Design, Construction, and Test of Compact, Distributed-Charge, X-Band Accelerator Systems that Enable Image-Guided, VHEE FLASH Radiotherapy.

The design and optimization of laser-Compton x-ray systems based on compact distributed charge accelerator structures can enable micron-scale imaging of disease and the concomitant production of beams of Very High Energy Electrons (VHEEs) capable of producing FLASH-relevant dose rates. The physics of laser-Compton x-ray scattering ensures that the scattered x-rays follow exactly the trajectory of the incident electrons, thus providing a route to image-guided, VHEE FLASH radiotherapy. The keys to a compact architecture capable of producing both laser-Compton x-rays and VHEEs are the use of X-band RF accelerator structures which have been demonstrated to operate with over 100 MeV/m acceleration gradients. The operation of these structures in a distributed charge mode in which each radiofrequency (RF) cycle of the drive RF pulse is filled with a low-charge, high-brightness electron bunch is enabled by the illumination of a high-brightness photogun with a train of UV laser pulses synchronized to the frequency of the underlying accelerator system. The UV pulse trains are created by a patented pulse synthesis approach which utilizes the RF clock of the accelerator to phase and amplitude modulate a narrow band continuous wave (CW) seed laser. In this way it is possible to produce up to 10 µA of average beam current from the accelerator. Such high current from a compact accelerator enables production of sufficient x-rays via laser-Compton scattering for clinical imaging and does so from a machine of "clinical" footprint. At the same time, the production of 1000 or greater individual micro-bunches per RF pulse enables > 10 nC of charge to be produced in a macrobunch of < 100 ns. The design, construction, and test of the 100-MeV class prototype system in Irvine, CA is also presented.

Tracking the Cognitive Band in an Open-Ended Task.

Open-ended tasks can be decomposed into the three levels of Newell's Cognitive Band: the Unit-Task level, the Operation level, and the Deliberate-Act level. We analyzed the video game Co-op Space Fortress at these levels, reporting both the match of a cognitive model to subject behavior and the use of electroencephalogram (EEG) to track subject cognition. The Unit Task level in this game involves coordinating with a partner to kill a fortress. At this highest level of the Cognitive Band, there is a good match between subject behavior and the model. The EEG signals were also strong enough to track when Unit Tasks succeeded or failed. The intermediate Operation level in this task involves legs of flight to achieve a kill. The EEG signals associated with these operations are much weaker than the signals associated with the Unit Tasks. Still, it was possible to reconstruct subject play with much better than chance success. There were significant differences in the leg behavior of subjects and models. Model behavior did not provide a good basis for interpreting a subject's behavior at this level. At the lowest Deliberate-Act level, we observed overlapping key actions, which the model did not display. Such overlapping key actions also frustrated efforts to identify EEG signals of motor actions. We conclude that the Unit-task level is the appropriate level both for understanding open-ended tasks and for using EEG to track the performance of open-ended tasks.

Periodic tapping mechanisms of skill learning in a fast-paced video game.

Timing plays a critical role when building up motor skill. In this study, we investigated and simulated human skill learning in a simplified variant of the Space Fortress video game named Auto Orbit with a strong timing component. Our principal aim was to test whether a computational model designed to simulate keypress actions repeated at rates slower than 500 ms (>500 ms) could also simulate human learning with repeated keypress actions taking place at very fast rates (≤500 ms). The main finding was that increasing speed stress forced human participants to qualitatively switch their behavior from a cognitively controlled strategy to an inherently rhythmic motor strategy. We show how the adaptive control of thought rational architecture's periodic tapping motor extension can replicate such rhythmic patterns of keypresses in two different computational models of human learning. The first model implements streamed motor actions across hands that are temporally decoupled, while the second model implements a coupled motor strategy in which actions from both hands are executed relative to the same periodic motor clock. Different subsets of subjects correspond to these two models. Our modeling simulations integrate previous psychological and motor control findings within a single cognitive architecture, and successfully replicate human behavioral patterns across a range of experimental measures at fast speed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).