Preoperative cognitive profile predictive of cognitive decline after subthalamic deep brain stimulation in Parkinson's disease

. 2024 Oct ; 60 (7) : 5764-5784. [epub] 20240830

Jazyk angličtina Země Francie Médium print-electronic

Typ dokumentu časopisecké články, pozorovací studie

Perzistentní odkaz   https://www.medvik.cz/link/pmid39212074

Grantová podpora
AZVNV19-04-00233 Czech Ministry of Health
GAUK254121 Grant Agency of Charles University
LX22NPO5107 National Institute for Neurological Research
European Union - Next Generation EU
Charles University: Cooperatio Program in Neuroscience

Cognitive decline represents a severe non-motor symptom of Parkinson's disease (PD) that can significantly reduce the benefits of subthalamic deep brain stimulation (STN DBS). Here, we aimed to describe post-surgery cognitive decline and identify pre-surgery cognitive profile associated with faster decline in STN DBS-treated PD patients. A retrospective observational study of 126 PD patients treated by STN DBS combined with oral dopaminergic therapy followed for 3.54 years on average (SD = 2.32) with repeated assessments of cognition was conducted. Pre-surgery cognitive profile was obtained via a comprehensive neuropsychological examination and data analysed using exploratory factor analysis and Bayesian generalized linear mixed models. On the whole, we observed a mild annual cognitive decline of 0.90 points from a total of 144 points in the Mattis Dementia Rating Scale (95% posterior probability interval [-1.19, -0.62]) with high inter-individual variability. However, true score changes did not reach previously reported reliable change cut-offs. Executive deficit was the only pre-surgery cognitive variable to reliably predict the rate of post-surgery cognitive decline. On the other hand, exploratory analysis of electrode localization did not yield any statistically clear results. Overall, our data and models imply mild gradual average annual post-surgery cognitive decline with high inter-individual variability in STN DBS-treated PD patients. Nonetheless, patients with worse long-term cognitive prognosis can be reliably identified via pre-surgery examination of executive functions. To further increase the utility of our results, we demonstrate how our models can help with disentangling true score changes from measurement error in future studies of post-surgery cognitive changes.

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Armstrong, M. J., & Okun, M. S. (2020). Diagnosis and treatment of Parkinson disease. Jama, 323(6), 548. https://doi.org/10.1001/jama.2019.22360

Barbosa, R., Guedes, L. C., Cattoni, M. B., Lobo, P. P., Caldas, A. C., Fabbri, M., Bastos, P., Valadas, A., Carvalho, H., Albuquerque, L., Reimão, S., Ferreira, A. G., Ferreira, J. J., Rosa, M. M., & Coelho, M. (2024). Long‐term follow‐up of subthalamic nucleus deep brain stimulation in patients with Parkinson's disease: An analysis of survival and disability milestones. Parkinsonism & Related Disorders, 118, 105921. https://doi.org/10.1016/j.parkreldis.2023.105921

Beck, A. T., Steer, R. A., & Brown, G. (1996). Beck depression inventory II. American Psychological Association (APA). https://doi.org/10.1037/t00742-000

Bezdicek, O., Lukavsky, J., Stepankova, H., Nikolai, T., Axelrod, B. N., Michalec, J., Růžička, E., & Kopecek, M. (2015). The Prague Stroop Test: Normative standards in older Czech adults and discriminative validity for mild cognitive impairment in Parkinson's disease. Journal of Clinical and Experimental Neuropsychology, 37(8), 794–807. https://doi.org/10.1080/13803395.2015.1057106

Bezdicek, O., Michalec, J., Nikolai, T., Havránková, P., Roth, J., Jech, R., & Růžička, E. (2015). Clinical validity of the Mattis dementia rating scale in differentiating mild cognitive impairment in Parkinson's disease and normative data. Dementia and Geriatric Cognitive Disorders, 39(5–6), 303–311. https://doi.org/10.1159/000375365

Bezdicek, O., Motak, L., Axelrod, B. N., Preiss, M., Nikolai, T., Vyhnalek, M., Poreh, A., & Ruzicka, E. (2012). Czech version of the trail making test: Normative data and clinical utility. Archives of Clinical Neuropsychology, 27(8), 906–914. https://doi.org/10.1093/arclin/acs084

Bezdicek, O., Stepankova, H., Axelrod, B. N., Nikolai, T., Sulc, Z., Jech, R., Růžička, E., & Kopecek, M. (2017). Clinimetric validity of the Trail Making Test Czech version in Parkinson's disease and normative data for older adults. The Clinical Neuropsychologist, 31(sup1), 42–60. https://doi.org/10.1080/13854046.2017.1324045

Bezdicek, O., Stepankova, H., Moták, L., Axelrod, B. N., Woodard, J. L., Preiss, M., Nikolai, T., Růžička, E., & Poreh, A. (2014). Czech version of Rey Auditory Verbal Learning test: Normative data. Aging, Neuropsychology, and Cognition, 21(6), 693–721. https://doi.org/10.1080/13825585.2013.865699

Bezdicek, O., Sulc, Z., Nikolai, T., Stepankova, H., Kopecek, M., Jech, R., & Růžička, E. (2017). A parsimonious scoring and normative calculator for the Parkinson's disease mild cognitive impairment battery. The Clinical Neuropsychologist, 31(6–7), 1231–1247. https://doi.org/10.1080/13854046.2017.1293161

Blume, J., Lange, M., Rothenfusser, E., Doenitz, C., Bogdahn, U., Brawanski, A., & Schlaier, J. (2017). The impact of white matter lesions on the cognitive outcome of subthalamic nucleus deep brain stimulation in Parkinson's disease. Clinical Neurology and Neurosurgery, 159, 87–92. https://doi.org/10.1016/j.clineuro.2017.05.023

Boel, J. A., Odekerken, V. J. J., Schmand, B. A., Geurtsen, G. J., Cath, D. C., Figee, M., van den Munckhof, P., de Haan, R. J., Schuurman, P. R., de Bie, R. M. A., Odekerken, V. J. J., Boel, J. A., van Laar, T., van Dijk, J. M. C., Mosch, A., Hoffmann, C. F. E., Nijssen, P. C. G., van Asseldonk, T., Beute, G. N., … de Bie, R. M. A. (2016). Cognitive and psychiatric outcome 3 years after globus pallidus pars interna or subthalamic nucleus deep brain stimulation for Parkinson's disease. Parkinsonism & Related Disorders, 33, 90–95. https://doi.org/10.1016/j.parkreldis.2016.09.018

Bove, F., Fraix, V., Cavallieri, F., Schmitt, E., Lhommée, E., Bichon, A., Meoni, S., Pélissier, P., Kistner, A., Chevrier, E., Ardouin, C., Limousin, P., Krack, P., Benabid, A. L., Chabardès, S., Seigneuret, E., Castrioto, A., & Moro, E. (2020). Dementia and subthalamic deep brain stimulation in Parkinson disease. Neurology, 95(4), e384–e392. https://doi.org/10.1212/wnl.0000000000009822

Bratsos, S. P., Karponis, D., & Saleh, S. N. (2018). Efficacy and safety of deep brain stimulation in the treatment of Parkinson's disease: A systematic review and meta‐analysis of randomized controlled trials. Cureus., 10, e3474. https://doi.org/10.7759/cureus.3474

Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258. https://doi.org/10.1177/0049124192021002005

Bucur, M., & Papagno, C. (2023). Deep brain stimulation in Parkinson disease: A meta‐analysis of the long‐term neuropsychological outcomes. Neuropsychology Review, 33(2), 307–346. https://doi.org/10.1007/s11065-022-09540-9

Burgess, P. W. (2014). Theory and methodology in executive function research. In P. Rabbitt (Ed.), Methodology of frontal and executive function (pp. 87–121). Psychology Press.

Bürkner, P.‐C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01

Bürkner, P.‐C., Gabry, J., & Vehtari, A. (2020). Efficient leave‐one‐out cross‐validation for Bayesian non‐factorized normal and Student‐t models. Computational Statistics, 36(2), 1243–1261. https://doi.org/10.1007/s00180-020-01045-4

Cappon, D., Gratwicke, J., Zrinzo, L., Akram, H., Hyam, J., Hariz, M., Limousin, P., Foltynie, T., & Jahanshahi, M. (2022). Deep brain stimulation of the nucleus basalis of Meynert for Parkinson's disease dementia: A 36 months follow up study. Movement Disorders Clinical Practice, 9(6), 765–774. https://doi.org/10.1002/mdc3.13510

Castrioto, A., Debû, B., Cousin, E., Pelissier, P., Lhommée, E., Bichon, A., Schmitt, E., Kistner, A., Meoni, S., Seigneuret, E., Chabardes, S., Krack, P., Moro, E., & Fraix, V. (2022). Long‐term independence and quality of life after subthalamic stimulation in Parkinson disease. European Journal of Neurology, 29(9), 2645–2653. https://doi.org/10.1111/ene.15436

Chung, S. J., Yoo, H. S., Lee, H. S., Lee, Y. H., Baik, K., Jung, J. H., Ye, B. S., Sohn, Y. H., & Lee, P. H. (2021). Baseline cognitive profile is closely associated with long‐term motor prognosis in newly diagnosed Parkinson's disease. Journal of Neurology, 268(11), 4203–4212. https://doi.org/10.1007/s00415-021-10529-2

Ciharova, M., Cígler, H., Dostálová, V., Šivicová, G., & Bezdicek, O. (2020). Beck depression inventory, second edition, Czech version: Demographic correlates, factor structure and comparison with foreign data. International Journal of Psychiatry in Clinical Practice, 24(4), 371–379. https://doi.org/10.1080/13651501.2020.1775854

Cinelli, C., Forney, A., & Pearl, J. (2022). A crash course in good and bad controls. Sociological Methods & Research, 53(3), 1071–1104. https://doi.org/10.1177/00491241221099552

Combs, H. L., Folley, B. S., Berry, D. T. R., Segerstrom, S. C., Han, D. Y., Anderson‐Mooney, A. J., Walls, B. D., & van Horne, C. (2015). Cognition and depression following deep brain stimulation of the subthalamic nucleus and Globus pallidus pars internus in Parkinson's disease: A meta‐analysis. Neuropsychology Review, 25(4), 439–454. https://doi.org/10.1007/s11065-015-9302-0

David, F. J., Munoz, M. J., & Corcos, D. M. (2020). The effect of STN DBS on modulating brain oscillations: Consequences for motor and cognitive behavior. Experimental Brain Research, 238(7–8), 1659–1676. https://doi.org/10.1007/s00221-020-05834-7

Defer, G.‐L., Widner, H., Marié, R.‐M., Rémy, P., & Levivier, M. (1999). Core assessment program for surgical interventional therapies in Parkinson's disease (CAPSIT‐PD). Movement Disorders, 14(4), 572–584. https://doi.org/10.1002/1531-8257(199907)14:4<572::AID-MDS1005>3.0.CO;2-C

Deffner, D., Rohrer, J. M., & McElreath, R. (2022). A causal framework for cross‐cultural generalizability. Advances in Methods and Practices in Psychological Science, 5(3), 25152459221106366. https://doi.org/10.1177/25152459221106366

Ewert, S., Plettig, P., Li, N., Chakravarty, M. M., Collins, D. L., Herrington, T. M., Kühn, A. A., & Horn, A. (2018). Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity. NeuroImage, 170, 271–282. https://doi.org/10.1016/j.neuroimage.2017.05.015

Filip, P., Mana, J., Lasica, A., Keller, J., Urgošík, D., May, J., Mueller, K., Jech, R., Bezdicek, O., & Růžička, F. (2024). Structural and microstructural predictors of cognitive decline in deep brain stimulation of subthalamic nucleus in Parkinson's disease. NeuroImage: Clinical, 42, 103617. https://doi.org/10.1016/j.nicl.2024.103617

Frydrychová, Z., Kopeček, M., Bezdicek, O., & Georgi Stepankova, H. (2018). Czech normative study of the Revised Rey Auditory Verbal Learning Test (RAVLT) in older adults. Ceskoslovenska Psychologie, 62(4), 330–349.

Gelman, A., Hill, J., & Yajima, M. (2012). Why we (usually) don't have to worry about multiple comparisons. Journal of Research on Educational Effectiveness, 5(2), 189–211. https://doi.org/10.1080/19345747.2011.618213

Gelman, A., & Vákár, M. (2021). Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data. Statistics in Medicine, 40(15), 3403–3424. https://doi.org/10.1002/sim.8973

Gruber, D., Calmbach, L., Kühn, A. A., Krause, P., Kopp, U. A., Schneider, G.‐H., & Kupsch, A. (2019). Longterm outcome of cognition, affective state, and quality of life following subthalamic deep brain stimulation in Parkinson's disease. Journal of Neural Transmission, 126(3), 309–318. https://doi.org/10.1007/s00702-019-01972-7

Harman, H. H., & Jones, W. H. (1966). Factor analysis by minimizing residuals (minres). Psychometrica, 31(3), 351–368. https://doi.org/10.1007/BF02289468

Hentz, J. G., Mehta, S. H., Shill, H. A., Driver‐Dunckley, E., Beach, T. G., & Adler, C. H. (2015). Simplified conversion method for unified Parkinson's disease rating scale motor examinations. Movement Disorders, 30(14), 1967–1970. https://doi.org/10.1002/mds.26435

Horn, A., & Kühn, A. A. (2015). Lead‐DBS: A toolbox for deep brain stimulation electrode localizations and visualizations. NeuroImage, 107, 127–135. https://doi.org/10.1016/j.neuroimage.2014.12.002

Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W.‐J., Reisert, M., Si, H., Oostenveld, R., Rorden, C., Yeh, F.‐C., Fang, Q., Herrington, T. M., Vorwerk, J., & Kühn, A. A. (2019). Lead‐DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage, 184, 293–316. https://doi.org/10.1016/j.neuroimage.2018.08.068

Hughes, A. J., Daniel, S. E., Kilford, L., & Lees, A. J. (1992). Accuracy of clinical diagnosis of idiopathic Parkinson's disease: A clinico‐pathological study of 100 cases. Journal of Neurology, Neurosurgery & Psychiatry, 55(3), 181–184. https://doi.org/10.1136/jnnp.55.3.181

Iannone, R. (2022). DiagrammeR: Graph/network visualization. https://CRAN.R-project.org/package=DiagrammeR

Jahanshahi, M., Leimbach, F., & Rawji, V. (2022). Short and long‐term cognitive effects of subthalamic deep brain stimulation in Parkinson's disease and identification of relevant factors. Journal of Parkinson's Disease, 12(7), 2191–2209. https://doi.org/10.3233/jpd-223446

Jech, R., Mueller, K., Urgosík, D., Sieger, T., Holiga, Š., Růžička, F., Dušek, P., Havránková, P., Vymazal, J., & Růžička, E. (2012). The subthalamic microlesion story in Parkinson's disease: Electrode insertion‐related motor improvement with relative cortico‐subcortical hypoactivation in fMRI. PLoS ONE, 7(11), e49056. https://doi.org/10.1371/journal.pone.0049056

Jech, R., Ruzicka, E., Ugosik, D., Serranova, T., Volfova, M., Novakova, O., Roth, J., Dusek, P., & Mecir, P. (2006). Deep brain stimulation of the subthalamic nucleus affects resting EEG and visual evoked potentials in Parkinson's disease. Clinical Neurophysiology, 117(5), 1017–1028. https://doi.org/10.1016/j.clinph.2006.01.009

John, K. D., Wylie, S. A., Dawant, B. M., Rodriguez, W. J., Phibbs, F. T., Bradley, E. B., Neimat, J. S., & van Wouwe, N. C. (2021). Deep brain stimulation effects on verbal fluency dissociated by target and active contact location. Annals of Clinical and Translational Neurology, 8(3), 613–622. https://doi.org/10.1002/acn3.51304

Josse, J., & Husson, F. (2016). missMDA: A package for handling missing values in multivariate data analysis. 70. https://doi.org/10.18637/jss.v070.i01

Jurica, P. J., Leitten, C. L., & Mattis, S. (2001). Dementia rating scale‐2 (DRS‐2) professional manual. Psychological Assessment Resources.

Kim, H.‐J., Jeon, B. S., Paek, S. H., Lee, K.‐M., Kim, J.‐Y., Lee, J.‐Y., Kim, H. J., Yun, J. Y., Kim, Y. E., Yang, H.‐J., & Ehm, G. (2014). Long‐term cognitive outcome of bilateral subthalamic deep brain stimulation in Parkinson's disease. Journal of Neurology, 261(6), 1090–1096. https://doi.org/10.1007/s00415-014-7321-z

Krishnan, S., Pisharady, K., Rajan, R., Sarma, S., Sarma, P., & Kishore, A. (2019). Predictors of dementia‐free survival after bilateral subthalamic deep brain stimulation for Parkinson's disease. Neurology India, 67(2), 459–466. https://doi.org/10.4103/0028-3886.258056

Limousin, P., Pollak, P., Benazzouz, A., Hoffmann, D., Le Bas, J., Broussolle, E., Perret, J., & Benabid, A. (1995). Effect of Parkinsonian signs and symptoms of bilateral subthalamic nucleus stimulation. Lancet (London, England), 345(8942), 91–95. https://doi.org/10.1016/s0140-6736(95)90062-4

Litvan, I., Goldman, J. G., Tröster, A. I., Schmand, B. A., Weintraub, D., Petersen, R. C., Mollenhauer, B., Adler, C. H., Marder, K., Williams‐Gray, C. H., Aarsland, D., Kulisevsky, J., Rodriguez‐Oroz, M. C., Burn, D. J., Barker, R. A., & Emre, M. (2012). Diagnostic criteria for mild cognitive impairment in Parkinson's disease: Movement Disorder Society Task Force guidelines. Movement Disorders, 27(3), 349–356. https://doi.org/10.1002/mds.24893

Lofredi, R., Auernig, C.‐G., Ewert, S., Irmen, F., Steiner, L. A., Scheller, U., van Wijk, B. C. M., Oxenford, S., Kühn, A. A., & Horn, A. (2022). Interrater reliability of deep brain stimulation electrode localizations. NeuroImage, 262, 119552. https://doi.org/10.1016/j.neuroimage.2022.119552

Lopez, F. V., Kenney, L. E., Ratajska, A., Jacobson, C. E., & Bowers, D. (2021). What does the Dementia Rating Scale‐2 measure? The relationship of neuropsychological measures to DRS‐2 total and subscale scores in non‐demented individuals with Parkinson's disease. The Clinical Neuropsychologist, 37(1), 174–193. https://doi.org/10.1080/13854046.2021.1999505

Lundberg, I., Johnson, R., & Stewart, B. M. (2021). What is your estimand? Defining the target quantity connects statistical evidence to theory. American Sociological Review, 86(3), 532–565. https://doi.org/10.1177/00031224211004187

Mazancova, A. F., Růžička, E., Jech, R., & Bezdicek, O. (2020). Test the best: Classification accuracies of four cognitive rating scales for Parkinson's disease mild cognitive impairment. Archives of Clinical Neuropsychology, 35(7), 1069–1077. https://doi.org/10.1093/arclin/acaa039

McElreath, R. (2020). Statistical rethinking: A Bayesian course with examples in r and STAN. Chapman; Hall/CRC. https://doi.org/10.1201/9780429029608

Mehanna, R., Bajwa, J. A., Fernandez, H., & Wagle Shukla, A. A. (2017). Cognitive impact of deep brain stimulation on Parkinson's disease patients. Parkinson's Disease, 2017, 3085140. https://doi.org/10.1155/2017/3085140

Michalec, J., Bezdicek, O., Nikolai, T., Harsa, P., Jech, R., Silhan, P., Hyza, M., Ruzicka, E., & Shallice, T. (2017). A comparative study of Tower of London scoring systems and normative data. Archives of Clinical Neuropsychology., 32, 328–338. https://doi.org/10.1093/arclin/acw111

Nikolai, T., Stepankova, H., Michalec, J., Bezdicek, O., Horáková, K., Marková, H., Ruzicka, E., & Kopecek, M. (2015). Tests of verbal fluency, Czech normative study in older patients. Česká a Slovenská Neurologie a Neurochirurgie, 78(3), 292–299. https://doi.org/10.14735/amcsnn2015292

Park, T., & Casella, G. (2008). The Bayesian lasso. Journal of the American Statistical Association, 103(482), 681–686. https://doi.org/10.1198/016214508000000337

Parsons, T. D., Rogers, S. A., Braaten, A. J., Woods, S. P., & Tröster, A. I. (2006). Cognitive sequelae of subthalamic nucleus deep brain stimulation in Parkinson's disease: A meta‐analysis. The Lancet Neurology, 5(7), 578–588. https://doi.org/10.1016/s1474-4422(06)70475-6

Partington, J. E., & Leiter, R. G. (1949). Partington's pathways test. Psychological Service Center Journal, 1, 11–20.

Pedersen, T. L. (2020). Patchwork: The composer of plots. https://CRAN.R-project.org/package=patchwork

Pedraza, O., Smith, G. E., Ivnik, R. J., Willis, F. B., Ferman, T. J., Petersen, R. C., Graff‐Radford, N. R., & Lucas, J. A. (2007). Reliable change on the dementia rating scale. Journal of the International Neuropsychological Society, 13(4), 716–720. https://doi.org/10.1017/S1355617707070920

Petry‐Schmelzer, J. N., Krause, M., Dembek, T. A., Horn, A., Evans, J., Ashkan, K., Rizos, A., Silverdale, M., Schumacher, W., Sack, C., Loehrer, P. A., Fink, G. R., Fonoff, E. T., Martinez‐Martin, P., Antonini, A., Barbe, M. T., Visser‐Vandewalle, V., Ray‐Chaudhuri, K., Timmermann, L., … Sauerbier, A. (2019). Non‐motor outcomes depend on location of neurostimulation in Parkinson's disease. Brain, 142(11), 3592–3604. https://doi.org/10.1093/brain/awz285

Planche, V., Munsch, F., Pereira, B., De Schlichting, E., Vidal, T., Coste, J., Morand, D., De Chazeron, I., Derost, P., Debilly, B., Llorca, P.‐M., Lemaire, J.‐J., Marques, A., & Durif, F. (2018). Anatomical predictors of cognitive decline after subthalamic stimulation in Parkinson's disease. Brain Structure and Function, 223(7), 3063–3072. https://doi.org/10.1007/s00429-018-1677-2

Pollak, P., Benabid, A., Gross, C., Gao, D., Laurent, A., Benazzouz, A., Hoffmann, D., Gentil, M., & Perret, J. (1993). Effects of the stimulation of the subthalamic nucleus in Parkinson disease. Revue Neurologique, 149(3), 175–176.

R Core Team. (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/

Reich, M. M., Hsu, J., Ferguson, M., Schaper, F. L. W. V. J., Joutsa, J., Roothans, J., Nickl, R. C., Frankemolle‐Gilbert, A., Alberts, J., Volkmann, J., & Fox, M. D. (2022). A brain network for deep brain stimulation induced cognitive decline in Parkinson's disease. Brain, 145(4), 1410–1421. https://doi.org/10.1093/brain/awac012

Revelle, W. (2022). Psych: Procedures for psychological, psychometric, and personality research. https://CRAN.R-project.org/package=psych

Schupbach, W. M. M. (2005). Stimulation of the subthalamic nucleus in Parkinson's disease: A 5 year follow up. Journal of Neurology, Neurosurgery & Psychiatry, 76(12), 1640–1644. https://doi.org/10.1136/jnnp.2005.063206

Schüpbach, W. M. M., Maltête, D., Houeto, J. L., du Montcel, S. T., Mallet, L., Welter, M. L., Gargiulo, M., Béhar, C., Bonnet, A. M., Czernecki, V., Pidoux, B., Navarro, S., Dormont, D., Cornu, P., & Agid, Y. (2007). Neurosurgery at an earlier stage of Parkinson disease. Neurology, 68(4), 267–271. https://doi.org/10.1212/01.wnl.0000250253.03919.fb

Shallice, T. (1982). Specific impairments of planning. Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 298(1089), 199–209. https://doi.org/10.1098/rstb.1982.0082

Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis. Oxford University Press New York. https://doi.org/10.1093/acprof:oso/9780195152968.001.0001

Smeding, H. M. M., Speelman, J. D., Huizenga, H. M., Schuurman, P. R., & Schmand, B. (2009). Predictors of cognitive and psychosocial outcome after STN DBS in Parkinson's disease. Journal of Neurology, Neurosurgery & Psychiatry, 82(7), 754–760. https://doi.org/10.1136/jnnp.2007.140012

Specketer, K., Zabetian, C. P., Edwards, K. L., Tian, L., Quinn, J. F., Peterson‐Hiller, A. L., Chung, K. A., Hu, S.‐C., Montine, T. J., & Cholerton, B. A. (2019). Visuospatial functioning is associated with sleep disturbance and hallucinations in nondemented patients with Parkinson's disease. Journal of Clinical and Experimental Neuropsychology, 41(8), 803–813. https://doi.org/10.1080/13803395.2019.1623180

Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the state‐trait anxiety inventory. Consulting Psychologists Press.

Stan Development Team. (2020). Stan modeling language users guide and reference manual, version 2.21.0. http://mc-stan.org/

Thomson, G. (1951). The factorial analysis of human ability. University of London Press.

Tomlinson, C. L., Stowe, R., Patel, S., Rick, C., Gray, R., & Clarke, C. E. (2010). Systematic review of levodopa dose equivalency reporting in Parkinson's disease. Movement Disorders, 25(15), 2649–2653. https://doi.org/10.1002/mds.23429

Tuerlinckx, F., Rijmen, F., Verbeke, G., & De Boeck, P. (2006). Statistical inference in generalized linear mixed models: A review. British Journal of Mathematical and Statistical Psychology, 59(2), 225–255. https://doi.org/10.1348/000711005x79857

Urgosik, D., Jech, R., Ruzicka, E., Ruzicka, F., Liscák, R., & Vladyka, V. (2011). Deep brain stimulation in movement disorders: A Prague‐center experience. Casopis Lekaru Ceskych, 150(4‐5), 223–228.

Van Bork, R., Rhemtulla, M., Sijtsma, K., & Borsboom, D. (2022). A causal theory of error scores. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000521

van Zwet, E. W. (2019). A default prior for regression coefficients. Statistical Methods in Medical Research, 28(12), 3799–3807. https://doi.org/10.1177/0962280218817792

van Zwet, E. W., & Cator, E. A. (2021). The significance filter, the winner's curse and the need to shrink. Statistica Neerlandica, 75(4), 437–452. https://doi.org/10.1111/stan.12241

Vehtari, A., Simpson, D., Gelman, A., Yao, Y., & Gabry, J. (2015). Pareto smoothed importance sampling. 10.48550/ARXIV.1507.02646

Wechsler, D. (2010). Wechsler adult intelligence scale ‐ third revision. Hogrefe ‐ Testcentrum.

Wechsler, D. (2011). Wechsler memory scale ‐third edition abbreviated. Hogrefe ‐ Testcentrum.

Whitney, P., & Hinson, J. M. (2010). Measurement of cognition in studies of sleep deprivation (pp. 37–48). Elsevier. https://doi.org/10.1016/b978-0-444-53702-7.00003-8

Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. https://ggplot2.tidyverse.org

Wilke, C. O. (2024). Ggridges: Ridgeline plots in'ggplot2’. https://wilkelab.org/ggridges/

Wood, S. N., Scheipl, F., & Faraway, J. J. (2012). Straightforward intermediate rank tensor product smoothing in mixed models. Statistics and Computing, 23(3), 341–360. https://doi.org/10.1007/s11222-012-9314-z

Xu, Y., Qin, G., Tan, B., Fan, S., An, Q., Gao, Y., Fan, H., Xie, H., Wu, D., Liu, H., Yang, G., Fang, H., Xiao, Z., Zhang, J., Zhang, H., Shi, L., & Yang, A. (2023). Deep brain stimulation electrode reconstruction: Comparison between lead‐DBS and surgical planning system. Journal of Clinical Medicine, 12(5), 1781. https://doi.org/10.3390/jcm12051781

Yarkoni, T. (2020). The generalizability crisis. Behavioral and Brain Sciences, 45, e1. https://doi.org/10.1017/s0140525x20001685

Zhang, S., Heck, P. R., Meyer, M. N., Chabris, C. F., Goldstein, D. G., & Hofman, J. M. (2023). An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability. Proceedings of the National Academy of Sciences, 120(33), e2302491120. https://doi.org/10.1073/pnas.2302491120

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