Resting-state functional magnetic resonance imaging (rs-fMRI) plays a crucial role in Parkinson’s disease (PD) research by providing a non-invasive way to observe and analyze brain activity patterns when a person is not engaged in any specific task. This technique measures spontaneous fluctuations in brain activity, allowing researchers to examine how different brain regions communicate and form networks during rest. Understanding these resting-state networks is particularly important in Parkinson’s research because PD is characterized not only by motor symptoms but also by widespread changes in brain connectivity and function.
One of the primary contributions of rs-fMRI in Parkinson’s research is its ability to detect alterations in functional connectivity—the way different parts of the brain synchronize their activity. In Parkinson’s disease, especially in early or mild cognitive impairment stages (PD-MCI), studies have shown significant weakening in the connectivity of key brain networks such as the default mode network (DMN), which is involved in memory, attention, and self-referential thought. This weakening correlates with cognitive decline and can help identify patients at risk of progressing to dementia. By mapping these connectivity changes, rs-fMRI helps researchers understand how Parkinson’s affects not only motor circuits but also cognitive and emotional processing networks.
Resting-state fMRI also reveals asymmetries related to the side of symptom onset in Parkinson’s disease. For example, differences in regional brain homogeneity—how similar the activity is within a localized brain region—have been observed depending on whether symptoms start on the left or right side of the body. These findings suggest that the disease’s impact on brain networks can be lateralized, which may influence symptom presentation and progression. Such insights are valuable for tailoring personalized treatment approaches.
Another important role of rs-fMRI is in tracking disease progression and phenoconversion, which is the transition from a prodromal or early state to full-blown Parkinson’s disease. In conditions that often precede PD, such as idiopathic REM sleep behavior disorder (iRBD), rs-fMRI studies have identified progressive disruptions in resting-state networks. These disruptions reflect increasing functional segregation and loss of connectivity, which may serve as early biomarkers for identifying individuals likely to develop Parkinson’s. This early detection is critical for timely intervention and for testing neuroprotective therapies.
Furthermore, rs-fMRI contributes to understanding the neurochemical underpinnings of Parkinson’s by linking functional connectivity patterns to neurotransmitter systems. For instance, research has shown that dopamine and serotonin levels covary with activity in functionally connected brain regions in PD patients. Since dopamine depletion is a hallmark of Parkinson’s, observing how its distribution relates to resting-state networks helps clarify the disease’s impact on brain function and guides the development of targeted treatments.
In addition to these research applications, resting-state fMRI offers practical advantages. It does not require patients to perform tasks, which is beneficial for those with motor impairments or cognitive difficulties common in Parkinson’s. This makes it a patient-friendly tool for repeated assessments over time, enabling longitudinal studies that monitor how brain connectivity changes with disease progression or in response to therapies.
Overall, resting-state fMRI serves as a window into the complex brain network alterations in Parkinson’s disease. It helps identify early functional changes before structural damage becomes apparent, tracks disease evolution, links symptoms to specific network disruptions, and connects brain activity patterns to underlying neurochemical changes. This comprehensive perspective is essential for advancing our understanding of Parkinson’s and improving diagnosis, prognosis, and treatment strategies.
