The basal ganglia play key roles in adaptive behaviors guided by reward and punishment. However, despite accumulating knowledge, few studies have tested how heterogeneous signals in the basal ganglia are organized and coordinated for goal-directed behavior. In this study, we investigated neuronal signals of the direct and indirect pathways of the basal ganglia as rats performed a lever push/pull task for a probabilistic reward. In the dorsomedial striatum, we found that optogenetically and electrophysiologically identified direct pathway neurons encoded reward outcomes, whereas indirect pathway neurons encoded no-reward outcome and next-action selection. Outcome coding occurred in association with the chosen action. In support of pathway-specific neuronal coding, light activation induced a bias on repeat selection of the same action in the direct pathway, but on switch selection in the indirect pathway. Our data reveal the mechanisms underlying monitoring and updating of action selection for goal-directed behavior through basal ganglia circuits.

The structure of water in the liquid and supercritical states has been investigated with a newly developed rapid liquid and amorphous x-ray diffractometer using an imaging plate area detector. This new method has enabled us to reduce the measuring time to only one hour for each sample, which is less by a factor of about 100 than the time usually needed with a conventional θ–θ type diffractometer, and thus to measure x-ray scatterings of water at high temperatures and pressures, including supercritical state. In this study the temperature range of 300–649 K with pressures of 0.1–98.1 MPa was covered (Tc=647.3 K, Pc=22.12 MPa, ρc=0.322 g/cm3 for water). Densities of sample water were kept constant at 1.0, 0.95, 0.9, 0.8, and 0.7 g/cm3 by controlling temperature and pressure. The radial distribution functions (RDFs) have shown that the peaks for the second and further neighbors interactions disappear over 416 K and 0.95 g/cm3, showing the breakdown of local tetrahedral icelike structure in water. The analysis of the first peak of the RDFs has revealed that with increasing temperature the coordination number of the first neighbor interaction around 2.9 Å decreases from 3.1 at 300 K and 1.0 g/cm3 to 1.6 at 649 K and 0.7 g/cm3, whereas the interaction around 3.4 Å increases from 1.3 to 2.3 at the corresponding temperatures, resulting in a constant coordination number of around four in the first shell under the nearly constant densities. These findings are discussed with the recent results of computer simulation, neutron scattering, and Raman spectroscopic studies on water at high temperatures and pressures.

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The thalamus provides a massive input to the striatum, but despite accumulating evidence, the functions of this system remain unclear. It is known, however, that the centromedian (CM) and parafascicular (Pf) nuclei of the thalamus can strongly influence particular striatal neuron subtypes, notably including the cholinergic interneurons of the striatum (CINs), key regulators of striatal function. Here, we highlight the thalamostriatal system through the CM-Pf to striatal CINs. We consider how, by virtue of the direct synaptic connections of the CM and PF, their neural activity contributes to the activity of CINs and striatal projection neurons (SPNs). CM-Pf neurons are strongly activated at sudden changes in behavioral context, such as switches in action-outcome contingency or sequence of behavioral requirements, suggesting that their activity may represent change of context operationalized as associability. Striatal CINs, on the other hand, acquire and loose responses to external events associated with particular contexts. In light of this physiological evidence, we propose a hypothesis of the CM-Pf-CINs system, suggesting that it augments associative learning by generating an associability signal and promotes reinforcement learning guided by reward prediction error signals from dopamine-containing neurons. We discuss neuronal circuit and synaptic organizations based on in vivo/in vitro studies that we suppose to underlie our hypothesis. Possible implications of CM-Pf-CINs dysfunction (or degeneration) in brain diseases are also discussed by focusing on Parkinson's disease.

GaN technology is not only gaining traction in power and RF electronics but is also rapidly expanding into other application areas including digital and quantum computing electronics. This paper provides a glimpse of future GaN device technologies and advanced modeling approaches that can push the boundaries of these applications in terms of performance and reliability. While GaN power devices have recently been commercialized in the 15–900 V classes, new GaN devices are greatly desirable to explore both higher-voltage and ultra-low-voltage power applications. Moving into the RF domain, ultra-high frequency GaN devices are being used to implement digitized power amplifier circuits, and further advances using the hardware–software co-design approach can be expected. On the horizon is the GaN CMOS technology, a key missing piece to realize the full-GaN platform with integrated digital, power, and RF electronics technologies. Although currently a challenge, high-performance p-type GaN technology will be crucial to realize high-performance GaN CMOS circuits. Due to its excellent transport characteristics and ability to generate free carriers via polarization doping, GaN is expected to be an important technology for ultra-low temperature and quantum computing electronics. Finally, given the increasing cost of hardware prototyping of new devices and circuits, the use of high-fidelity device models and data-driven modeling approaches for technology-circuit co-design are projected to be the trends of the future. In this regard, physically inspired, mathematically robust, less computationally taxing, and predictive modeling approaches are indispensable. With all these and future efforts, we envision GaN to become the next Si for electronics.

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