Search

When making decisions in a cluttered world, humans and other animals often have to hold multiple items in memory at once--such as the different items on a shopping list. Psychophysical experiments in humans and other animals have shown remembered stimuli can sometimes become confused, with participants reporting chimeric stimuli composed of features from different stimuli. In particular, subjects will often make "swap errors" where they misattribute a feature from one object as belonging to another object. While swap errors have been described behaviorally and theoretical explanations have been proposed, their neural mechanisms are unknown. Here, we elucidate these neural mechanisms by analyzing neural population recordings from monkeys performing two multistimulus working memory tasks. In these tasks, monkeys were cued to report the color of an item that either was previously shown at a corresponding location or will be shown at the corresponding location. Animals made swap errors in both tasks. In the neural data, we find evidence that the neural correlates of swap errors emerged when correctly remembered information is selected from working memory. This led to a representation of the distractor color as if it were the target color, underlying the eventual swap error. We did not find consistent evidence that swap errors arose from misinterpretation of the cue or errors during encoding or storage in working memory. These results provide evidence that swap errors emerge during selection of correctly remembered information from working memory, and highlight this selection as a crucial--yet surprisingly brittle--neural process. [ABSTRACT FROM AUTHOR]

A pedestrian crossing a street during rush hour often looks and listens for potential danger. When they hear several different horns, they localize the cars that are honking and decide whether or not they need to modify their motor plan. How does the pedestrian use this auditory information to pick out the corresponding cars in visual space? The integration of distributed representations like these is called the assignment problem, and it must be solved to integrate distinct representations across but also within sensory modalities. Here, we identify and analyze a solution to the assignment problem: the representation of one or more common stimulus features in pairs of relevant brain regions—for example, estimates of the spatial position of cars are represented in both the visual and auditory systems. We characterize how the reliability of this solution depends on different features of the stimulus set (e.g., the size of the set and the complexity of the stimuli) and the details of the split representations (e.g., the precision of each stimulus representation and the amount of overlapping information). Next, we implement this solution in a biologically plausible receptive field code and show how constraints on the number of neurons and spikes used by the code force the brain to navigate a tradeoff between local and catastrophic errors. We show that, when many spikes and neurons are available, representing stimuli from a single sensory modality can be done more reliably across multiple brain regions, despite the risk of assignment errors. Finally, we show that a feedforward neural network can learn the optimal solution to the assignment problem, even when it receives inputs in two distinct representational formats. We also discuss relevant results on assignment errors from the human working memory literature and show that several key predictions of our theory already have support. Author summary: Human and animal behavior relies on the integration of distinct sources of information about the same objects in the world—for instance, social behavior requires the correct integration of people with their words, even when multiple people are talking over each other. We formalize this integration process and show that it relies on at least partial redundancy between these different sources of information. In the case of integrating vocalizations with their source, this redundancy could be provided by the distinct representations of spatial position in the visual and auditory systems. Then, we show that the necessity of this integration process produces a trade-off between the representation of redundant information (for reliable integration) and the representation of non-redundant information (which is to be integrated), with implications for modular organization in the brain. Finally, we show that a simple feedforward neural network can integrate as reliably as predicted by our theory—as well as make predictions from our theory that can be tested in neural data. Overall, this work provides insight into how the brain makes sense of its distributed and sometimes distinct representations of the world. [ABSTRACT FROM AUTHOR]

The Air Force Research Laboratory's Demonstration and Science Experiments (DSX) spacecraft carried a high‐voltage very low frequency transmitter and a sensitive broadband receiver to medium Earth orbit in 2019. During many pulsed transmission experiments, DSX detected apparent "boomerang" echoes when its emitted waves refracted in the magnetosphere and returned to the spacecraft. We simulated a series of these detected pulses using cold plasma ray tracing to characterize their likely wavelengths, indices of refraction, and initial wave normal angles. The waves were shown to remain relatively local to DSX, to be lightly damped, and to have a wide variety of wavelengths and indices of refraction, but they were all emitted with very oblique wave normal angles tightly clustered about half a degree from the Gendrin angle, which theoretical antenna models predict is preferentially excited. Our results are remarkably consistent with this prediction but are statistically biased closer to the resonance cone, possibly because of limitations in the ray tracing technique. The result is robust to perturbations of the simulation and confirms a very narrow beam of oblique radiation quite unlike the behavior of a dipole in vacuo. Key Points: The Demonstration and Science Experiments (DSX) very low frequency transmitter emitted waves that returned to the spacecraft via magnetospheric reflectionRay tracing analysis indicates that the waves have initial wave normal angles near the Gendrin angle and the cold plasma resonance coneThe results are consistent with current theoretical treatments of the DSX antenna [ABSTRACT FROM AUTHOR]

The Air Force Research Laboratory's Demonstration and Science Experiments (DSX) mission investigated wave-particle interactions and the particle and space environment in Medium Earth Orbit (MEO) from June 2019 to May 2021. Its Wave-Particle Interactions Experiment conducted over 1,300 active high power very low frequency transmissions in the radiation belts providing observations of antenna performance and signal propagation from a controlled source. This included hundreds of transmissions while in magnetic conjunction with other satellites. The Loss Cone Imager and Space Weather Experiment suite observed electron and proton populations over a wide energy range, with several of these instruments providing pitch-angle resolution. The Space Environmental Effects Experiment investigated effects of the MEO environment on electronics and materials. The Adaptive Controls Experiment demonstrated technology for on-board identification and control of large structure vibrational modes. We describe the DSX instrument capabilities and on orbit performance, science planning and operations for carrying out an array of active and passive experiments, and some initial results in brief. We also describe plans for further work and data release. [ABSTRACT FROM AUTHOR]