"The eyes are the window to the representation": Linking gaze to memory precision and decision weights in object discrimination tasks.

Humans selectively attend to task-relevant information in order to make accurate decisions. However, selective attention incurs consequences if the learning environment changes unexpectedly. This trade-off has been underscored by studies that compare learning behaviors between adults and young children: broad sampling during learning comes with a breadth of information in memory, often allowing children to notice details of the environment that are missed by their more selective adult counterparts. The current work extends the exemplar-similarity account of object discrimination to consider both the intentional and consequential aspects of selective attention when predicting choice. In a novel direct input approach, we used trial-level eye-tracking data from training and test to replace the otherwise freely estimated attention dynamics of the model. We demonstrate that only a model imbued with gaze correlates of memory precision in addition to decision weights can accurately predict key behaviors associated with (a) selective attention to a relevant dimension, (b) distributed attention across dimensions, and (c) flexibly shifting strategies between tasks. Although humans engage in selective attention with the intention of being accurate in the moment, our findings suggest that its consequences on memory constrain the information that is available for making decisions in the future. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Role of Attention in Category Representation.

Numerous studies have found that selective attention affects category learning. However, previous research did not distinguish between the contribution of focusing and filtering components of selective attention. This study addresses this issue by examining how components of selective attention affect category representation. Participants first learned a rule-plus-similarity category structure, and then were presented with category priming followed by categorization and recognition tests. Additionally, to evaluate the involvement of focusing and filtering, we fit models with different attentional mechanisms to the data. In Experiment 1, participants received rule-based category training, with specific emphasis on a single deterministic feature (D feature). Experiment 2 added a recognition test to examine participants' memory for features. Both experiments indicated that participants categorized items based solely on the D feature, showed greater memory for the D feature, were primed exclusively by the D feature without interference from probabilistic features (P features), and were better fit by models with focusing and at least one type of filtering mechanism. The results indicated that selective attention distorted category representation by highlighting the D feature and attenuating P features. To examine whether the distorted representation was specific to rule-based training, Experiment 3 introduced training, emphasizing all features. Under such training, participants were no longer primed by the D feature, they remembered all features well, and they were better fit by the model assuming only focusing but no filtering process. The results coupled with modeling provide novel evidence that while both focusing and filtering contribute to category representation, filtering can also result in representational distortion.

The Pigeon as a Model of Complex Visual Processing and Category Learning.

Over the past 30 years, behavioral, computational, and neuroscientific investigations have yielded fresh insights into how pigeons adapt to the diverse complexities of their visual world. A prime area of interest has been how pigeons categorize the innumerable individual stimuli they encounter. Most studies involve either photorealistic representations of actual objects thus affording the virtue of being naturalistic, or highly artificial stimuli thus affording the virtue of being experimentally manipulable. Together those studies have revealed the pigeon to be a prodigious classifier of both naturalistic and artificial visual stimuli. In each case, new computational models suggest that elementary associative learning lies at the root of the pigeon's category learning and generalization. In addition, ongoing computational and neuroscientific investigations suggest how naturalistic and artificial stimuli may be processed along the pigeon's visual pathway. Given the pigeon's availability and affordability, there are compelling reasons for this animal model to gain increasing prominence in contemporary neuroscientific research.

A multifaceted approach to global health.

World Health Day underscores the scientific community's commitment to achieving health equity for all. It is paramount to eliminate bias in research that has traditionally focused on men, neglecting the specific needs of diverse populations. Innovative clinical trial designs are being developed with more inclusive enrollment. Ensuring equitable access to essential antibiotics, coupled with robust infection prevention and control measures, is vital to safeguarding public health. The pursuit of health equity extends beyond the realm of medicine. Investments in local food production and robust social safety nets are critical for mitigating the effects of climate change on access to healthy diets. Additionally, in times of polycrisis, prioritizing the unique needs of children and empowering community-led healthcare initiatives in conflict zones are essential steps. By taking these actions, we can move closer to realizing everyone's fundamental right to health.

Underrepresentation of racial and ethnic minority groups in gynecologic oncology: An analysis of over 250 trials.

OBJECTIVE: To describe the participation of racial and ethnic minority groups (REMGs) in gynecologic oncology trials. METHODS: Gynecologic oncology studies registered on ClinicalTrials.gov between 2007 and 2020 were identified. Trials with published results were analyzed based on reporting of race/ethnicity in relation to disease site and trial characteristics. Expected enrollment by race/ethnicity was calculated and compared to actual enrollment, adjusted for 2010 US Census population data. RESULTS: 2146 gynecologic oncology trials were identified. Of published trials (n = 252), 99 (39.3%) reported race/ethnicity data. Recent trials were more likely to report these data (36% from 2007 to 2009; 51% 2013-2015; and 53% from 2016 to 2018, p = 0.01). Of all trials, ovarian cancer trials were least likely to report race/ethnicity data (32.1% vs 39.3%, p = 0.011). Population-adjusted under-enrollment for Blacks was 7-fold in ovarian cancer, Latinx 10-fold for ovarian and 6-fold in uterine cancer trials, Asians 2.5-fold in uterine cancer trials, and American Indian and Alaska Native individuals 6-fold in ovarian trials. Trials for most disease sites have enrolled more REMGs in recent years - REMGs made up 19.6% of trial participants in 2007-2009 compared to 38.1% in 2016-2018 (p < 0.0001). CONCLUSION: Less than half of trials that published results reported race/ethnicity data. Available data reveals that enrollment of REMGs is significantly below expected rates based on national census data. These disparities persisted even after additionally adjusting for population size. Despite improvement in recent years, additional recruitment of REMGs is needed to achieve more representative and equitable participation in gynecologic cancer clinical trials.

The pigeon as a machine: Complex category structures can be acquired by a simple associative model.

Never known for its smarts, the pigeon has proven to be a prodigious classifier of complex visual stimuli. What explains its surprising success? Does it possess elaborate executive functions akin to those deployed by humans? Or does it effectively deploy an unheralded, but powerful associative learning mechanism? In a series of experiments, we first confirm that pigeons can learn a variety of category structures - some devised to foil the use of advanced cognitive processes. We then contrive a simple associative learning model to see how effectively the model learns the same tasks given to pigeons. The close fit of the associative model to pigeons' categorization behavior provides unprecedented support for associative learning as a viable mechanism for mastering complex category structures and for the pigeon's using this mechanism to adapt to a rich visual world. This model will help guide future neuroscientific research into the biological substrates of visual cognition.

Sex-specific ultraviolet radiation tolerance across Drosophila.

The genetic basis of phenotypic differences between species is among the most longstanding questions in evolutionary biology. How new genes form and the processes selection acts to produce differences across species are fundamental to understand how species persist and evolve in an ever-changing environment. Adaptation and genetic innovation arise in the genome by a variety of sources. Functional genomics requires both intrinsic genetic discoveries, as well as empirical testing to observe adaptation between lineages. Here we explore two species of Drosophila on the island of Sao Tome and mainland Africa, D. santomea and D. yakuba. These two species both inhabit the island, but occupy differing species distributions based on elevation, with D. yakuba also having populations on mainland Africa. Intrinsic evidence shows genes between species may have a role in adaptation to higher UV tolerance with DNA repair mechanisms (PARP) and resistance to humeral stress lethal effects (Victoria). We conducted empirical assays between island D. santomea, D. yakuba, and mainland D. yakuba. Flies were shocked with UVB radiation (@ 302 nm) at 1650-1990 mW/cm2 for 30 minutes on a transilluminator apparatus. Custom 5-wall acrylic enclosures were constructed for viewing and containment of flies. All assays were filmed. Island groups did show significant differences between fall-time under UV stress and recovery time post-UV stress test between regions and sex. This study shows evidence that mainland flies are less resistant to UV radiation than their island counterparts. Further work exploring the genetic basis for UV tolerance will be conducted from empirical assays. Understanding the mechanisms and processes that promote adaptation and testing extrinsic traits within the context of the genome is crucially important to understand evolutionary machinery.

Obstetric Clinical Trial Diversity: Analysis of Trial Focus and Representation From 2007 to 2020.

Inclusive clinical trials are necessary to improve maternal health equity. We aimed to analyze the current state of race and ethnicity reporting and representation in obstetric trials and the association with trial focus for all U.S.-based obstetric trials between 2007 and 2020. In this cross-sectional, multivariable regression analysis, the exposure variable was clinical trial focus (eg, prematurity), and the outcomes were race and ethnicity reporting and representation of diverse cohorts. Obstetric anesthesia trials reported race and ethnicity the least frequently of all trial foci (adjusted odds ratio 0.2, 95% CI 0.08-0.48). Hypertension and obstetric anesthesia trials enrolled the lowest proportion of Black participants, and prematurity trials enrolled the lowest proportion of Latinx and Asian participants. All researchers should strive to improve measurement and reporting of demographic data as well participation of diverse cohorts.

Using Unsupervised Machine Learning as an Alternative to Curated Medical School Rankings.

This cross-sectional study compares an unsupervised machine learning algorithm's ability to group schools into tiers vs the US News & World Report's medical school rankings.

Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms.

When making decisions based on probabilistic outcomes, people guide their behavior using knowledge gathered through both indirect descriptions and direct experience. Paradoxically, how people obtain information significantly impacts apparent preferences. A ubiquitous example is the description-experience gap: individuals seemingly overweight low probability events when probabilities are described yet underweight them when probabilities must be experienced firsthand. A leading explanation for this fundamental gap in decision-making is that probabilities are weighted differently when learned through description relative to experience, yet a formal theoretical account of the mechanism responsible for such weighting differences remains elusive. We demonstrate how various learning and memory retention models incorporating neuroscientifically motivated learning mechanisms can explain why probability weighting and valuation parameters often are found to vary across description and experience. In a simulation study, we show how learning through experience can lead to systematically biased estimates of probability weighting when using a traditional cumulative prospect theory model. We then use hierarchical Bayesian modeling and Bayesian model comparison to show how various learning and memory retention models capture participants' behavior over and above changes in outcome valuation and probability weighting, accounting for description and experience-based decisions in a within-subject experiment. We conclude with a discussion of how substantive models of psychological processes can lead to insights that heuristic statistical models fail to capture.

Characterizing Clinical Trials in Plastic and Reconstructive Surgery: A Systematic Review of ClinicalTrials.gov From 2007 to 2020.

BACKGROUND: Clinical trials form the backbone of evidence-based medicine. ClinicalTrials.gov is the world's largest clinical trial registry, and the state of clinical trials in plastic and reconstructive surgery (PRS) within that database has not been comprehensively studied. To that end, we explored the distribution of therapeutic areas that are under investigation, impact of funding on study design and data reporting, and trends in research patterns of all PRS interventional clinical trials registered with ClinicalTrials.gov. METHODS: Using the ClinicalTrials.gov database, we identified and extracted all clinical trials relevant to PRS that were submitted between 2007 and 2020. Studies were classified based on anatomic locations, therapeutic categories, and specialty topics. Cox proportional hazard was used to calculate adjusted hazard ratios (HRs) for early discontinuation and results reporting. RESULTS: A total of 3224 trials that included 372,095 participants were identified. The PRS trials grew at an annual rate of 7.9%. The therapeutic classes most represented were wound healing (41.3%) and cosmetics (18.1%). Funding for PRS clinical trials is largely provided through academic institutions (72.7%), while industry and US government constituted a minority. Industry-funded studies were more likely to be discontinued early than those funded by academics (HR, 1.89) or government (HR, 1.92) and to be nonblinded and nonrandomized. Academic-funded studies were the least likely to report results data within 3 years of trial completion (odds ratio, 0.87). CONCLUSIONS: A gulf exists in the representation of different PRS specialties among clinical trials. We highlight the role of funding source in trial design and data reporting to identify a potential source of financial waste and to stress the need for continued appropriate oversight.

Is Oligometastatic Cancer Curable? A Survey of Oncologist Perspectives, Decision Making, and Communication.

Purpose: Oligometastatic disease (OMD) refers to a limited state of metastatic cancer, which potentially derives benefit from local treatments. Given the relative novelty of this paradigm, oncologist perspectives on OMD are not well established. We thus explored oncologist views on curability of and treatment recommendations for patients with OMD. Methods and Materials: We developed a survey focused on oncologist views of 3 subtypes of OMD: synchronous, oligorecurrent, and oligoprogressive. Eligible participants included medical and radiation oncologists at 2 large cancer centers invited to participate between May and June 2022. Participants were presented with 3 hypothetical patient scenarios and asked about treatment recommendations, rationale, and demographic information. Results: Of 44 respondents, over half (61.4%) agreed that synchronous OMD is curable. A smaller proportion (46.2% and 13.5%) agreed for oligorecurrence and oligoprogression, respectively. When asked whether they use the word "cure" or "curative" in discussing prognosis, 31.8% and 33.3% agreed for synchronous and oligorecurrent OMD, respectively, while 78.4% disagreed for oligoprogression. Views on curability did not significantly affect treatment recommendations. More medical oncologists recommended systemic treatment only compared with radiation oncologists for the synchronous OMD (50.0% vs 5.3%; P < .01) and oligoprogression cases (43.8% vs 10.5%; P = .02), not the oligorecurrent case. There were no significant differences in confidence in treatment recommendations by specialty. Conclusions: In this exploratory study, we found notable divergence in oncologists' views about curability of OMD as well as variability in treatment recommendations, suggesting need for more robust research on outcomes of patients with OMD.

Race and Ethnicity Reporting and Representation in Pediatric Clinical Trials.

BACKGROUND AND OBJECTIVES: Representative enrollment of racial and ethnic minoritized populations in biomedical research ensures the generalizability of results and equitable access to novel therapies. Previous studies on pediatric clinical trial diversity are limited to subsets of journals or disciplines. We aimed to evaluate race and ethnicity reporting and representation in all US pediatric clinical trials on ClinicalTrials.gov. METHODS: We performed a cross-sectional study of US-based clinical trials registered on ClinicalTrials.gov that enrolled participants aged <18 years old between October 2007 and March 2020. We used descriptive statistics, compound annual growth rates, and multivariable logistic regression for data analysis. Estimates of US population statistics and disease burden were calculated with the US Census, Kids' Inpatient Database, and National Survey of Children's Health. RESULTS: Among 1183 trials encompassing 405 376 participants, race and ethnicity reporting significantly increased from 27% in 2007 to 87% in 2018 (P < .001). The median proportional enrollment of Asian American children was 0.6% (interquartile range [IQR], 0%-3.7%); American Indian, 0% (IQR, 0%-0%); Black, 12% (IQR, 2.9%-28.4%); Hispanic, 7.1% (IQR, 0%-18.6%); and white 66.4% (IQR, 41.5%-81.6%). Asian American, Black, and Hispanic participants were underrepresented relative to US population demographics. Compared with expected proportions based on disease prevalence and hospitalizations, Asian American and Hispanic participants were most consistently underrepresented across diagnoses. CONCLUSIONS: While race and ethnicity reporting in pediatric clinical trials has improved, the representative enrollment of minoritized participants remains an ongoing challenge. Evidence-based and policy solutions are needed to address these disparities to advance biomedical innovation for all children.

Cognition: The power of simple associative learning.

Associative learning is traditionally considered to be slow and inefficient compared to 'smarter' rule-based learning. New research reveals the remarkable ability of associative learning in acquiring exceedingly complex categories.

Analysis of Female Participant Representation in Registered Oncology Clinical Trials in the United States from 2008 to 2020.

BACKGROUND: Female underrepresentation in oncology clinical trials can result in outcome disparities. We evaluated female participant representation in US oncology trials by intervention type, cancer site, and funding. MATERIALS AND METHODS: Data were extracted from the publicly available Aggregate Analysis of ClinicalTrials.gov database. Initially, 270,172 studies were identified. Following the exclusion of trials using Medical Subject Heading terms, manual review, those with incomplete status, non-US location, sex-specific organ cancers, or lacking participant sex data, 1650 trials consisting of 240,776 participants remained. The primary outcome was participation to prevalence ratio (PPR): percent females among trial participants divided by percent females in the disease population per US Surveillance, Epidemiology, and End Results Program data. PPRs of 0.8-1.2 reflect proportional female representation. RESULTS: Females represented 46.9% of participants (95% CI, 45.4-48.4); mean PPR for all trials was 0.912. Females were underrepresented in surgical (PPR 0.74) and other invasive (PPR 0.69) oncology trials. Among cancer sites, females were underrepresented in bladder (odds ratio [OR] 0.48, 95% CI 0.26-0.91, P = .02), head/neck (OR 0.44, 95% CI 0.29-0.68, P < .01), stomach (OR 0.40, 95% CI 0.23-0.70, P < .01), and esophageal (OR 0.40 95% CI 0.22-0.74, P < .01) trials. Hematologic (OR 1.78, 95% CI 1.09-1.82, P < .01) and pancreatic (OR 2.18, 95% CI 1.46-3.26, P < .01) trials had higher odds of proportional female representation. Industry-funded trials had greater odds of proportional female representation (OR 1.41, 95% CI 1.09-1.82, P = .01) than US government and academic-funded trials. CONCLUSIONS: Stakeholders should look to hematologic, pancreatic, and industry-funded cancer trials as exemplars of female participant representation and consider female representation when interpreting trial results.

Race and Ethnicity Reporting and Representation in Obstetrics and Gynecology Clinical Trials and Publications From 2007-2020.

Importance: Clinical trials guide evidence-based obstetrics and gynecology (OB-GYN) but often enroll nonrepresentative participants. Objective: To characterize race and ethnicity reporting and representation in US OB-GYN clinical trials and their subsequent publications and to analyze the association of subspecialty and funding with diverse representation. Design and Setting: Cross-sectional analysis of all OB-GYN studies registered on ClinicalTrials.gov (2007-2020) and publications from PubMed and Google Scholar (2007-2021). Analyses included logistic regression controlling for year, subspecialty, phase, funding, and site number. Data from 332 417 studies were downloaded. Studies with a noninterventional design, with a registration date before October 1, 2007, without relevance to OB-GYN, with no reported results, and with no US-based study site were excluded. Exposures: OB-GYN subspecialty and funder. Main Outcomes and Measures: Reporting of race and ethnicity data and racial and ethnic representation (the proportion of enrollees of American Indian or Alaskan Native, Asian, Black, Latinx, or White identity and odds of representation above US Census estimates by race and ethnicity). Results: Among trials with ClinicalTrials.gov results (1287 trials with 591 196 participants) and publications (1147 trials with 821 111 participants), 662 (50.9%) and 856 (74.6%) reported race and ethnicity data, respectively. Among publications, gynecology studies were significantly less likely to report race and ethnicity than obstetrics (adjusted odds ratio [aOR], 0.54; 95% CI, 0.38-0.75). Reproductive endocrinology and infertility trials had the lowest odds of reporting race and ethnicity (aOR, 0.14; 95% CI, 0.07-0.27; reference category, obstetrics). Obstetrics and family planning demonstrated the most diverse clinical trial cohorts. Compared with obstetric trials, gynecologic oncology had the lowest odds of Black representation (ClinicalTrials.gov: aOR, 0.04; 95% CI, 0.02-0.09; publications: aOR, 0.06; 95% CI, 0.03-0.11) and Latinx representation (ClinicalTrials.gov: aOR, 0.05; 95% CI, 0.02-0.14; publications: aOR, 0.23; 95% CI, 0.10-0.48), followed by urogynecology and reproductive endocrinology and infertility. Urogynecology (ClinicalTrials.gov: aOR, 0.15; 95% CI, 0.05-0.39; publications: aOR, 0.24; 95% CI, 0.09-0.58) had the lowest odds of Asian representation. Conclusions and Relevance: Race and ethnicity reporting and representation in OB-GYN trials are suboptimal. Obstetrics and family planning trials demonstrate improved representation is achievable. Nonetheless, all subspecialties should strive for more equitably representative research.

The benefits of immature cognitive control: How distributed attention guards against learning traps.

Cognitive control allows one to focus one's attention efficiently on relevant information while filtering out irrelevant information. This ability provides a means of rapid and effective learning, but using this control also brings risks. Importantly, useful information may be ignored and missed, and learners may fall into "learning traps" (e.g., learned inattention) wherein they fail to realize that what they ignore carries important information. Previous research has shown that adults may be more prone to such traps than young children, but the mechanisms underlying this difference are unclear. The current study used eye tracking to examine the role of attentional control during learning in succumbing to these learning traps. The participants, 4-year-old children and adults, completed a category learning task in which an unannounced switch occurred wherein the feature dimensions most relevant to correct categorization became irrelevant and formerly irrelevant dimensions became relevant. After the switch, adults were more likely than children to ignore the new highly relevant dimension and settle on a suboptimal categorization strategy. Furthermore, eye-tracking analyses reveal that greater attentional selectivity during learning (i.e., optimizing attention to focus only on the most relevant sources of information) predicted this tendency to miss important information later. Children's immature cognitive control, leading to broadly distributed attention, appears to protect children from this trap-although at the cost of less efficient and slower learning. These results demonstrate the double-edged sword of cognitive control and suggest that immature control may serve an adaptive function early in development.

The quest for simplicity in human learning: Identifying the constraints on attention.

For better or worse, humans live a resource-constrained existence; only a fraction of physical sensations ever reach conscious awareness, and we store a shockingly small subset of these experiences in memory for later use. Here, we examined the effects of attention constraints on learning. Among models that frame selective attention as an optimization problem, attention orients toward information that will reduce errors. Using this framing as a basis, we developed a suite of models with a range of constraints on the attention available during each learning event. We fit these models to both choice and eye-fixation data from four benchmark category-learning data sets, and choice data from another dynamic categorization data set. We found consistent evidence for computations we refer to as "simplicity", where attention is deployed to as few dimensions of information as possible during learning, and "competition", where dimensions compete for selective attention via lateral inhibition.

As within, so without, as above, so below: Common mechanisms can support between- and within-trial category learning dynamics.

Two fundamental difficulties when learning novel categories are deciding (a) what information is relevant and (b) when to use that information. Although previous theories have specified how observers learn to attend to relevant dimensions over time, those theories have largely remained silent about how attention should be allocated on a within-trial basis, which dimensions of information should be sampled, and how the temporal order of information sampling influences learning. Here, we use the adaptive attention representation model (AARM) to demonstrate that a common set of mechanisms can be used to specify: (a) How the distribution of attention is updated between trials over the course of learning and (b) how attention dynamically shifts among dimensions within a trial. We validate our proposed set of mechanisms by comparing AARM's predictions to observed behavior in four case studies, which collectively encompass different theoretical aspects of selective attention. We use both eye-tracking and choice response data to provide a stringent test of how attention and decision processes dynamically interact during category learning. Specifically, how does attention to selected stimulus dimensions gives rise to decision dynamics, and in turn, how do decision dynamics influence which dimensions are attended to via gaze fixations? (PsycInfo Database Record (c) 2022 APA, all rights reserved).