used to analyze RSNs.
• 3 groups were studied: PD patients with normal cognition (NC), PD patients with MCI, and healthy controls (HC).
• Connectivity was assessed using Z-score coefficients within the default mode network (DMN), salience network (SN), and central executive network (CEN).

Main Results:

• DMN and SN connectivity were reduced in PD patients irrespective of cognitive status.
• In PD with NC, DMN nodes negatively correlated with global cognition, while SN nodes positively correlated.
• This inverse relationship was absent in PD with MCI. Executive function correlated with CEN connectivity, and language function correlated with SN connectivity in PD with MCI.

Conclusions:

• Cognitive impairment in PD is associated with distinct RSN alterations.
• RSN differences between PD with MCI and PD with NC suggest a differentiated neurodegenerative pattern.
• These findings highlight the potential of RSNs as biomarkers for cognitive status in Parkinson's Disease.