Learning from the past and expecting the future in Parkinsonism: dopaminergic influence on predictions about the timing of future events
Open accessAbstract
The prolonged reaction times seen in Parkinson's disease (PD) have been linked to a dopaminergic-dependent deficit in using prior information to prepare responses, but also have been explained by an altered temporal processing. However, an underlying cognitive mechanism linking dopamine, temporal processing and response preparation remains elusive. To address this, we studied PD patients, with or without medication, and age-matched healthy individuals using a variable foreperiod task requiring speeded responses to a visual stimulus occurring at variable onset-times, with block-wise changes in the temporal predictability of visual stimuli. Compared with controls, unmedicated patients showed impaired use of prior information to prepare their responses, as reflected by slower reaction times, regardless of the level of temporal predictability. Crucially, after dopamine administration normal performance was restored, with faster responses for high temporal predictability. Using Bayesian hierarchical drift-diffusion modelling, we estimated the parameters that determine temporal preparation. In this theoretical framework, impaired temporal preparation under dopaminergic depletion was driven by inflexibly high decision boundaries (i.e. participants were always extremely cautious). This indexes high levels of uncertainty about temporal predictions irrespectively of stimulus onset predictability. Our results suggest that dopaminergic depletion in PD affects the uncertainty of predictions about the timing of future events (temporal predictions), which are crucial for the anticipatory preparation of responses. Dopamine, which is affected in PD, controls the ability to predict the timing of future events.
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Previous research shows improvements in patients taking medications acting on the dopaminergic system.
“previous research showing improvements in patients taking medications acting on the dopaminergic system (Tomassini et al., 2019; Wolpe et al., 2015).”
From Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review. (2025) · cites this paper as Tomassini et al., 2019
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,588 · see citing works
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282 · see citing works
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,406 · see citing works
The Hospital Anxiety and Depression Scale
Zigmond, A. S., & Snaith, R. P. (1983) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.1983.tb09716.x · Cited by 47,139 · see citing works
Hirono, N., Mori, E., Ikejiri, Y., Imamura, T., Shimomura, T., Hashimoto, M., Yamashita, H., & Ikeda, M. (1997) · PubMed · Cited by 21,010 · see citing works
Kok, J. S., Berg, I. J., & Scherder, E. J. A. (2013) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000353441 · Cited by 20,589 · see citing works
Older Adults' Reasons for Using Technology while Aging in Place
Peek, S. T. M., Luijkx, K. G., Rijnaard, M. D., Nieboer, M. E., van der Voort, C. S., Aarts, S., van Hoof, J., Vrijhoef, H. J., & Wouters, E. (2015) · Gerontology · doi:10.1159/000430949 · Cited by 19,803 · see citing works
Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly
Kangas, M., Korpelainen, R., Vikman, I., Nyberg, L., & Jämsä, T. J. (2014) · Gerontology · doi:10.1159/000362720 · Cited by 19,003 · see citing works
Depression and quality of life in older persons: A review
Sivertsen, H., Bjørkløf, G. H., Engedal, K., Selbæk, G., & Helvik, A.-S. (2015) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000437299 · Cited by 14,152 · see citing works
Parkinsonism: onset, progression, and mortality
Hoehn, M. M., & Yahr, M. D. (1967) · Neurology · doi:10.1212/wnl.17.5.427 · Cited by 12,107 · see citing works
Overdependence on degraded gist memory in Alzheimer's disease.
Gallo, D. A., Shahid, K. R., Olson, M. A., Solomon, T. M., Schacter, D. L., & Budson, A. E. (2006) · Neuropsychology · doi:10.1037/0894-4105.20.6.625 · Cited by 4,756 · see citing works
Systematic review of levodopa dose equivalency reporting in Parkinson's disease
Tomlinson, C. L., Stowe, R. L., Patel, S., Rick, C., Gray, R. G., & Clarke, C. E. (2010) · Movement Disorders · doi:10.1002/mds.23429 · Cited by 4,219 · see citing works
Dopamine in motivational control: rewarding, aversive, and alerting
Bromberg-Martin, E. S., Matsumoto, M., & Hikosaka, O. (2010) · Neuron · doi:10.1016/j.neuron.2010.11.022 · Cited by 2,396 · see citing works
Design and Analysis: A Researcher's Handbook
Morgan, J. (2005) · Technometrics · doi:10.1198/tech.2005.s329 · Cited by 2,365 · see citing works
Discrete coding of reward probability and uncertainty by dopamine neurons
Fiorillo, C. D., Tobler, P. N., & Schultz, W. (2003) · Science · doi:10.1126/science.1077349 · Cited by 2,085 · see citing works
(1986) · Cited by 2,022 · see citing works
Foreperiod and simple reaction time.
Niemi, P., & Näätänen, R. (1981) · Psychological Bulletin · doi:10.1037/0033-2909.89.1.133 · Cited by 1,133 · see citing works
HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python
Wiecki, T. V., Sofer, I., & Frank, M. J. (2013) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2013.00014 · Cited by 1,047 · see citing works
Neuropharmacology of timing and time perception
Meck, W. H. (1996) · Cognitive Brain Research · doi:10.1016/0926-6410(96)00009-2 · Cited by 952 · see citing works
Bayesian decision theory in sensorimotor control
Kording, K. P., & Wolpert, D. M. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.05.003 · Cited by 866 · see citing works
Neuroanatomical and Neurochemical Substrates of Timing
Coull, J. T., Cheng, R., & Meck, W. H. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2010.113 · Cited by 801 · see citing works
Noise characteristics and prior expectations in human visual speed perception
Stocker, A. A., & Simoncelli, E. P. (2006) · Nature Neuroscience · doi:10.1038/nn1669 · Cited by 780 · see citing works
Temporal context calibrates interval timing
Jazayeri, M., & Shadlen, M. N. (2010) · Nature Neuroscience · doi:10.1038/nn.2590 · Cited by 773 · see citing works
Toward a neurobiology of temporal cognition: advances and challenges
Gibbon, J., Malapani, C., Dale, C. L., & Gallistel, C. R. (1997) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(97)80005-0 · Cited by 766 · see citing works
The neural basis of the speed–accuracy tradeoff
Bogacz, R., Wagenmakers, E., Forstmann, B. U., & Nieuwenhuis, S. (2009) · Trends in Neurosciences · doi:10.1016/j.tins.2009.09.002 · Cited by 721 · see citing works
Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold
Cavanagh, J. F., Wiecki, T. V., Cohen, M. X., Figueroa, C. M., Samanta, J., Sherman, S. J., & Frank, M. J. (2011) · Nature Neuroscience · doi:10.1038/nn.2925 · Cited by 647 · see citing works
Striatum and pre-SMA facilitate decision-making under time pressure
Forstmann, B. U., Dutilh, G., Brown, S. D., Neumann, J., von Cramon, D. Y., Ridderinkhof, K. R., & Wagenmakers, E. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0805903105 · Cited by 642 · see citing works
Nobre, A. C., Correa, Á., & Coull, J. T. (2007) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2007.07.006 · Cited by 561 · see citing works
Why Don't We Move Faster? Parkinson's Disease, Movement Vigor, and Implicit Motivation
Mazzoni, P., Hristova, A., & Krakauer, J. W. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.0264-07.2007 · Cited by 557 · see citing works
Frank, M. J., & O'Reilly, R. C. (2006) · Behavioral Neuroscience · doi:10.1037/0735-7044.120.3.497 · Cited by 472 · see citing works
Dopamine, affordance and active inference
Friston, K. J., Shiner, T., FitzGerald, T., Galea, J. M., Adams, R., Brown, H., Dolan, R. J., Moran, R., Stephan, K. E., & Bestmann, S. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002327 · Cited by 381 · see citing works
Self-citationNeural Mechanisms of Speed-Accuracy Tradeoff
Heitz, R. P., & Schall, J. D. (2012) · Neuron · doi:10.1016/j.neuron.2012.08.030 · Cited by 373 · see citing works
Cortico-striatal connections predict control over speed and accuracy in perceptual decision making
Forstmann, B. U., Anwander, A., Schäfer, A., Neumann, J., Brown, S. D., Wagenmakers, E., Bogacz, R., & Turner, R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1004932107 · Cited by 368 · see citing works
Midbrain dopamine neurons control judgment of time
Soares, S., Atallah, B. V., & Paton, J. J. (2016) · Science · doi:10.1126/science.aah5234 · Cited by 362 · see citing works
Time uncertainty in simple reaction time.
Klemmer, E. T. (1956) · Journal of Experimental Psychology · doi:10.1037/h0042317 · Cited by 308 · see citing works
Pathway-specific dopamine abnormalities in schizophrenia
Weinstein, J., Chohan, M. O., Slifstein, M., Kegeles, L., Moore, H., & Abi-Dargham, A. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.03.2104 · Cited by 275 · see citing works
The Speed-Accuracy Tradeoff in the Elderly Brain: A Structural Model-Based Approach
Forstmann, B. U., Tittgemeyer, M., Wagenmakers, E., Derrfuß, J., Imperati, D., & Brown, S. D. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.0309-11.2011 · Cited by 252 · see citing works
Assessment of Parkinsonʼs Disease
Larsen, T., Calne, S. M., & Calne, D. B. (1984) · Clinical Neuropharmacology · doi:10.1097/00002826-198406000-00008 · Cited by 230 · see citing works
A neural mechanism of speed-accuracy tradeoff in macaque area LIP
Hanks, T., Kiani, R., & Shadlen, M. N. (2014) · eLife · doi:10.7554/elife.02260 · Cited by 222 · see citing works
Optimal policy for value-based decision-making
Tajima, S., Drugowitsch, J., & Pouget, A. (2016) · Nature Communications · doi:10.1038/ncomms12400 · Cited by 209 · see citing works
Hallucinations and perceptual inference
Friston, K. J. (2005) · Behavioral and Brain Sciences · doi:10.1017/s0140525x05290131 · Cited by 196 · cited 1× · see citing works
“A Bayesian model of hallucinations posits that dopaminergic up-regulation can lead to a systematic underestimation of the uncertainty of predictions resulting in hallucinatory percepts reflecting excessive biases toward sensory expectations (Friston, 2005).”
BackgroundA perceptual inference mechanism for hallucinations linked to striatal dopamine
Cassidy, C. M., Balsam, P. D., Weinstein, J. J., Rosengard, R. J., Slifstein, M., Daw, N. D., Abi-Dargham, A., & Horga, G. (2018) · Current Biology · doi:10.1016/j.cub.2017.12.059 · Cited by 176 · see citing works
Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing
Acerbi, L., Wolpert, D. M., & Vijayakumar, S. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002771 · Cited by 161 · see citing works
Temporally Extended Dopamine Responses to Perceptually Demanding Reward-Predictive Stimuli
Nomoto, K., Schultz, W., Watanabe, T., & Sakagami, M. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.4828-09.2010 · Cited by 158 · see citing works
MOVEMENT VARIABILITY AND BRADYKINESIA IN PARKINSON'S DISEASE
Sheridan, M. R., & Flowers, K. A. (1990) · Brain · doi:10.1093/brain/113.4.1149 · Cited by 147 · see citing works
Näätänen, R. (1970) · Acta Psychologica · doi:10.1016/0001-6918(70)90035-1 · Cited by 141 · see citing works
Banca, P., Vestergaard, M. D., Rankov, V., Baek, K., Mitchell, S., Lapa, T. R., Castelo-Branco, M. S., & Voon, V. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2014.303 · Cited by 138 · see citing works
Dopamine neurons code subjective sensory experience and uncertainty of perceptual decisions
de Lafuente, V., & Romo, R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117636108 · Cited by 117 · see citing works
Application of the diffusion model to two-choice tasks for adults 75-90 years old.
Ratcliff, R., Thapar, A., & McKoon, G. (2007) · Psychology and Aging · doi:10.1037/0882-7974.22.1.56 · Cited by 106 · see citing works
Motor and cognitive performances of parkinsonian patients in the on and off phases of the disease.
Girotti, F., Carella, F., Grassi, M. P., Soliveri, P., Marano, R., & CARACENI, T. (1986) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.49.6.657 · Cited by 104 · see citing works
Zhang, J., Rittman, T., Nombela, C., Fois, A. F., Coyle-Gilchrist, I. T. S., Barker, R. A., Hughes, L. E., & Rowe, J. B. (2015) · Brain · doi:10.1093/brain/awv331 · Cited by 101 · see citing works
Distinct mechanisms mediate speed-accuracy adjustments in cortico-subthalamic networks
Herz, D. M., Tan, H., Brittain, J., Fischer, P., Cheeran, B., Green, A. L., FitzGerald, J. J., Aziz, T. Z., Ashkan, K., Little, S. J., et al. (2017) · eLife · doi:10.7554/elife.21481 · Cited by 99 · see citing works
STARKSTEIN, S. E., Esteguy, M., Berthier, M. L., Garcia, H., & Leiguarda, R. C. (1989) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.52.3.338 · Cited by 82 · see citing works
Jahanshahi, M., Brown, R. G., & MARSDEN, C. D. (1992) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.55.12.1168 · Cited by 78 · see citing works
Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
Ahrens, M. B., & Sahani, M. (2011) · Current Biology · doi:10.1016/j.cub.2010.12.043 · Cited by 68 · see citing works
Separation of phasic arousal and expectancy effects in a speeded reaction time task via fMRI
Hackley, S. A., Langner, R., Rolke, B., Erb, M., Grodd, W., & Ulrich, R. (2008) · Psychophysiology · doi:10.1111/j.1469-8986.2008.00722.x · Cited by 60 · see citing works
Usefulness of movement time in the assessment of Parkinson's disease
Zappia, M., Montesanti, R., Colao, R., & Quattrone, A. (1994) · Journal of Neurology · doi:10.1007/bf00873517 · Cited by 58 · see citing works
Reduced pupillary reward sensitivity in Parkinson’s disease
Manohar, S., & Husain, M. (2015) · npj Parkinson's Disease · doi:10.1038/npjparkd.2015.26 · Cited by 56 · see citing works
A Bayesian hierarchical diffusion model decomposition of performance in Approach–Avoidance Tasks
Krypotos, A., Beckers, T., Kindt, M., & Wagenmakers, E. (2014) · Cognition & Emotion · doi:10.1080/02699931.2014.985635 · Cited by 54 · see citing works
Dopamine neurons encode errors in predicting movement trigger occurrence
Pasquereau, B., & Turner, R. S. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00401.2014 · Cited by 53 · see citing works
Galea, J. M., Bestmann, S., Beigi, M., Jahanshahi, M., & Rothwell, J. C. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.3621-11.2012 · Cited by 52 · see citing works
Self-citationThe Role of Dopamine in Temporal Uncertainty
Tomassini, A., Ruge, D., Galea, J. M., Penny, W. D., & Bestmann, S. (2015) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00880 · Cited by 48 · see citing works
Self-citationPatients with Parkinson’s Disease Show Impaired Use of Priors in Conditions of Sensory Uncertainty
Perugini, A., Ditterich, J., & Basso, M. A. (2016) · Current Biology · doi:10.1016/j.cub.2016.05.039 · Cited by 41 · see citing works
Hadj‐Bouziane, F., Bénatru, I., Brovelli, A., Klinger, H., Thobois, S., Broussolle, E., Boussaoud, D., & Meunier, M. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00351 · Cited by 30 · see citing works
Mamassian, P., & Landy, M. S. (2010) · Nature Neuroscience · doi:10.1038/nn0810-914 · Cited by 25 · see citing works
Strategies in probabilistic feedback learning in Parkinson patients OFF medication
Bellebaum, C., Kobza, S., Ferrea, S., Schnitzler, A., Pollok, B., & Südmeyer, M. (2016) · Neuroscience · doi:10.1016/j.neuroscience.2016.01.060 · Cited by 9 · see citing works
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1 of the 67 references couldn’t be matched to a known paper.
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Reduced drift rate: a biomarker of impaired information processing in functional movement disorders
Sadnicka, A., Daum, C., Meppelink, A.-M., Manohar, S., & Edwards, M. J. (2019) · Brain · doi:10.1093/brain/awz387 · Cited by 48 · see citing works
Self-citationFMTP: A unifying computational framework of temporal preparation across time scales.
Salet, J. M., Kruijne, W., van Rijn, H., Los, S. A., & Meeter, M. (2022) · Psychological Review · doi:10.1037/rev0000356 · Cited by 38 · see citing works
Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review.
Qela, B., Damiani, S., De Santis, S., Groppi, F., Pichiecchio, A., Asteggiano, C., Brondino, N., Monteleone, A. M., Grassi, L., Politi, P., et al. (2025) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2025.106020 · Cited by 26 · see citing works
“This observation is in contrast with previous research showing improvements in patients taking medications acting on the dopaminergic system (Tomassini et al., 2019; Wolpe et al., 2015).”
The temporal context in bayesian models of interval timing: Recent advances and future directions.
Sadibolova, R., & Terhune, D. B. (2022) · Behavioral Neuroscience · doi:10.1037/bne0000513 · Cited by 14 · see citing works
Chassignolle, M., Jovanović, L., Schmidt‐Mutter, C., Behr, G., Giersch, A., & Coull, J. T. (2021) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01700 · Cited by 12 · see citing works
Behroozmand, R., & Johari, K. (2019) · Behavioural Brain Research · doi:10.1016/j.bbr.2019.111939 · Cited by 11 · see citing works
A proxy measure of striatal dopamine predicts individual differences in temporal precision
Sadibolova, R., Monaldi, L., & Terhune, D. B. (2022) · Psychonomic Bulletin & Review · doi:10.3758/s13423-022-02077-1 · Cited by 10 · see citing works
Review: Subjective Time Perception, Dopamine Signaling, and Parkinsonian Slowness
Miyawaki, E. K. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.927160 · Cited by 10 · see citing works
Impaired sensory evidence accumulation and network function in Lewy body dementia
O’Callaghan, C., Firbank, M., Tomassini, A., Schumacher, J., O'Brien, J. T., & Taylor, J. (2021) · Brain Communications · doi:10.1093/braincomms/fcab089 · Cited by 8 · see citing works
Self-citationTrempler, I., Bürkner, P.-C., El-Sourani, N., Binder, E., Reker, P., Fink, G. R., & Schubotz, R. I. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116674 · Cited by 6 · see citing works
Parkinson’s disease impairs cortical sensori-motor decision-making cascades
Tomassini, A., Cope, T., Zhang, J., & Rowe, J. B. (2024) · Brain Communications · doi:10.1093/braincomms/fcae065 · Cited by 2 · see citing works
Self-citationHow Does Temporal Blurring Alter Movement Timing?
Drążyk, D., & Missal, M. (2023) · eNeuro · doi:10.1523/eneuro.0496-22.2023 · Cited by 1 · see citing works
The neurobiology of normal and pathological prior beliefs during cognitive control
Rondot, L. (2020) · theses.fr (ABES) · doi:10.70675/de55dc43ze329z41adz92f4z21076f73ccf6
Dopaminergic modulation of the sense of agency influences moral behavior in Parkinson’s disease
Ponsi, G., Villa, R., Vico, I. A. D., Panasiti, M. S., Schepisi, M., Tinazzi, M., & Aglioti, S. M. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2513356123
Buikema, L., Sadikov, A., Jahanshahi, M., Vinke, S., & Georgiev, D. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106719
Schoenfeld, M. J., Burke, R., Schneider, T. R., & Engel, A. K. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1790156
- Authors
- Tomassini, A., Pollak, T. A., Edwards, M. J., & Bestmann, S.
- Affiliations
- MRC Cognition and Brain Sciences Unit (GB)
- King's College London (GB)
- St George's, University of London (GB)
- University College London (GB)
- Corresponding author
- Tomassini, Alessandro
- Venue
- Neuropsychologia
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 127
- Pages
- 9-18
- ISSN
- 0028-3932 (ISSN-L)
- PMC
- PMC6456720
- OpenAlex
- W2914826980
- Cited by
- 16
- References
- 67
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 4 · 2021: 2 · 2020: 2 · 2019: 2
- FWCI
- 1.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Neuropsychologia (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- St George's Online Research Archive (St George's University of London) (acceptedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- European Research Council (260424)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- Parkinson's disease, parkinsonism, dopamine, temporal prediction, temporal processing, response preparation, prior information, temporal predictability, decision boundaries, dopaminergic therapy
- MeSH terms
- Aged, Cognition, Decision Making, Dopamine, Female, Humans, Male, Middle Aged, Photic Stimulation, Psychomotor Performance, Reaction Time, Parkinsonian Disorders, Uncertainty, Anticipation, Psychological
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