Biology subjects

Peters, J.

Publications and source records attributed to Peters, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Bilayer-forming lipids enhance archaeal monolayer membrane stability

Archaeal membranes exhibit remarkable stability under extreme environmental conditions, a feature attributed to their unique lipid composition. While it is widely accepted that tetraether lipids confer structural integrity by forming monolayers, the role of bilayer-forming diether lipids in membrane stability remains unclear. Here, we demonstrate that the incorporation of diethers into archaeal-like lipid assemblies enhances membrane organization and adaptability under thermal stress. Using neutron diffraction, we show that membranes composed of mixed diethers and tetraethers exhibit greater structural order and stability compared to pure lipid systems. Contrary to expectations, monolayer-forming tetraethers alone display increased variability in lamellar spacing under fluctuating temperature and humidity, whereas mixed lipid membranes maintain a consistent architecture. Furthermore, neutron scattering length density profiles reveal an unexpected density feature at the bilayer midplane, challenging conventional models of archaeal monolayer organization. These findings suggest that molecular diversity of lipid molecules, rather than tetraether dominance, plays a critical role in membrane auto assembly, stability and adaptability. Our results provide new insights into archaeal membrane adaptation strategies, with implications for the development of bioinspired, robust synthetic membranes for industrial and biomedical applications.

biophysics↗

bioRxiv2025

In the brain of the beholder: whole brain dynamics shape the perception during ambiguous motion

Visual perception is typically based on a one-to-one mapping between stimuli and conscious experiences. However, under bistable conditions, identical sensory inputs can elicit alternating perceptions, requiring the brain to resolve ambiguity. The mechanisms underlying transitions between distinct perceptual states and their sustained maintenance remain poorly understood. In this ultra-high-field (7T) fMRI study, we investigated the neural dynamics of perception using a bistable motion stimulus (ambiguous motion quartet) that evoked endogenous alternations between horizontal and vertical motion, compared to a control condition (physical motion quartet) with unambiguous sensory input. Consistent with previous findings, the human motion complex (hMT+) played a central role in processing both physical and ambiguous motion conditions. By dissociating neural activity during perceptual transitions from sustained perceptions, we found that hMT+ mostly interacts dynamically with area 46 in the frontal cortex and PF/PFm within the inferior parietal lobe during transitions and with subregions of the superior parietal lobe during sustained perceptions. Beyond local activity, computational modeling revealed an increase in hierarchical organization across cortical networks during the ambiguous condition. In particular, the same frontal and parietal regions exhibited ascension within the functional hierarchy, likely reflecting their specific role in coordinating computations for resolving ambiguity.

neuroscience↗

bioRxiv2024

Multimodal laminar characterization of visual areas along the cortical hierarchy

Understanding the relationship between brain structure and function is a central goal in neuroscience. While post-mortem studies using microscopic techniques have provided detailed insights into the brains cytoarchitectonic and myeloarchitectonic patterns, linking these structural findings to functional outcomes remains challenging. Magnetic resonance imaging (MRI) has emerged as a powerful non-invasive tool for studying both structure and function, but discrepancies in spatial resolution between structural and functional imaging, especially in layer-fMRI, complicate the interpretation of functional results. In this study, we explore how visual cortical hierarchy relates to microscopic and mesoscopic laminar features. Focusing on visual areas that span progressive hierarchical levels, V1, V2, V3, and hMT+, we apply a multimodal approach combining post-mortem histology, post-mortem and in-vivo quantitative MRI (qMRI), and resting-state layer-fMRI. Using the open-access post-mortem AHEAD dataset, which integrates histological and qMRI contrasts from the same brain samples, we bridge microscopic observations with qMRI data. In parallel, we incorporate high-resolution [Formula] MRI and resting-state layer-fMRI from the same participant, allowing for a comparative analysis of laminar profiles across cortical depth. For computing laminar profiles, we developed an analysis pipeline that bridges histology images, mesoscopic qMRI, and layer-fMRI. Our findings highlight parvalbumin laminar profiles (reflecting interneuron parvalbumin density) as the most discriminative feature for differentiating brain areas. Additionally, we report laminar quantitative [Formula] profiles from post-mortem and in-vivo data, together with [Formula]-weighted resting-state layer-fMRI, all of which exhibit a similar overall shape across modalities. Using our methodological framework, a similar laminar characterization can be extended to study other brain regions. Generative models for layer fMRI will benefit from incorporating these new empirical microstructural (parvalbumin) and physical quantitative [Formula] data, leading to more area-specific and accurate models. HighlightsO_LIWe present a multimodal analysis of the laminar organization of four visual regions (V1, V2, V3, hMT+), characterizing progressive visual hierarchy levels in humans. This analysis spans from post-mortem microscopy and quantitative MRI (qMRI) to in-vivo qMRI and laminar fMRI during resting state. C_LIO_LIAmong the three microscopy contrasts, parvalbumin, a marker of interneuron density, emerges as the most distinctive regional feature. Notably, the parvalbumin laminar profiles vary across hierarchy levels, with hMT+ showing the greatest divergence compared to V1, V2, and V3. C_LIO_LIQuantitative [Formula] measurements, from both post-mortem and in-vivo data, reveal a clear increase towards the superficial cortical layers. These depth-dependent patterns closely mirror the laminar profiles observed in both task and resting-state fMRI. C_LIO_LISurprisingly, no substantial difference was observed in laminar [Formula] profiles between post-mortem and in-vivo data across the visual areas. C_LI

neuroscience↗

bioRxiv2024

In the brain of the beholder: bi-stable motion reveals mesoscopic-scale feedback modulation in V1

Understanding the neural processes underlying conscious perception remains a central goal in neuroscience. Visual illusions, whether static or dynamic, provide an effective ecological paradigm for studying conscious perception, as they induce subjective experiences from constant visual inputs. While previous neuroimaging studies have dissociated perceptual interpretation of visual motion from sensory input within the motion-sensitive area (hMT+) in humans, less is known about the role of V1 and its relationship to hMT+ during a bistable perception. To address this, we conducted a layer-fMRI study at 7 T with human participants exposed to a bistable motion quartet stimulus. Despite a constant sensory input, the bistable motion quartet elicits switching horizontal and vertical apparent motion percepts likely due to lateral and feedback connections across low and high-level brain regions (feedback processing). As control, we used an "unambiguous" version of the motion quartet, hereafter referred to as "physical" motion stimulus, where horizontal and vertical motion is physically presented as visual stimulus in an alternated fashion (feedforward processing). With the advantage of a sub-millimeter resolution gained at ultra-high field (7 Tesla), we aimed to unveil the differential laminar modulation of V1 (low visual area) and hMT+ (high-visual area) during the physical and bistable condition. Our results indicate that: O_LIhMT+ functional activity correlates with conscious perception during both physical and ambiguous stimuli with similar strength. There is no evidence of differential laminar profiles in hMT+ between the two experimental conditions. C_LIO_LIBetween inducer squares, V1 shows a significantly reduced functional response to the ambiguous stimulus compared to the physical stimulus, as it primarily reflects feedback signals with diminished feedforward input. Distinct V1 laminar profiles differentiate the two experimental conditions. C_LIO_LIThe temporal dynamics of V1 and hMT+ become more similar during the ambiguous condition. C_LIO_LIV1 exhibits reduced specificity to horizontal and vertical motion perception during the ambiguous condition at the retinotopic locations corresponding to the perceived motion. C_LI Our findings demonstrate that during the ambiguous condition, there is a stronger temporal coupling between hMT+ and V1 due to feedback signals from hMT+ to V1. Such feedback to V1 might be contributing to the stabilization of the vivid perception of directed motion at the face of constant ambiguous stimulation.

neuroscience↗

bioRxiv2024

Dopamine and temporal discounting: revisiting pharmacology and individual differences

Disorders characterised by changes in dopamine (DA) neurotransmission are often linked to changes in the temporal discounting of future rewards. Likewise, pharmacological manipulations of DA neuro-transmission in healthy individuals modulate temporal discounting, but there is considerable variability in the directionality of reported pharmacological effects, as enhancements and reductions of DA signalling have been linked to both increases and reductions of temporal discounting. This may be due to meaningful individual differences in drug effects and/or false positive findings in small samples. To resolve these inconsistencies, we 1) revisited pharmacological effects of the DA precursor L-DOPA on temporal discounting in a large sample of N = 76 healthy participants (n = 44 male) and 2) examined several putative proxy measures for DA to revisit the role of individual differences in a randomised, double-blind placebo-controlled pre-registered study (https://osf.io/a4k9j/). Replicating previous findings, higher rewards were discounted less (magnitude effect). Computational modelling using hierarchical Bayesian parameter estimation confirmed that the data in both drug conditions were best accounted for by a non-linear temporal discounting drift diffusion model. In line with recent animal and human work, L-DOPA reliably reduced the discount rate with a small effect size, challenging earlier findings in substantially smaller samples. We found no credible evidence for linear or quadratic effects of putative DA proxy measures on model parameters, calling into question the role of these measures in accounting for individual differences in DA drug effects.

neuroscience↗

bioRxiv2024

Uridine Phosphorylase-1 supports metastasis of mammary cancer by altering immune and extracellular matrix landscapes of the lung

Understanding the mechanisms that facilitate early events in metastatic seeding is key to developing therapeutic approaches to reduce metastasis - the leading cause of cancer-related death. Using whole animal screens in genetically engineered mouse models of cancer we have identified circulating metabolites associated with metastasis. Specifically, we highlight the pyrimidine uracil as a prominent metastasis-associated metabolite. Uracil is generated by neutrophils expressing the enzyme uridine phosphorylase-1 (UPP1), and neutrophil specific Upp1 expression is increased in cancer. Altered UPP1 activity influences expression of adhesion molecules on the surface of neutrophils, leading to decreased neutrophil motility in the pre-metastatic lung. Furthermore, we find that UPP1-expressing neutrophils suppress T-cell proliferation, and the UPP1 product uracil can increase fibronectin deposition in the extracellular microenvironment. Consistently, knockout or inhibition of UPP1 in mice with mammary tumours increases the number of T-cells and reduces fibronectin content in the lung and decreases the proportion of mice that develop lung metastasis. These data indicate that UPP1 influences neutrophil behaviour and extracellular matrix deposition in the lung and suggest that pharmacological targeting of this pathway could be an effective strategy to reduce metastasis.

cancer biology↗

bioRxiv2024

A meta reinforcement learning account of behavioral adaptation to volatility in recurrent neural networks

Natural environments often exhibit various degrees of volatility, ranging from slowly changing to rapidly changing contingencies. How learners adapt to changing environments is a central issue in both reinforcement learning theory and psychology. For example, learners may adapt to changes in volatility by increasing learning if volatility increases, and reducing it if volatility decreases. Computational neuroscience and neural network modeling work suggests that this adaptive capacity may result from a meta-reinforcement learning process (implemented for example in the prefrontal cortex), where past experience endows the system with the capacity to rapidly adapt to environmental conditions in new situations. Here we provide direct evidence for a meta-reinforcement learning account of adaptation to environmental volatility. Recurrent neural networks (RNNs) were trained on a restless four-armed bandit reinforcement learning problem under three different training regimes (low volatility training only, medium volatility training only, or meta-volatility training across a range of volatilities). We show that, in contrast to RNNs trained in the low volatility regime, RNNs trained under the medium or meta-volatility regimes exhibited a superior adaption to environmental volatility. This was reflected in a better performance, and computational modeling of the networks behavior revealed a more adaptive adjustment of learning and exploration to varying levels of volatility during test. Results extend the meta-RL account to volatility adaptation and confirm past experience as a crucial factor of adaptive decision-making.

neuroscience↗

bioRxiv2024

Ambulatory physiological measures obtained under naturalistic urban mobility conditions have acceptable reliability

Ambulatory assessment methods in psychology and clinical neuroscience are powerful research tools for collecting data outside of the laboratory. These methods encompass physiological, behavioral, and self-report measures obtained while individuals navigate in real-world environments, thereby increasing the ecological validity of experimental approaches. Despite the recent increase in applications of ambulatory physiology, data on the reliability of these measures is still limited. To address this issue, twenty-six healthy participants (N = 15 female, 18-34 years) completed an urban walking route (2.1 km, 30 min walking duration, temperature M = 19.8{degrees} degree Celsius, Range = 12{degrees}-37{degrees} degrees Celsius) on two separate testing days, while GPS-location and ambulatory physiological measures (cardiovascular and electrodermal activity) were continuously recorded. Bootstrapped test-retest reliabilities of single measures and aggregate scores derived via principal component analysis (PCA) were computed. The first principal component (PC#1) accounted for 39% to 45% of variance across measures. PC#1 scores demonstrated an acceptable test-retest reliability (r = .60) across testing days, exceeding the reliabilities of most individual measures (heart rate: r = .53, heart rate variability: r = .50, skin conductance level: r = .53, no. of skin conductance responses: r = .28, skin conductance response amplitude: r = .60). Results confirm that ambulatory physiological measures recorded during naturalistic navigation in urban environments exhibit acceptable test-retest reliability, in particular when compound scores across physiological measures are analyzed, a prerequisite for applications in (clinical) psychology and digital health. Author summaryPsychophysiological assessments have been predominantly limited to controlled laboratory settings, leaving the reliability of field measurements unclear. In this study, we conducted a proof-of-concept investigation in N=26 healthy participants navigating the same urban route on two separate days. Cardiovascular and electrodermal activity were continuously recorded and combined with GPS-based location tracking. Psychophysiological measurements obtained under naturalistic urban mobility conditions showed acceptable test-retest reliability, in particular when multiple measures where combined into a compound score via principal component analysis. Shedding light on the reliability of ambulatory assessments in urban environments emphasizes the potential for psychophysiological measurements to contribute valuable insights beyond the constraints of traditional laboratory settings.

physiology↗

bioRxiv2024

Mobile-CRISPRi as a powerful tool for modulating Vibrio gene expression

CRISPRi (Clustered Regularly Interspaced Palindromic Repeats interference) is a gene knockdown method that uses a deactivated Cas9 protein (dCas9) that binds a specific gene target locus dictated by an encoded guide RNA (sgRNA) to block transcription. Mobile-CRISPRi is a suite of modular vectors that enable CRISPRi knockdowns in diverse bacteria by integrating IPTG-inducible dcas9 and sgRNA genes into the genome using Tn7 transposition. Here, we show that the Mobile-CRISPRi system functions robustly and specifically in multiple Vibrio species: Vibrio cholerae, Vibrio fischeri, Vibrio vulnificus, Vibrio parahaemolyticus, and Vibrio campbellii. We demonstrate efficacy by targeting both essential and non-essential genes that function to produce defined, measurable phenotypes: bioluminescence, quorum sensing, cell division, and growth arrest. We anticipate that Mobile-CRISPRi will be used in Vibrio species to systematically probe gene function and essentiality in various behaviors and native environments.

molecular biology↗

bioRxiv2023

Pharmacological enhancement of dopamine neurotransmission does not affect illusory pattern perception

Psychotic symptoms and delusional belief have been linked to dopamine transmission in both healthy and clinical samples and are assumed to result at least in part from perceiving illusory patterns in noise. However, the existing literature on the role of dopamine in detecting patterns in noise is inconclusive. To address this issue, we assessed the effect of manipulating dopaminergic neurotransmission on illusory pattern perception in healthy individuals (n = 48, n = 19 female) in a double-blind placebo-controlled within-subjects design (see preregistration at https://osf.io/a4k9j/). We predicted individuals on vs. off L-DOPA to be more likely to perceive illusory patterns, specifically objects in images containing only noise. Using a signal detection model, however, we found no credible evidence that L-DOPA compared to placebo increased false alarm rates. Further, L-DOPA did not modulate measures of accuracy, discrimination sensitivity and response bias. In all cases, Bayesian statistics revealed strong evidence in favour of the null hypothesis Future studies should address possible dose-dependent effects and differential effects in healthy vs. clinical samples.

neuroscience↗

bioRxiv2023

Exposure of Mycobacterium tuberculosis to human alveolar lining fluid shows temporal and strain-specific adaptation to the lung environment

Upon infection, Mycobacterium tuberculosis (M.tb) reaches the alveolar space and comes in close contact with human alveolar lining fluid (ALF) for an uncertain period of time prior to its encounter with alveolar cells. We showed that homeostatic ALF hydrolytic enzymes modify the M.tb cell envelope, driving M.tb-host cell interactions. Still, the contribution of ALF during M.tb infection is poorly understood. Here, we exposed 4 M.tb strains with different levels of virulence, transmissibility, and drug resistance (DR) to physiological concentrations of human ALF for 15-min and 12-h, and performed RNA sequencing. Gene expression analysis showed a temporal and strain-specific adaptation to human ALF. Differential expression (DE) of ALF-exposed vs. unexposed M.tb revealed a total of 397 DE genes associated with lipid metabolism, cell envelope and processes, intermediary metabolism and respiration, and regulatory proteins, among others. Most DE genes were detected at 12-h post-ALF exposure, with DR-M.tb strain W-7642 having the highest number of DE genes. Interestingly, genes from the KstR2 regulon, which controls the degradation of cholesterol C and D rings, were significantly upregulated in all strains post-ALF exposure. These results indicate that M.tb-ALF contact drives initial metabolic and physiologic changes in M.tb, with potential implications in infection outcome. IMPORTANCETuberculosis, caused by airborne pathogen Mycobacterium tuberculosis (M.tb), is one of the leading causes of mortality worldwide. Upon infection, M.tb reaches the alveoli and gets in contact with human alveolar lining fluid (ALF), where ALF hydrolases modify the M.tb cell envelope driving subsequent M.tb-host cell interactions. Still, the contributions of ALF during infection are poorly understood. We exposed 4 M.tb strains to ALF for 15-min and 12-h and performed RNA sequencing, demonstrating a temporal and strain-specific adaptation of M.tb to ALF. Interestingly, genes associated with cholesterol degradation were highly upregulated in all strains. This study shows for the first time that ALF drives global metabolic changes in M.tb during the initial stages of the infection, with potential implications in disease outcome. Biologically relevant networks and common and strain-specific bacterial determinants derived from this study could be further investigated as potential therapeutic candidates.

microbiology↗

bioRxiv2023

Layered Structure of Cortex Explains Reversal Dynamics in Bistable Perception

Bistable perception involves the spontaneous alternation between two exclusive interpretations of a single stimulus. Previous research has suggested that this perceptual phenomenon results from winnerless dynamics in the cortex. Indeed, winnerless dynamics can explain many key behavioral characteristics of bistable perception. However, it fails to explain an increase in alternation rate that is typically observed in response to increased stimulus drive and instead predicts a decline in alternation rate. To reconcile this discrepancy, several lines of work have augmented winnerless dynamics with additional processes such as global gain control, input suppression, and release mechanisms. These offer potential explanations at an algorithmic level. But it remains unclear which, if any, of these mechanisms are implemented in the cortex and what their biological substrates might be. We show that the answers to these questions lie within the architecture of the cortical microcircuit. Utilizing a dynamic mean field approach, we implement a laminar columnar circuit with empirically derived interlaminar connectivity. By coupling two such circuits such that they exhibit competition, we are able to produce winnerless dynamics reflective of bistable perception. Within our model, we identify two mechanisms through which the layered structure of the cortex gives rise to increased alternation rate in response to increased stimulus drive. First, deep layers act to inhibit the upper layers, thereby reducing the attractor depth and increasing the alternation rate. Second, recurrent connections between superficial and granular layers implement an input suppression mechanism which again reduces the attractor depth of the winnerless competition. These findings demonstrate the functional significance of the layered cortical architecture as they showcase perceptual implications of neuroatomical properties such as interlaminar connectivity and layer-specific activation. Author summaryIn our study, we explore the mechanistic underpinnings of bistable perception, a phenomenon where a single visual stimulus can be perceived in two distinct ways, and where our percept alternates spontaneously between interpretations. Although winnerless competition mechanisms have been widely recognized to govern this, they fall short in explaining why we observe more perceptual alternations with a stronger stimulus. To uncover the cortexs role in this discrepancy, we constructed a detailed model that mirrors the layered structure and interlaminar connections of the cortex. Remarkably, the architecture of these layers emerged as instrumental players. We discovered that the deeper layers of the cortex seem to inhibit the upper layers, facilitating a quicker alternation between perceptions when stimulated. Additionally, the interlaminar recurrent connections between the upper output layer and middle input layer appeared to destabilize the prevailing interpretation of the stimulus, leading to faster alternations. Our research illuminates how the complex architecture of the cortex, particularly the interconnections between its layers, plays a pivotal role in influencing our perception. The layered structure of the cortex goes beyond mere anatomy; it influences our perceptual experiences.

neuroscience↗

bioRxiv2023

Signatures of heuristic-based directed exploration in two-step sequential decision task behaviour.

Processes formalized in classic Reinforcement Learning (RL) theory, such as model-based (MB) control and exploration strategies have proven fertile in cognitive and computational neuroscience, as well as computational psychiatry. Dysregulations in MB control and exploration and their neurocomputational underpinnings play a key role across several psychiatric disorders. Yet, computational accounts mostly study these processes in isolation. The current study extended standard hybrid models of a widely-used sequential RL-task (two-step task; TST) employed to measure MB control. We implemented and compared different computational model extensions for this task to quantify potential exploration mechanisms. In two independent data sets spanning two different variants of the task, an extension of a classical hybrid RL model with a heuristic-based exploration mechanism provided the best fit, and revealed a robust positive effect of directed exploration on choice probabilities in stage one of the task. Posterior predictive checks further showed that the extended model reproduced choice patterns present in both data sets. Results are discussed with respect to implications for computational psychiatry and the search for neurocognitive endophenotypes.

neuroscience↗

bioRxiv2023

Human-level reinforcement learning performance of recurrent neural networks is linked to hyperperseveration, not directed exploration

A key feature of animal and human decision-making is to balance the exploration of unknown options for information gain (directed exploration) versus selecting known options for immediate reward (exploitation), which is often examined using restless bandit tasks. Recurrent neural network models (RNNs) have recently gained traction in both human and systems neuroscience work on reinforcement learning, due to their ability to show meta-learning of task domains. Here we comprehensively compared the performance of a range of RNN architectures as well as human learners on restless four-armed bandit problems. The best-performing architecture (LSTM network with computation noise) exhibited human-level performance. Computational modeling of behavior first revealed that both human and RNN behavioral data contain signatures of higher-order perseveration, i.e., perseveration beyond the last trial, but this effect was more pronounced in RNNs. In contrast, human learners, but not RNNs, exhibited a positive effect of uncertainty on choice probability (directed exploration). RNN hidden unit dynamics revealed that exploratory choices were associated with a disruption of choice predictive signals during states of low state value, resembling a win-stay-loose-shift strategy, and resonating with previous single unit recording findings in monkey prefrontal cortex. Our results highlight both similarities and differences between exploration behavior as it emerges in meta-learning RNNs, and computational mechanisms identified in cognitive and systems neuroscience work.

neuroscience↗

bioRxiv2023

Compressed phenotypic screens for complex multicellular models and high-content assays

High-throughput phenotypic screens leveraging biochemical perturbations, high-content readouts, and complex multicellular models could advance therapeutic discovery yet remain constrained by limitations of scale. To address this, we establish a method for compressing screens by pooling perturbations followed by computational deconvolution. Conducting controlled benchmarks with a highly bioactive small molecule library and a high-content imaging readout, we demonstrate increased efficiency for compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening to examine transcriptional responses of patient-derived pancreatic cancer organoids to a library of tumor-microenvironment (TME)-nominated recombinant protein ligands. Using single-cell RNA-seq as a readout, we uncover reproducible phenotypic shifts induced by ligands that correlate with clinical features in larger datasets and are distinct from reference signatures available in public databases. In sum, our approach enables phenotypic screens that interrogate complex multicellular models with rich phenotypic readouts to advance translatable drug discovery as well as basic biology.

systems biology↗

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.

neuroscience↗

bioRxiv2022

Therapeutic trial of anle138b in mouse models of genetic prion disease

Phenotypic screening has yielded small molecule inhibitors of prion replication that are effective in vivo against certain prion strains but not others. Here we sought to test the small molecule anle138b in multiple mouse models of prion disease. In mice inoculated with the RML strain of prions, anle138b doubled survival and durably suppressed astrogliosis measured by live animal bioluminescence imaging. In knock-in mouse models of the D178N and E200K mutations that cause genetic prion disease, however, we were unable to identify a clear, quantifiable disease endpoint against which to measure therapeutic efficacy. Among untreated animals, the mutations did not impact overall survival, and bioluminescence remained low out to >20 months of age. Vacuolization and PrP deposition were observed in some brain regions in a subset of mutant animals, but appeared unable to carry the weight of a primary endpoint in a therapeutic study. We conclude that not all animal models of prion disease are suited to well-powered therapeutic efficacy studies, and care should be taken in choosing the models that will support drug development programs.

neuroscience↗

bioRxiv2022

Dopamine regulates decision thresholds in human reinforcement learning.

Dopamine fundamentally contributes to reinforcement learning by encoding prediction errors, deviations of an outcome from expectation. Prediction error coding in dopaminergic regions in human functional neuroimaging studies is well replicated. In contrast, replications of behavioral and neural effects of pharmacological modulations of the dopamine system in human reinforcement learning are scarce. Additionally, dopamine contributes to action selection, but direct evidence and process-specific accounts in human reinforcement learning are lacking. Here we examined dopaminergic mechanisms underlying human reinforcement learning in a within-subjects pharmacological approach in male human volunteers (n=31, within-subjects design; Placebo, 150mg L-dopa, 2mg Haloperidol) in combination with functional magnetic resonance imaging and a stationary reinforcement learning task. We had two aims. First, we aimed to replicate previously reported beneficial effects of L-dopa vs. Haloperidol on reinforcement learning from gains. This replication was not successful. We observed no performance benefit of L-Dopa vs. Haloperidol, and no evidence for alterations in neural prediction error signaling. In contrast, Bayesian analyses provided moderate evidence in favor of the null hypothesis. This unsuccessful replication is likely at least partly due to a number of differences in experimental design. Second, using combined reinforcement learning drift diffusion models, we tested the recent proposal that dopamine contributes to action selection by regulating decision thresholds. Model comparison revealed that the data were best accounted for by a reinforcement learning drift diffusion model with separate learning rates for positive and negative prediction errors. The model accounted for both reductions in RTs and increases in accuracy over the course of learning. The only parameter showing robust drug effects was the boundary separation parameter, which revealed reduced decision thresholds under both L-Dopa and Haloperidol, compared to Placebo, and the degree of threshold reduction accounted for individual differences in RTs between conditions. Results are in line with the idea that striatal dopamine regulates decision thresholds during action selection, and that lower dosages of D2 receptor antagonists increase striatal DA release via an inhibition of autoreceptor-mediated feedback mechanisms.

neuroscience↗