Patient-specific functional networks track early cognitive alterations and minor hallucinations in Parkinson’s disease – Nature Mental Health

patient-specific-functional-networks-track-early-cognitive-alterations-and-minor-hallucinations-in-parkinson’s-disease-–-nature-mental-health
  • Kalia, L. V. & Lang, A. E. Parkinson’s disease. Lancet 386, 896–912 (2015).

    Article  PubMed  Google Scholar 

  • Braak, H. et al. Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol. Aging 24, 197–211 (2003).

    Article  PubMed  Google Scholar 

  • Pagonabarraga, J., Bejr-Kasem, H., Martinez-Horta, S. & Kulisevsky, J. Parkinson disease psychosis: from phenomenology to neurobiological mechanisms. Nat. Rev. Neurol. 20, 135–150 (2024).

    Article  PubMed  Google Scholar 

  • Postuma, R. B. & Berg, D. Advances in markers of prodromal Parkinson disease. Nat. Rev. Neurol. 12, 622–634 (2016).

    Article  PubMed  Google Scholar 

  • Fénelon, G. Psychosis in Parkinson’s disease: phenomenology, frequency, risk factors, and current understanding of pathophysiologic mechanisms. CNS Spectr. 13, 18–25 (2008).

    Article  PubMed  Google Scholar 

  • Fénelon, G., Soulas, T., Zenasni, F. & De Langavant, L. C. The changing face of Parkinson’s disease-associated psychosis: a cross-sectional study based on the new NINDS–NIMH criteria. Mov. Disord. 25, 755–759 (2010).

    Article  Google Scholar 

  • Ffytche, D. H. et al. The psychosis spectrum in Parkinson disease. Nat. Rev. Neurol. 13, 81–95 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  • Lenka, A., Hegde, S., Jhunjhunwala, K. R. & Pal, P. K. Interactions of visual hallucinations, rapid eye movement sleep behavior disorder and cognitive impairment in Parkinson’s disease: a review. Parkinsonism Relat. Disord. 22, 1–8 (2016).

    Article  PubMed  Google Scholar 

  • Bernasconi, F. et al. Theta oscillations and minor hallucinations in Parkinson’s disease reveal decrease in frontal lobe functions and later cognitive decline. Nat. Ment. Health 1, 477–488 (2023).

    Article  Google Scholar 

  • Lenka, A., Pagonabarraga, J., Pal, P. K., Bejr-Kasem, H. & Kulisvesky, J. Minor hallucinations in Parkinson disease: a subtle symptom with major clinical implications. Neurology 93, 259–266 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  • Fénelon, G., Mahieux, F., Huon, R. & Ziégler, M. Hallucinations in Parkinson’s disease: prevalence, phenomenology and risk factors. Brain 123, 733–745 (2000).

    Article  PubMed  Google Scholar 

  • Aarsland, D. et al. Parkinson disease-associated cognitive impairment. Nat. Rev. Dis. Primers 7, 47 (2021).

    Article  PubMed  Google Scholar 

  • Levin, J., Hasan, A. & Höglinger, G. U. Psychosis in Parkinson’s disease: identification, prevention and treatment. J. Neural Transm. 123, 45–50 (2016).

    Article  PubMed  Google Scholar 

  • Diederich, N. J., Fénelon, G., Stebbins, G. & Goetz, C. G. Hallucinations in Parkinson disease. Nat. Rev. Neurol. 5, 331–342 (2009).

    Article  PubMed  Google Scholar 

  • Forsaa, E. B., Larsen, J. P., Wentzel-Larsen, T. & Alves, G. What predicts mortality in Parkinson disease? A prospective population-based long-term study. Neurology 75, 1270–1276 (2010).

    Article  PubMed  Google Scholar 

  • Galvin, J. E., Pollack, J. & Morris, J. C. Clinical phenotype of Parkinson disease dementia. Neurology 67, 1605–1611 (2006).

    Article  PubMed  Google Scholar 

  • Marinus, J., Zhu, K., Marras, C., Aarsland, D. & van Hilten, J. J. Risk factors for non-motor symptoms in Parkinson’s disease. Lancet Neurol. 17, 559–568 (2018).

    Article  PubMed  Google Scholar 

  • Aarsland, D., Larsen, J. P., Tandberg, E. & Laake, K. Predictors of nursing home placement in Parkinson’s disease: a population-based, prospective study. J. Am. Geriatr. Soc. 48, 938–942 (2000).

    Article  PubMed  Google Scholar 

  • Goetz, C. G., Emre, M. & Dubois, B. Parkinson’s disease dementia: definitions, guidelines, and research perspectives in diagnosis. Ann. Neurol. 64, S81–92 (2008).

    Article  PubMed  Google Scholar 

  • Gonzalez, M. C., Dalen, I., Maple-Grødem, J., Tysnes, O.-B. & Alves, G. Parkinson’s disease clinical milestones and mortality. npj Parkinsons Dis. 8, 58 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  • Lenka, A., Jhunjhunwala, K. R., Saini, J. & Pal, P. K. Structural and functional neuroimaging in patients with Parkinson’s disease and visual hallucinations: a critical review. Parkinsonism Relat. Disord. 21, 683–691 (2015).

    Article  PubMed  Google Scholar 

  • Goetz, C. G., Vaughan, C. L., Goldman, J. G. & Stebbins, G. T. I finally see what you see: Parkinson’s disease visual hallucinations captured with functional neuroimaging. Mov. Disord. 29, 115–117 (2014).

    Article  PubMed  Google Scholar 

  • Bhome, R., Thomas, G. E. C., Zarkali, A. & Weil, R. S. Structural and functional imaging correlates of visual hallucinations in Parkinson’s Disease. Curr. Neurol. Neurosci. Rep. 23, 287–299 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  • Shine, J. M., Halliday, G. M., Naismith, S. L. & Lewis, S. J. G. Visual misperceptions and hallucinations in Parkinson’s disease: dysfunction of attentional control networks? Mov. Disord. 26, 2154–2159 (2011).

    Article  PubMed  Google Scholar 

  • Shine, J. M., O’Callaghan, C., Halliday, G. M. & Lewis, S. J. G. Tricks of the mind: visual hallucinations as disorders of attention. Prog. Neurobiol. 116, 58–65 (2014).

    Article  PubMed  Google Scholar 

  • Shine, J. M. et al. Abnormal connectivity between the default mode and the visual system underlies the manifestation of visual hallucinations in Parkinson’s disease: a task-based fMRI study. npj Parkinsons Dis. 1, 15003 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Weil, R. S. et al. Visual dysfunction in Parkinson’s disease. Brain 139, 2827–2843 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • Ravina, B. et al. Diagnostic criteria for psychosis in Parkinson’s disease: report of an NINDS, NIMH work group. Mov. Disord. 22, 1061–1068 (2007).

    Article  PubMed  Google Scholar 

  • Pagonabarraga, J. et al. Minor hallucinations occur in drug-naive Parkinson’s disease patients, even from the premotor phase. Mov. Disord. 31, 45–52 (2016).

    Article  PubMed  Google Scholar 

  • de Maindreville, A. D., Fénelon, G. & Mahieux, F. Hallucinations in Parkinson’s disease: a follow-up study. Mov. Disord. 20, 212–217 (2005).

    Article  PubMed  Google Scholar 

  • Bernasconi, F. et al. Robot-induced hallucinations in Parkinson’s disease depend on altered sensorimotor processing in fronto-temporal network. Sci. Transl. Med. 13, eabc8362 (2021).

    Article  PubMed  Google Scholar 

  • Zhong, M. et al. Aberrant gray matter volume and functional connectivity in Parkinson’s disease with minor hallucination. Front. Aging Neurosci. 14, 923560 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  • Bejr-kasem, H. et al. Minor hallucinations reflect early gray matter loss and predict subjective cognitive decline in Parkinson’s disease. Eur. J. Neurol. 28, 438–447 (2021).

    Article  PubMed  Google Scholar 

  • Baik, K. et al. Functional brain networks of minor and well-structured major hallucinations in Parkinson’s disease. Mov. Disord. 39, 318–327 (2024).

    Article  PubMed  Google Scholar 

  • Bejr-kasem, H. et al. Disruption of the default mode network and its intrinsic functional connectivity underlies minor hallucinations in Parkinson’s disease. Mov. Disord. 34, 78–86 (2019).

    Article  PubMed  Google Scholar 

  • Finn, E. S. et al. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nat. Neurosci. 18, 1664–1671 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Amico, E. & Goñi, J. The quest for identifiability in human functional connectomes. Sci. Rep. 8, 8254 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • da Silva Castanheira, J., Orozco Perez, H. D., Misic, B. & Baillet, S. Brief segments of neurophysiological activity enable individual differentiation. Nat. Commun. 12, 5713 (2021).

    Article  Google Scholar 

  • Finn, E. S. & Rosenberg, M. D. Beyond fingerprinting: choosing predictive connectomes over reliable connectomes. NeuroImage 239, 118254 (2021).

    Article  PubMed  Google Scholar 

  • Rosenberg, M. D. et al. A neuromarker of sustained attention from whole-brain functional connectivity. Nat. Neurosci. 19, 165–171 (2016).

    Article  PubMed  Google Scholar 

  • Kaufmann, T. et al. Delayed stabilization and individualization in connectome development are related to psychiatric disorders. Nat. Neurosci. 20, 513–515 (2017).

    Article  PubMed  Google Scholar 

  • Kaufmann, T. et al. Stability of the brain functional connectome fingerprint in individuals with schizophrenia. JAMA Psychiatry 75, 749–751 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Fu, Z., Liu, J., Salman, M. S., Sui, J. & Calhoun, V. D. Functional connectivity uniqueness and variability? Linkages with cognitive and psychiatric problems in children. Nat. Ment. Health 1, 956–970 (2023).

    Article  Google Scholar 

  • Sorrentino, P. et al. Clinical connectome fingerprints of cognitive decline. NeuroImage 238, 118253 (2021).

    Article  PubMed  Google Scholar 

  • Stampacchia, S. et al. Fingerprints of brain disease: connectome identifiability in Alzheimer’s disease. Commun. Biol. 7, 1169 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  • da Silva Castanheira, J. et al. The neurophysiological brain-fingerprint of Parkinson’s disease. eBioMedicine 105, 105201 (2024).

    Article  Google Scholar 

  • Troisi Lopez, E. et al. Fading of brain network fingerprint in Parkinson’s disease predicts motor clinical impairment. Hum. Brain Mapp. 44, 1239–1250 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  • Vignando, M. et al. Mapping brain structural differences and neuroreceptor correlates in Parkinson’s disease visual hallucinations. Nat. Commun. 13, 519 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  • Ballanger, B. et al. Serotonin 2A receptors and visual hallucinations in Parkinson disease. Arch. Neurol. 67, 416–421 (2010).

    Article  PubMed  Google Scholar 

  • Firbank, M. J. et al. Reduced occipital GABA in Parkinson disease with visual hallucinations. Neurology 91, e675–e685 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Pini, L., Lista, S., Griffa, A., Allali, G. & Imbimbo, B. P. Can brain network connectivity facilitate the clinical development of disease-modifying anti-Alzheimer drugs? Brain Commun. 7, fcae460 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  • Ramduny, J. & Kelly, C. Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction. Neuropsychopharmacology 50, 114–123 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  • Kim, N. Y. et al. Lesions causing hallucinations localize to one common brain network. Mol. Psychiatry 26, 1299–1309 (2021).

    Article  PubMed  Google Scholar 

  • Pagonabarraga, J. et al. Neural correlates of minor hallucinations in non-demented patients with Parkinson’s disease. Parkinsonism Relat. Disord. 20, 290–296 (2014).

    Article  PubMed  Google Scholar 

  • Moberget, T. & Ivry, R. B. Prediction, psychosis, and the cerebellum. Biol. Psychiatry Cogn. Neurosci. Neuroimaging 4, 820–831 (2019).

    PubMed  PubMed Central  Google Scholar 

  • Blanke, O. et al. Neurological and robot-controlled induction of an apparition. Curr. Biol. 24, 2681–2686 (2014).

    Article  PubMed  Google Scholar 

  • Bejr-Kasem, H. et al. The role of attentional control over interference in minor hallucinations in Parkinson’s disease. Parkinsonism Relat. Disord. 102, 101–107 (2022).

    Article  PubMed  Google Scholar 

  • Rajamani, N. et al. Deep brain stimulation of symptom-specific networks in Parkinson’s disease. Nat. Commun. 15, 4662 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  • Zarkali, A. et al. Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson’s disease. Commun. Biol. 5, 928 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  • Huot, P. et al. Increased 5-HT2A receptors in the temporal cortex of parkinsonian patients with visual hallucinations. Mov. Disord. 25, 1399–1408 (2010).

    Article  PubMed  Google Scholar 

  • Perry, E. K. & Perry, R. H. Acetylcholine and hallucinations: disease-related compared to drug-induced alterations in human consciousness. Brain Cogn. 28, 240–258 (1995).

    Article  PubMed  Google Scholar 

  • Pasquini, J., Brooks, D. J. & Pavese, N. The cholinergic brain in Parkinson’s disease. Mov. Disord. Clinical Practice 8, 1012–1026 (2021).

    Article  Google Scholar 

  • Albert, L., Potheegadoo, J., Herbelin, B., Bernasconi, F. & Blanke, O. Numerosity estimation of virtual humans as a digital-robotic marker for hallucinations in Parkinson’s disease. Nat. Commun. 15, 1905 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  • Bernasconi, F. et al. Neuroscience robotics for controlled induction and real-time assessment of hallucinations. Nat. Protoc. 17, 2966–2989 (2022).

    Article  PubMed  Google Scholar 

  • Gordon, E. M. et al. Precision functional mapping of individual human brains. Neuron 95, 791–807 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  • Postuma, R. B. et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov. Disord. 30, 1591–1601 (2015).

    Article  PubMed  Google Scholar 

  • Goetz, C. G. et al. Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov. Disord. 23, 2129–2170 (2008).

    Article  PubMed  Google Scholar 

  • Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L. & Petersen, S. E. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage 59, 2142–2154 (2012).

    Article  PubMed  Google Scholar 

  • Power, J. D. et al. Methods to detect, characterize, and remove motion artifact in resting state fMRI. NeuroImage 84, 320–341 (2014).

    Article  PubMed  Google Scholar 

  • Amico, E. et al. Mapping the functional connectome traits of levels of consciousness. NeuroImage 148, 201–211 (2017).

    Article  PubMed  Google Scholar 

  • Shen, X., Tokoglu, F., Papademetris, X. & Constable, R. T. Groupwise whole-brain parcellation from resting-state fMRI data for network node identification. NeuroImage 82, 403–415 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  • Greve, D. N. & Fischl, B. Accurate and robust brain image alignment using boundary-based registration. NeuroImage 48, 63–72 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  • Yeo, B. T. T. et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J. Neurophysiol. 106, 1125–1165 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  • Amico, E. et al. The disengaging brain: dynamic transitions from cognitive engagement and alcoholism risk. NeuroImage 209, 116515 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  • Amico, E. & Goñi, J. Mapping hybrid functional-structural connectivity traits in the human connectome. Netw. Neurosci. 2, 306–322 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Van De Ville, D., Farouj, Y., Preti, M. G., Liégeois, R. & Amico, E. When makes you unique: temporality of the human brain fingerprint. Sci. Adv. 7, eabj0751 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  • Stampacchia, S. et al. Fingerprinting of brain disease: connectome identifiability in Alzheimer’s disease. Commun. Biol. 7, 1169 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  • McGraw, K. O. & Wong, S. P. Forming inferences about some intraclass correlation coefficients. Psychol. Methods 1, 30–46 (1996).

  • Birn, R. M. et al. The effect of scan length on the reliability of resting-state fMRI connectivity estimates. NeuroImage 83, 550–558 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  • Somandepalli, K. et al. Short-term test–retest reliability of resting state fMRI metrics in children with and without attention-deficit/hyperactivity disorder. Dev. Cogn. Neurosci. 15, 83–93 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Shehzad, Z. et al. The resting brain: unconstrained yet reliable. Cereb. Cortex 19, 2209–2229 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  • Shah, L. M., Cramer, J. A., Ferguson, M. A., Birn, R. M. & Anderson, J. S. Reliability and reproducibility of individual differences in functional connectivity acquired during task and resting state. Brain Behav. 6, e00456 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • Noble, S., Scheinost, D. & Constable, R. T. A decade of test–retest reliability of functional connectivity: a systematic review and meta-analysis. NeuroImage 203, 116157 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  • Cicchetti, D. V. & Sparrow, S. A. Developing criteria for establishing interrater reliability of specific items: applications to assessment of adaptive behavior. Am. J. Ment. Defic. 86, 127–137 (1981).

    PubMed  Google Scholar 

  • Xia, M., Wang, J. & He, Y. BrainNet viewer: a network visualization tool for human brain connectomics. PLoS ONE 8, e68910 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  • Fernández de Bobadilla, R. et al. Parkinson’s disease-cognitive rating scale: psychometrics for mild cognitive impairment. Mov. Disord. 28, 1376–1383 (2013).

    Article  PubMed  Google Scholar 

  • Markello, R. D. et al. neuromaps: structural and functional interpretation of brain maps. Nat Methods 19, 1472–1479 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  • Savli, M. et al. Normative database of the serotonergic system in healthy subjects using multi-tracer PET. NeuroImage 63, 447–459 (2012).

    Article  PubMed  Google Scholar 

  • Kaller, S. et al. Test–retest measurements of dopamine D1-type receptors using simultaneous PET/MRI imaging. Eur. J. Nucl. Med. Mol. Imaging 44, 1025–1032 (2017).

    Article  PubMed  Google Scholar 

  • Alakurtti, K. et al. Long-term test–retest reliability of striatal and extrastriatal dopamine D2/3 receptor binding: study with [11C]raclopride and high-resolution PET. J. Cereb. Blood Flow Metab. 35, 1199–1205 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Dukart, J. et al. Cerebral blood flow predicts differential neurotransmitter activity. Sci. Rep. 8, 4074 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  • Naganawa, M. et al. First in human assessment of the novel M1 muscarinic acetylcholine receptor PET radiotracer 11C-LSN3172176. J. Nucl. Med. https://doi.org/10.2967/jnumed.120.246967 (2020).

  • Hillmer, A. T. et al. Imaging of cerebral α4β2* nicotinic acetylcholine receptors with (−)−[18F]Flubatine PET: implementation of bolus plus constant infusion and sensitivity to acetylcholine in human brain. NeuroImage 141, 71–80 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  • R: a language and environment for statistical computing. https://www.R-project.org/ (R Core Team, 2020).

  • MATLAB (The MathWorks Inc., 2022).

  • Frossard, J. & Renaud, O. Permutation tests for regression, ANOVA, and comparison of signals: the permuco package. J. Stat. Soft. 99, 1–32 (2021).

  • Sareen, E. et al. Exploring MEG brain fingerprints: evaluation, pitfalls, and interpretations. NeuroImage 240, 118331 (2021).

    Article  PubMed  Google Scholar 

  • Comments

    Leave a Reply

    Your email address will not be published. Required fields are marked *