Auditory and visual category learning in children and adults

Categories are fundamental to everyday life and the ability to learn new categories is relevant across the lifespan. Categories are ubiquitous across modalities, supporting complex processes such as object recognition and speech perception. Prior work has proposed that different categories may engage learning systems with unique developmental trajectories. There is a limited understanding of how perceptual and cognitive development influences learning as prior studies have examined separate participants in a single modality. The current study presents a comprehensive assessment of category learning in 8-12-year-old children (12 female; 34 white, 1 Asian, 1 more than one race; M household income $85-$100 K) and 18-61-year-old adults (13 female; 32 white, 10 Black or African American, 4 Asian, 2 more than one race, 1 other; M household income $40-55 K) in a broad sample collected online from the United States. Across multiple sessions, participants learned categories across modalities (auditory, visual) that engage different learning systems (explicit, procedural). Unsurprisingly, adults outperformed children across all tasks. However, this enhanced performance was asymmetrical across categories and modalities. Adults far outperformed children in learning visual explicit categories and auditory procedural categories, with fewer differences across development for other types of categories. Adults' general benefit over children was due to enhanced information processing, while their superior performance for visual explicit and auditory procedural categories was associated with less cautious correct responses. These results demonstrate an interaction between perceptual and cognitive development that influences learning of categories that may correspond to the development of real-world skills such as speech perception and reading. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Financial incentives facilitate stronger neural computation of prosocial decisions in lower empathic adult females

Financial incentives are commonly used to motivate behaviors. However, there is also evidence that incentives can impede the behavior they are supposed to foster, for example, documented by a decrease in blood donations if a financial incentive is offered. Based on these findings, previous studies assumed that prosocial motivation is shaped by incentives. However, so far, there is no direct evidence showing an interaction between financial incentives and a specific prosocial motive. Combining drift-diffusion modeling and fMRI, we investigated the effect of financial incentives on empathy, i.e., one of the key motives driving prosocial decisions. In the empathy-alone condition, participants made prosocial decisions based on empathy. In the empathy-bonus condition, they were offered a financial bonus for prosocial decisions, in addition to empathy induction. On average, the bonus enhanced the information accumulation in empathy-based decisions. On the neural level, this enhancement was related to the anterior insula, the same region that also correlated with empathy ratings. Moreover, the effect of the financial incentive on anterior insula activation was stronger the lower a person scored on empathy. These findings show that financial incentives enhance prosocial motivation in the absence of empathy.

The Role of the Dorsal-Lateral Prefrontal Cortex in Reward Sensitivity During Approach-Avoidance Conflict

Approach-Avoidance conflict (AAC) arises from decisions with embedded positive and negative outcomes, such that approaching leads to reward and punishment and avoiding to neither. Despite its importance, the field lacks a mechanistic understanding of which regions are driving avoidance behavior during conflict. In the current task, we utilized transcranial magnetic stimulation (TMS) and drift-diffusion modeling to investigate the role of one of the most prominent regions relevant to AAC-the dorsolateral prefrontal cortex (dlPFC). The first experiment uses in-task disruption to examine the right dlPFC's (r-dlPFC) causal role in avoidance behavior. The second uses single TMS pulses to probe the excitability of the r-dlPFC, and downstream cortical activations, during avoidance behavior. Disrupting r-dlPFC during conflict decision-making reduced reward sensitivity. Further, r-dlPFC was engaged with a network of regions within the lateral and medial prefrontal, cingulate, and temporal cortices that associate with behavior during conflict. Together, these studies use TMS to demonstrate a role for the dlPFC in reward sensitivity during conflict and elucidate the r-dlPFC's network of cortical regions associated with avoidance behavior. By identifying r-dlPFC's mechanistic role in AAC behavior, contextualized within its conflict-specific downstream neural connectivity, we advance dlPFC as a potential neural target for psychiatric therapeutics.

Giant Enhancement of Radiative Recombination in Perovskite Light-Emitting Diodes with Plasmonic Core-Shell Nanoparticles

The integration of nanoparticles (NPs) into functional materials is a powerful tool for the smart engineering of their physical properties. If properly designed and optimized, NPs possess unique optical, electrical, quantum, and other effects that will improve the efficiency of optoelectronic devices. Here, we propose a novel approach for the enhancement of perovskite light-emitting diodes (PeLEDs) based on electronic band structure deformation by core-shell NPs forming a metal-oxide-semiconductor (MOS) structure with an Au core and SiO2 shell located in the perovskite layer. The presence of the MOS interface enables favorable charge distribution in the active layer through the formation of hole transporting channels. For the PeLED design, we consider integration of the core-shell NPs in the realistic numerical model. Using our verified model, we show that, compared with the bare structure, the incorporation of NPs increases the radiative recombination rate of PeLED by several orders of magnitude. It is intended that this study will open new perspectives for further efficiency enhancement of perovskite-based optoelectronic devices with NPs.

Consistent Device Simulation Model Describing Perovskite Solar Cells in Steady-State, Transient, and Frequency Domain

A variety of experiments on vacuum-deposited methylammonium lead iodide perovskite solar cells are presented, including JV curves with different scan rates, light intensity-dependent open-circuit voltage, impedance spectra, intensity-modulated photocurrent spectra, transient photocurrents, and transient voltage step responses. All these experimental data sets are successfully reproduced by a charge drift-diffusion simulation model incorporating mobile ions and charge traps using a single set of parameters. While previous modeling studies focused on a single experimental technique, we combine steady-state, transient, and frequency-domain simulations and measurements. Our study is an important step toward quantitative simulation of perovskite solar cells, leading to a deeper understanding of the physical effects in these materials. The analysis of the transient current upon voltage turn-on in the dark reveals that the charge injection properties of the interfaces are triggered by the accumulation of mobile ionic defects. We show that the current rise of voltage step experiments allow for conclusions about the recombination at the interface. Whether one or two mobile ionic species are used in the model has only a minor influence on the observed effects. A delayed current rise observed upon reversing the bias from +3 to -3 V in the dark cannot be reproduced yet by our drift-diffusion model. We speculate that a reversible chemical reaction of mobile ions with the contact material may be the cause of this effect, thus requiring a future model extension. A parameter variation is performed in order to understand the performance-limiting factors of the device under investigation.