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.

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.

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).

An Integrated Model of Collaborative Skill Acquisition: Anticipation, Control Tuning, and Role Adoption.

We studied collaborative skill acquisition in a dynamic setting with the game Co-op Space Fortress. While gaining expertise, the majority of subjects became increasingly consistent in the role they adopted without being able to communicate. Moreover, they acted in anticipation of the future task state.

The environmental basis of memory.

Memory should make more available things that are more likely to be needed. Across multiple environmental domains, it has been shown that such a system would match qualitatively the memory effects involving repetition, delay, and spacing (Schooler & Anderson, 2017). To obtain data of sufficient size to study how detailed patterns of past appearance predict probability of being needed again, we examined the patterns with which words appear in large two data sets: tweets from popular sources and comments on popular subreddits.

A decay-based account of learning and adaptation in complex skills.

How do humans adapt to parametric changes in a task without having to learn a new skill from scratch? Many studies of memory and sensorimotor adaptation have proposed theories that incorporate a decay on prior events, which leads the agent to eventually forget old experiences. This study investigates if a similar decay mechanism can account for human adaptation in complex skills that require the simultaneous integration of cognitive, motor, and perceptual processes. In 2 experiments, subjects learned to play a novel racing video game while adapting to parametric changes in the physics of the game's controls.

Cognitive & motor skill transfer across speeds: A video game study.

We examined the detailed behavioral characteristics of transfer of skill and the ability of the adaptive control of thought rational (ACT-R) architecture to account for this with its new Controller module. We employed a simple action video game called Auto Orbit and investigated the control tuning of timing skills across speed perturbations of the environment. In Auto Orbit, players needed to learn to alternate turn and shot actions to blow and burst balloons under time constraints imposed by balloon resets and deflations.

Discovering skill.

This paper shows how identical skills can emerge either from instruction or discovery when both result in an understanding of the causal structure of the task domain. The paper focuses on the discovery process, extending the skill acquisition model of Anderson et al. (2019) to address learning by discovery.

Reconstructing fine-grained cognition from brain activity.

We describe the Sketch-and-Stitch method for bringing together a cognitive model and EEG to reconstruct the cognition of a subject. The method was tested in the context of a video game where the actions are highly interdependent and variable: simply changing whether a key was pressed or not for a 30th of a second can lead to a very different outcome. The Sketch level identifies the critical events in the game and the Stitch level fills in the detailed actions between these events.

Learning rapid and precise skills.

A theory is presented about how instruction and experience combine to produce human fluency in a complex skill. The theory depends critically on 4 aspects of the ACT-R architecture. The first is the timing of various modules, particularly motor timing, which results in behavior that closely matches human behavior.

Learning Problem-Solving Rules as Search Through a Hypothesis Space.

Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem property such as computational difficulty of the rules biased the search process and so affected learning.

End effects and cross-dimensional interference in identification of time and length: Evidence for a common memory mechanism.

Memory plays a critical role in time estimation, yet detailed mechanisms underlying temporal memory have not been fully understood. The current functional magnetic resonance imaging (fMRI) study investigated memory phenomena in absolute identification of time durations and line lengths. In both time and length identification, participants responded faster to end-of-range stimuli (e.

Not taking the easy road: When similarity hurts learning.

Two experimental studies examined the effects of example format and example similarity on mathematical problem solving across different learning contexts. Participants were more successful inducing a correct problem-solving rule when they were provided with annotated examples rather than nonannotated examples. The effects of example similarity varied depending on learning context.

Visuospatial referents facilitate the learning and transfer of mathematical operations: extending the role of the angular gyrus.

Different external representations for learning and solving mathematical operations may affect learning and transfer. To explore the effects of learning representations, learners were each introduced to two new operations (b↑n and b↓n) via either formulas or graphical representations. Both groups became adept at solving regular (trained) problems.

Individual differences and workload effects on strategy adoption in a dynamic task.

The current study investigated the effects of individual differences and workload on strategy adaptivity in a complex, dynamic task called the Space Fortress game (Donchin, 1989). Participants learned to use a strategy of flying a ship in circles around the fortress in a standard game environment. Once they mastered the strategy, they were assigned to different workload conditions and transferred to a nonstandard environment in which a strong wind was introduced that made it more difficult to achieve a circular orbit.

Brain networks supporting execution of mathematical skills versus acquisition of new mathematical competence.

This fMRI study examines how students extend their mathematical competence. Students solved a set of algebra-like problems. These problems included Regular Problems that have a known solution technique and Exception Problems that but did not have a known technique.

Tracking children's mental states while solving algebra equations.

Behavioral and function magnetic resonance imagery (fMRI) data were combined to infer the mental states of students as they interacted with an intelligent tutoring system. Sixteen children interacted with a computer tutor for solving linear equations over a six-day period (days 0-5), with days 1 and 5 occurring in an fMRI scanner. Hidden Markov model algorithms combined a model of student behavior with multi-voxel imaging pattern data to predict the mental states of students.

Cognitive and metacognitive activity in mathematical problem solving: prefrontal and parietal patterns.

Students were taught an algorithm for solving a new class of mathematical problems. Occasionally in the sequence of problems, they encountered exception problems that required that they extend the algorithm. Regular and exception problems were associated with different patterns of brain activation.

Neural imaging to track mental states while using an intelligent tutoring system.

Hemodynamic measures of brain activity can be used to interpret a student's mental state when they are interacting with an intelligent tutoring system. Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distribution of solution times from measures of problem complexity.