Biology subjects

Erdmann, T.

Publications and source records attributed to Erdmann, T..

4 recordsLinked to original sources

bioRxiv2025

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

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.

neuroscience↗

bioRxiv2024

A neural mechanism for compositional generalization of structure in humans

A human ability to adapt to the dynamics of novel environments relies on abstracting and generalizing from past experiences. Previous research has focused on how humans generalize from isolated sequential processes, yet we know little about mechanisms that enable adaptation to more complex dynamics, including those that govern much everyday experience. Here, using a novel sequence learning task based on graph factorization, coupled with simultaneous magnetoencephalography (MEG) recordings, we ask whether reuse of experiential "building blocks" enable inference and generalization. Behavioral results were consistent with participants decomposing task experience into subprocesses, abstracting their dynamical structure away from their sensory specifics and transferring these to a new task environment. Neurally, this transfer was associated with a learning-induced, condition-specific, increase in neural similarity among stimuli conditional on their structural role in abstract subprocesses that were shared across task phases. Consistent with this, a complementary dynamical role decoding analysis revealed enhanced neural decodability for stimuli sharing identical structural transition types across experiential contexts, specifically when prior experience included the relevant graph structure. Decoding strength for these role representations was positively related to behavioral success in subprocess knowledge transfer, a relationship that will require future independent replication. These findings provide neural evidence consistent with the idea that a structural scaffolding mechanism supports generalization of experience to new contexts.

neuroscience↗

bioRxiv2022

Malt1-dependent cleavage of Tensin-3 controls B-cell adhesion and lymphomagenesis

The protease Malt1 controls the development and function of lymphocytes and promotes lymphomagenesis by cleaving a limited set of cellular substrates, many of which regulate gene transcription. Here, we report the identification of the integrin-binding scaffold protein Tensin-3 as a Malt1 substrate in activated B cells. B cells expressing a non-cleavable form of Tensin-3 (TNS3-nc) showed normal NF-{kappa}B and JNK transcriptional responses but increased and prolonged integrin-dependent adhesion upon activation. Moreover, mice expressing a non-cleavable form of Tensin-3 displayed reduced antibody production in response to immunization with a T-cell dependent antigen. We also explored the role of Tensin-3 in diffuse large B cell lymphomas and mantle cell lymphomas characterized by constitutive Malt1 activity, which showed strong constitutive Tensin-3 cleavage and a correlating reduction in total Tensin-3 levels. Silencing of Tensin-3 expression in Malt1-driven lymphoma models did not affect cellular proliferation but enhanced the dissemination of xenografted lymphoma cells. Thus, Malt1-dependent Tensin-3 cleavage limits integrin-dependent B-cell adhesion and promotes humoral immune responses and metastatic spreading of B cell lymphomas in a transcription-independent manner.

immunology↗

bioRxiv2018

Chromatin conformation analysis of primary patient tissue using a low input Hi-C method

Chromatin conformation constitutes a fundamental level of eukaryotic genome regulation. However, our ability to examine its biological function and role in disease is limited by the large amounts of starting material required to perform current experimental approaches. Here, we present Low-C, a Hi-C method for low amounts of input material. By systematically comparing Hi-C libraries made with decreasing amounts of starting material we show that Low-C is highly reproducible and robust to experimental noise. To demonstrate the suitability of Low-C to analyse rare cell populations, we produce Low-C maps from primary B-cells of a diffuse large B-cell lymphoma patient. We detect a common reciprocal translocation t (3;14) (q27;q32) affecting the BCL6 and IGH loci and abundant local structural variation between the patient and healthy B-cells. The ability to study chromatin conformation in primary tissue will be fundamental to fully understand the molecular pathogenesis of diseases and to eventually guide personalised therapeutic strategies.

genomics↗