MétaCan
Menu
Back to cohort
Record W2916943068 · doi:10.1093/brain/awz010

Mesolimbic dopamine and anterior cingulate cortex connectivity changes lead to impulsive behaviour in Parkinson’s disease

2019· letter· en· W2916943068 on OpenAlexafffund
Antonio P. Strafella

Bibliographic record

VenueBrain · 2019
Typeletter
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity of TorontoCentre for Addiction and Mental HealthUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsParkinson's diseaseAnterior cingulate cortexNeuroscienceDopaminePsychologyCingulate cortexCortex (anatomy)DiseaseMedicineInternal medicineCentral nervous systemCognition

Abstract

fetched live from OpenAlex

This scientific commentary refers to ‘Dopamine metabolism of the nucleus accumbens and fronto-striatal connectivity modulate impulse control’, by Hammes et al.. (doi:10.1093/brain/awz007). Dopamine replacement therapy (DRT) in Parkinson’s disease may give rise to impulsive-compulsive behaviours (ICBs) (Ray and Strafella, 2013). These include pathological gambling, hypersexual behaviour, and compulsive shopping or eating, along with punding and dopamine dysregulation syndrome (Cilia and van Eimeren, 2011). In general, medicated patients with high trait impulsivity are also more susceptible to developing ICBs. ICBs that follow DRT are known as ‘behavioural addictions’ and show some similarities to chemical forms of addiction, suggesting an overlap in their neurobiology. ICBs are generally associated with dysfunction of specific brain regions within the mesocorticolimbic system, which is heavily involved in the modulation of behaviour, motivation, and decision-making (Probst and van Eimeren, 2013). Abnormalities have been shown in those pathways expressing mainly dopamine (Ray and Strafella, 2013). In fact, previous imaging studies in patients with Parkinson’s disease receiving DRT have suggested that decreased availability of the dopamine transporter (DAT) in the ventral striatum (i.e. nucleus accumbens) is often associated with (Cilia et al., 2010) or may even predate (Vriend et al., 2014) the increased risk of ICBs. Besides these dopaminergic changes, changes in functional connectivity in prefrontal-striatal loops, including in the anterior cingulate cortex (ACC), have also been reported (van Eimeren et al., 2010), along with abnormalities in cortical thickness (Tessitore et al., 2016). Together, these studies imply that the neural mechanisms associated with development of behavioural addictions span molecular to system and structural levels, and are complex and poorly understood. In this issue of Brain, Hammes and co-workers address this knowledge gap by testing the hypothesis that a reduction in dopaminergic projections to the nucleus accumbens (rather than a downregulation of DAT or an upregulation of synaptic dopamine excretion) may be responsible for the development of ICBs in Parkinson’s disease (Hammes et al., 2019). Using a multimodal neuroimaging approach (Fig. 1), Hammes et al. aimed to investigate the relationship between striatal dopamine synthesis, fronto-limbic connectivity and cortical thickness in patients with ICBs. To accomplish this, 80 participants (mean age: 68 ± 9.9 years) underwent resting state functional MRI and T1-weighted anatomical imaging. In 59 of the participants, 18F-DOPA-PET was also performed, and voxel-wise Patlak slopes, measuring dopamine synthesis capacity, were calculated. All participants completed the QUIP-RS questionnaire, a validated test to quantify severity of ICBs in Parkinson’s disease. In all, 18 of 62 patients (29%) were positive for at least one ICB category (three for gambling, 11 for hypersexuality, five for compulsive shopping and 10 for compulsive eating) and seven patients were positive for more than one category. A voxel-wise correlation analysis between dopamine synthesis capacity and QUIP-RS score was conducted for striatal regions. Voxel-wise correlations were also performed to investigate the relationship between symptom severity and functional connectivity. Mesolimbic dopamine and cingulate cortex. Hammes et al. used a multimodal neuroimaging approach to investigate the neural origins of impulsive-compulsive behaviours in patients with Parkinson’s disease receiving dopamine replacement therapy. The results reveal a reduction of mesolimbic dopaminergic projections in conjunction with altered functional connectivity and structure of the anterior cingulate cortex. The results were quite compelling. A negative correlation was observed between dopamine synthesis capacity and QUIP-RS score in the nucleus accumbens, suggesting an impaired dopamine synthesis capacity. Not surprisingly, those patients with more severe ICBs had weaker functional connectivity between the nucleus accumbens and the rostral ACC. In addition, cortical thickness in the subgenual rostral ACC was positively correlated with ICB severity. Overall, these observations suggest that a reduction of mesolimbic dopaminergic projections in conjunction with dysfunctional connectivity and structure of the ACC—a region known to play a key role in behavioural addictions—may represent neurobiological risk factors for development of ICBs in patients receiving DRT (Fig. 1). These observations seem to confirm the similarities with other forms of addiction in the general population, where a reduction of dopamine synthesis capacity has also been found in binge eaters and cocaine abusers (Wu et al., 1997; Majuri et al., 2017). While the positive association between severity of ICB symptoms and reduced dopamine synthesis capacity seems at first glance to disagree with the ‘dopaminergic overdose’ theory of ICBs, in general the findings are in line with those of previous studies using molecular imaging and functional MRI in patients with Parkinson’s disease and behavioural addictions (Ray and Strafella, 2013). Given that a history of ICBs is a risk factor for developing behavioural addictions with DRT, it is tempting to speculate that a premorbid vulnerability of the dopaminergic terminals in the ventral striatum may help determine the future incidence of these behavioural complications in Parkinson’s disease. However, whether this vulnerability is the consequence of a pre-existing condition, a Parkinson’s disease-related neurodegeneration, or both, warrants further study. As in every study, there are a few limitations that may have influenced the outcomes. These include the fact that ICBs were not measured in all patients using standardized semi-structured interviews. In addition, while different types of ICBs (e.g. gambling, hypersexuality, compulsive shopping, compulsive eating) were considered together in the study, it is not clear to date whether these behavioural complications are associated with the same neural abnormalities. Patients also scored worse than controls on the Parkinson Neuropsychometric Dementia Assessment, raising the possibility that dementia may have influenced cognitive processing in these individuals. Despite these limitations, the findings by Hammes et al. provide key insights into the mechanisms underlying the development of behavioural addictions, and emphasize the role of a complex interaction between mesolimbic dopaminergic projections in the ventral striatum and altered functional connectivity and structure of the ACC. In addition, they set the stage for future exciting and larger scale research. Dopamine dysregulation syndrome: A dysfunction of the reward system observed with chronic use of dopaminergic medications. Patlak slope: A graphical analysis technique used to analyse pharmacokinetics of tracers. Punding: Stereotypical behaviour with repetitive handling and examining of objects. A.P.S. is supported by Canadian Institutes of Health Research (MOP-136778) and the Canada Research Chair Program. The author reports no competing interests.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0260.018
Insufficient payload (model declined to judge)0.0050.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.270
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueBrainSame topicNeurological disorders and treatmentsFrench-language works237,207