TY - JOUR
T1 - The neurophysiological brain-fingerprint of Parkinson's disease
AU - PREVENT-AD Research Group
AU - Quebec Parkinson Network
AU - da Silva Castanheira, Jason
AU - Wiesman, Alex I.
AU - Hansen, Justine Y.
AU - Misic, Bratislav
AU - Baillet, Sylvain
AU - Breitner, John
AU - Poirier, Judes
AU - Bellec, Pierre
AU - Bohbot, Véronique
AU - Chakravarty, Mallar
AU - Collins, Louis
AU - Etienne, Pierre
AU - Evans, Alan
AU - Gauthier, Serge
AU - Hoge, Rick
AU - Ituria-Medina, Yasser
AU - Multhaup, Gerhard
AU - Münter, Lisa Marie
AU - Rajah, Natasha
AU - Rosa-Neto, Pedro
AU - Soucy, Jean Paul
AU - Vachon-Presseau, Etienne
AU - Villeneuve, Sylvia
AU - Amouyel, Philippe
AU - Appleby, Melissa
AU - Ashton, Nicholas
AU - Auld, Daniel
AU - Ayranci, Gülebru
AU - Bedetti, Christophe
AU - Beland, Marie Lise
AU - Blennow, Kaj
AU - Westman, Ann Brinkmalm
AU - Cuello, Claudio
AU - Dadar, Mahsa
AU - Daoust, Leslie Ann
AU - Das, Samir
AU - Dauar-Tedeschi, Marina
AU - De Beaumont, Louis
AU - Dea, Doris
AU - Descoteaux, Maxime
AU - Dufour, Marianne
AU - Farzin, Sarah
AU - Ferdinand, Fabiola
AU - Fonov, Vladimir
AU - Gonneaud, Julie
AU - Kat, Justin
AU - Kazazian, Christina
AU - Labonté, Anne
AU - Leoutsakos, Jeannie Marie
AU - Brandt, Jason
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/7
Y1 - 2024/7
N2 - Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by theQuebec Parkinson Network (QPN), thePre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, theCambridge Centre for Aging Neuroscience (Cam-CAN), and theOpen MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).
AB - Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by theQuebec Parkinson Network (QPN), thePre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, theCambridge Centre for Aging Neuroscience (Cam-CAN), and theOpen MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).
KW - Arrhythmic brain activity
KW - Brain-fingerprinting
KW - Magnetoencephalography
KW - Movement disorders
KW - Neural dynamics
KW - Oscillations
KW - Parkinson's disease
UR - http://www.scopus.com/inward/record.url?scp=85196546016&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85196546016&partnerID=8YFLogxK
U2 - 10.1016/j.ebiom.2024.105201
DO - 10.1016/j.ebiom.2024.105201
M3 - Article
C2 - 38908100
AN - SCOPUS:85196546016
SN - 2352-3964
VL - 105
JO - EBioMedicine
JF - EBioMedicine
M1 - 105201
ER -