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The prospect of rewards can have strong modulatory effects on response preparation. Importantly, selection and execution of movements in real life happens under an environment characterized by uncertainty and dynamic changes. The current study investigated how the brain’s motor system adapts to the dynamic changes in the environment in pursuit of rewards. In addition, we studied how the prefrontal cognitive control system contributes in this adaptive control of motor behavior. To this end, we tested the effect of rewards and expectancy on the hallmark neural signals that reflect activity in motor and prefrontal systems, the lateralized readiness potential (LRP) and the mediofrontal (mPFC) theta oscillations, while participants performed an expected and unexpected action to retrieve rewards. To better capture the dynamic changes in neural processes represented in the LRP waveform, we decomposed the LRP into the preparation (LRPprep) and execution (LRPexec) components. The overall pattern of LRPprepand LRPexecconfirmed that they each reflect motor preparation based on the expectancy and motor execution when making a response that is either or not in line with the expectations. In the comparison of LRP magnitude across task conditions, we found a greater LRPprepwhen large rewards were more likely, reflecting a greater motor preparation to obtain larger rewards. We also found a greater LRPexecwhen large rewards were presented unexpectedly, suggesting a greater motor effort placed for executing a correct movement when presented with large rewards. In the analysis of mPFC theta, we found a greater theta power prior to performing an unexpected than expected response, indicating its contribution in response conflict resolution. Collectively, these results demonstrate an optimized motor control to maximize rewards under the dynamic changes of real-life environment.

The University of Oxford has developed an open-access software platform known as luox, which incorporates elements of CIE publications for the calculation of certain quantities integrated from spectral data. Under the terms of a licence agreement between the University of Oxford and the CIE, the CIE has agreed to endorse the software following a black-box validation of the software. This is the report of that validation exercise, based on the work of an ad hoc task group of the CIE Board of Administration. The task group selected 43 spectra from various sources, 19 being spectra with 5 nm intervals and 24 being spectra with 1 nm intervals, and calculated luminance (illuminance), a-opic radiances (a-opic irradiances), a-opic equivalent daylight luminances (a-opic equivalent daylight illuminances), a-opic efficacies of luminous radiation, and chromaticity coordinates using both luox and a variety of other available reference calculation tools, both public and private. Tolerance intervals were established for each quantity, and the deviation between the test values from luox and the reference values were calculated for each spectrum. The results for all of these evaluations showed consistency between the test values and the reference values. Based on these results, the CIE approves the following statement concerning the luox software, as per the aforementioned licence agreement: “This software incorporates methods, formulae, spectral function calculations and spectra from the International Commission on Illumination (CIE). The CIE endorses this software having made a black-box evaluation of the software as of Feb. 11, 2021, finding that the software performs satisfactorily. This software is not a replacement for the CIE publications and works from which it is derived. The user is advised to consult the original publications and works for proper understanding of and calculation of the result of this software.”

Energetic particle precipitation (EPP) is known to be an important source of chemical changes in the polar middle atmosphere in winter. Recent modeling studies further suggest that chemical changes induced by EPP can also cause dynamic changes in the middle atmosphere. In this study, we investigated the atmospheric responses to the precipitation of medium-to-high energy electrons (MEEs) over the period 2005–2013 using the Specific Dynamics Whole Atmosphere Community Climate Model (SD-WACCM). Our results show that the MEE precipitation significantly increases the amounts of NOₓ and HOₓ, resulting in mesospheric and stratospheric ozone losses by up to 60% and 25% respectively during polar winter. The MEE-induced ozone loss generally increases the temperature in the lower mesosphere but decreases the temperature in the upper mesosphere with large year-to-year variability, not only by radiative effects but also by adiabatic effects. The adiabatic effects by meridional circulation changes may be dominant for the mesospheric temperature changes. In particular, the meridional circulation changes occasionally act in opposite ways to vary the temperature in terms of height variations, especially at around the solar minimum period with low geomagnetic activity, which cancels out the temperature changes to make the average small in the polar mesosphere for the 9-year period.