When decisions are made under speed pressure, “urgency” signals elevate neural activity toward action-triggering thresholds independent of the sensory evidence, thus incurring a cost to choice accuracy. While urgency signals have been observed in brain circuits involved in preparing actions, their influence at other levels of the sensorimotor pathway remains unknown. We used a novel contrast-comparison paradigm to simultaneously trace the dynamics of sensory evidence encoding, evidence accumulation, motor preparation, and muscle activation in humans. Results indicate speed pressure impacts multiple sensorimotor levels but in crucially distinct ways. Evidence-independent urgency was applied to cortical action-preparation signals and downstream muscle activation, but not directly to upstream levels. Instead, differential sensory evidence encoding was enhanced in a way that partially countered the negative impact of motor-level urgency on accuracy, and these opposing sensory-boost and motor-urgency effects had knock-on effects on the buildup and pre-response amplitude of a motor-independent representation of cumulative evidence.

In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively [1-6], but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases are affected by starting the integrator closer to the more valuable bound. Here, we show significant departures from this account for humans making rapid sensory-instructed action choices. Behavior was best explained by a simple model in which the evidence representation-and hence, rate of accumulation-is itself biased by value and is non-stationary, increasing over the short decision time frame. Because the value bias initially dominates, the model uniquely predicts a dynamic "turn-around" effect on low-value cues, where the accumulator first launches toward the incorrect action but is then re-routed to the correct one. This was clearly exhibited in electrophysiological signals reflecting motor preparation and evidence accumulation. Finally, we construct an extended model that implements this dynamic effect through plausible sensory neural response modulations and demonstrate the correspondence between decision signal dynamics simulated from a behavioral fit of that model and the empirical decision signals. Our findings suggest that value and sensory information can exert simultaneous and dynamically countervailing influences on the trajectory of the accumulation-to-bound process, driving rapid, sensory-guided actions.

The neural correlates of memory formation in humans have long been investigated by exposing subjects to diverse material and comparing responses to items later remembered to those forgotten. Tasks requiring memorization of sensory sequences afford unique possibilities for linking neural memorization processes to behavior, because, rather than comparing across different items of varying content, each individual item can be examined across the successive learning states of being initially unknown, newly learned, and eventually, fully known. Sequence learning paradigms have not yet been exploited in this way, however. Here, we analyze the event-related potentials of subjects attempting to memorize sequences of visual locations over several blocks of repeated observation, with respect to pre- and post-block recall tests. Over centro-parietal regions, we observed a rapid P300 component superimposed on a broader positivity, which exhibited distinct modulations across learning states that were replicated in two separate experiments. Consistent with its well-known encoding of surprise, the P300 deflection monotonically decreased over blocks as locations became better learned and hence more expected. In contrast, the broader positivity was especially elevated at the point when a given item was newly learned, i.e., started being successfully recalled. These results implicate the Broad Positivity in endogenously-driven, intentional memory formation, whereas the P300, in processing the current stimulus to the degree that it was previously uncertain, indexes the cumulative knowledge thereby gained. The decreasing surprise/P300 effect significantly predicted learning success both across blocks and across subjects. This presents a new, neural-based means to evaluate learning capabilities independent of verbal reports, which could have considerable value in distinguishing genuine learning disabilities from difficulties to communicate the outcomes of learning, or perceptual impairments, in a range of clinical brain disorders.

High-density, integrated silicon electrodes have begun to transform systems neuroscience, by enabling large-scale neural population recordings with single cell resolution. Existing technologies, however, have provided limited functionality in nonhuman primate species such as macaques, which offer close models of human cognition and behavior. Here, we report the design, fabrication, and performance of Neuropixels 1.0-NHP, a high channel count linear electrode array designed to enable large-scale simultaneous recording in superficial and deep structures within the macaque or other large animal brain. These devices were fabricated in two versions: 4416 electrodes along a 45 mm shank, and 2496 along a 25 mm shank. For both versions, users can programmably select 384 channels, enabling simultaneous multi-area recording with a single probe. We demonstrate recording from over 3000 single neurons within a session, and simultaneous recordings from over 1000 neurons using multiple probes. This technology represents a significant increase in recording access and scalability relative to existing technologies, and enables new classes of experiments involving fine-grained electrophysiological characterization of brain areas, functional connectivity between cells, and simultaneous brain-wide recording at scale.

Neurobiological investigations of perceptual decision-making have furnished the first glimpse of a flexible cognitive process at the level of single neurons (Shadlen & Newsome, 1996; Shadlen & Kiani 2013). Neurons in the parietal and prefrontal cortex (Kim & Shadlen, 1999; Romo, Hernandez & Zainos, 2004; Hernandez, Zainos & Romo, 2002; Ding & Gold, 2012) are thought to represent the accumulation of noisy evidence, acquired over time, leading to a decision. Neural recordings averaged over many decisions have provided support for the deterministic rise in activity to a termination bound (Roitman & Shadlen, 2002). Critically, it is the unobserved stochastic component that is thought to confer variability in both choice and decision time (Gold & Shadlen, 2007). Here, we elucidate this stochastic, diffusion-like signal on individual decisions by recording simultaneously from hundreds of neurons in the lateral intraparietal cortex (LIP). We show that a small subset of these neurons, previously studied singly, represent a combination of deterministic drift and stochastic diffusion—the integral of noisy evidence—during perceptual decision making, and we provide direct support for the hypothesis that this diffusion signal is the quantity responsible for the variability in choice and reaction times. Neuronal state space and decoding analyses, applied to the whole population, also identify the drift diffusion signal. However, we show that the signal relies on the subset of neurons with response fields that overlap the choice targets. This parsimonious observation would escape detection by these powerful methods, absent a clear hypothesis.

N95 filtering facepiece respirators (FFRs) are essential for the protection of healthcare professionals and other high-risk groups against Coronavirus Disease of 2019 (COVID-19). In response to shortages in FFRs during the ongoing COVID-19 pandemic, the Food and Drug Administration issued an Emergency Use Authorization permitting FFR decontamination and reuse. However, although industrial decontamination services are available at some large institutions, FFR decontamination is not widely accessible. To be effective, FFR decontamination must (1) inactivate the virus; (2) preserve FFR integrity, specifically fit and filtering capability; and (3) be non-toxic and safe. Here we identify and test at-home heat-based methods for FFR decontamination that meet these requirements using common household appliances. Our results identify potential protocols for simple and accessible FFR decontamination, while also highlighting unsuitable methods that may jeopardize FFR integrity.

Shortages in N95 filtering facepiece respirators (FFRs) are significant as FFRs are essential for the protection of healthcare professionals and other high-risk groups against Coronavirus Disease of 2019 (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2. In response to these shortages during the ongoing COVID-19 pandemic, the Food and Drug Administration issued an Emergency Use Authorization (EUA) permitting FFR decontamination and reuse. However, although industrial decontamination services are available at some large institutions, FFR decontamination is not widely available.Effective FFR decontamination must 1) deactivate the virus; 2) preserve FFR integrity, specifically fit and filtering capability; and 3) be non-toxic and safe. Here we identify and compare at-home methods for heat-based FFR decontamination that meet these requirements, but utilize common household appliances. Our results identify viable protocols for simple and accessible FFR decontamination, while also highlighting methods that may jeopardize FFR integrity and should be avoided.One sentence summarySurvey of at-home methods for N95 respirator decontamination using heat and evaluation of their effects on N95 respirator integrity.

When decision makers prioritize speed over accuracy, neural activity is elevated in brain circuits involved in preparing actions. Such "urgency" signal components, defined by their independence from sensory evidence, are observed even before evidence is presented and can grow dynamically during decision formation. Is urgency applied globally, or are there adjustments of a distinct nature applied at different processing levels? Using a novel multi-level recording paradigm, we show that dynamic urgency impacting cortical action-preparation signals is echoed downstream in electromyographic indices of muscle activation, but does not directly influence upstream cortical levels. A motor-independent representation of cumulative evidence reached lower pre-response levels under conditions of greater motor-level urgency, paralleling a decline in choice accuracy. At the sensory level itself, we find a boost in differential evidence, which is correlated with changes in pupil size and acts to alleviate, rather than contribute to, the overall accuracy cost under speed pressure.. CC-BY-NC 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/203141 doi: bioRxiv preprint first posted online Oct. 14, 2017; 3 When situations call for it, animals can prioritize speed over accuracy in their sensoryguided actions. Prominent computational models suggest that sensorimotor decisions are made by drawing sequential samples from noisy evidence representations and integrating them up to an action-triggering threshold 1,2 . In this framework speed can be emphasized at the expense of accuracy by lowering this threshold, which in the models may be constant or collapsing (i.e., narrowing) over the timeframe of the decision 3,4 .Neural circuits involved in preparing decision-reporting actions have been found to implement such adjustments in the form of "urgency" signal components, which nonselectively elevate activity towards action thresholds. A "static" component of urgency has been widely observed in raised baseline activity before evidence presentation 5-8 , and recent work has further revealed a "dynamic" component that grows over the course of a decision, effectively implementing a collapsing bound [8][9][10][11] . A key defining property of urgency is that it is generated purely from knowledge of time constraints and/or elapsed time itself, and it contributes to neural buildup activity alongside, but strictly independent of, the influence of sensory evidence 12 . This means that any speed benefits of urgency necessarily incur a cost to choice accuracy. Thus far, urgency components have been identified only in neural circuits involved in preparing actions. Recent work has implicated diffusely-projecting neuromodulatory systems in the generation of urgency 11,13 , suggesting that it may, in fact, act globally, i.e., at all levels of the sensor...