Balancing Act: Acute and Contextual Vestibular Sensations of Cranial Electrotherapy Stimulation Using Survey and Sensor Outcomes in a Non-Clinical Sample.

Cranial electrotherapy stimulation (CES) delivers low-intensity electrical currents to the brain to treat anxiety, depression, and pain. Though CES is considered safe and cost-effective, little is known about side effects emerging across different contexts. Our objective was to investigate how varying physical and cognitive demands impact the frequency and intensity of CES vestibular sensations in a sample of healthy young adults. We used a 2 (stimulation: sham, active) × 2 (physical demand: static sway, dynamic sit-to-stand) × 2 (cognitive demand: single-task remain silent, dual-task count backward) repeated measures design. Vestibular sensations were measured with surveys and wearable sensors capturing balance changes. Active stimulation did not influence reported vestibular sensations. Instead, high physical demand predicted more sensation reports. High cognitive demand, but not active stimulation, predicted postural sway unsteadiness. Significant effects of active stimulation on balance were observed only during the dynamic sit-to-stand transitions. In summary, CES induces vestibular sensations only for a specific outcome under certain circumstances. Our findings imply that consumers can safely maximize the benefits of CES while ensuring they are taking steps to minimize any potential side effects by considering their context and circumstances.

The relationship between sustained attention and parasympathetic functioning.

Sustained attention (SA) is an important cognitive ability that plays a crucial role in successful cognitive control. Resting vagally-mediated heart rate variability (vmHRV) has emerged as an informative index of parasympathetic nervous system activity and a sensitive correlate of individual differences in cognitive control. However, it is unclear how resting vmHRV is associated with individual differences in sustained attention. The primary aim of the current study was to assess if resting vmHRV was associated with individual differences in performance on a neuropsychological assessment of sustained attention. We further aimed to characterize the relationship between resting vmHRV and dispositional factors related to sustained attention, specifically attentional errors in daily life, self-regulation, mindfulness and media-multitasking. Based on previous work, we hypothesized higher resting vmHRV would be associated with better sustained attention across task-based and self-report measures. We did not find resting vmHRV to be significantly associated with performance measures on a task-based assessment of sustained attention. Further, resting vmHRV was not significantly associated with attention errors, self-regulation, mindfulness, or media-multitasking. This work stands to expand the current understanding between parasympathetic functioning, cognition, and behavior, investigating the unexplored domain of sustained attention and related dispositional factors.

Machine learning classification of diagnostic accuracy in pathologists interpreting breast biopsies.

OBJECTIVE: This study explores the feasibility of using machine learning to predict accurate versus inaccurate diagnoses made by pathologists based on their spatiotemporal viewing behavior when evaluating digital breast biopsy images. MATERIALS AND METHODS: The study gathered data from 140 pathologists of varying experience levels who each reviewed a set of 14 digital whole slide images of breast biopsy tissue. Pathologists' viewing behavior, including zooming and panning actions, was recorded during image evaluation. A total of 30 features were extracted from the viewing behavior data, and 4 machine learning algorithms were used to build classifiers for predicting diagnostic accuracy. RESULTS: The Random Forest classifier demonstrated the best overall performance, achieving a test accuracy of 0.81 and area under the receiver-operator characteristic curve of 0.86. Features related to attention distribution and focus on critical regions of interest were found to be important predictors of diagnostic accuracy. Further including case-level and pathologist-level information incrementally improved classifier performance. DISCUSSION: Results suggest that pathologists' viewing behavior during digital image evaluation can be leveraged to predict diagnostic accuracy, affording automated feedback and decision support systems based on viewing behavior to aid in training and, ultimately, clinical practice. They also carry implications for basic research examining the interplay between perception, thought, and action in diagnostic decision-making. CONCLUSION: The classifiers developed herein have potential applications in training and clinical settings to provide timely feedback and support to pathologists during diagnostic decision-making. Further research could explore the generalizability of these findings to other medical domains and varied levels of expertise.

Pathologist pupil dilation reflects experience level and difficulty in diagnosing medical images.

Purpose: Digital whole slide imaging allows pathologists to view slides on a computer screen instead of under a microscope. Digital viewing allows for real-time monitoring of pathologists' search behavior and neurophysiological responses during the diagnostic process. One particular neurophysiological measure, pupil diameter, could provide a basis for evaluating clinical competence during training or developing tools that support the diagnostic process. Prior research shows that pupil diameter is sensitive to cognitive load and arousal, and it switches between exploration and exploitation of a visual image. Different categories of lesions in pathology pose different levels of challenge, as indicated by diagnostic disagreement among pathologists. If pupil diameter is sensitive to the perceived difficulty in diagnosing biopsies, eye-tracking could potentially be used to identify biopsies that may benefit from a second opinion. Approach: We measured case onset baseline-corrected (phasic) and uncorrected (tonic) pupil diameter in 90 pathologists who each viewed and diagnosed 14 digital breast biopsy cases that cover the diagnostic spectrum from benign to invasive breast cancer. Pupil data were extracted from the beginning of viewing and interpreting of each individual case. After removing 122 trials ( < 10 % ) with poor eye-tracking quality, 1138 trials remained. We used multiple linear regression with robust standard error estimates to account for dependent observations within pathologists. Results: We found a positive association between the magnitude of phasic dilation and subject-centered difficulty ratings and between the magnitude of tonic dilation and untransformed difficulty ratings. When controlling for case diagnostic category, only the tonic-difficulty relationship persisted. Conclusions: Results suggest that tonic pupil dilation may indicate overall arousal differences between pathologists as they interpret biopsy cases and could signal a need for additional training, experience, or automated decision aids. Phasic dilation is sensitive to characteristics of biopsies that tend to elicit higher difficulty ratings and could indicate a need for a second opinion.

From Image to Diagnosis: Characterizing Sources of Error in Histopathologic Interpretation.

An accurate histopathologic diagnosis on surgical biopsy material is necessary for the clinical management of patients and has important implications for research, clinical trial design/enrollment, and public health education. This study used a mixed methods approach to isolate sources of diagnostic error while residents and attending pathologists interpreted digitized breast biopsy slides. Ninety participants, including pathology residents and attending physicians at major United States medical centers reviewed a set of 14 digitized whole-slide images of breast biopsies. Each case had a consensus-defined diagnosis and critical region of interest (cROI) representing the most significant pathology on the slide. Participants were asked to view unmarked digitized slides, draw their participant region of interest (pROI), describe its features, and render a diagnosis. Participants' review behavior was tracked using case viewer software and an eye-tracking device. Diagnostic accuracy was calculated in comparison to the consensus diagnosis. We measured the frequency of errors emerging during 4 interpretive phases: (1) detecting the cROI, (2) recognizing its relevance, (3) using the correct terminology to describe findings in the pROI, and (4) making a diagnostic decision. According to eye-tracking data, trainees and attending pathologists were very likely (∼94% of the time) to find the cROI when inspecting a slide. However, trainees were less likely to consider the cROI relevant to their diagnosis. Pathology trainees (41% of cases) were more likely to use incorrect terminology to describe pROI features than attending pathologists (21% of cases). Failure to accurately describe features was the only factor strongly associated with an incorrect diagnosis. Identifying where errors emerge in the interpretive and/or descriptive process and working on building organ-specific feature recognition and verbal fluency in describing those features are critical steps for achieving competency in diagnostic decision making.

Zoom behavior during visual search modulates pupil diameter and reflects adaptive control states.

Adaptive gain theory proposes that the dynamic shifts between exploration and exploitation control states are modulated by the locus coeruleus-norepinephrine system and reflected in tonic and phasic pupil diameter. This study tested predictions of this theory in the context of a societally important visual search task: the review and interpretation of digital whole slide images of breast biopsies by physicians (pathologists). As these medical images are searched, pathologists encounter difficult visual features and intermittently zoom in to examine features of interest. We propose that tonic and phasic pupil diameter changes during image review may correspond to perceived difficulty and dynamic shifts between exploration and exploitation control states. To examine this possibility, we monitored visual search behavior and tonic and phasic pupil diameter while pathologists (N = 89) interpreted 14 digital images of breast biopsy tissue (1,246 total images reviewed). After viewing the images, pathologists provided a diagnosis and rated the level of difficulty of the image. Analyses of tonic pupil diameter examined whether pupil dilation was associated with pathologists' difficulty ratings, diagnostic accuracy, and experience level. To examine phasic pupil diameter, we parsed continuous visual search data into discrete zoom-in and zoom-out events, including shifts from low to high magnification (e.g., 1× to 10×) and the reverse. Analyses examined whether zoom-in and zoom-out events were associated with phasic pupil diameter change. Results demonstrated that tonic pupil diameter was associated with image difficulty ratings and zoom level, and phasic pupil diameter showed constriction upon zoom-in events, and dilation immediately preceding a zoom-out event. Results are interpreted in the context of adaptive gain theory, information gain theory, and the monitoring and assessment of physicians' diagnostic interpretive processes.

Transcranial direct current stimulation (tDCS) to dorsolateral prefrontal cortex influences perceived pleasantness of food.

The ability to regulate the intake of unhealthy foods is critical in modern, calorie dense food environments. Frontal areas of the brain, such as the dorsolateral prefrontal cortex (DLPFC), are thought to play a central role in cognitive control and emotional regulation. Therefore, increasing activity in the DLPFC may enhance these functions which could improve the ability to reappraise and resist consuming highly palatable but unhealthy foods. One technique for modifying brain activity is transcranial direct current stimulation (tDCS), a non-invasive technique for modulating neuronal excitability that can influence performance on a range of cognitive tasks. We tested whether anodal tDCS targeting the right DLPFC would influence how people perceived highly palatable foods. In the present study, 98 participants were randomly assigned to receive a single session of active tDCS (2.0 mA) or sham stimulation. While receiving active or sham stimulation, participants viewed images of highly palatable foods and reported how pleasant it would be to eat each food (liking) and how strong their urge was to eat each food (wanting). We found that participants who received active versus sham tDCS stimulation perceived food as less pleasant, but there was no difference in how strong their urge was to eat the foods. Our findings suggest that modulating excitability in the DLPFC influences "liking" but not "wanting" of highly palatable foods. Non-invasive brain stimulation might be a useful technique for influencing the hedonic experience of eating but more work is needed to understand when and how it influences food cravings.

Ultra-brief training in cognitive reappraisal or mindfulness reduces anxiety and improves motor performance efficiency under stress.

BACKGROUND AND OBJECTIVES: We examined the effects of ultra-brief training in mindfulness and cognitive reappraisal on affective response and performance under stress. We hypothesized that one or both types of training would decrease affective responding and improve performance, and that these effects might be moderated by acute stress induction. DESIGN: We manipulated training (mindfulness, cognitive reappraisal, control) between subjects and level of stress (low, high) within subjects in a 3 × 2 mixed factorial design. Method: Participants (N = 112, ages 18-35) completed two sessions on different days. In each session, they received mindfulness or cognitive reappraisal training or listened to a control script prior to a low- or high-stress simulated hostage situation. We measured motor performance efficiency (proportion of shots that hit hostile and hostage targets), affective responding (self-reported anxiety, salivary cortisol and alpha amylase, and autonomic physiology), and physical activity. RESULTS: Compared to control instructions, ultra-brief training in cognitive reappraisal or mindfulness reduced subjective anxiety and increased performance efficiency. There were few effects of training on other measures. CONCLUSION: Ultra-brief training in cognitive reappraisal or mindfulness prior to a stressful task may be both helpful and harmful; effects are preliminary and subject to boundary conditions.

Characterizing Relationships Among the Cognitive, Physical, Social-emotional, and Health-related Traits of Military Personnel.

INTRODUCTION: Personnel engaged in high-stakes occupations, such as military personnel, law enforcement, and emergency first responders, must sustain performance through a range of environmental stressors. To maximize the effectiveness of military personnel, an a priori understanding of traits can help predict their physical and cognitive performance under stress and adversity. This work developed and assessed a suite of measures that have the potential to predict performance during operational scenarios. These measures were designed to characterize four specific trait-based domains: cognitive, health, physical, and social-emotional. MATERIALS AND METHODS: One hundred and ninety-one active duty U.S. Army soldiers completed interleaved questionnaire-based, seated task-based, and physical task-based measures over a period of 3-5 days. Redundancy analysis, dimensionality reduction, and network analyses revealed several patterns of interest. RESULTS: First, unique variable analysis revealed a minimally redundant battery of instruments. Second, principal component analysis showed that metrics tended to cluster together in three to five components within each domain. Finally, analyses of cross-domain associations using network analysis illustrated that cognitive, health, physical, and social-emotional domains showed strong construct solidarity. CONCLUSIONS: The present battery of metrics presents a fieldable toolkit that may be used to predict operational performance that can be clustered into separate components or used independently. It will aid predictive algorithm development aimed to identify critical predictors of individual military personnel and small-unit performance outcomes.

Are Pathologists Self-Aware of Their Diagnostic Accuracy? Metacognition and the Diagnostic Process in Pathology.

BACKGROUND: Metacognition is a cognitive process that involves self-awareness of thinking, understanding, and performance. This study assesses pathologists' metacognition by examining the association between their diagnostic accuracy and self-reported confidence levels while interpreting skin and breast biopsies. DESIGN: We studied 187 pathologists from the Melanoma Pathology Study (M-Path) and 115 pathologists from the Breast Pathology Study (B-Path). We measured pathologists' metacognitive ability by examining the area under the curve (AUC), the area under each pathologist's receiver operating characteristic (ROC) curve summarizing the association between confidence and diagnostic accuracy. We investigated possible relationships between this AUC measure, referred to as metacognitive sensitivity, and pathologist attributes. We also assessed whether higher metacognitive sensitivity affected the association between diagnostic accuracy and a secondary diagnostic action such as requesting a second opinion. RESULTS: We found no significant associations between pathologist clinical attributes and metacognitive AUC. However, we found that pathologists with higher AUC showed a stronger trend to request secondary diagnostic action for inaccurate diagnoses and not for accurate diagnoses compared with pathologists with lower AUC. LIMITATIONS: Pathologists reported confidence in specific diagnostic terms, rather than the broader classes into which the diagnostic terms were later grouped to determine accuracy. In addition, while there is no gold standard for the correct diagnosis to determine the accuracy of pathologists' interpretations, our studies achieved a high-quality reference diagnosis by using the consensus diagnosis of 3 experienced pathologists. CONCLUSIONS: Metacognition can affect clinical decisions. If pathologists have self-awareness that their diagnosis may be inaccurate, they can request additional tests or second opinions, providing the opportunity to correct inaccurate diagnoses. HIGHLIGHTS: Metacognitive sensitivity varied across pathologists, with most showing higher sensitivity than expected by chance.None of the demographic or clinical characteristics we examined was significantly associated with metacognitive sensitivity.Pathologists with higher metacognitive sensitivity were more likely to request additional tests or second opinions for their inaccurate diagnoses.

An analysis of pathologists' viewing processes as they diagnose whole slide digital images.

Although pathologists have their own viewing habits while diagnosing, viewing behaviors leading to the most accurate diagnoses are under-investigated. Digital whole slide imaging has enabled investigators to analyze pathologists' visual interpretation of histopathological features using mouse and viewport tracking techniques. In this study, we provide definitions for basic viewing behavior variables and investigate the association of pathologists' characteristics and viewing behaviors, and how they relate to diagnostic accuracy when interpreting whole slide images. We use recordings of 32 pathologists' actions while interpreting a set of 36 digital whole slide skin biopsy images (5 sets of 36 cases; 180 cases total). These viewport tracking data include the coordinates of a viewport scene on pathologists' screens, the magnification level at which that viewport was viewed, as well as a timestamp. We define a set of variables to quantify pathologists' viewing behaviors such as zooming, panning, and interacting with a consensus reference panel's selected region of interest (ROI). We examine the association of these viewing behaviors with pathologists' demographics, clinical characteristics, and diagnostic accuracy using cross-classified multilevel models. Viewing behaviors differ based on clinical experience of the pathologists. Pathologists with a higher caseload of melanocytic skin biopsy cases and pathologists with board certification and/or fellowship training in dermatopathology have lower average zoom and lower variance of zoom levels. Viewing behaviors associated with higher diagnostic accuracy include higher average and variance of zoom levels, a lower magnification percentage (a measure of consecutive zooming behavior), higher total interpretation time, and higher amount of time spent viewing ROIs. Scanning behavior, which refers to panning with a fixed zoom level, has marginally significant positive association with accuracy. Pathologists' training, clinical experience, and their exposure to a range of cases are associated with their viewing behaviors, which may contribute to their diagnostic accuracy. Research in computational pathology integrating digital imaging and clinical informatics opens up new avenues for leveraging viewing behaviors in medical education and training, potentially improving patient care and the effectiveness of clinical workflow.

Effect of Prior Diagnoses on Dermatopathologists' Interpretations of Melanocytic Lesions: A Randomized Controlled Trial.

Importance: Medical second opinions are common, although little is known about the best processes for obtaining them. This study assesses whether knowledge of a prior physician's diagnosis influences consulting physicians' diagnoses. Objective: To measure the extent to which dermatopathologists' diagnoses are influenced by prior diagnostic information from another dermatopathologist. Design, Setting, and Participants: Dermatopathologists were randomly assigned to interpret 1 slide set of 18 melanocytic skin biopsy specimens in 2 phases (5 slide sets totaling 90 cases). Phase 1 interpretations were conducted without prior diagnostic information. After a washout period of 12 or more months, dermatopathologists' phase 2 interpretations were conducted with their identical slide set; for a random subset of cases in phase 2, participants were shown prior diagnoses by other dermatopathologists that were either more or less severe than their own phase 1 diagnosis of the case. Using the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis tool, cases ranged from class I (benign) to class V (≥pT1b invasive melanoma). Data collection took place from August 2018 to March 2021, and data analysis was performed from March to December 2021. Intervention: Prior diagnoses were actual diagnoses from board-certified and/or fellowship-trained dermatopathologists. A prior diagnosis was always in a more severe or less severe diagnostic class than the participant's phase 1 interpretation; more or less severe was determined by the randomization scheme. In the control condition of no prior diagnostic information, the participants were told that a prior diagnosis was not available. Main Outcomes and Measures: When exposure was to a prior diagnosis in a higher diagnostic class, the primary study outcome was whether a participant's diagnosis in phase 2 was in a higher diagnostic class than the participant's diagnosis in phase 1. When exposure was to a prior diagnosis in a lower diagnostic class, the primary study outcome was whether a participant's diagnosis in phase 2 was in a lower diagnostic class than the participant's diagnosis in phase 1. The effect of prior diagnostic information was measured using the relative risk (RR) of each outcome relative to the control condition of no prior diagnostic information, adjusted for the diagnostic class of the phase 1 diagnosis. Prior to data collection, it was hypothesized that participants would be swayed in the direction of prior diagnostic information. Results: A total of 149 dermatopathologists (median [range] age, 47 years [34-76] years; 101 [68%] were male) provided 5322 interpretations of study cases. Participants were more likely to increase the severity of their diagnosis when the prior diagnosis was of greater severity compared with when no prior diagnosis was provided (RR, 1.52; 95% CI, 1.34-1.73); likewise, participants gave less severe diagnoses when prior diagnoses were of lesser severity (RR, 1.38; 95% CI, 1.19-1.59). Trends were similar among dermatopathologists who had previously stated they were "not at all influenced" by prior diagnoses. Prior diagnoses also swayed dermatopathologists away from correct diagnoses. Conclusions and Relevance: In this randomized controlled trial, despite the preference of most dermatopathologists to receive prior diagnoses when providing second opinions, this information swayed them away from a correct diagnosis to an incorrect diagnosis.

What Is Targeted When We Train Working Memory? Evidence From a Meta-Analysis of the Neural Correlates of Working Memory Training Using Activation Likelihood Estimation.

Working memory (WM) is the system responsible for maintaining and manipulating information, in the face of ongoing distraction. In turn, WM span is perceived to be an individual-differences construct reflecting the limited capacity of this system. Recently, however, there has been some evidence to suggest that WM capacity can increase through training, raising the possibility that training can functionally alter the neural structures supporting WM. To address the hypothesis that the neural substrates underlying WM are targeted by training, we conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies of WM training using Activation Likelihood Estimation (ALE). Our results demonstrate that WM training is associated exclusively with decreases in blood oxygenation level-dependent (BOLD) responses in clusters within the fronto-parietal system that underlie WM, including the bilateral inferior parietal lobule (BA 39/40), middle (BA 9) and superior (BA 6) frontal gyri, and medial frontal gyrus bordering on the cingulate gyrus (BA 8/32). We discuss the various psychological and physiological mechanisms that could be responsible for the observed reductions in the BOLD signal in relation to WM training, and consider their implications for the construct of WM span as a limited resource.

Modulating Cognitive-Motor Multitasking with Commercial-off-the-Shelf Non-Invasive Brain Stimulation.

One growing area of multitasking research involves a focus on performing cognitive and motor tasks in tandem. In these situations, increasing either cognitive or motor demands has implications for performance in both tasks, an effect which is thought to be due to competing neural resources. Separate research suggests that non-invasive brain stimulation may offer a means to mitigate performance decrements experienced during multitasking. In the present study, we investigated the degree to which a commercially available non-invasive brain stimulation device (Halo Sport) alters balance performance in the presence of different types of cognitive demands. Specifically, we tested if performing a secondary cognitive task impacts postural sway in healthy young adults and if we could mitigate this impact using transcranial direct current stimulation (tDCS) applied over the primary motor cortex. Furthermore, we included conditions of unstable and stable surfaces and found that lower surface stability increased postural sway. In addition, we found that cognitive load impacted postural sway but in the opposite pattern we had anticipated, with higher sway found in the single-task control condition compared to executive function conditions. Finally, we found a small but significant effect of tDCS on balance with decreased sway for active (compared to sham) tDCS.

Building a transdisciplinary expert consensus on the cognitive drivers of performance under pressure: An international multi-panel Delphi study.

Introduction: The ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure. Methods: International experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance. Results: Sixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control-Performance Monitoring; (3) Arousal and Regulatory Systems-Arousal; (4) Cognitive Control-Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control-Response Selection and Inhibition/Suppression; (6) Working memory-Flexible Updating; (7) Working memory-Active Maintenance; (8) Perception and Understanding of Self-Self-knowledge; (9) Working memory-Interference Control, and (10) Expert-suggested-Shifting. Discussion: Our results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization.

More scanning, but not zooming, is associated with diagnostic accuracy in evaluating digital breast pathology slides.

Diagnoses of medical images can invite strikingly diverse strategies for image navigation and visual search. In computed tomography screening for lung nodules, distinct strategies, termed scanning and drilling, relate to both radiologists' clinical experience and accuracy in lesion detection. Here, we examined associations between search patterns and accuracy for pathologists (N = 92) interpreting a diverse set of breast biopsy images. While changes in depth in volumetric images reveal new structures through movement in the z-plane, in digital pathology changes in depth are associated with increased magnification. Thus, "drilling" in radiology may be more appropriately termed "zooming" in pathology. We monitored eye-movements and navigation through digital pathology slides to derive metrics of how quickly the pathologists moved through XY (scanning) and Z (zooming) space. Prior research on eye-movements in depth has categorized clinicians as either "scanners" or "drillers." In contrast, we found that there was no reliable association between a clinician's tendency to scan or zoom while examining digital pathology slides. Thus, in the current work we treated scanning and zooming as continuous predictors rather than categorizing as either a "scanner" or "zoomer." In contrast to prior work in volumetric chest images, we found significant associations between accuracy and scanning rate but not zooming rate. These findings suggest fundamental differences in the relative value of information types and review behaviors across two image formats. Our data suggest that pathologists gather critical information by scanning on a given plane of depth, whereas radiologists drill through depth to interrogate critical features.

Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach.

Wearable technologies for measuring digital and chemical physiology are pervading the consumer market and hold potential to reliably classify states of relevance to human performance including stress, sleep deprivation, and physical exertion. The ability to efficiently and accurately classify physiological states based on wearable devices is improving. However, the inherent variability of human behavior within and across individuals makes it challenging to predict how identified states influence human performance outcomes of relevance to military operations and other high-stakes domains. We describe a computational modeling approach to address this challenge, seeking to translate user states obtained from a variety of sources including wearable devices into relevant and actionable insights across the cognitive and physical domains. Three status predictors were considered: stress level, sleep status, and extent of physical exertion; these independent variables were used to predict three human performance outcomes: reaction time, executive function, and perceptuo-motor control. The approach provides a complete, conditional probabilistic model of the performance variables given the status predictors. Construction of the model leverages diverse raw data sources to estimate marginal probability density functions for each of six independent and dependent variables of interest using parametric modeling and maximum likelihood estimation. The joint distributions among variables were optimized using an adaptive LASSO approach based on the strength and directionality of conditional relationships (effect sizes) derived from meta-analyses of extant research. The model optimization process converged on solutions that maintain the integrity of the original marginal distributions and the directionality and robustness of conditional relationships. The modeling framework described provides a flexible and extensible solution for human performance prediction, affording efficient expansion with additional independent and dependent variables of interest, ingestion of new raw data, and extension to two- and three-way interactions among independent variables. Continuing work includes model expansion to multiple independent and dependent variables, real-time model stimulation by wearable devices, individualized and small-group prediction, and laboratory and field validation.

A Critical Review of Cranial Electrotherapy Stimulation for Neuromodulation in Clinical and Non-clinical Samples.

Cranial electrotherapy stimulation (CES) is a neuromodulation tool used for treating several clinical disorders, including insomnia, anxiety, and depression. More recently, a limited number of studies have examined CES for altering affect, physiology, and behavior in healthy, non-clinical samples. The physiological, neurochemical, and metabolic mechanisms underlying CES effects are currently unknown. Computational modeling suggests that electrical current administered with CES at the earlobes can reach cortical and subcortical regions at very low intensities associated with subthreshold neuromodulatory effects, and studies using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) show some effects on alpha band EEG activity, and modulation of the default mode network during CES administration. One theory suggests that CES modulates brain stem (e.g., medulla), limbic (e.g., thalamus, amygdala), and cortical (e.g., prefrontal cortex) regions and increases relative parasympathetic to sympathetic drive in the autonomic nervous system. There is no direct evidence supporting this theory, but one of its assumptions is that CES may induce its effects by stimulating afferent projections of the vagus nerve, which provides parasympathetic signals to the cardiorespiratory and digestive systems. In our critical review of studies using CES in clinical and non-clinical populations, we found severe methodological concerns, including potential conflicts of interest, risk of methodological and analytic biases, issues with sham credibility, lack of blinding, and a severe heterogeneity of CES parameters selected and employed across scientists, laboratories, institutions, and studies. These limitations make it difficult to derive consistent or compelling insights from the extant literature, tempering enthusiasm for CES and its potential to alter nervous system activity or behavior in meaningful or reliable ways. The lack of compelling evidence also motivates well-designed and relatively high-powered experiments to assess how CES might modulate the physiological, affective, and cognitive responses to stress. Establishing reliable empirical links between CES administration and human performance is critical for supporting its prospective use during occupational training, operations, or recovery, ensuring reliability and robustness of effects, characterizing if, when, and in whom such effects might arise, and ensuring that any benefits of CES outweigh the risks of adverse events.

Melanoma in the Blink of an Eye: Pathologists' Rapid Detection, Classification, and Localization of Skin Abnormalities.

Expert radiologists can quickly extract a basic "gist" understanding of a medical image following less than a second exposure, leading to above-chance diagnostic classification of images. Most of this work has focused on radiology tasks (such as screening mammography), and it is currently unclear whether this pattern of results and the nature of visual expertise underlying this ability are applicable to pathology, another medical imaging domain demanding visual diagnostic interpretation. To further characterize the detection, localization, and diagnosis of medical images, this study examined eye movements and diagnostic decision-making when pathologists were briefly exposed to digital whole slide images of melanocytic skin biopsies. Twelve resident (N = 5), fellow (N = 5), and attending pathologists (N = 2) with experience interpreting dermatopathology briefly viewed 48 cases presented for 500 ms each, and we tracked their eye movements towards histological abnormalities, their ability to classify images as containing or not containing invasive melanoma, and their ability to localize critical image regions. Results demonstrated rapid shifts of the eyes towards critical abnormalities during image viewing, high diagnostic sensitivity and specificity, and a surprisingly accurate ability to localize critical diagnostic image regions. Furthermore, when pathologists fixated critical regions with their eyes, they were subsequently much more likely to successfully localize that region on an outline of the image. Results are discussed relative to models of medical image interpretation and innovative methods for monitoring and assessing expertise development during medical education and training.

Analysis of Regions of Interest and Distractor Regions in Breast Biopsy Images.

This paper studies why pathologists can misdiagnose diagnostically challenging breast biopsy cases, using a data set of 240 whole slide images (WSIs). Three experienced pathologists agreed on a consensus reference ground-truth diagnosis for each slide and also a consensus region of interest (ROI) from which the diagnosis could best be made. A study group of 87 other pathologists then diagnosed test sets (60 slides each) and marked their own regions of interest. Diagnoses and ROIs were categorized such that if on a given slide, their ROI differed from the consensus ROI and their diagnosis was incorrect, that ROI was called a distractor. We used the HATNet transformer-based deep learning classifier to evaluate the visual similarities and differences between the true (consensus) ROIs and the distractors. Results showed high accuracy for both the similarity and difference networks, showcasing the challenging nature of feature classification with breast biopsy images. This study is important in the potential use of its results for teaching pathologists how to diagnose breast biopsy slides.