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| Name | Class |
|---|---|
| University Hospital Bispebjerg and Frederiksberg | OTHER |
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The goal of this observational study is to investigate whether the healthy human brain shows a diversity of optimistic and pessimistic reward signals and whether changes in this distribution in Parkinson's disease (PD) can provide mechanistic insights into the cause of symptoms.
The main hypotheses it aims to test are:
Researchers will compare the diversity of optimistic and pessimistic dopamine reward signals in patients with PD and healthy participants to see if there is a skewed distribution of optimistic and pessimistic reward signals in PD. Participants will play a task probing reward- and movement related brain activity in an MRI scanner. Researchers will derive functional topographic maps of optimism/pessimism in VTA, substantia nigra pars compacta (SNc), striatum and cortical areas such as the anterior cingulate cortex (ACC).
In sub-study 1, participants will be tested on one study day where patients with PD are tested in the off-medication state (40 control participants, 40 patients with PD).
In sub-study 2, to test whether/how dopaminergic medication affects the distribution of optimism/pessimism, participants will be tested on two study days (30 control participants, 30 patients with PD). Patients with PD are tested one day in the off-medication state, another day in the on-medication state (order counterbalanced between patients with PD). Control participants are tested on two days without medication challenge to test for test-retest effects.
The dopamine system is tasked with motivating action and driving learning and thus lies at the core of adaptive behaviour. Whereas motivation of action has consistently been found to be impaired in Parkinson's disease (PD), less is known about the potential impairments of reward-based learning in PD.
In this project, investigators use reinforcement learning (RL) as a computational framework for understanding the role of dopamine in reward-based learning in health and in PD. RL can be defined as learning based on prior experiences. A core concept of RL is the reward prediction error (RPE). An RPE is the deviation between an obtained reward and an expected reward that an agent (e.g. a person) gets in a given environment. The RPE is used to update future expectations in similar situations. Thus, RPEs are critical for the agent's ability to adapt its behavior to the environment. These RPEs are signalled by dopamine neurons in the ventral tegmental area (VTA).
Recent advancements in the study of RL in mice have fundamentally changed our understanding of dopamine's role in reward-based learning. Dabney et al. (2020) discovered with single-cell recordings how dopamine signals in the VTA systematically differ in their RPE signals. They proposed a distributional RL (distRL) model where neurons can have diverse firing patterns. Neurons can be so-called "pessimistic" neurons which expect low rewards and can be positively surprised (as expressed by increased firing rate) by rewards that are even below-average, whereas "optimistic" neurons expect high rewards and can be negatively surprised (expressed by a decreased firing rate) even by above-average rewards. It remains to be examined whether distRL also applies to the dopamine system in the healthy human brain. Furthermore, if distRL does apply to the human brain, this framework might provide mechanistic insights into the cause of a range of different symptoms in PD.
The importance of dopamine is particularly prominent in PD, a progressive neurodegenerative disease, in which the progressive loss of dopamine neurons in the midbrain causes the classical motor symptoms (referred to as parkinsonism) and contributes to non-motor disturbances, such as apathy and cognitive slowing. PD is the second most frequent age-related neurodegenerative disorder and the global burden of PD has more than doubled over the last two decades mainly as a result of increasing numbers of older people.
Dopamine neurons have been suggested to be especially vulnerable to neurotoxicity. Interactive cascades of dopamine oxidation and mitochondrial stress due to aberrant calcium signaling are thought to be main causes of neurodegeneration. In this context, distRL and its representational implementation in dopaminergic cells leads to novel hypotheses: The pessimistic dopamine neurons (which are positively "surprised" by most outcomes and increase their firing rate) are exposed to higher oxidative mitochondrial stress over their lifetime than optimistic neurons and would thus be more prone to neurodegeneration than optimistic neurons. While the prominent motor symptoms are caused by massive degeneration in the SN, neurodegeneration in the less vulnerable VTA is less extensive, but still of relevant size. Consequently, already shortly after diagnosis, reward signaling in the VTA is significantly reduced. Thus, investigators of this project hypothesize that neurodegeneration in both the SN and VTA is biased towards "pessimistic" neurons. Consequently, for most reward outcomes in an environment, there are fewer neurons responding with dopamine release to an outcome (but the same number of neurons responding with a pause in firing). This results in a reduced overall dopamine response to most events, favouring anhedonia and apathy.
Investigators of this project will use functional magnetic resonance imaging (fMRI) and derive functional maps of optimism/pessimism. During the fMRI experiment, participants will be shown different stimuli ("cards") and, upon squeezing a grip-force device, they win or lose a small amount of money each time, accumulating money as they play. The different stimuli have different probabilities of leading to a reward or loss event which participants learn through observation. Some trials are forced-choice trials with only a single stimulus available, other trials are open-choice trials where participants get to choose between stimuli and can thus affect their accumulated earnings by choosing the stimuli that they have observed to be most beneficial.
The investigators will test the following main hypotheses:
In a second study-arm, investigators will also explore whether/how medication state affects the distribution of optimistic and pessimistic prediction error signals. Here, patients with PD are tested one day in the off-medication state, another day in the on-medication state (order counterbalanced between patients with PD). The pragmatic off-medication state implies that patients will not have taken their morning dose of antiparkinsonian medication before arrival. Control participants are tested on two days without medication challenge to test for test-retest effects.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with Parkinson's Disease | Inclusion criteria:
Exclusion criteria:
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| Healthy controls | Inclusion criteria
Exclusion criteria
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| Measure | Description | Time Frame |
|---|---|---|
| Topographic distribution of the degree of optimism or pessimism | The main outcome measure is the topographic distribution of the degree of optimism or pessimism of each voxel's prediction error signal across the brains' cortical and sub-cortical grey matter. Investigators focus on the dopaminergic midbrain regions VTA/SNc and their main target region, the striatum. In sub-study 1, this distribution will be compared between people with Parkinson's disease and healthy controls. In sub-study 2, the change in distribution between the off- and the on-medication state in patients with PD will be compared to the test-retest change in distribution in control participants. | Day 1 and Day 2 |
| Measure | Description | Time Frame |
|---|---|---|
| Movement Disorder Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS) | MDS-UPDRS total score (sum of all 4 sub-scores listed below, range 0-260; higher score = worse outcome) and all four sub-scores. Sub-scores include: Part l subscore: Non-Motor Aspects of Experiences of Daily Living (nM-EDL; range 0-52; higher score = worse outcome); Part ll sub-score: motor experiences of daily living (M-EDL; range 0-52; higher score = worse outcome); Part lll sub-score: motor examination (range 0-132; higher score = worse outcome); Part lV sub-score: motor complications (range 0-24; higher score = worse outcome). |
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PD PATIENTS:
Inclusion Criteria:
Exclusion Criteria:
HEALTHY CONTROLS:
Inclusion criteria:
Exclusion criteria:
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Patients with PD and healthy volunteers, who are age- and sex-matched to the PD group.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| David Meder, PhD | Contact | 004529892696 | davidm@drcmr.dk | |
| Ditte H Frantzen, MSc | Contact | 004542152404 | dittehf@drcmr.dk |
| Name | Affiliation | Role |
|---|---|---|
| David Meder, PhD | Danish Research Centre for Magnetic Resonance (DRCMR), Hvidovre Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Danish Research Centre for Magnetic Resonance (DRCMR), Hvidovre Hospital | Recruiting | Hvidovre | 2650 | Denmark |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25058111 | Background | Surmeier DJ, Graves SM, Shen W. Dopaminergic modulation of striatal networks in health and Parkinson's disease. Curr Opin Neurobiol. 2014 Dec;29:109-17. doi: 10.1016/j.conb.2014.07.008. Epub 2014 Jul 22. | |
| 17418429 | Background | Sulzer D. Multiple hit hypotheses for dopamine neuron loss in Parkinson's disease. Trends Neurosci. 2007 May;30(5):244-50. doi: 10.1016/j.tins.2007.03.009. Epub 2007 Apr 5. |
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The pseudonymized data can only be shared with a formal Data Processing Agreement and a formal approval by the Danish Data Protection agency in line with the requirements of the European General Data Protection Regulation. If complete anonymization can be achieved, individual data will be shared openly after study completion.
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| Day 1 and Day 2 |
| Major Depression Inventory (MDI) | Major Depression Inventory (MDI) total score (range 0-50; higher score = worse outcome) | Day 1 and Day 2 |
| Montreal Cognitive Assessment (MoCA) | Montreal Cognitive Assessment (MoCA) total score (range 0-30; higher score = better outcome) and sub-scores. Sub-scores include: Visuospatial/executive (range 0-5; higher score = better outcome); Naming (range 0-3; higher score = better outcome); Attention (range 0-6; higher score = better outcome); Language (range 0-3; higher score = better outcome); Abstraction (range 0-2; higher score = better outcome); Delayed recall (range 0-5; higher score = better outcome); Orientation (range 0-6; higher score = better outcome). Additionally, Memory Index Score (range 0-15; higher score = better outcome) is also examined. | PD patients: ON-medication (Day 1 or Day 2, counterbalanced). Healthy controls: Day 1. |
| Apathy Scale (AS) | Apathy Scale (AS) total score (range 0-42; higher score = worse outcome) | Day 1 and Day 2 |
| Lille Apathy Rating Scale (LARS) | Lille Apathy Rating Scale (LARS) total score (range -36-36; higher score = worse outcome), sub-scores and factoral sub-scores. Sub-scores include: everyday productivity (EP); interests (INT); initiative (INI); novelty seeking (NS); motivation (M); emotional responses (ER); concern (C); social life (SL); self awareness (SA). Factorial sub-scores include: intellectual curiosity (IC); emotion (E); action initiation (AI); self awareness (SA). All sub-scores and factorial sub-scores have a range -4-4 and a higher score means worse outcome. | Day 1 and Day 2 |
| Edinburgh Handedness Inventory (EHI) | Edinburgh Handedness Inventory (EHI) handedness category (L, R, A) and Laterality Quotient (range -100-100; less than -40 means left-handed (L), -40 to 40 means ambidextrous (A), greater than 40 means right-handed (R)). | PD patients: ON-medication (Day 1 or Day 2, counterbalanced). Healthy controls: Day 1. |
| Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease - Rating Scale (QUIP-RS) | Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease - Rating Scale (QUIP-RS) total score (range 0-112; higher score = worse outcome), total impulsive-compulsive disorder (ICD) score (range 0-64; higher score = worse outcome) and six sub-scores. Sub-scores include: sub-score A: Gambling (range 0-16; higher score = worse outcome), sub-score B: Sex (range 0-16; higher score = worse outcome), sub-score C: Buying (range 0-16; higher score = worse outcome), sub-score D: Eating (range 0-16; higher score = worse outcome), sub-score E: Hobbyism-Punding (range 0-32; higher score = worse outcome) and sub-score F: PD-Medication Use (range 0-16; higher score = worse outcome). | Day 1 and Day 2 |
| Snaith-Hamilton Pleasure Scale (SHAPS) | Snaith-Hamilton Pleasure Scale (SHAPS) total score (range 0-14; higher score = worse outcome) | Day 1 and Day 2 |
| Temporal Experience of Pleasure Scale (TEPS) | Temporal Experience of Pleasure Scale (TEPS) total score (range 18-108; higher score = better outcome) and two sub-scores. Sub-scores include: Anticipatory (ANT; range 10-60; higher score = better outcome) and consummatory (CON; range 8-48; higher score = better outcome). | Day 1 and Day 2 |
| Paired Associates Learning (PAL) from Cambridge Neuropsychological Testing Automated Battery (CANTAB), Total errors adjusted | Total errors adjusted (for expected errors on attempts that were not reached). | Day 1 and Day 2 |
| Paired Associates Learning (PAL) from Cambridge Neuropsychological Testing Automated Battery (CANTAB), Mean errors to success | Mean errors to success (number of trials required to locate the pattern(s) correctly). | Day 1 and Day 2 |
| Paired Associates Learning (PAL) from Cambridge Neuropsychological Testing Automated Battery (CANTAB), First attempt memory score | First attempt memory score (number of times a pattern was correctly recalled on the first attempt). | Day 1 and Day 2 |
| Paired Associates Learning (PAL) from Cambridge Neuropsychological Testing Automated Battery (CANTAB), Number of patterns reached | Number of patterns reached (number of patterns on the last problem being reached). | Day 1 and Day 2 |
| Neural activity (BOLD response) | Beyond the primary outcome measure (topographic distribution of the degree of optimism/pessimism of prediction error signals), other neural responses to experimental events (motor responses, contrasts between neural responses to winning vs. losing money) will be explored. | Day 1 and Day 2 |
| Response time | Time from stimulus presentation to response during fMRI task | Day 1 and Day 2 |
| Grip force | Maximally achieved grip force during responses | Day 1 and Day 2 |
| Response vigor | Maximally achieved vigor ("yank"/slope) of each grip response | Day 1 and Day 2 |
| 19230774 | Background | Bezprozvanny I. Calcium signaling and neurodegenerative diseases. Trends Mol Med. 2009 Mar;15(3):89-100. doi: 10.1016/j.molmed.2009.01.001. Epub 2009 Feb 21. |
| 30287051 | Background | GBD 2016 Parkinson's Disease Collaborators. Global, regional, and national burden of Parkinson's disease, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018 Nov;17(11):939-953. doi: 10.1016/S1474-4422(18)30295-3. Epub 2018 Oct 1. |
| 25870025 | Background | Sierra M, Carnicella S, Strafella AP, Bichon A, Lhommee E, Castrioto A, Chabardes S, Thobois S, Krack P. Apathy and Impulse Control Disorders: Yin & Yang of Dopamine Dependent Behaviors. J Parkinsons Dis. 2015;5(3):625-36. doi: 10.3233/JPD-150535. |
| 19127584 | Background | Obeso JA, Marin C, Rodriguez-Oroz C, Blesa J, Benitez-Temino B, Mena-Segovia J, Rodriguez M, Olanow CW. The basal ganglia in Parkinson's disease: current concepts and unexplained observations. Ann Neurol. 2008 Dec;64 Suppl 2:S30-46. doi: 10.1002/ana.21481. |
| 31942076 | Background | Dabney W, Kurth-Nelson Z, Uchida N, Starkweather CK, Hassabis D, Munos R, Botvinick M. A distributional code for value in dopamine-based reinforcement learning. Nature. 2020 Jan;577(7792):671-675. doi: 10.1038/s41586-019-1924-6. Epub 2020 Jan 15. |
| 9054347 | Background | Schultz W, Dayan P, Montague PR. A neural substrate of prediction and reward. Science. 1997 Mar 14;275(5306):1593-9. doi: 10.1126/science.275.5306.1593. |
| 30465864 | Background | Meder D, Herz DM, Rowe JB, Lehericy S, Siebner HR. The role of dopamine in the brain - lessons learned from Parkinson's disease. Neuroimage. 2019 Apr 15;190:79-93. doi: 10.1016/j.neuroimage.2018.11.021. Epub 2018 Nov 20. |
| 29505948 | Background | Stauffer WR. The biological and behavioral computations that influence dopamine responses. Curr Opin Neurobiol. 2018 Apr;49:123-131. doi: 10.1016/j.conb.2018.02.005. Epub 2018 Mar 2. |