Biology subjects

Tittgemeyer, M.

Publications and source records attributed to Tittgemeyer, M..

14 recordsLinked to original sources

bioRxiv2026

Motor learning adapts to effort-dependent uncertainty

Adaptive behaviour depends on continuously updating motor control when action outcomes differ from expectations. Because action execution and sensory feedback are noisy, the value of an error depends on how reliably it reflects the consequences of an action. Most studies have manipulated the reliability of sensory feedback or action outcomes rather than uncertainty generated by the action itself. Here we show that motor adaptation is calibrated to effort-dependent uncertainty arising during action generation. Using a force-based motor adaptation paradigm, we demonstrate that greater effort progressively increased uncertainty in action execution and proprioceptive feedback, with corresponding changes in adaptation rate that closely matched normative predictions. Reward enhanced adaptation by improving proprioceptive precision rather than directly changing adaptation rate. Supporting this framework, patients with major depressive disorder exhibited elevated execution and proprioceptive uncertainty, impaired reward-dependent improvement in proprioceptive precision, and slower motor adaptation. These findings establish intrinsic uncertainty as a general determinant of adaptive behaviour, linking action generation, sensory evaluation, and motivation.

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bioRxiv2026

Metabolic state and energy reserve dynamically shape human decision-making

Animals continuously adapt their behaviour to changing physiological needs through flexible regulation of behavioural control. However, how the energetic state shapes the distinct components of this adaptive control in humans remains poorly understood. Here, we tested how fasting-induced energy deficits and stored energy reserves jointly regulate inhibitory control and incentive motivation in healthy participants. Fasting selectively increased impulsivity for food rewards, an effect attenuated by body fat percentage. In contrast, fasting increased effort expenditure across both food and monetary rewards, revealing a domain-general increase in motivation best explained by relative energy deficit--the ratio of energy expended during fasting to stored energy reserves. Neither effect was explained by changes in subjective reward valuation. Although self-report questionnaires captured stable behavioural tendencies, they failed to account for state-dependent behavioural variation. Together, these findings show that inhibitory control and motivation are governed by distinct metabolic principles operating across different timescales, revealing that adaptive behavioural control depends on the energetic significance of metabolic state rather than on fasting alone.

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bioRxiv2025

Ghrelin and risky decision-making: No credible evidence for homeostatic state modulation of neural or behavioural effects

Risk-taking is often thought to depend on homeostatic systems. However, evidence remains mixed, and the underlying mechanisms remain debated. One candidate that might drive changes in risky decision-making due to changes in homeostatic systems may be the hunger hormone ghrelin, which interacts with the dopaminergic system. In two studies, we examined the effects of experimental interventions known to affect ghrelin levels on human risky choice in healthy male participants, either after a brief fasting period (study 1, N = 37; N = 26 for fMRI analyses) or a single night of total sleep deprivation (study 2, N = 40; N = 36 for fMRI analyses). We found no credible effects of the experimental manipulations on the proportion of risky choices. In addition, computational modelling indicated that the standard prospect theory, without accounting for choice repetition, best described the observed behaviour. However, it did not reveal consistent effects of state manipulations on model parameters, and the inclusion of manipulation-induced changes in ghrelin levels in the model likewise revealed no robust associations. FMRI analyses did not reveal effects of state manipulation on neural signatures of subjective value or choice in a priori defined regions of interest (bilateral ventromedial prefrontal cortex, ventral striatum, posterior cingulate cortex, and anterior cingulate cortex for subjective value; bilateral anterior insula, ventral striatum, and right medial prefrontal cortex for choice). Our results suggest that state-dependent influences on risky decision-making may be weaker than previously thought.

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bioRxiv2025

Reduced Model-Based Control in Gambling Disorder Despite Intact Neural Value and Task Structure Representations

Disordered gambling has been linked to impairments in goal-directed (model-based) control and reinforcement learning. Here we investigated the potential neural basis of this impairment using a sequential reinforcement learning task (modified two-step-task), computational modeling, and functional magnetic resonance imaging (fMRI) in individuals exhibiting symptoms of disordered gambling (GD) and matched healthy controls (HC, n=30 per group). Model-agnostic analyses replicated the effects of reduced performance and reduced model-based control in the gambling group, both in terms of choice and response time effects. Computational modeling of choice behavior confirmed that this effect was due to reduced model-based control in the gambling group. Analyses of choices and response times using drift diffusion modeling revealed a more complex pattern, where behavioral impairments in the gambling group were linked to changes across several parameters reflecting drift rate modulation and asymptote, as well as non-decision time. Despite these pronounced behavioral differences, the gambling group exhibited largely intact neural effects related to the task transition structure, reward feedback and trial-to-trial behavioral adjustments. Results are discussed with respect to current neurocomputational models of behavioral dysregulation in disordered gambling.

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bioRxiv2025

A lateralized pathway for associating nutrients with flavors

Animals learn about the external world, in part, via interoceptive signals1,2. For example, the nutrient content of food is first estimated in the mouth, in the form of flavor, and then measured again via slower signals from the gut. How these signals from the mouth and gut are integrated to drive learning is unknown. Here we identify a lateralized dopamine pathway that is specialized for learning about the nutrient content of food. We show that dopamine neurons in the ventral tegmental area (VTADA) are necessary for associating nutrients with flavors, and that post-ingestive nutrients trigger DA release selectively in a small region of the anterior basolateral amygdala (BLA) but not canonical DA targets in striatum. Remarkably, this nutrient-triggered DA release occurs preferentially on the left side of the brain in both mice and humans, revealing that the DA system is functionally lateralized. We identify the gut sensors that are responsible for nutrient-triggered DA release; show that they activate BLA-projecting DA neurons defined by expression of cholecystokinin (CCK); and demonstrate that stimulation of DA axon terminals in the anterior BLA drives flavor-nutrient learning but not other aspects of feeding behavior. Two-photon imaging of neurons in the left anterior BLA reveals that they integrate gustatory and post-ingestive cues, and silencing these neurons prevents flavor-nutrient learning. These findings establish a neural basis for how animals learn about the nutrient content of their food. They also reveal unexpectedly that post-ingestive nutrients are differentially represented on the right and left sides of the brain.

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bioRxiv2024

Putaminal dopamine modulates movement motivation in Parkinson's disease

The relative inability to produce effortful movements (akinesia) is the most specific motor sign of Parkinsons disease. The motor motivation hypothesis suggests that akinesia may not reflect a deficiency in motor control per se, but a deficiency in cost-benefit considerations for motor effort. For the first time, we investigated the quantitative effect of dopamine depletion on the motivation of motor effort in Parkinsons disease. A total of 21 patients with Parkinsons disease and 26 healthy controls were included. An incentivized force task was used to capture the amount of effort participants were willing to invest for different monetary incentive levels and dopamine transporter depletion in the bilateral putamen was assessed. Our results demonstrate that patients with Parkinsons disease applied significantly less grip force than healthy controls, especially for low incentive levels. Congruously, decrease of motor effort with greater loss of putaminal dopaminergic terminals was most pronounced for low incentive levels. This signifies that putaminal dopamine is most critical to motor effort when the trade-off with the benefit is poor. Taken together, we provide direct evidence that the reduction of effortful movements in Parkinsons disease depends on motivation and that this effect is associated with putaminal dopaminergic degeneration.

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bioRxiv2024

Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease

IntroductionRecent studies in Parkinsons disease (PD) patients reported disruptions in dynamic functional connectivity (dFC, i.e., a characterization of spontaneous fluctuations in functional connectivity over time). Here, we assessed whether the integrity of striatal dopamine terminals directly modulates dFC metrics in separate PD cohorts, indexing dopamine-dependent changes in large-scale brain network dynamics and its implications in clinical features. MethodsWe pooled data from two cohorts reflecting early PD. From the Parkinsons Progression Marker Initiative (PPMI) cohort, resting-state functional magnetic resonance imaging (rsfMRI) and dopamine transporter (DaT) SPECT were available for 63 PD patients and 16 age- and sex-matched healthy controls. From the clinical research group 219 (KFO) cohort, rsfMRI imaging was available for 52 PD patients and 17 age- and sex-matched healthy controls. A subset of 41 PD patients and 13 healthy control subjects additionally underwent 18F-DOPA-PET imaging. The striatal synthesis capacity of 18F-DOPA PET and dopamine terminal quantity of DaT SPECT images were extracted for the putamen and the caudate. After rsfMRI pre-processing, an independent component analysis was performed on both cohorts simultaneously. Based on the derived components, an individual sliding window approach (44s window) and a subsequent k-means clustering were conducted separately for each cohort to derive dFC states (reemerging intra- and interindividual connectivity patterns). From these states we derived temporal metrics, such as average dwell time per state, state attendance, and number of transitions and compared them between groups and cohorts. Further, we correlated these with the respective measures for local dopaminergic impairment and clinical severity. ResultsIn both cohorts, dFC analysis resulted in three distinct states, varying in connectivity patterns and strength. In the PPMI cohort, PD patients showed a lower state attendance for the globally integrated (GI) state (X2(1, N=79) = 5.82, p= 0.016) and a lower number of transitions (U(N=79) = 337.5, z = -2.06 p= .039) than controls. Significantly, worse motor scores (UPDRS-III) and dopaminergic impairment in the putamen and the caudate were associated with low average dwell time in the GI state (UPDRS-III: {tau}b(N=63) = -.281; p =.003, DaT putamen: {tau}b(N=63)=.213, p= .023, DaT caudate: {tau}b(N=63)=.209, p= .025) and a low total number of transitions (UPDRS-III: {tau}b(N=63)= -.308; p = .001, DaT putamen: {tau}b(N=63)=.350, p<.001, DaT caudate: {tau}b(N=63)=.251, p=.007). Additionally, worse motor performance was associated with a low number of bi-directional transitions between the GI and the lesser connected (LC) state ({tau}b(N=63)= -.237; p =.019). These results could not be reproduced in the KFO cohort: No group differences in dFC measures or associations between dFC variables and dopamine synthesis capacity or clinical measure were observed. ConclusionIn early PD, relative preservation of motor performance may be linked to a more dynamic engagement of an interconnected brain state. Specifically, those large-scale network dynamics seem to depend on striatal dopamine availability. Notably, we obtained these results in only one cohort, but not in a replication sample. Key pointsO_LIExploring dopamines role in brain network dynamics in two Parkinsons disease (PD) cohorts, we unraveled PD-specific changes in dynamic functional connectivity (dFC). C_LIO_LIIn the discovery cohort, results suggest striatal dopamine availability influences large-scale network dynamics that are relevant in motor control. C_LIO_LIIn the confirmation cohort, these findings were not replicated, indicating PD-specific dFC changes are dependent on unrecognized cohort features. C_LI

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bioRxiv2022

Appetitive cue exposure increases neural reward responses without modulating temporal discounting

When given a choice, humans and many animals prefer smaller but sooner over larger but later rewards, a tendency referred to as temporal discounting. Alterations in devaluation of future rewards have been reported in a range of maladaptive behaviors and clinical conditions. Although temporal discounting is highly stable over time and testing environments (e.g., laboratory vs. virtual reality), it is partly under contextual control. For example, highly appetitive cues such as erotic images might increase preferences for immediate rewards, although overall evidence remains mixed. Dopaminergic circuit activity and striatal dopamine concentrations are often assumed to drive increases in temporal discounting following appetitive cue-exposure, yet this was never explicitly tested. Here we examined cue-reactivity effects (erotic vs. neutral pictures) on subsequent temporal discounting in a pre-registered within-subjects study in healthy male participants (n=38). Functional magnetic resonance imaging (fMRI) assessed neural cue-reactivity, value-computations and choice-related effects. Preregistered analyses replicated previous findings of value coding in ventromedial prefrontal cortices, striatum and cingulate cortex. Likewise, as hypothesized, lateral prefrontal cortex activity increased during choices of delayed rewards, potentially reflecting cognitive control. As predicted, erotic vs. neutral cue exposure was associated with increased activity in attention and reward circuits. Contrary to our preregistered hypotheses, temporal discounting was largely unaffected by cue exposure. Likewise, cue-reactivity in key areas of the dopaminergic reward circuit (Nacc, VTA) was not significantly associated with changes in behavior. Our results indicate that behavioral effects of erotic cue exposure on temporal discounting might not be as unequivocal as previously thought and raise doubt on the hypothesis of an upregulated dopaminergic ramping mechanism, that might support myopic approach behavior towards immediate rewards.

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bioRxiv2020

Technical Note: A fast and robust integrator of delay differential equations in DCM for electrophysiological data

Dynamic causal models (DCMs) of electrophysiological data allow, in principle, for inference on hidden, bulk synaptic function in neural circuits. The directed influences between the neuronal elements of modeled circuits are subject to delays due to the finite transmission speed of axonal connections. Ordinary differential equations are therefore not adequate to capture the ensuing circuit dynamics, and delay differential equations (DDEs) are required instead. Previous work has illustrated that the integration of DDEs in DCMs benefits from sophisticated integration schemes in order to ensure rigorous parameter estimation and correct model identification. However, integration schemes that have been proposed for DCMs either emphasise speed (at the possible expense of accuracy) or robustness (but with computational costs that are problematic in practice). In this technical note, we propose an alternative integration scheme that overcomes these shortcomings and offers high computational efficiency while correctly preserving the nature of delayed effects. This integration scheme is available as open-source code in the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) toolbox and can be easily integrated into existing software (SPM) for the analysis of DCMs for electrophysiological data. While this paper focuses on its application to the convolution-based formalism of DCMs, the new integration scheme can be equally applied to more advanced formulations of DCMs (e.g. conductance based models). Our method provides a new option for electrophysiological DCMs that offers the speed required for scientific projects, but also the accuracy required for rigorous translational applications, e.g. in computational psychiatry.

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bioRxiv2020

Increased prefrontal top-down control in older adults predicts motor performance and age-group association

Bimanual motor control declines during ageing, affecting the ability of older adults to maintain independence. An important underlying factor is cortical atrophy, particularly affecting frontal and parietal areas in older adults. As these regions and their interplay are highly involved in bimanual motor preparation, we investigated age-related connectivity changes between prefrontal and premotor areas of young and older adults during the preparatory phase of complex bimanual movements using high-density electroencephalography. Generative modelling showed that excitatory interhemispheric prefrontal to premotor coupling in older adults predicted age-group affiliation and was associated with poor motor-performance. In contrast, excitatory intrahemispheric prefrontal to premotor coupling enabled older adults to maintain motor-performance at the cost of lower movement speed. Our results disentangle the complex interplay in the prefrontal-premotor network during movement preparation underlying reduced bimanual control and the well-known speed-accuracy trade-off seen in older adults.

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bioRxiv2020

A prospective longitudinal study shows putamen volume is associated with moderate amphetamine use and resultant cognitive impairments

BackgroundAmphetamine-type stimulants (ATS) have become a critical public health issue. Animal models have indicated a clear neurotoxic potential of ATSs. In humans, chronic use has been associated with cognitive deficits and structural brain abnormalities. However, cross-sectional retrospective designs in chronic users cannot truly determine the causal direction of the effects. MethodsIn a prospective-longitudinal study design cognitive functioning and brain structure were assessed at baseline and at 12-months follow-up in occasional ATS users (cumulative lifetime use <10 units at baseline). ResultsExamination of change-scores between the initial examination and follow-up revealed declined verbal memory performance and putamen volume in users with high relative to low interim ATS exposure. In the entire sample interim ATS use, memory decline and putamen volume reductions were strongly associated. ConclusionsThe present findings support the hypothesis that ATS use is associated with deficient dorsal striatal morphology which might reflect alterations in dopaminergic pathways. More importantly, these findings strongly suggest that even occasional, low-dose ATS use disrupts striatal integrity and cognitive functioning.

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bioRxiv2020

Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses

AO_SCPLOWBSTRACTC_SCPLOWDrugs affecting neuromodulation, for example by dopamine or acetylcholine, take centre stage among therapeutic strategies in psychiatry. These neuromodulators can change both neuronal gain and synaptic plasticity and therefore affect electrophysiological measures. An important goal for clinical diagnostics is to exploit this effect in the reverse direction, i.e., to infer the status of specific neuromodulatory systems from electrophysiological measures. In this study, we provide proof-of-concept that the functional status of cholinergic (specifically muscarinic) receptors can be inferred from electrophysiological data using generative (dynamic causal) models. To this end, we used epidural EEG recordings over two auditory cortical regions during a mismatch negativity (MMN) paradigm in rats. All animals were treated, across sessions, with muscarinic receptor agonists and antagonists at different doses. Together with a placebo condition, this resulted in five levels of muscarinic receptor status. Using a dynamic causal model - embodying a small network of coupled cortical microcircuits - we estimated synaptic parameters and their change across pharmacological conditions. The ensuing parameter estimates associated with (the neuromodulation of) synaptic efficacy showed both graded muscarinic effects and predictive validity between agonistic and antagonistic pharmacological conditions. This finding illustrates the potential utility of generative models of electrophysiological data as computational assays of muscarinic function. In application to EEG data of patients from heterogeneous spectrum diseases, e.g. schizophrenia, such models might help identify subgroups of patients that respond differentially to cholinergic treatments. SO_SCPLOWIGNIFICANCEC_SCPLOW SO_SCPLOWTATEMENTC_SCPLOWIn psychiatry, the vast majority of pharmacological treatments affect actions of neuromodulatory transmitters, e.g. dopamine or acetylcholine. As treatment is largely trial-and-error based, one of the goals for computational psychiatry is to construct mathematical models that can serve as "computational assays" and infer the status of specific neuromodulatory systems in individual patients. This neuro-modelling strategy has great promise for electrophysiological data in particular but requires careful validation. The present study demonstrates that the functional status of cholinergic (muscarinic) receptors can be inferred from electrophysiological data using dynamic causal models of neural circuits. While accuracy needs to be enhanced and our results must be replicated in larger samples, our current results provide proof-of-concept for computational assays of muscarinic function using EEG.

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bioRxiv2019

Atypical processing of uncertainty in individuals at risk for psychosis

BackgroundCurrent theories of psychosis highlight the role of abnormal learning signals, i.e., prediction errors (PEs) and uncertainty, in the formation of delusional beliefs. We employed computational analyses of behaviour and functional magnetic resonance imaging (fMRI) to examine whether such abnormalities are evident in at-risk mental state (ARMS) individuals. MethodsNon-medicated ARMS individuals (n=13) and control participants (n=13) performed a probabilistic learning paradigm during fMRI data acquisition. We used a hierarchical Bayesian model to infer subject-specific computations from behaviour - with a focus on PEs and uncertainty (or its inverse, precision) at different levels, including environmental volatility - and used these computational quantities for analyses of fMRI data. ResultsComputational modelling of ARMS individuals behaviour indicated volatility estimates converged to significantly higher levels than in controls. Model-based fMRI demonstrated increased activity in prefrontal and insular regions of ARMS individuals in response to precision-weighted low-level outcome PEs, while activations of prefrontal, orbitofrontal and anterior insula cortex by higher-level PEs (that serve to update volatility estimates) were reduced. Additionally, prefrontal cortical activity in response to outcome PEs in ARMS was negatively associated with clinical measures of global functioning. ConclusionsOur results suggest a multi-faceted learning abnormality in ARMS individuals under conditions of environmental uncertainty, comprising higher levels of volatility estimates combined with reduced cortical activation, and abnormally high activations in prefrontal and insular areas by precision-weighted outcome PEs. This atypical representation of high- and low-level learning signals might reflect a predisposition to delusion formation.

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bioRxiv2019

Cortico-basal white matter alterations occurring in Parkinson’s disease

Magnetic resonance imaging studies typically use standard anatomical atlases for identification and analyses of (patho-)physiological effects on specific brain areas; these atlases often fail to incorporate neuroanatomical alterations that may occur with both age and disease. The present study utilizes Parkinsons disease and age-specific anatomical atlases of the subthalamic nucleus for diffusion tractography, assessing tracts that run between the subthalamic nucleus and a-priori defined cortical areas known to be affected by Parkinsons disease. The results show that the strength of white matter fiber tracts appear to remain structurally unaffected by disease. Contrary to that, Fractional Anisotropy values were shown to decrease in Parkinsons disease patients for connections between the subthalamic nucleus and the pars opercularis of the inferior frontal gyrus, anterior cingulate cortex, the dorsolateral prefrontal cortex and the pre-supplementary motor, collectively involved in preparatory motor control, decision making and task monitoring. While the biological underpinnings of fractional anisotropy alterations remain elusive, they may nonetheless be used as an index of Parkinsons disease. Moreover, we find that failing to account for structural changes occurring in the subthalamic nucleus with age and disease reduce the accuracy and influence the results of tractography, highlighting the importance of using appropriate atlases for tractography.

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