Effects of PPP1R1B (DARPP-32) Polymorphism on Feedback-Related Brain Potentials Across the Life Span

Maximizing gains during probabilistic reinforcement learning requires the updating of choice – outcome expectations at the time when the feedback about a specific choice or action is given. Extant theories and evidence suggest that dopaminergic modulation plays a crucial role in reinforcement learning and the updating of choice – outcome expectations. Furthermore, recently a positive component of the event-related potential about 200 ms (P2) after feedback has been suggested to reflect such updating. The efficacy of dopaminergic modulation changes across the life span. However, to date investigations of age-related differences in feedback-related P2 during reinforcement learning are still scarce. The present study thus aims to investigate whether individual differences in the feedback-related P2 would be associated with polymorphic variations in a dopamine relevant gene PPP1R1B (also known as DARPP-32) and whether the genetic effect may differ between age groups. We observed larger P2 amplitudes in individuals carrying the genotype associated with higher dopamine receptor efficacy, i.e., a allele homozygotes of a single nucleotide polymorphism (rs907094) of the PPP1R1B gene. Moreover, this effect was more pronounced in children and older adults in comparison to adolescents and younger adults. Together, our findings indicate that polymorphic variations in a dopamine relevant gene are associated with individual differences in brain-evoked potentials of outcome updating and hint at the possibility that genotype effects on neurocognitive phenotypes may vary as a function of brain maturation and aging

Differential Influence of Levodopa on Reward-Based Learning in Parkinson's Disease

The mesocorticolimbic dopamine (DA) system linking the dopaminergic midbrain to the prefrontal cortex and subcortical striatum has been shown to be sensitive to reinforcement in animals and humans. Within this system, coexistent segregated striato-frontal circuits have been linked to different functions. In the present study, we tested patients with Parkinson's disease (PD), a neurodegenerative disorder characterized by dopaminergic cell loss, on two reward-based learning tasks assumed to differentially involve dorsal and ventral striato-frontal circuits. 15 non-depressed and non-demented PD patients on levodopa monotherapy were tested both on and off medication. Levodopa had beneficial effects on the performance on an instrumental learning task with constant stimulus-reward associations, hypothesized to rely on dorsal striato-frontal circuits. In contrast, performance on a reversal learning task with changing reward contingencies, relying on ventral striato-frontal structures, was better in the unmedicated state. These results are in line with the “overdose hypothesis” which assumes detrimental effects of dopaminergic medication on functions relying upon less affected regions in PD. This study demonstrates, in a within-subject design, a double dissociation of dopaminergic medication and performance on two reward-based learning tasks differing in regard to whether reward contingencies are constant or dynamic. There was no evidence for a dose effect of levodopa on reward-based behavior with the patients’ actual levodopa dose being uncorrelated to their performance on the reward-based learning tasks

Attitude Control and Stabilization of Spacecraft with a Captured Asteroid

National Aeronautics and Space Administration's Asteroid Redirect Mission (ARM) aims to capture a Near Earth Orbit (NEO) asteroid or a piece of a large asteroid and transport it to the Earth{Moon system. In this paper, we provide a detailed analysis of one of the main control challenges for the first ARM mission concept, namely despinning and three-axis stabilizing the asteroid and spacecraft combination after the ARM spacecraft captures the tumbling NEO asteroid. We first show that control laws, which explicitly use the dynamics of the system in their control law equation, encounter a fundamental limitation due to modeling uncertainties. We show that in the presence of large modeling uncertainties, the resultant disturbance torque for such control laws may well exceed the maximum control torque of the conceptual ARM spacecraft. We then numerically compare the performance of three viable control laws: the robust nonlinear tracking control law, the adaptive nonlinear tracking control law, and the simple derivative plus proportional-derivative linear control strategy. We conclude that under very small mod- eling uncertainties, which can be achieved using online system identification, the robust nonlinear tracking control law guarantees exponential convergence to the fuel-optimal reference trajectory and hence consumes the least fuel. On the other hand, in the presence of large modeling uncertainties, measurement errors, and actuator saturations, the best strategy for stabilizing the asteroid and spacecraft combination is to first despin the system using a derivative (rate damping) linear control law and then stabilize the system in the desired orientation using the simple proportional-derivative linear control law. More-over, the fuel consumed by the conceptual ARM spacecraft using these control strategies is upper bounded by 300 kg for the nominal range of NEO asteroid parameters. We conclude this paper with specific design guidelines for the ARM spacecraft for efficiently stabilizing the tumbling NEO asteroid and spacecraft combination

Development and testing of a pyro-driven launcher for harpoon-based comet sample acquisition

The CORSAIR (COmet Rendezvous, Sample Acquisition, Investigation, and Return) mission is a proposal for the fourth NASA New Frontiers program. It belongs to the Comet Surface Sample Return mission theme which focuses on acquiring and returning to Earth a macroscopic sample from the surface of a comet nucleus. CORSAIR uses a harpoon-based Sample Acquisition System (SAS) with the spacecraft hovering several meters above the comet surface. This stand-off strategy overcomes disadvantages of systems using drills or shovels. Since comets are low gravity objects, these techniques would require anchoring before sampling, which is not necessary here. Moreover, the harpoon-based system allows for acquiring several samples from different locations on the comet maximizing the scientifc output of the mission. Each SAS assembly consists of a pyro-driven launcher, a Sample Acquisition and Retrieval Projectile (SARP) and a retraction system using a deployable composite boom structure. In order to collect enough cometary material, the launcher has to provide the required kinetic energy to the SARP. Due to high energy densities, pyrotechnically actuated devices ultimately reduce the overall system mass and dimensions. Here, an overview of the development, design and testing of the launcher is given. Furthermore, the launcher theory is introduced explaining the entire reaction chain: initiation -> gas dynamics -> SARP motion

The Neural Basis of Following Advice

Learning by following explicit advice is fundamental for human cultural evolution, yet the neurobiology of adaptive social learning is largely unknown. Here, we used simulations to analyze the adaptive value of social learning mechanisms, computational modeling of behavioral data to describe cognitive mechanisms involved in social learning, and model-based functional magnetic resonance imaging (fMRI) to identify the neurobiological basis of following advice. One-time advice received before learning had a sustained influence on people's learning processes. This was best explained by social learning mechanisms implementing a more positive evaluation of the outcomes from recommended options. Computer simulations showed that this “outcome-bonus” accumulates more rewards than an alternative mechanism implementing higher initial reward expectation for recommended options. fMRI results revealed a neural outcome-bonus signal in the septal area and the left caudate. This neural signal coded rewards in the absence of advice, and crucially, it signaled greater positive rewards for positive and negative feedback after recommended rather than after non-recommended choices. Hence, our results indicate that following advice is intrinsically rewarding. A positive correlation between the model's outcome-bonus parameter and amygdala activity after positive feedback directly relates the computational model to brain activity. These results advance the understanding of social learning by providing a neurobiological account for adaptive learning from advice

Tunable Photodetectors via In Situ Thermal Conversion of TiS3 to TiO2

In two-dimensional materials research, oxidation is usually considered as a common source for the degradation of electronic and optoelectronic devices or even device failure. However, in some cases a controlled oxidation can open the possibility to widely tune the band structure of 2D materials. In particular, we demonstrate the controlled oxidation of titanium trisulfide (TiS3), a layered semicon-ductor that has attracted much attention recently thanks to its quasi-1D electronic and optoelectron-ic properties and its direct bandgap of 1.1 eV. Heating TiS3 in air above 300 °C gradually converts it into TiO2, a semiconductor with a wide bandgap of 3.2 eV with applications in photo-electrochemistry and catalysis. In this work, we investigate the controlled thermal oxidation of indi-vidual TiS3 nanoribbons and its influence on the optoelectronic properties of TiS3-based photodetec-tors. We observe a step-wise change in the cut-off wavelength from its pristine value ~1000 nm to 450 nm after subjecting the TiS3 devices to subsequent thermal treatment cycles. Ab-initio and many-body calculations confirm an increase in the bandgap of titanium oxysulfide (TiO2-xSx) when in-creasing the amount of oxygen and reducing the amount of sulfur