The brain-fingerprint of Parkinson’s disease.
Our lab publishes in open-access in the journal eBiomedicine, which is part of The Lancet group, a new study that reveals distinct patterns of brain activity that differentiate individuals with Parkinson’s disease (PD) from healthy controls with remarkable accuracy. We believe these findings open new avenues for understanding and potentially treating Parkinson’s disease.
Key Findings:
Unique Brain-Fingerprints: The study demonstrates that the brain activity of patients with PD shows distinctive activity patterns that differ significantly from those of healthy individuals. We leveraged a brain-fingerprinting method we had developed previously that identifies individual traits from minute-long recordings of spontaneous brain activity using magnetoencephalographic imaging (MEG) — a technique with millisecond temporal resolution that our lab has contributed to develop over the years.
High Accuracy: The study’s findings show, in particular, that the rhythmic components of these brain-fingerprints can distinguish patients with PD from healthy controls with approximately 90% accuracy. This high level of precision underscores the potential of brain-fingerprinting as a diagnostic tool.
Association with Symptoms: Our study also reveals that traits of these brain-fingerprints are related to certain aspects of Parkinson’s symptoms, meaning, for example, they can indicate whether symptoms are more pronounced in each patients and how they are related to the activity of specific brain regions. This insight could lead to more systematic diagnostic approaches.
Neurotransmitter Systems: We also found that the topography of the brain-fingerprints cortical aligns with how certain neurotransmitters known to be involved in Parkinson’s disease are concentrated across the cortex. We hope these observations will inspire future pharmacological studies to advance insights into the disease’s pathophysiology.
Implications for Treatment: Overall, our present findings suggest that individualized brain-fingerprints obtained from short sessions of MEG imaging represent a practical approach to, potentially, help monitor disease progression and tailor treatment strategies. For instance, identifying specific brain activity patterns associated with PD symptoms could help in targeting therapeutic interventions more precisely, including with brain stimulation devices, potentially improving their efficacy.
Funding and Acknowledgements: We are grateful for the generous participation of all individuals involved in the study, especially patient volunteers with Parkinson’s disease. This research was supported by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD) program, the Cambridge Centre for Aging Neuroscience (cam-CAN), and the Open MEG Archives (OMEGA). Additional funding was provided by the NIH, the Natural Sciences and Engineering Research Council of Canada, and the Canada Research Chair in Neural Dynamics of Brain Systems.