Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.01.08.631868

Differential effects of dopamine and serotonin on reward and punishment processes in humans: A systematic review and meta-analysis

Abstract

ImportanceTo support treatment assignment, mechanistic biomarkers should be selectively sensitive to specific interventions. Here, we examine whether different components of reinforcement learning in humans satisfy this necessary precondition. We focus on pharmacological manipulations of dopamine and serotonin that form the backbone of first-line management of common mental illnesses such as depression and anxiety. ObjectiveTo perform a meta-analysis of pharmacological manipulations of dopamine and serotonin and examine whether they show distinct associations with reinforcement learning components in humans. Data SourcesOvid MEDLINE/PubMed, Embase, and PsycInfo databases were searched for studies published between January 1, 1946 and January 19, 2023 (repeated April 9, 2024, and October 15, 2024) investigating dopaminergic or serotonergic effects on reward/punishment processes in humans, according to PRISMA guidelines. Study SelectionStudies reporting randomized, placebo-controlled, dopaminergic or serotonergic manipulations on a behavioral outcome from a reward/punishment processing task in healthy humans were included. Data Extraction and SynthesisStandardized mean difference (SMD) scores were calculated for the comparison between each drug (dopamine/serotonin) and placebo on a behavioral reward or punishment outcome and quantified in random-effects models for overall reward/punishment processes and four main subcategories. Study quality (Cochrane Collaborations tool), moderators, heterogeneity, and publication bias were also assessed. Main Outcome(s) and Measure(s)Performance on reward/punishment processing tasks. ResultsIn total, 68 dopamine and 39 serotonin studies in healthy volunteers were included (Ndopamine=2291, Nplacebo=2284; Nserotonin=1491, Nplacebo=1523). Dopamine was associated with an increase in overall reward (SMD=0.18, 95%CI [0.09 0.28]) but not punishment function (SMD=-0.06, 95%CI [-0.26,0.13]). Serotonin was not meaningfully associated with overall punishment (SMD=0.22, 95%CI [-0.04,0.49]) or reward (SMD=0.02, 95%CI [-0.33,0.36]). Importantly, dopaminergic and serotonergic manipulations had distinct associations with subcomponents. Dopamine was associated with reward learning/sensitivity (SMD=0.26, 95%CI [0.11,0.40]), reward discounting (SMD=-0.08, 95%CI [-0.14,-0.01]) and reward vigor (SMD=0.32, 95%CI [0.11,0.54]). By contrast, serotonin was associated with punishment learning/sensitivity (SMD=0.32, 95%CI [0.05,0.59]), reward discounting (SMD=-0.35, 95%CI [-0.67,-0.02]), and aversive Pavlovian processes (within-subject studies only; SMD=0.36, 95%CI [0.20,0.53]). Conclusions and RelevancePharmacological manipulations of both dopamine and serotonin have measurable associations with reinforcement learning in humans. The selective associations with different components suggests that reinforcement learning tasks could form the basis of selective, mechanistically interpretable biomarkers to support treatment assignment. Key pointsO_ST_ABSQuestionC_ST_ABSDo pharmacological manipulations of dopamine and serotonin affect components of reinforcement learning in humans? FindingsUpregulating dopamine is associated with increased reward learning/sensitivity and reward response vigor, and decreased reward discounting. Upregulation of serotonin is associated with increased punishment learning/sensitivity and decreased reward discounting. MeaningPharmacological manipulations of dopamine and serotonin have dissociable associations with different components of reinforcement learning. This forms a necessary basis for the development of selective markers for treatment assignment.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mkrtchian, A., Qiu, Z., Abir, Y., Erdmann, T., Dercon, Q., Sedlinska, T., Browning, M., Costello, H., Huys, Q. J. M.. 2025-01-10. Differential effects of dopamine and serotonin on reward and punishment processes in humans: A systematic review and meta-analysis. https://doi.org/10.1101/2025.01.08.631868

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Enhanced cortical tracking of unfamiliar languages in both monolinguals and bilinguals

Humans routinely encounter speech in languages they have never heard, yet how the brain responds to such input and whether bilingual experience shapes this response remains unknown. Here, we used electroencephalography (EEG) and temporal response function (TRF) modeling to examine cortical tracking of the speech envelope in 24 English-monolingual and 24 English-Mandarin bilingual adults. Participants listened to naturally produced continuous speech in three languages: English (familiar to all), Mandarin (familiar to bilinguals only), and Vietnamese (unfamiliar to all). We report two main findings. First, both monolinguals and bilinguals showed enhanced cortical tracking for unfamiliar relative to familiar languages, evidenced by higher EEG prediction accuracy (PA). Monolinguals showed enhanced tracking for both Mandarin and Vietnamese, whereas bilinguals showed enhancement only for Vietnamese, consistent with Mandarin being a familiar language for this group. This finding suggests that enhanced cortical encoding of unfamiliar speech is a general property of the listening brain, not a signature of listening to a non-native language or reduced language proficiency. Second, bilinguals strikingly showed stronger cortical tracking than monolinguals overall, in both PA and TRF peak weights, with the TRF peak weight advantage present across all three languages, suggesting a difference in how bilingual experience shapes the neural encoding of speech. These findings have implications for understanding how the brain navigates the linguistic diversity of everyday life in an increasingly global, multilingual world.

neuroscience↗

Endosomal pH Triggers Amyloid β Oligomerization and Maladaptive Phenotypic Plasticity in Alzheimers Disease

Endosomal dysfunction is a presymptomatic hallmark of neurodegeneration. Recent evidence highlights dysregulation of endosomal pH as a central pathogenic hub in Alzheimer's disease (AD); however, the mechanisms linking pH shifts to neurodegeneration remain incompletely defined. Here, we use a quantitative model of endosomal acidification driven by proton pumping via the vacuolar ATPase, proton leak via the endosomal Na/H exchanger NHE6, and other ion-regulating elements. The model recapitulates how downregulation of NHE6 in AD promotes endosomal hyperacidification, potentially triggering maladaptive phenotypic plasticity, an initially adaptive response that becomes pathological. Analysis of human brain datasets reveals reciprocal enrichment of NHE6 in neurons and the related NHE9 in glia, with NHE6 co-expression networks enriched for synaptic signalling. Systematic curation of NHE6 patient variants indicates that loss-of-function is associated with late regression, consistent with progressive endosomal hyperacidification, supporting a conceptual framework where early compensation transitions to neurodegeneration. Mathematical analyses calibrated for neuronal endosomes reveal a saturable relationship between luminal pH and NHE6 dosage, with threshold-like behaviour below ~50% expression that hyperacidifies endosomes, correlating with AD severity. Our model suggests this pH shift may exponentially accelerate A{beta} oligomerization and enhance {beta}-secretase activity. Furthermore, A{beta} oligomerization estimates correlate with dysregulation of calcium signalling and synaptic dysfunction. Model findings are compared with experimental results from NHE6-null mice and a cell culture model of AD. Drawing parallels to cancer, we propose that endosomal pH serves as a conserved regulator of adaptive-to-maladaptive transitions. Restoring physiological endosomal pH may offer a therapeutic window to prevent irreversible neurodegeneration in AD.

neuroscience↗

Diet Quality from Midlife to Later Life Relates to Late-Life Brain Health and Verbal Memory in the SG70 Cohort

Healthy diet across adulthood is associated with better late-life cognition, but how life-course diet quality relates to brain integrity, and whether brain measures mediate diet-cognition associations, remains unclear as studies with long-term diet records and detailed neurocognitive measures are lacking. We studied 892 participants from the SG70 study, nested within the Singapore Chinese Health Study, with adherence to the Dietary Approaches to Stop Hypertension diet (DASH) assessed between 1993--2025. Dietary quality during midlife, ages 44--55 years, and early elderhood, ages 61--73 years, was examined in relation to seven cognitive domains, brain morphometry, white matter hyperintensities and free-water MRI markers in late life, ages 68--82 years. Higher DASH adherence at both life stages was significantly associated with better late-ife verbal memory, and remained so when both life stages were modelled jointly. Higher midlife DASH adherence was associated with greater white matter volume in association tracts, whereas higher early-elderhood DASH adherence was associated with lower white matter hyperintensity (deep basal ganglia and anterior periventricular regions) and lower frontal and occipital grey matter free water, suggesting lower neurovascular and inflammatory burden. Mediation analyses indicated that white matter volume accounted for 12.3% in mediating the midlife DASH--verbal memory association, while cortical free water accounted for 12.5% in mediating the early-elderhood DASH--verbal memory association. Importantly, participants whose DASH adherence improved from lower adherence in midlife to better adherence in later life showed better verbal memory and more favourable brain integrity than those with persistently low adherence. These findings identify midlife and post-midlife diet quality as modifiable life-course exposures associated with late-life cognitive resilience through differences in macrostructural and microstructural brain integrity.

neuroscience↗