Recent Advances at the Interface of Neuroscience and Artificial Neural Networks.

Biological neural networks adapt and learn in diverse behavioral contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This review highlights recent advances in computational and experimental research to advance our understanding of biological and artificial intelligence. In particular, we discuss critical mechanisms from the cellular, systems, and cognitive neuroscience fields that have contributed to refining the architecture and training algorithms of ANNs. Additionally, we discuss how recent work used ANNs to understand complex neuronal correlates of cognition and to process high throughput behavioral data.

An exploratory study of distractions during the induction phase of pediatric procedural sedation with propofol.

INTRODUCTION: Distractions are a leading cause of disturbance to workflow during medical care. Distractions affecting the anesthetic team in the operating room are frequent and have a negative impact on patient care one-fifth of the time. The objective of this study was to evaluate the frequency, source, target, and impact of distractions during the induction phase of pediatric procedural sedation outside the operating room. METHODS: Distractions were analyzed during propofol induction for oncology procedures from 45 video recordings. Distraction was defined as any event that disturbs or has potential to disturb the sedation team from performing their primary tasks. The type of distraction was cataloged into communication, coordination, extraneous events, equipment, layout, and usability. A five-point Likert scale was used to quantify the impact on the sedation team or its members. RESULTS: All patients had a diagnosis of acute lymphocytic leukemia and had a mean age of 8.4 years. Five hundred and sixty-seven distractions occurred and averaged 12.6 events (±5.6) per induction (mean induction time 3 min 12 s). Extraneous events were most common, accounting for 55% (312/567) of all distractions. Most distractions had an impact on the sedation team's workflow, resulting in multitasking (46%, n = 262), and in either brief or complete disruption from a primary task (17%). Sedation nurses were impacted most often, 62% of the time. Coordination and usability issues resulted in the greatest negative impact, mean ± SD, 3.7 ± 1.0 and 3.5 ± 0.9, respectively. There was no significant association between distractions and adverse events or induction length. DISCUSSION: Distractions are common during procedural sedation, with extraneous events being most frequent. Coordination issues within the team and usability problems had the greatest negative impact on sedation team workflow. Nurses were the most frequent target. CONCLUSION: Distractions impacted sedation team workflow but had no association with patient outcomes.

Tuned inhibition in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior.

Current dominant views hold that perceptual confidence reflects the probability that a decision is correct. Although these views have enjoyed some empirical support, recent behavioral results indicate that confidence and the probability of being correct can be dissociated. An alternative hypothesis suggests that confidence instead reflects the magnitude of evidence in favor of a decision while being relatively insensitive to the evidence opposing the decision. We considered how this alternative hypothesis might be biologically instantiated by developing a simple neural network model incorporating a known property of sensory neurons: tuned inhibition. The key idea of the model is that the level of inhibition that each accumulator unit receives from units with the opposite tuning preference, i.e. its inhibition 'tuning', dictates its contribution to perceptual decisions versus confidence judgments, such that units with higher tuned inhibition (computing relative evidence for different perceptual interpretations) determine perceptual discrimination decisions, and units with lower tuned inhibition (computing absolute evidence) determine confidence. We demonstrate that this biologically plausible model can account for several counterintuitive findings reported in the literature where confidence and decision accuracy dissociate. By comparing model fits, we further demonstrate that a full complement of behavioral data across several previously published experimental results-including accuracy, reaction time, mean confidence, and metacognitive sensitivity-is best accounted for when confidence is computed from units without, rather than units with, tuned inhibition. Finally, we discuss predictions of our results and model for future neurobiological studies. These findings suggest that the brain has developed and implements this alternative, heuristic theory of perceptual confidence computation by relying on the diversity of neural resources available.

Anticholinergics and serious adverse events in pediatric procedural sedation: A report of the pediatric sedation research consortiums.

BACKGROUND: Pediatric sedation is a clinical activity with potential for serious but rare airway adverse events, particularly laryngospasm. Anticholinergic drugs, atropine and glycopyrrolate, are frequently used with the intention to improve sedation safety by virtue of their antisialagogue effects. AIMS: The objective of this study is to describe the current practice of anticholinergic use in pediatric sedation and to compare the frequency of serious sedation-related adverse events in patients who received anticholinergics to those who did not. METHODS: We examined prospectively collected data from the Pediatric Sedation Research Consortium database. Patient characteristics, procedure type, sedation provider, sedatives, location of sedation, anticholinergic administered, adverse events, and airway interventions were reported. Propensity score matching and multivariable logistic regression were used to test whether any association exists between anticholinergic use and serious sedation-related adverse events. RESULTS: Anticholinergics were administered in 7.1% (n = 18 707) of all cases (n = 263 883) reported between November 2011 and October 2017. When anticholinergics were used, atropine was used in 22% (n = 4111) and glycopyrrolate in 78.1% (n = 14 601) of sedations. Use of anticholinergics was more common in patients with well-described risk factors for airway adverse events: active/history of upper respiratory infection, history of reactive airway disease/asthma, and exposure to smoke. However, infants and ASA 3 patients were not associated with higher rate of anticholinergic use. Anticholinergic use was independently associated with an increase in the odds of serious adverse events, OR 1.8 (95% CI 1.6-2.1), especially airway adverse events. CONCLUSIONS: In this large Pediatric Sedation Research Consortium study, we found the use of anticholinergic adjuvants independently associated with greater odds of serious adverse events, especially airway adverse events, after adjusting for well-known sedation risk factors using propensity score matching and multivariate analysis.

Superior colliculus neuronal ensemble activity signals optimal rather than subjective confidence.

Recent studies suggest that neurons in sensorimotor circuits involved in perceptual decision-making also play a role in decision confidence. In these studies, confidence is often considered to be an optimal readout of the probability that a decision is correct. However, the information leading to decision accuracy and the report of confidence often covaried, leaving open the possibility that there are actually two dissociable signal types in the brain: signals that correlate with decision accuracy (optimal confidence) and signals that correlate with subjects' behavioral reports of confidence (subjective confidence). We recorded neuronal activity from a sensorimotor decision area, the superior colliculus (SC) of monkeys, while they performed two different tasks. In our first task, decision accuracy and confidence covaried, as in previous studies. In our second task, we implemented a motion discrimination task with stimuli that were matched for decision accuracy but produced different levels of confidence, as reflected by behavioral reports. We used a multivariate decoder to predict monkeys' choices from neuronal population activity. As in previous studies on perceptual decision-making mechanisms, we found that neuronal decoding performance increased as decision accuracy increased. However, when decision accuracy was matched, performance of the decoder was similar between high and low subjective confidence conditions. These results show that the SC likely signals optimal decision confidence similar to previously reported cortical mechanisms, but is unlikely to play a critical role in subjective confidence. The results also motivate future investigations to determine where in the brain signals related to subjective confidence reside.

Social relevance modulates multivariate neural representations of threat generalization in children and adults.

Few studies have examined threat generalization across development and no developmental studies have compared the generalization of social versus nonsocial threat, making it difficult to identify contextual factors that contribute to threat learning across development. The present study assessed youth and adults' multivoxel neural representations of social versus nonsocial threat stimuli. Twenty adults (Mage  = 25.7 ± 4.9) and 16 youth (Mage  = 14.1 ± 1.7) completed two conditioning and extinction recall paradigms: one social and one nonsocial paradigm. Three weeks after conditioning, participants underwent a functional magnetic resonance imaging extinction recall task that presented the extinguished threat cue (CS+), a safety cue (CS-), and generalization stimuli (GS) consisting of CS-/CS+ blends. Across age groups, neural activity patterns and self-reported fear and memory ratings followed a linear generalization gradient for social threat stimuli and a quadratic generalization gradient for nonsocial threat stimuli, indicating enhanced threat/safety discrimination for social relative to nonsocial threat stimuli. The amygdala and ventromedial prefrontal cortex displayed the greatest neural pattern differentiation between the CS+ and GS/CS-, reinforcing their role in threat learning and extinction recall. Contrary to predictions, age did not influence threat representations. These findings highlight the importance of the social relevance of threat on generalization across development.

Anodal Transcranial Direct Current Stimulation to the Left Rostrolateral Prefrontal Cortex Selectively Improves Source Memory Retrieval.

Functional neuroimaging studies have consistently implicated the left rostrolateral prefrontal cortex (RLPFC) as playing a crucial role in the cognitive operations supporting episodic memory and analogical reasoning. However, the degree to which the left RLPFC causally contributes to these processes remains underspecified. We aimed to assess whether targeted anodal stimulation-thought to boost cortical excitability-of the left RLPFC with transcranial direct current stimulation (tDCS) would lead to augmentation of episodic memory retrieval and analogical reasoning task performance in comparison to cathodal stimulation or sham stimulation. Seventy-two healthy adult participants were evenly divided into three experimental groups. All participants performed a memory encoding task on Day 1, and then on Day 2, they performed continuously alternating tasks of episodic memory retrieval, analogical reasoning, and visuospatial perception across two consecutive 30-min experimental sessions. All groups received sham stimulation for the first experimental session, but the groups differed in the stimulation delivered to the left RLPFC during the second session (either sham, 1.5 mA anodal tDCS, or 1.5 mA cathodal tDCS). The experimental group that received anodal tDCS to the left RLPFC during the second session demonstrated significantly improved episodic memory source retrieval performance, relative to both their first session performance and relative to performance changes observed in the other two experimental groups. Performance on the analogical reasoning and visuospatial perception tasks did not exhibit reliable changes as a result of tDCS. As such, our results demonstrate that anodal tDCS to the left RLPFC leads to a selective and robust improvement in episodic source memory retrieval.

On a 'failed' attempt to manipulate visual metacognition with transcranial magnetic stimulation to prefrontal cortex.

Rounis, Maniscalco, Rothwell, Passingham, and Lau (2010) reported that stimulation of prefrontal cortex impairs visual metacognition. Bor, Schwartzman, Barrett, and Seth (2017) attempted to replicate this result, but adopted an experimental design that reduced their chanceof obtaining positive findings. Despite that, their results appeared initially consistent with those of Rounis et al., but they subsequently claimed it was necessary to discard ∼30% of their subjects, after which they reported a null result. Using computer simulations, we found that, contrary to their supposed purpose, excluding subjects by Bor et al.'s criteria does not reduce false positive rates. Including both their positive and negative result in a Bayesian framework, we show the correct interpretation is that PFC stimulation likely impaired visual metacognition, exactly contradicting Bor et al.'s claims. That lesion and inactivation studies demonstrate similar positive effects further suggests that Bor et al.'s reported negative finding isn't evidence against the role of prefrontal cortex in metacognition.

Delirium in Critically Ill Children: An International Point Prevalence Study.

OBJECTIVES: To determine prevalence of delirium in critically ill children and explore associated risk factors. DESIGN: Multi-institutional point prevalence study. SETTING: Twenty-five pediatric critical care units in the United States, the Netherlands, New Zealand, Australia, and Saudi Arabia. PATIENTS: All children admitted to the pediatric critical care units on designated study days (n = 994). INTERVENTION: Children were screened for delirium using the Cornell Assessment of Pediatric Delirium by the bedside nurse. Demographic and treatment-related variables were collected. MEASUREMENTS AND MAIN RESULTS: Primary study outcome measure was prevalence of delirium. In 159 children, a final determination of mental status could not be ascertained. Of the 835 remaining subjects, 25% screened positive for delirium, 13% were classified as comatose, and 62% were delirium-free and coma-free. Delirium prevalence rates varied significantly with reason for ICU admission, with highest delirium rates found in children admitted with an infectious or inflammatory disorder. For children who were in the PICU for 6 or more days, delirium prevalence rate was 38%. In a multivariate model, risk factors independently associated with development of delirium included age less than 2 years, mechanical ventilation, benzodiazepines, narcotics, use of physical restraints, and exposure to vasopressors and antiepileptics. CONCLUSIONS: Delirium is a prevalent complication of critical illness in children, with identifiable risk factors. Further multi-institutional, longitudinal studies are required to investigate effect of delirium on long-term outcomes and possible preventive and treatment measures. Universal delirium screening is practical and can be implemented in pediatric critical care units.

The presynaptic choline transporter imposes limits on sustained cortical acetylcholine release and attention.

Functional variation in the gene encoding the presynaptic choline transporter (CHT) has been linked to attention-deficit/hyperactivity disorder. Here, we report that a heterozygous deletion in the CHT gene in mice (CHT(+/-)) limits the capacity of cholinergic neurons to sustain acetylcholine (ACh) release and attentional performance. Cortical microdialysis and amperometric methods revealed that, whereas wild-type and CHT(+/-) animals support equivalent basal ACh release and choline clearance, CHT(+/-) animals exhibit a significant inability to elevate extracellular ACh following basal forebrain stimulation, in parallel with a diminished choline clearance capacity following cessation of stimulation. Consistent with these findings, the density of CHTs in cortical synaptosomal plasma membrane-enriched fractions from unstimulated CHT(+/-) animals matched those observed in wild-type animals despite reductions in CHT levels in total extracts, achieved via a redistribution of CHT from vesicle pools. As a consequence, in CHT(+/-) animals, basal forebrain stimulation was unable to mobilize wild-type quantities of CHT to the plasma membrane. In behavioral studies, CHT(+/-) mice were impaired in performing a sustained attention task known to depend on cortical cholinergic activity. In wild-type mice, but not CHT(+/-) mice, attentional performance increased the density of CHTs in the synaptosomal membrane in the right frontal cortex. Basal CHT levels in vesicle-enriched membranes predicted the degree of CHT mobilization as well as individual variations in performance on the sustained attention task. Our findings demonstrate biochemical and physiological alterations that underlie cognitive impairments associated with genetically imposed reductions in choline uptake capacity.

Behavioral and neural measures of confidence using a novel auditory pitch identification task.

Observers can discriminate between correct versus incorrect perceptual decisions with feelings of confidence. The centro-parietal positivity build-up rate (CPP slope) has been suggested as a likely neural signature of accumulated evidence, which may guide both perceptual performance and confidence. However, CPP slope also covaries with reaction time, which also covaries with confidence in previous studies, and performance and confidence typically covary; thus, CPP slope may index signatures of perceptual performance rather than confidence per se. Moreover, perceptual metacognition-including neural correlates-has largely been studied in vision, with few exceptions. Thus, we lack understanding of domain-general neural signatures of perceptual metacognition outside vision. Here we designed a novel auditory pitch identification task and collected behavior with simultaneous 32-channel EEG in healthy adults. Participants saw two tone labels which varied in tonal distance on each trial (e.g., C vs D, C vs F), then heard a single auditory tone; they identified which label was correct and rated confidence. We found that pitch identification confidence varied with tonal distance, but performance, metacognitive sensitivity (trial-by-trial covariation of confidence with accuracy), and reaction time did not. Interestingly, however, while CPP slope covaried with performance and reaction time, it did not significantly covary with confidence. We interpret these results to mean that CPP slope is likely a signature of first-order perceptual processing and not confidence-specific signals or computations in auditory tasks. Our novel pitch identification task offers a valuable method to examine the neural correlates of auditory and domain-general perceptual confidence.

Unconscious Perception of Vernier Offsets.

The comparison between conscious and unconscious perception is a cornerstone of consciousness science. However, most studies reporting above-chance discrimination of unseen stimuli do not control for criterion biases when assessing awareness. We tested whether observers can discriminate subjectively invisible offsets of Vernier stimuli when visibility is probed using a bias-free task. To reduce visibility, stimuli were either backward masked or presented for very brief durations (1-3 milliseconds) using a modern-day Tachistoscope. We found some behavioral indicators of perception without awareness, and yet, no conclusive evidence thereof. To seek more decisive proof, we simulated a series of Bayesian observer models, including some that produce visibility judgements alongside type-1 judgements. Our data are best accounted for by observers with slightly suboptimal conscious access to sensory evidence. Overall, the stimuli and visibility manipulations employed here induced mild instances of blindsight-like behavior, making them attractive candidates for future investigation of this phenomenon.

Development of infection prevention program standards for critical access hospitals.

Although critical access hospitals are small, the expected infection prevention activities remain extensive. Program standards, aligned with the Association for Professionals in Infection Control and Epidemiology infection prevention competency model domains, were developed and implemented in a midwestern health care system. Time estimates for completion of each activity were assigned and then extrapolated to offer guidance on necessary full-time equivalents for adequate staffing.

A predictor-informed multi-subject bayesian approach for dynamic functional connectivity.

Dynamic functional connectivity investigates how the interactions among brain regions vary over the course of an fMRI experiment. Such transitions between different individual connectivity states can be modulated by changes in underlying physiological mechanisms that drive functional network dynamics, e.g., changes in attention or cognitive effort. In this paper, we develop a multi-subject Bayesian framework where the estimation of dynamic functional networks is informed by time-varying exogenous physiological covariates that are simultaneously recorded in each subject during the fMRI experiment. More specifically, we consider a dynamic Gaussian graphical model approach where a non-homogeneous hidden Markov model is employed to classify the fMRI time series into latent neurological states. We assume the state-transition probabilities to vary over time and across subjects as a function of the underlying covariates, allowing for the estimation of recurrent connectivity patterns and the sharing of networks among the subjects. We further assume sparsity in the network structures via shrinkage priors, and achieve edge selection in the estimated graph structures by introducing a multi-comparison procedure for shrinkage-based inferences with Bayesian false discovery rate control. We evaluate the performances of our method vs alternative approaches on synthetic data. We apply our modeling framework on a resting-state experiment where fMRI data have been collected concurrently with pupillometry measurements, as a proxy of cognitive processing, and assess the heterogeneity of the effects of changes in pupil dilation on the subjects' propensity to change connectivity states. The heterogeneity of state occupancy across subjects provides an understanding of the relationship between increased pupil dilation and transitions toward different cognitive states.

Secretory factors released from high dose radiation-activated osteoclasts increase the expression level of pain-associated neuropeptides in sensory neuronal cultures.

Stereotactic Body Radiation Therapy for lung tumors near the chest wall often causes significant chest wall pain (CWP), negatively impacting patients' quality of life. The mechanisms behind SBRT-induced CWP remain unclear and may involve multiple factors. We investigated the potential crosstalk between radiation-activated osteoclasts and sensory neurons, focusing on osteoclast-derived factors in CWP. Using the murine pre-osteoclast cell line Raw264.7, we induced differentiation with RANKL, followed by 10Gy gamma-irradiation. Conditioned media from these irradiated osteoclasts was used to treat sensory neuronal cultures from mouse dorsal root ganglia. Neuronal cultures were also directly exposed to 10Gy radiation, with and without osteoclast co-culture. Analysis of osteoclast markers and pain-associated neuropeptides was conducted using RT-qPCR and histochemical staining. Osteoclast differentiation and activity were inhibited using Osteoprotegerin and risedronate. Results showed that high-dose radiation significantly increased osteoclast size, resorption pit size, and activity biomarkers. Neurons treated with CM from irradiated osteoclasts showed increased expression of pain-associated neuropeptides CGRP and Substance P, which was mitigated by osteoprotegerin and risedronate. This study suggests that high-dose radiation enhances osteoclast activity, upregulating pain-associated neuropeptides in sensory neurons, and that inhibitors like osteoprotegerin and risedronate may offer therapeutic strategies for managing radiation-induced pain.

Tests for consciousness in humans and beyond.

Which systems/organisms are conscious? New tests for consciousness ('C-tests') are urgently needed. There is persisting uncertainty about when consciousness arises in human development, when it is lost due to neurological disorders and brain injury, and how it is distributed in nonhuman species. This need is amplified by recent and rapid developments in artificial intelligence (AI), neural organoids, and xenobot technology. Although a number of C-tests have been proposed in recent years, most are of limited use, and currently we have no C-tests for many of the populations for which they are most critical. Here, we identify challenges facing any attempt to develop C-tests, propose a multidimensional classification of such tests, and identify strategies that might be used to validate them.

Toward 'Computational-Rationality' Approaches to Arbitrating Models of Cognition: A Case Study Using Perceptual Metacognition.

Perceptual confidence results from a metacognitive process which evaluates how likely our percepts are to be correct. Many competing models of perceptual metacognition enjoy strong empirical support. Arbitrating these models traditionally proceeds via researchers conducting experiments and then fitting several models to the data collected. However, such a process often includes conditions or paradigms that may not best arbitrate competing models: Many models make similar predictions under typical experimental conditions. Consequently, many experiments are needed, collectively (sub-optimally) sampling the space of conditions to compare models. Here, instead, we introduce a variant of optimal experimental design which we call a computational-rationality approach to generative models of cognition, using perceptual metacognition as a case study. Instead of designing experiments and post-hoc specifying models, we began with comprehensive model comparison among four competing generative models for perceptual metacognition, drawn from literature. By simulating a simple experiment under each model, we identified conditions where these models made maximally diverging predictions for confidence. We then presented these conditions to human observers, and compared the models' capacity to predict choices and confidence. Results revealed two surprising findings: (1) two models previously reported to differently predict confidence to different degrees, with one predicting better than the other, appeared to predict confidence in a direction opposite to previous findings; and (2) two other models previously reported to equivalently predict confidence showed stark differences in the conditions tested here. Although preliminary with regards to which model is actually 'correct' for perceptual metacognition, our findings reveal the promise of this computational-rationality approach to maximizing experimental utility in model arbitration while minimizing the number of experiments necessary to reveal the winning model, both for perceptual metacognition and in other domains.

Serious Infusion Reactions in Two Adolescents Receiving Bebtelovimab.

There is scant literature available for pediatric prescribers regarding safety and efficacy of monoclonal antibody formulations against coronavirus disease 2019 (COVID-19). Here, we present 2 cases of serious infusion reactions in adolescent patients receiving the monoclonal antibody bebtelovimab and a succinct review of available antiviral medications for pediatric patients with mild or moderate COVID-19.

A Novel Hidden Markov Approach to Studying Dynamic Functional Connectivity States in Human Neuroimaging.

Introduction: Hidden Markov models (HMMs) are a popular choice to extract and examine recurring patterns of activity or functional connectivity in neuroimaging data, both in terms of spatial patterns and their temporal progression. Although many diverse HMMs have been applied to neuroimaging data, most have defined states based on activity levels (intensity-based [IB] states) rather than patterns of functional connectivity between brain areas (connectivity-based states), which is problematic if we want to understand connectivity dynamics: IB states are unlikely to provide comprehensive information about dynamic connectivity patterns. Methods: We addressed this problem by introducing a new HMM that defines states based on full functional connectivity (FFC) profiles among brain regions. We empirically explored the behavior of this new model in comparison to existing approaches based on IB or summed functional connectivity states using the Human Connectome Project unrelated 100 functional magnetic resonance imaging "resting-state" dataset. Results: Our FFC model discovered connectivity states with more distinguishable (i.e., unique and separable from each other) patterns than previous approaches, and recovered simulated connectivity-based states more faithfully than the other models tested. Discussion: Thus, if our goal is to extract and interpret connectivity states in neuroimaging data, our new model outperforms previous methods, which miss crucial information about the evolution of functional connectivity in the brain. Impact statement Hidden Markov models (HMMs) can be used to investigate brain states noninvasively. Previous models "recover" connectivity from intensity-based hidden states, or from connectivity "summed" across nodes. In this study, we introduce a novel connectivity-based HMM and show how it can reveal true connectivity hidden states under minimal assumptions.